From 8588d36eb45757fba37131f92d6a2b0ff91b7791 Mon Sep 17 00:00:00 2001 From: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com> Date: Thu, 10 Apr 2025 13:59:40 -0400 Subject: [PATCH] v1.0.0 Release Candidate (#95) * chore: Update versioning for release * fix: remove db creation at start and sync migrations and models * fix: Checkpoint changing metamessage schema * chore: linter fixes * fix: session cloning working * Hybrid long-term memory (#92) * Add TOM method switching * Add system prompt and note on format * Add persistence tweaks * Specify format for each section of user representation * Parse XML tags before saving representation metamessage * Clean up * Use Claude 3.5 Haiku and refine prompt * Simplify message processing * chore: update token limit on dialectic and model for deriver * Add embedding-based long-term fact retrieval * Fix bug preventing new documents from being created * Use multiple queries + tweak prompt * Fix collection name bug + add duplicate removal * First implementation of on-demand user rep generation * WIP debug on-demand user rep changes * Fixed representations not being stored & deriver issue * Some speed improvements * Play with number of facts / queries * WIP prompt caching for Claude * WIP fix anthropic caching * Anthropic prompt caching working but messages too short * Use Cerebras for small inferences * Make dialectic responses 1000 tokens max * Make user representation generation model a constant * Use llama 3.1 8b for query generation * Update env template * Add crud.get_or_create_protected_collection * rabbit comments * Fix linter issues * Add Cerebras to stream router method * Better handling of default-empty string args * Change prints to debug logs * Add error handling to TOM inference * Handle missing/empty client in model responses * Handle no messages case in get_chat_history * Fix indent * Add error handling to single_prompt methods * Fix get_or_create_user_protected_collection * Simplify openAI-compatible model client instantiation * Remove health endpoint * Remove LocalEmbeddingStore * Change prints to debug logs * Change sentry track * Code review changes * Add README to ToM module * Switch to Groq * Fix inconsistent openai compatible provider list in stream() * Update env template to include Groq variables * Add model_client tests * fix: Fix unit tests --------- Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com> * add scoped API keys (#91) * add AUTH_JWT_SECRET and ADMIN_KEY, use in security middleware (TODO granular keys) * WIP: convert all API paths to use scoped keys * add basic unit tests for API keys, ruff formatting * MVP of route using JWT for payload * add get_user_from_token * add key table to postgres, use it to enable key revocation * add key revocation pt 2 -- fix order of param checks * finish convenience routes that assume params from JWT * add tests for key API * get_keys * add secrets utility script, add key rotation, fill out tests * add tiny cache as PoC * nits, validations, etc * only create keys table migration if necessary * fix keys tests to always use auth * tiny fix to make custom DATABASE_SCHEMA work * review: add better docs, fix security issue with cache, clear db on rotation, and more * remove rotation * remove key database entirely * Add `/all` path to get all apps (#94) * add `/all` path for apps * assert vector extension installed (need this for groudon) * review --------- Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com> * add scoped API keys (#91) * add AUTH_JWT_SECRET and ADMIN_KEY, use in security middleware (TODO granular keys) * WIP: convert all API paths to use scoped keys * add basic unit tests for API keys, ruff formatting * MVP of route using JWT for payload * add get_user_from_token * add key table to postgres, use it to enable key revocation * add key revocation pt 2 -- fix order of param checks * finish convenience routes that assume params from JWT * add tests for key API * get_keys * add secrets utility script, add key rotation, fill out tests * add tiny cache as PoC * nits, validations, etc * only create keys table migration if necessary * fix keys tests to always use auth * tiny fix to make custom DATABASE_SCHEMA work * review: add better docs, fix security issue with cache, clear db on rotation, and more * remove rotation * remove key database entirely * Add `/all` path to get all apps (#94) * add `/all` path for apps * assert vector extension installed (need this for groudon) * review --------- Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com> * chore: README and CHANGELOG updates * add JWT expiry * fix: Consolidate get methods with JWT token resolution * chore: Add Annotation to Path, Query, and Body params * chore: run ruff formatter * chore: nits & add one exhaustive test of a query route * fix: undo change to fly.toml * fix: Langfuse tracing * Consolidate Get Methods (#96) * fix: Consolidate get methods with JWT token resolution * chore: Add Annotation to Path, Query, and Body params * chore: run ruff formatter * chore: nits & add one exhaustive test of a query route * fix: undo change to fly.toml --------- Co-authored-by: dr-frmr * fix: dev-667 fix streaming endpoint * fix: Anthropic Langfuse Tracing * fix: add scripts folder to dockerfile * fix: Remove redundant fields from pydantic schemas * fix: Add deeper protection on reserved collection * fix: Consolidate chat and stream methods * docs: Update Mintlify API Reference and Changelog * remove langchain guide, update architecture diagram * honcho mcp server * chore: Update .env template * update discord, temporarily remove other guides * Limit dialectic & deriver context usage with two-scale progressive summarization (#97) * WIP two tiered summaries * Move to process_item * Save user rep metamessage even if no message_id * Change number of messages per short summary * Fix broken mock * Remove prints * chore: fix test --------- Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com> * feat: Add Gemini Support, link facts to message, use 8b for dialectic fact queries * chore: Styling * chore: coderabbit nitpicks * keep dialectic guide * Add streaming guide * Remove TODO from dialectic guide * Fix JS snippets that referred to honcho singleton as client * Add App explanation to architecture page --------- Co-authored-by: Dani Balcells <18307962+danibalcells@users.noreply.github.com> Co-authored-by: doria <93405247+dr-frmr@users.noreply.github.com> Co-authored-by: dr-frmr Co-authored-by: vintro Co-authored-by: Daniel Balcells --- .env.template | 43 +- .github/workflows/fly-deploy.yml | 18 + .github/workflows/unittest.yml | 2 +- CHANGELOG.md | 22 +- CONTRIBUTING.md | 16 +- Dockerfile | 1 + README.md | 34 +- .../endpoint/apps/get-all-apps.mdx | 3 + docs/api-reference/endpoint/apps/get-app.mdx | 4 +- .../collections/get-collection-by-id.mdx | 3 - .../endpoint/collections/get-collection.mdx | 3 + .../endpoint/keys/create-key.mdx | 3 + .../metamessages/create-metamessage.mdx | 4 +- .../endpoint/metamessages/get-metamessage.mdx | 4 +- .../metamessages/get-metamessages-by-user.mdx | 3 - .../metamessages/get-metamessages.mdx | 4 +- .../metamessages/update-metamessage.mdx | 4 +- .../endpoint/sessions/get-session.mdx | 4 +- .../api-reference/endpoint/users/get-user.mdx | 4 +- docs/contributing/guidelines.mdx | 4 +- docs/contributing/self-hosting.mdx | 14 +- docs/getting-started/architecture.mdx | 123 +- docs/guides/dialectic-endpoint.mdx | 88 +- docs/guides/discord.mdx | 318 +- docs/guides/honcho-mcp.mdx | 62 + docs/guides/langchain.mdx | 94 - docs/guides/streaming-response.mdx | 240 + docs/mint.json | 21 +- docs/openapi.json | 2624 +- docs/package-lock.json | 19701 ++++++++++++++-- docs/package.json | 1 + migrations/env.py | 2 +- ...change_metamessages_to_user_level_with_.py | 161 + pyproject.toml | 9 +- scripts/__init__.py | 0 scripts/generate_jwt_secret.py | 38 + scripts/provision_db.py | 18 + src/agent.py | 542 +- src/crud.py | 651 +- src/db.py | 25 +- src/deriver/__main__.py | 8 +- src/deriver/consumer.py | 341 +- src/deriver/queue.py | 71 +- src/deriver/tom/README.md | 13 + src/deriver/tom/__init__.py | 62 +- src/deriver/tom/conversational.py | 4 +- src/deriver/tom/embeddings.py | 114 + src/deriver/tom/long_term.py | 216 + src/deriver/tom/single_prompt.py | 179 +- src/exceptions.py | 18 +- src/main.py | 57 +- src/models.py | 59 +- src/routers/apps.py | 108 +- src/routers/collections.py | 151 +- src/routers/documents.py | 112 +- src/routers/keys.py | 58 + src/routers/messages.py | 76 +- src/routers/metamessages.py | 132 +- src/routers/sessions.py | 271 +- src/routers/users.py | 119 +- src/schemas.py | 35 +- src/security.py | 208 +- src/utils/__init__.py | 21 + src/utils/history.py | 392 + src/utils/model_client.py | 541 + tests/conftest.py | 117 +- tests/routes/test_apps.py | 50 +- tests/routes/test_collections.py | 57 +- tests/routes/test_documents.py | 51 +- tests/routes/test_keys.py | 63 + tests/routes/test_messages.py | 19 +- tests/routes/test_metamessages.py | 98 +- tests/routes/test_scoped_api.py | 628 + tests/routes/test_sessions.py | 26 +- tests/routes/test_users.py | 4 +- tests/routes/test_validation_api.py | 190 +- tests/test_schema_validations.py | 13 +- tests/utils/test_model_client.py | 191 + uv.lock | 1416 +- 79 files changed, 26274 insertions(+), 4930 deletions(-) create mode 100644 .github/workflows/fly-deploy.yml create mode 100644 docs/api-reference/endpoint/apps/get-all-apps.mdx delete mode 100644 docs/api-reference/endpoint/collections/get-collection-by-id.mdx create mode 100644 docs/api-reference/endpoint/collections/get-collection.mdx create mode 100644 docs/api-reference/endpoint/keys/create-key.mdx delete mode 100644 docs/api-reference/endpoint/metamessages/get-metamessages-by-user.mdx create mode 100644 docs/guides/honcho-mcp.mdx delete mode 100644 docs/guides/langchain.mdx create mode 100644 docs/guides/streaming-response.mdx create mode 100644 migrations/versions/b765d82110bd_change_metamessages_to_user_level_with_.py create mode 100644 scripts/__init__.py create mode 100755 scripts/generate_jwt_secret.py create mode 100644 scripts/provision_db.py create mode 100644 src/deriver/tom/README.md create mode 100644 src/deriver/tom/embeddings.py create mode 100644 src/deriver/tom/long_term.py create mode 100644 src/routers/keys.py create mode 100644 src/utils/__init__.py create mode 100644 src/utils/history.py create mode 100644 src/utils/model_client.py create mode 100644 tests/routes/test_keys.py create mode 100644 tests/routes/test_scoped_api.py create mode 100644 tests/utils/test_model_client.py diff --git a/.env.template b/.env.template index c31cca36..cd4cdad8 100644 --- a/.env.template +++ b/.env.template @@ -1,23 +1,44 @@ CONNECTION_URI=postgresql+psycopg://testuser:testpwd@localhost:5432/honcho # sample for local database - # CONNECTION_URI=postgresql+psycopg://testuser:testpwd@database:5432/honcho # sample for docker-compose database -OPENAI_API_KEY= # Used for vector embeddings -ANTHROPIC_API_KEY= # Used for the deriver and dialectic API - -# Logging - -SENTRY_ENABLED=false # Set to true to enable Sentry logging and tracing +# Use something unique here if you want to share a database with other projects. +# Leave blank for public. Make sure to avoid `-` in name. +DATABASE_SCHEMA= # Auth -USE_AUTH_SERVICE=false -SECRET_KEY= +# Set to true to enable API authorization. Blank is equivalent to false. +USE_AUTH=false +# Required if USE_AUTH is true. Generate with scripts/generate_jwt_secret.py +AUTH_JWT_SECRET= + +# These are included for convenience in local testing if you want to quickly swap out providers +# but are not actually used by Honcho +OPENROUTER_API_KEY= +OPENROUTER_BASE_URL=https://openrouter.ai/api/v1 +CEREBRAS_API_KEY= +CEREBRAS_BASE_URL=https://api.cerebras.ai/v1 +GROQ_API_KEY= +GROQ_BASE_URL=https://api.groq.com/openai/v1 + +# These are the ones that are actually used by the model client +OPENAI_COMPATIBLE_BASE_URL= +OPENAI_COMPATIBLE_API_KEY= # Sentry +SENTRY_ENABLED=false SENTRY_DSN= # Deriver DERIVER_WORKERS=1 -TOM_METHOD="single_prompt" -USER_REPRESENTATION_METHOD="single_prompt" +# Anthropic +ANTHROPIC_API_KEY= +OPENAI_API_KEY= + +# Langfuse +LANGFUSE_SECRET_KEY= +LANGFUSE_PUBLIC_KEY= +LANGFUSE_HOST=https://us.cloud.langfuse.com + +# set logger level +LOG_LEVEL=INFO diff --git a/.github/workflows/fly-deploy.yml b/.github/workflows/fly-deploy.yml new file mode 100644 index 00000000..b0c246ed --- /dev/null +++ b/.github/workflows/fly-deploy.yml @@ -0,0 +1,18 @@ +# See https://fly.io/docs/app-guides/continuous-deployment-with-github-actions/ + +name: Fly Deploy +on: + push: + branches: + - main +jobs: + deploy: + name: Deploy app + runs-on: ubuntu-latest + concurrency: deploy-group # optional: ensure only one action runs at a time + steps: + - uses: actions/checkout@v4 + - uses: superfly/flyctl-actions/setup-flyctl@master + - run: flyctl deploy --remote-only + env: + FLY_API_TOKEN: ${{ secrets.FLY_API_TOKEN }} diff --git a/.github/workflows/unittest.yml b/.github/workflows/unittest.yml index 4b7b7574..733215e7 100644 --- a/.github/workflows/unittest.yml +++ b/.github/workflows/unittest.yml @@ -47,7 +47,7 @@ jobs: run: uv run pytest -x env: CONNECTION_URI: postgresql+psycopg://postgres:postgres@localhost:5432/test_db - USE_AUTH_SERVICE: false + USE_AUTH: false SENTRY_ENABLED: false OPENTELEMETRY_ENABLED: false OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} diff --git a/CHANGELOG.md b/CHANGELOG.md index 9588c304..6454d06d 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,14 +5,30 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](http://keepachangelog.com/) and this project adheres to [Semantic Versioning](http://semver.org/). +## [1.0.0] + +### Added + +- JWT based API authentication +- Configurable logging +- Consolidated LLM Inference via `ModelClient` class +- Dynamic logging configurable via environment variables + +### Changed + +- Deriver & Dialectic API to use Hybrid Memory Architecture +- Metamessages are not strictly tied to a message +- Database provisioning is a separate script instead of happening on startup +- Consolidated `session/chat` and `session/chat/stream` endpoints + ## [0.0.16] -## Added +### Added - Detailed custom exceptions for better error handling - CLAUDE.md for claude code -## Changed +### Changed - Deriver to use a new cognitive architecture that only updates on user messages and updates user representation to apply more confidence scores to its known @@ -22,7 +38,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/). - SQLAlchemy echo changed to false by default, can be enabled with SQL_DEBUG environment flag -## Fixed +### Fixed - Self-hosting documentation and README to mention `uv` instead of `poetry` diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index ca8e2676..44d6302f 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -91,10 +91,24 @@ that they are disabled you can verify the following environment variables are set to false. ```env -USE_AUTH_SERVICE=false +USE_AUTH=false SENTRY_ENABLED=false ``` +If you set `USE_AUTH` to true you will need to generate a JWT secret. You can +do this with the following command: + +```bash +python scripts/generate_jwt_secret.py +``` + +This will generate a JWT secret and print it to the console. You can then set +the `AUTH_JWT_SECRET` environment variable. This is required for `USE_AUTH`. + +```env +AUTH_JWT_SECRET= +``` + 5. Launch the API With the dependencies installed, a database setup and enabled with `pgvector`, diff --git a/Dockerfile b/Dockerfile index 0aeda081..2a4f0532 100644 --- a/Dockerfile +++ b/Dockerfile @@ -35,6 +35,7 @@ ENV PATH="/app/.venv/bin:$PATH" COPY --chown=app:app src/ /app/src/ COPY --chown=app:app migrations/ /app/migrations/ +COPY --chown=app:app scripts/ /app/scripts/ COPY --chown=app:app alembic.ini /app/alembic.ini EXPOSE 8000 diff --git a/README.md b/README.md index 3f6224a7..803891b7 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # 🫡 Honcho -![Static Badge](https://img.shields.io/badge/Version-0.0.16-blue) +![Static Badge](https://img.shields.io/badge/Version-1.0.0-blue) [![Discord](https://img.shields.io/discord/1016845111637839922?style=flat&logo=discord&logoColor=23ffffff&label=Plastic%20Labs&labelColor=235865F2)](https://discord.gg/plasticlabs) [![arXiv](https://img.shields.io/badge/arXiv-2310.06983-b31b1b.svg)](https://arxiv.org/abs/2310.06983) ![GitHub License](https://img.shields.io/github/license/plastic-labs/honcho) @@ -75,10 +75,10 @@ Below is a mapping of the different primitives. Apps └── Users ├── Sessions - │ ├── Messages - │ └── Metamessages - └── Collections - └── Documents + │ └── Messages + ├── Collections + │ └── Documents + └── Metamessages ``` Users familiar with APIs such as the OpenAI Assistants API will be familiar with @@ -105,18 +105,6 @@ The `Session` object represents a set of interactions a `User` has with an The `Message` represents an atomic interaction of a `User` in a `Session`. `Message`s are labed as either a `User` or AI message. -#### Metamessages - -A `Metamessage` is similar to a `Message` with different use case. They are -meant to be used to store intermediate inference from AI assistants or other -derived information that is separate from the main `User` `App` interaction -loop. For complicated prompting architectures like [metacognitive prompting](https://arxiv.org/abs/2310.06983) -metamessages can store thought and reflection steps along with having developer -information such as logs. - -Each `Metamessage` is associated with a `Message`. The convention we recommend -is to attach a `Metamessage` to the `Message` it was derived from or based on. - #### Collections At a high level a `Collection` is a named group of `Documents`. Developers @@ -132,6 +120,18 @@ PDF files, and more. As stated before a `Document` is vector embedded data stored in a `Collection`. +#### Metamessages + +A `Metamessage` is similar to a `Message` with different use case. They are +meant to be used to store intermediate inference from AI assistants or other +derived information that is separate from the main `User` `App` interaction +loop. For complicated prompting architectures like [metacognitive prompting](https://arxiv.org/abs/2310.06983) +metamessages can store thought and reflection steps along with having developer +information such as logs. + +Each `Metamessage` is associated with a `User` with the ability to optionally +tie to a `Session` and a `Message`. + ### Insights The Insight functionality of Honcho is built on top of the Storage service. As diff --git a/docs/api-reference/endpoint/apps/get-all-apps.mdx b/docs/api-reference/endpoint/apps/get-all-apps.mdx new file mode 100644 index 00000000..52b4472f --- /dev/null +++ b/docs/api-reference/endpoint/apps/get-all-apps.mdx @@ -0,0 +1,3 @@ +--- +openapi: post /v1/apps/list +--- \ No newline at end of file diff --git a/docs/api-reference/endpoint/apps/get-app.mdx b/docs/api-reference/endpoint/apps/get-app.mdx index 34e1def7..10f471a9 100644 --- a/docs/api-reference/endpoint/apps/get-app.mdx +++ b/docs/api-reference/endpoint/apps/get-app.mdx @@ -1,3 +1,3 @@ --- -openapi: get /v1/apps/{app_id} ---- \ No newline at end of file +openapi: get /v1/apps +--- diff --git a/docs/api-reference/endpoint/collections/get-collection-by-id.mdx b/docs/api-reference/endpoint/collections/get-collection-by-id.mdx deleted file mode 100644 index 390ea384..00000000 --- a/docs/api-reference/endpoint/collections/get-collection-by-id.mdx +++ /dev/null @@ -1,3 +0,0 @@ ---- -openapi: get /v1/apps/{app_id}/users/{user_id}/collections/{collection_id} ---- \ No newline at end of file diff --git a/docs/api-reference/endpoint/collections/get-collection.mdx b/docs/api-reference/endpoint/collections/get-collection.mdx new file mode 100644 index 00000000..014ecae9 --- /dev/null +++ b/docs/api-reference/endpoint/collections/get-collection.mdx @@ -0,0 +1,3 @@ +--- +openapi: get /v1/apps/{app_id}/users/{user_id}/collections +--- \ No newline at end of file diff --git a/docs/api-reference/endpoint/keys/create-key.mdx b/docs/api-reference/endpoint/keys/create-key.mdx new file mode 100644 index 00000000..6a522ffb --- /dev/null +++ b/docs/api-reference/endpoint/keys/create-key.mdx @@ -0,0 +1,3 @@ +--- +openapi: post /v1/keys +--- \ No newline at end of file diff --git a/docs/api-reference/endpoint/metamessages/create-metamessage.mdx b/docs/api-reference/endpoint/metamessages/create-metamessage.mdx index 755d8f3d..257301c3 100644 --- a/docs/api-reference/endpoint/metamessages/create-metamessage.mdx +++ b/docs/api-reference/endpoint/metamessages/create-metamessage.mdx @@ -1,3 +1,3 @@ --- -openapi: post /v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages ---- \ No newline at end of file +openapi: post /v1/apps/{app_id}/users/{user_id}/metamessages +--- diff --git a/docs/api-reference/endpoint/metamessages/get-metamessage.mdx b/docs/api-reference/endpoint/metamessages/get-metamessage.mdx index 187df41c..f24428dc 100644 --- a/docs/api-reference/endpoint/metamessages/get-metamessage.mdx +++ b/docs/api-reference/endpoint/metamessages/get-metamessage.mdx @@ -1,3 +1,3 @@ --- -openapi: get /v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages/{metamessage_id} ---- \ No newline at end of file +openapi: get /v1/apps/{app_id}/users/{user_id}/metamessages/{metamessage_id} +--- diff --git a/docs/api-reference/endpoint/metamessages/get-metamessages-by-user.mdx b/docs/api-reference/endpoint/metamessages/get-metamessages-by-user.mdx deleted file mode 100644 index ca013d21..00000000 --- a/docs/api-reference/endpoint/metamessages/get-metamessages-by-user.mdx +++ /dev/null @@ -1,3 +0,0 @@ ---- -openapi: post /v1/apps/{app_id}/users/{user_id}/metamessages/list ---- \ No newline at end of file diff --git a/docs/api-reference/endpoint/metamessages/get-metamessages.mdx b/docs/api-reference/endpoint/metamessages/get-metamessages.mdx index 629c64b5..31fa3ad8 100644 --- a/docs/api-reference/endpoint/metamessages/get-metamessages.mdx +++ b/docs/api-reference/endpoint/metamessages/get-metamessages.mdx @@ -1,3 +1,3 @@ --- -openapi: post /v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages/list ---- \ No newline at end of file +openapi: post /v1/apps/{app_id}/users/{user_id}/metamessages/list +--- diff --git a/docs/api-reference/endpoint/metamessages/update-metamessage.mdx b/docs/api-reference/endpoint/metamessages/update-metamessage.mdx index c94afcb0..a5635edf 100644 --- a/docs/api-reference/endpoint/metamessages/update-metamessage.mdx +++ b/docs/api-reference/endpoint/metamessages/update-metamessage.mdx @@ -1,3 +1,3 @@ --- -openapi: put /v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages/{metamessage_id} ---- \ No newline at end of file +openapi: put /v1/apps/{app_id}/users/{user_id}/metamessages/{metamessage_id} +--- diff --git a/docs/api-reference/endpoint/sessions/get-session.mdx b/docs/api-reference/endpoint/sessions/get-session.mdx index 18c8b94f..de833e08 100644 --- a/docs/api-reference/endpoint/sessions/get-session.mdx +++ b/docs/api-reference/endpoint/sessions/get-session.mdx @@ -1,3 +1,3 @@ --- -openapi: get /v1/apps/{app_id}/users/{user_id}/sessions/{session_id} ---- \ No newline at end of file +openapi: get /v1/apps/{app_id}/users/{user_id}/sessions +--- diff --git a/docs/api-reference/endpoint/users/get-user.mdx b/docs/api-reference/endpoint/users/get-user.mdx index 420a260f..9efe2e3a 100644 --- a/docs/api-reference/endpoint/users/get-user.mdx +++ b/docs/api-reference/endpoint/users/get-user.mdx @@ -1,3 +1,3 @@ --- -openapi: get /v1/apps/{app_id}/users/{user_id} ---- \ No newline at end of file +openapi: get /v1/apps/{app_id}/users +--- diff --git a/docs/contributing/guidelines.mdx b/docs/contributing/guidelines.mdx index 1e39a270..5d8b1b7b 100644 --- a/docs/contributing/guidelines.mdx +++ b/docs/contributing/guidelines.mdx @@ -14,4 +14,6 @@ a project manager. Feel free to join us in our [discord](http://discord.gg/plasticlabs) to discuss your changes or get help. Your changes will undergo a period of testing and discussion before finally -being entered into the `main` branch and being staged for release +being entered into the `main` branch and being staged for release. For more +details, check out our [contributing](https://github.com/plastic-labs/honcho/blob/main/CONTRIBUTING.md) +document. diff --git a/docs/contributing/self-hosting.mdx b/docs/contributing/self-hosting.mdx index 0f752b56..c9d36812 100644 --- a/docs/contributing/self-hosting.mdx +++ b/docs/contributing/self-hosting.mdx @@ -18,7 +18,7 @@ The minimum poetry version is `0.4.9` ### Setup Once the dependencies are installed on the system run the following steps to get -the local project setup. +the local project setup. 1. Clone the repository @@ -49,14 +49,14 @@ source honcho/.venv/bin/activate 3. Set up a database -Honcho utilized [Postgres](https://www.postgresql.org/) for its database with +Honcho utilized [Postgres](https://www.postgresql.org/) for its database with pgvector. An easy way to get started with a postgresdb is to create a project with [Supabase](https://supabase.com/) A `docker-compose` template is also available with a database configuration -available. +available. -4. Edit the environment variables. +4. Edit the environment variables. Honcho uses a `.env` file for managing runtime environment variables. A `.env.template` file is included for convenience. Several of the configurations @@ -75,10 +75,10 @@ ANTHROPIC_API_KEY= # API Key for Anthropic used for the deriver and dialectic AP The template has the additional functionality disabled by default. To ensure that they are disabled you can verify the following environment variables are -set to false. +set to false. ```env -USE_AUTH_SERVICE=false +USE_AUTH=false SENTRY_ENABLED=false ``` @@ -99,7 +99,7 @@ necessary tables for Honcho to operate. As mentioned earlier a `docker-compose` template is included for running Honcho. As an alternative to running Honcho locally it can also be run with the compose -template. +template. Copy the template and update the appropriate environment variables before launching the service. diff --git a/docs/getting-started/architecture.mdx b/docs/getting-started/architecture.mdx index db622500..3fcd244c 100644 --- a/docs/getting-started/architecture.mdx +++ b/docs/getting-started/architecture.mdx @@ -4,22 +4,24 @@ description: 'Learn the core primitives and the structure of Honcho' icon: 'building' --- -Honcho is a user context management system for AI powered applications. It is -inspired by but not a 1:1 mapping of the OpenAI Assistants API. While we are -building many similar primitives, we are going about it differently. +Honcho is a user context management system for AI powered applications. +The storage concepts are inspired by, but not a 1:1 mapping of, the OpenAI +Assistants API. The insights concepts are inspired by cognitive science, +philosophy, and machine learning. Honcho is open source. We believe trust and transparency are vital for developing AI technology. We're also focused on using and supporting existing tools rather than developing from scratch. -One of the main objectives of the Honcho project is to promote community -exploration of *user models*. Language models are highly capable of modeling -human psychology. By building a data management framework that is user-centric, -we aim to address not only practical application development issues (like -scaling, statefulness, etc.) but also kickstart exploration of the design space -of what's possible in terms of building user models. You can read more about -Honcho's origin, inspiration and philosophy on our -[blog](https://blog.plasticlabs.ai). +We focus on flexible, user-centric storage primitives to promote community +exploration of novel memory frameworks and the usage of the +[Dialectic API](https://blog.plasticlabs.ai/blog/Introducing-Honcho's-Dialectic-API) +to support them. Language models are highly capable of modeling human psychology. +By building a data management framework that is user-centric, we aim to address +not only practical application development issues (like scaling, statefulness, +etc.) but also kickstart exploration of the design space of what's possible +given access to rich user models. You can read more about Honcho's origin, +inspiration and philosophy on our [blog](https://blog.plasticlabs.ai). ## Core Primitives @@ -29,11 +31,92 @@ Using Honcho has the following flow: 3. Create a `Session` for a `User`. 4. Create a `Collection` for a `User` 5. Add `Message`s to a `User`'s `Session`. -6. Add `Metamessage`s to `User`'s `Message`s +6. Add `Metamessage`s to a `User` (optional links to `Session`, `Message`) 7. Add `Document`s to a `User`'s `Collection` -![DB Schema](../images/db_schema.png) +```mermaid +erDiagram + App ||--o{ User : "has" + User ||--o{ Session : "has" + User ||--o{ Collection : "has" + User ||--o{ Metamessage : "has" + Session ||--o{ Message : "contains" + Session ||--o{ Metamessage : "has" + Message ||--o{ Metamessage : "has" + Collection ||--o{ Document : "contains" + + App { + BigInteger id PK + string public_id + string name + datetime created_at + jsonb h_metadata "metadata" + } + + User { + BigInteger id PK + string public_id + string name + jsonb h_metadata "metadata" + datetime created_at + string app_id FK + } + + Session { + BigInteger id PK + string public_id + boolean is_active + jsonb h_metadata "metadata" + datetime created_at + string user_id FK + } + + Message { + BigInteger id PK + string public_id + string session_id FK + boolean is_user + string content + jsonb h_metadata "metadata" + datetime created_at + } + + Metamessage { + BigInteger id PK + string public_id + string metamessage_type + string content + string user_id FK + string session_id FK "nullable" + string message_id FK "nullable" + datetime created_at + jsonb h_metadata "metadata" + } + + Collection { + BigInteger id PK + string public_id + string name + datetime created_at + jsonb h_metadata "metadata" + string user_id FK + } + + Document { + BigInteger id PK + string public_id + jsonb h_metadata "metadata" + string content + vector embedding "1536" + datetime created_at + string collection_id FK + } +``` + +### Apps + +An `App` is the highest-level primitive in Honcho. It is the scope that all of your `Users` are bound to. ### Users @@ -54,9 +137,15 @@ This is pretty straightforward. ### Metamessages -Plenty of applications have intermediate steps between `User` input and the -response that gets sent. The `Metamessage` object allows you to store those -intermediate steps and link them to the messages they were derived from. +Success in LLM applications is dependent on elegant context management, so we +provide a `Metamessage` object for flexible context storage and construction. Each +`Metamessage` is tied to a `User` object via the required `user_id` argument. Keeping +this separate from the core user-assistant message history ensures the +insights service running ambiently is doing so on authentic ground truth +We've found this particularly useful for storing intermediate inferences, +constructing very specific chat histories, and more. Metamessages can optionally be +attached to sessions and/or messages, so constructing historical context for inference is +as easy as possible. ### Collections @@ -80,4 +169,4 @@ developers implement their own solutions that without a doubt increase overhead and maintenance. Our goal with Honcho is to provide a simple and flexible storage framework accompanied by a smooth developer experience to ease pains building the cumbersome parts of LLM applications. We hope this will allow -developers more freedom to explore exciting, yet-to-be-discovered areas! \ No newline at end of file +developers more freedom to explore exciting, yet-to-be-discovered areas! diff --git a/docs/guides/dialectic-endpoint.mdx b/docs/guides/dialectic-endpoint.mdx index 601ca19c..5d86d6d5 100644 --- a/docs/guides/dialectic-endpoint.mdx +++ b/docs/guides/dialectic-endpoint.mdx @@ -1,38 +1,25 @@ --- title: "Dialectic Endpoint" -description: "An endpoint for easily reasoning about your users" +description: "An endpoint for reasoning about your users" icon: "comments" --- -> This guide goes over automatic insights generated by Honcho. An example -> of this being used can be found in [Curation Buddy](https://github.com/vintrocode/curation-buddy) - -Honcho will do automatic reasoning for you to derive facts about users and -allow your own agents to use them to reason about the user's needs. There are -two aspects to this: - -1. Automatic Fact Derivation -2. Dialectic Endpoint +Honcho by default runs ambient inference on top of the `message` objects you store. Those messages serve as the ground truth upon which facts about the user are derived and stored. The **Dialectic Endpoint** is the natural language interface through which insights are synthesized from those facts. We believe [intellectual respect](https://blog.plasticlabs.ai/extrusions/Extrusion-02.24) for LLMs is paramount in building effective AI agents/apps. It follows that the LLM should know better than any human what would aid them in their generation task. Thus, the Dialectic endpoint exists for flexible agent-to-agent communication. ## Automatic Fact Derivation -When you are saving conversations in sessions and messages via Honcho an automatic callback is run that -will reason about the conversations and store facts in a `collection` named **Honcho**. This is a reserved `collection` -specifically for the backend Honcho agent to interact with. - -These facts are derived asynchonously and automatically as your users interact with your agents. +On every message written to a session, an automatic callback is run that will reason about the conversation and store facts in a `collection` named `honcho`. This is a reserved `collection` specifically for the backend Honcho agent to interact with. ## Dialectic Endpoint -You can make use the automatically derived facts in the `Honcho` collection directly by querying the documents stored in it, -but an alternative is to use the *Dialectic Endpoint`. What this is, is an endpoint that allows you to talk to an agent that -can automatically take the collection into their context and reason about the users with you. +You can query the automatically derived facts in the `honcho` collection directly, or you can offload this task to our agent and use the Dialectic endpoint. This endpoint allows you to define logic enabling your agent to talk to our agent that automatically retrieves and synthesizes facts from the collection. -This chat interface is exposed via the `Sessions` object. +This chat interface is exposed via the `chat` endpoint. It accepts a string or a list of strings. Below is some example code on how this works. -Belows is some example code on how this works. +## Prerequisites -```python + +```python Python from honcho import Honcho honcho = Honcho() @@ -46,11 +33,64 @@ user = honcho.apps.users.get_or_create(app_id=app.id, name="demo-user") # create a new session session = honcho.apps.users.session.create(app_id=app.id, user_id=user.id) -# Talk to the dialectic agent to reason about their needs -answer = honcho.apps.users.session.chat(app_id=app.id, user_id=user.id, session_id=session.id, query="What is the user's favorite way of completing the task") +# (assuming some messages have been written to Honcho for the deriver to use) ``` - +```javascript NodeJS +import Honcho from 'honcho-ai'; + +const honcho = new Honcho(); // defaults to demo server + +// Create or get an existing App +const app = await honcho.apps.getOrCreate('demo-app'); + +// create or get user +const user = await honcho.apps.users.getOrCreate(app.id, 'demo-user'); + +// create a new session (need to send empty body because it's a POST request) +const session = await honcho.apps.users.sessions.create(app.id, user.id, {}); + +// (assuming some messages have been written to Honcho for the deriver to use) +``` + +## Static Dialectic Call + + +```python Python +query = "What is the user's favorite way of completing the task?" +answer = honcho.apps.users.session.chat(app_id=app.id, user_id=user.id, session_id=session.id, queries=query) +``` + +```javascript NodeJS +const query = 'What is the user's favorite way of completing the task?' +const DialecticResponse = await honcho.apps.users.sessions.chat(app.id, user.id, session.id, { + queries: query, +}); +``` + + +## Streaming Dialectic Call + + +```python Python +with honcho.apps.users.sessions.with_streaming_response.stream( + app_id=app.id, + user_id=user.id, + session_id=session.id, + queries="What do we know about the user", + ) as response: + print(response) + for line in response.iter_text(): + print(line) + time.sleep(0.025) +``` + +```javascript NodeJS + +``` + + +We've designed the Dialectic endpoint to be infinitely flexible. We wrote an incomplete list of ideas on how to use it on our blog [here](https://blog.plasticlabs.ai/blog/Introducing-Honcho's-Dialectic-API#how-it-works). diff --git a/docs/guides/discord.mdx b/docs/guides/discord.mdx index cc32361a..797f15c2 100644 --- a/docs/guides/discord.mdx +++ b/docs/guides/discord.mdx @@ -5,7 +5,7 @@ description: "Discord is a powerful chat application that handles many UI compli sidebarTitle: 'Discord' --- -> Example code is available on [GitHub](https://github.com/plastic-labs/honcho-python/blob/main/examples/discord/roast-bot/main.py) +> Example code is available on [GitHub](https://github.com/plastic-labs/discord-python-starter) Any application interface that defines logic based on events and supports special commands can work easily with Honcho. Here's how to use Honcho with @@ -19,56 +19,83 @@ Most Discord bots have async functions that listen for specific events, the most ```python @bot.event async def on_message(message): + """Event that is run when a message is sent in a channel or DM that the bot has access to""" + global last_message_id if message.author == bot.user: + # ensure the bot does not reply to itself return - user_id = f"discord_{str(message.author.id)}" - user = honcho.apps.users.get_or_create(name=user_id, app_id=app.id) + is_dm = isinstance(message.channel, discord.DMChannel) + is_reply_to_bot = ( + message.reference and message.reference.resolved.author == bot.user + ) + is_mention = bot.user.mentioned_in(message) - # Get the session associated with the user and location - location_id = str(message.channel.id) # Get the channel id for the message + if is_dm or is_reply_to_bot or is_mention: + # Remove the bot's mention from the message content if present + input = message.content.replace(f"<@{bot.user.id}>", "").strip() - sessions = [ - session - for session in honcho.apps.users.sessions.list( - user_id=user.id, app_id=app.id, is_active=True, location_id=location_id + # If the message is empty after removing the mention, ignore it + if not input: + return + + # Get a user object for the message author + user_id = f"discord_{str(message.author.id)}" + user = honcho.apps.users.get_or_create(name=user_id, app_id=app.id) + + # Use the channel ID as the location_id (for DMs, this will be unique to the user) + location_id = str(message.channel.id) + + # Get or create a session for this user and location + session, _ = get_session(user.id, location_id, create=True) + + # Get messages + history_iter = honcho.apps.users.sessions.messages.list( + app_id=app.id, session_id=session.id, user_id=user.id ) - ] + history = list(msg for msg in history_iter) - if len(sessions) > 0: - session = sessions[0] - else: - session = honcho.apps.users.sessions.create(user_id=user.id, app_id=app.id, location_id=location_id) + # Add user message to session + user_msg = honcho.apps.users.sessions.messages.create( + app_id=app.id, + user_id=user.id, + session_id=session.id, + content=input, + is_user=True, + ) + last_message_id = user_msg.id - history = [ - message - for message in honcho.apps.users.sessions.messages.list(session_id=session.id, app_id=app.id, user_id=user.id) - ] - chat_history = messages_to_langchain(history) + async with message.channel.typing(): + response = llm(input, history) - inp = message.content - honcho.apps.users.sessions.messages.create( - app_id=app.id, - user_id=user.id, - session_id=session.id, - content=input, - is_user=True, - ) + if len(response) > 1500: + # Split response into chunks at newlines, keeping under 1500 chars + chunks = [] + current_chunk = "" + for line in response.splitlines(keepends=True): + if len(current_chunk) + len(line) > 1500: + chunks.append(current_chunk) + current_chunk = line + else: + current_chunk += line + if current_chunk: + chunks.append(current_chunk) + for chunk in chunks: + await message.channel.send(chunk) + else: + await message.channel.send(response) - async with message.channel.typing(): - response = await chain.ainvoke({"chat_history": chat_history, "input": inp}) - await message.channel.send(response) - - honcho.apps.users.sessions.messages.create( - app_id=app.id, - user_id=user.id, - session_id=session.id, - content=response, - is_user=False, - ) + # Add bot message to session + honcho.apps.users.sessions.messages.create( + app_id=app.id, + user_id=user.id, + session_id=session.id, + content=response, + is_user=False, + ) ``` -Let's break down what each chunk of code is doing... +Let's break down what this code is doing... ```python @bot.event async def on_message(message): @@ -79,67 +106,114 @@ async def on_message(message): This is how you define an event function in `py-cord` that listens for messages and checks that the bot doesn't respond to itself. ```python +is_dm = isinstance(message.channel, discord.DMChannel) +is_reply_to_bot = ( + message.reference and message.reference.resolved.author == bot.user +) +is_mention = bot.user.mentioned_in(message) +``` + +These lines check what kind of message is being sent in Discord, which is a useful condition to check before entering the reply logic. The code inside that if-statement is commented quite well, so we'll just go over the relevant Honcho parts. + +```python +# Get a user object for the message author user_id = f"discord_{str(message.author.id)}" +user = honcho.apps.users.get_or_create(name=user_id, app_id=app.id) +``` + +Here we're getting or creating a user for an app that's been defined at the top of the file. + +```python +# Use the channel ID as the location_id (for DMs, this will be unique to the user) location_id = str(message.channel.id) + +# Get or create a session for this user and location +session, _ = get_session(user.id, location_id, create=True) ``` -Honcho accepts a `location_id` argument to help separate out locations messages were sent (which is convenient for Discord channels). +Here we're using the discord channel ID as a unique `location_id` to attach as metadata to the session. Then we have a nice [helper function](https://github.com/plastic-labs/discord-python-starter/blob/main/src/bot.py#L85) to take care of some of the session querying logic--we'll dive into that shortly. ```python -sessions = [ - session - for session in honcho.apps.users.sessions.list( - user_id=user.id, app_id=app.id, is_active=True, location_id=location_id +# Get messages +history_iter = honcho.apps.users.sessions.messages.list( + app_id=app.id, session_id=session.id, user_id=user.id +) +history = list(msg for msg in history_iter) +``` + +When you call the `list` method, it returns an iterable which you can quickly loop over to create a list of `Message` objects. Then, we make the call to the LLM using another neat [helper function](https://github.com/plastic-labs/discord-python-starter/blob/main/src/bot.py#L52) that we will cover. + +## Helper functions + +The first helper function we create is called `get_session`. This simplifies a lot of our session-querying logic. + +```python +def get_session(user_id, location_id, create=False): + # Get an existing session for the user and location or optionally create a new one if none exists. + # Returns a tuple of (session, is_new) where is_new indicates if a new session was created. + + # Query for *active* sessions with both user_id and location_id + sessions_iter = honcho.apps.users.sessions.list( + app_id=app.id, user_id=user_id, reverse=True, is_active=True + ) + sessions = list(session for session in sessions_iter) + + # Find the right session + for session in sessions: + if session.metadata.get("location_id") == location_id: + return session, False + + # If no session is found and create is True, create a new one + if create: + print("No active session found, creating new one") + return honcho.apps.users.sessions.create( + user_id=user_id, + app_id=app.id, + metadata={"location_id": location_id}, + ), True + + return None, False +``` + +You can see the `list` method on the sessions object similarly returns an iterable. This is a common pattern in Honcho--use list comprehension to create your new python list. Then loop through those session objects to find the appropriate `location_id` in the metadata, and if none are found then create a new session. You'll also notice we list messages in `reverse=True` order--this means you will get the most recent ones first. We also support native filtering by active sessions. + +The next helper function we create is called `llm`. This simplifies constructing the chat message object we're going to send to the inference provider. + +```python +def llm(prompt, previous_chats=None): + messages = [] + + # Add system message with documentation context + messages.append( + { + "role": "system", + "content": f"You are a helpful assistant." + } + ) + + if previous_chats: + messages.extend( + [ + {"role": "user" if msg.is_user else "assistant", "content": msg.content} + for msg in previous_chats + ] ) - ] -if len(sessions) > 0: - session = sessions[0] -else: - session = honcho.apps.users.sessions.create(user_id=user.id, app_id=app.id, location_id=location_id) + + + messages.append({"role": "user", "content": prompt}) + + try: + completion = openai.chat.completions.create( + model=MODEL_NAME, + messages=messages, + ) + return completion.choices[0].message.content + except Exception as e: + print(e) + return f"Error: {e}" ``` -Here we're querying honcho for the user's sessions based on the location (channel) they're in. This will get all the sessions, so the if statement just pops the most recent one (if there are many) or creates a new one if none exist. - -```python -history = [ - message - for message in honcho.apps.users.sessions.messages.list(session_id=session.id, app_id=app.id, user_id=user.id) - ] -chat_history = messages_to_langchain(history) - -# Add user message to session -input = message.content -honcho.apps.users.sessions.messages.create( - app_id=app.id, - user_id=user.id, - session_id=session.id, - content=input, - is_user=True, -) - -async with message.channel.typing(): - response = await chain.ainvoke({"chat_history": chat_history, "input": inp}) - await message.channel.send(response) - -# Add bot message to session -honcho.apps.users.sessions.messages.create( - app_id=app.id, - user_id=user.id, - session_id=session.id, - content=response, - is_user=False, -) -``` - -This chunk is all about constructing the object to send to an LLM API. We get -the messages from a `session` and construct a `chat_history` object with a -quick utility function (more on that in the [Langchain](./langchain) guide). -Then, we access the user message via `message.content` and add it to Honcho. -The `async with` method allows the bot to show that it's "typing" while waiting -for an LLM response and then uses `message.channel.send` to respond to the -user. We can then add that AI response to Honcho with the same -`session.create_message` method, this time specifying that this message did not -come from a user with `is_user=False`. +Note that `messages` is a list of dictionaries that are individually defined with key-value pairs for roles and content. We again use list comprehension to unpack historical message objects into the list that we send to the chat completions method. Honcho `Message` objects store role and content natively to make this context construction as simple as possible. If you're interested in learning more about native Honcho objects, you can check out the [`models.py`](https://github.com/plastic-labs/honcho/blob/main/src/models.py) file. ## Slash Commands @@ -147,38 +221,40 @@ Discord bots also offer slash command functionality. We can use Honcho to do interesting things via slash commands. Here's a simple example: ```python -@bot.slash_command(name = "restart", description = "Restart the Conversation") +@bot.slash_command( + name="restart", + description="Reset all of your messaging history with Honcho in this channel.", +) async def restart(ctx): - user_id=f"discord_{str(ctx.author.id)}" - user = honcho.apps.users.get_or_create(name=user_id, app_id=app.id) - location_id=str(ctx.channel_id) - sessions = [ - session - for session in honcho.apps.users.sessions.list( - user_id=user.id, app_id=app.id, is_active=True, location_id=location_id - ) - ] - if len(sessions) > 0: - honcho.apps.users.sessions.delete(app_id=app.id, user_id=user.id, session_id=sessions[0].id) + print(f"restarting conversation for {ctx.author.name}") + async with ctx.typing(): + user_name = f"discord_{str(ctx.author.id)}" + user = honcho.apps.users.get_or_create(name=user_name, app_id=app.id) + location_id = str(ctx.channel_id) + + # Get existing session + session, _ = get_session(user.id, location_id, create=False) + + if session: + # Delete the session + honcho.apps.users.sessions.delete( + app_id=app.id, user_id=user.id, session_id=session.id + ) + + msg = "The conversation has been restarted." - msg = "Great! The conversation has been restarted. What would you like to talk about?" await ctx.respond(msg) ``` -This slash command restarts a conversation with a bot. In that case, we want to remove that session from storage. You can see we follow the same steps to access the user metadata via commands from the application interface: -```python -user_id=f"discord_{str(ctx.author.id)}" -user = honcho.apps.users.get_or_create(name=user_id, app_id=app.id) -location_id=str(ctx.channel_id) -``` -Then we can retrieve and delete the session associated with that metadata: -```python -sessions = [ - session - for session in honcho.apps.users.sessions.list( - user_id=user.id, app_id=app.id, is_active=True, location_id=location_id - ) -] -if len(sessions) > 0: - honcho.apps.users.sessions.delete(app_id=app.id, user_id=user.id, session_id=sessions[0].id) -``` +This slash command restarts a conversation with a bot. In Honcho, the `delete` method marks a session's `is_active` field to `False`. + +## Recap + +How you use Honcho is tightly coupled with the client you're building in. Here, Discord serves as an example of an interactive chat interface. We're just scratching the surface of things you can do with Honcho, but we learned some key patterns: +- how to register users +- how to work with iterables when listing sessions, messages +- how to attach metadata to Honcho objects (like `location_id` on sessions) +- how to sort and filter when calling list methods + +You are well on your way to becoming a context construction master! Stay tuned for more in-depth examples. If you want a challenge, try deciphering how we construct context in one of our apps, [Bloom](https://github.com/plastic-labs/tutor-gpt/blob/main/app/Chat.tsx). + diff --git a/docs/guides/honcho-mcp.mdx b/docs/guides/honcho-mcp.mdx new file mode 100644 index 00000000..56a45db8 --- /dev/null +++ b/docs/guides/honcho-mcp.mdx @@ -0,0 +1,62 @@ +--- +title: "Honcho MCP" +icon: 'star-of-life' +description: "Use Honcho in Claude Desktop" +sidebarTitle: 'Claude Desktop' +--- + +You can let Claude use Honcho to manage its own memory in the native desktop app by using the Honcho MCP integration! Follow these steps: + +1. Clone the `honcho-mcp` repo: + +``` +git clone git@github.com:plastic-labs/honcho-mcp.git +``` + +2. Navigate into the `honcho-mcp` folder. + +``` +cd honcho-mcp +``` + +3. Sync the virtual environment. This package uses [uv](https://docs.astral.sh/uv/), [install](https://docs.astral.sh/uv/#installation) if you haven't. + +``` +uv sync +``` + +4. In Claude Desktop, go to the *top left Mac Toolbar* Settings > Developer and click "Edit Config" + +5. Add the following (and update paths!): + +``` +{ + "mcpServers": { + "Honcho": { + "command": "/path/to/uv", + "args": [ + "run", + "--with", + "mcp[cli]", + "mcp", + "run", + "/path/to/honcho-mcp/main.py" + ] + } + } +} +``` + +You probably will need to put the full path to the uv executable in the command field. You can get this by running `which uv` on MacOS/Linux or `where uv` on Windows. + +6. Restart the Claude Desktop app. Upon relaunch it should start Honcho and the tools should be available! + +Just note that, by default, the MCP server is set up to use the Honcho Demo server, which only persists data for 7 days. If you're using the hosted version of Honcho, copy the `.env.template` to a proper `.env` file and update the URL and API key variables accordingly. + +## Project Instructions + +Finally, Claude needs instructions on how to use Honcho. The Desktop app doesn't allow you to add system prompts directly, but you can create a project and paste these [instructions](https://github.com/plastic-labs/honcho-mcp/blob/main/instructions.txt) into the "Project Instructions" field. + +Be sure to update the \ and \ variables in the instructions.txt file. + +Claude should then query for insights before responding and write your messages to storage! If you come up with more creative ways to get Claude to manage its own memory with Honcho, feel free to [let us know](https://discord.gg/plasticlabs) or make a PR on this [repo](https://github.com/plastic-labs/honcho-mcp/tree/main)! \ No newline at end of file diff --git a/docs/guides/langchain.mdx b/docs/guides/langchain.mdx deleted file mode 100644 index c2960cd3..00000000 --- a/docs/guides/langchain.mdx +++ /dev/null @@ -1,94 +0,0 @@ ---- -title: 'LangChain Integration 🦜⛓️' -sidebarTitle: 'LangChain' -description: 'Using Honcho with LangChain with drop-in primitives' -icon: 'bird' ---- - -You can use Honcho to manage user context around LLM frameworks like LangChain. First, import the appropriate packages: - -```python -from honcho import Honcho - -from langchain_openai import ChatOpenAI -from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder -from langchain_core.output_parsers import StrOutputParser -from langchain_core.messages import AIMessage, HumanMessage - -from dotenv import load_dotenv # for loading in LLM API keys - -load_dotenv() # assumes you have a .env file with OPENAI_API_KEY defined -``` - -Next let's instantiate our Honcho client: - -```python -honcho = Honcho(environment="demo") -app_name = "LangChain App" -app = honcho.apps.get_or_create(name=app_name) # create or get app - -user_name = str(uuid4()) -user = honcho.apps.users.get_or_create(app_id=app.id, name=user_name) # create or get user -``` - -Then we can define our chain using the LangChain Expression Language ([LCEL](https://python.langchain.com/docs/expression_language/why)): -```python -prompt = ChatPromptTemplate.from_messages([ - ("system", "You are a helpful assistant."), - MessagesPlaceholder(variable_name="chat_history"), - ("user", "{input}") -]) -model = ChatOpenAI(model="gpt-3.5-turbo") -output_parser = StrOutputParser() - -chain = prompt | model | output_parser -``` - -Honcho returns lists of `Message` objects when queried using a built-in method like `get_messages()`, so a quick utility function is needed to change the list format to message objects LangChain expects: - -```python -def messages_to_langchain(messages: List): - new_messages = [] - for message in messages: - if message.is_user: - new_messages.append(HumanMessage(content=message.content)) - else: - new_messages.append(AIMessage(content=message.content)) - return new_messages -``` - -This method is importable with the following statement - -```python -from honcho.lib.ext.langchain import messages_to_langchain -``` - -Now we can structure Honcho calls around our LLM inference: -```python -sessions = [ - session for session in - honcho.apps.users.sessions.list( - app_id=app.id, - user_id=user.id, - location_id=location_id - ) -] # args come from application logic -session = sessions[0] # most recent session for user -history = [ - message for message in - honcho.apps.users.sessions.messages.list( - app_id=app.id, - user_id=user.id, - session_id=session.id - ) -] -chat_history = messages_to_langchain(history) # convert messages for LangChain -inp = "Here's a user message!" -honcho.apps.users.sessions.messages.create(app_id=app.id, user_id=user.id, is_user=True, content=inp) - -response = await chain.ainvoke({"chat_history": chat_history, "input": inp}) - -honcho.apps.users.sessions.messages.create(app_id=app.id, user_id=user.id, is_user=False, content=response) -``` - -Here we query messages from a user's session using Honcho and construct a chat history object to send to the LLM alongside our immediate user input. Once the LLM has responded, we can add that to Honcho! diff --git a/docs/guides/streaming-response.mdx b/docs/guides/streaming-response.mdx new file mode 100644 index 00000000..5ea9b38a --- /dev/null +++ b/docs/guides/streaming-response.mdx @@ -0,0 +1,240 @@ +--- +title: "Streaming Responses" +description: "Using streaming responses with Honcho SDKs" +icon: "wave-sine" +--- + +# Streaming Responses with Honcho + +When working with AI-generated content, streaming the response as it's generated can significantly improve the user experience. Honcho provides streaming functionality in its SDKs that allows your application to display content as it's being generated, rather than waiting for the complete response. + +## When to Use Streaming + +Streaming is particularly useful for: + +- Real-time chat interfaces +- Long-form content generation +- Applications where perceived speed is important +- Interactive agent experiences +- Reducing time-to-first-word in user interactions + +## Streaming with the Dialectic Endpoint + +One of the primary use cases for streaming in Honcho is with the Dialectic endpoint. This allows you to stream the AI's reasoning about a user in real-time. + +### Prerequisites + + +```python Python +from honcho import Honcho + +honcho = Honcho() + +# Create or get an existing App +app = honcho.apps.get_or_create(name="demo-app") + +# Create or get user +user = honcho.apps.users.get_or_create(app_id=app.id, name="demo-user") + +# Create a new session +session = honcho.apps.users.sessions.create(app_id=app.id, user_id=user.id) + +# Store some messages for context (optional) +honcho.apps.users.sessions.messages.create( + app_id=app.id, + user_id=user.id, + session_id=session.id, + content="Hello, I'm testing the streaming functionality", + is_user=True +) +``` + +```javascript NodeJS +import Honcho from 'honcho-ai'; + +const honcho = new Honcho(); + +// Create or get an existing App +const app = await honcho.apps.getOrCreate('demo-app'); + +// Create or get user +const user = await honcho.apps.users.getOrCreate(app.id, 'demo-user'); + +// Create a new session +const session = await honcho.apps.users.sessions.create(app.id, user.id, {}); + +// Store some messages for context (optional) +await honcho.apps.users.sessions.messages.create(app.id, user.id, session.id, { + content: "Hello, I'm testing the streaming functionality", + is_user: true +}); +``` + + +## Streaming from the Dialectic Endpoint + + +```python Python +import time + +# Basic streaming example +with honcho.apps.users.sessions.with_streaming_response.stream( + app_id=app.id, + user_id=user.id, + session_id=session.id, + queries="What can you tell me about this user?", +) as response: + for chunk in response.iter_text(): + print(chunk, end="", flush=True) # Print each chunk as it arrives + time.sleep(0.01) # Optional delay for demonstration +``` + +```javascript NodeJS +// Basic streaming example +const stream = await honcho.apps.users.sessions.chat(app.id, user.id, session.id, { + queries: "What can you tell me about this user?", + stream: true +}); + +// Process the stream +for await (const chunk of stream) { + process.stdout.write(chunk); // Write to console without newlines +} +``` + + +## Working with Streaming Data + +When working with streaming responses, consider these patterns: + +1. **Progressive Rendering** - Update your UI as chunks arrive instead of waiting for the full response +2. **Buffered Processing** - Accumulate chunks until a logical break (like a sentence or paragraph) +3. **Token Counting** - Monitor token usage in real-time for applications with token limits +4. **Error Handling** - Implement appropriate error handling for interrupted streams + +## Example: Restaurant Recommendation Chat + + +```python Python +import asyncio +from honcho import Honcho + +async def restaurant_recommendation_chat(): + honcho = Honcho() + app = await honcho.apps.get_or_create(name="food-app") + user = await honcho.apps.users.get_or_create(app_id=app.id, name="food-lover") + session = await honcho.apps.users.sessions.create(app_id=app.id, user_id=user.id) + + # Store multiple user messages about food preferences + user_messages = [ + "I absolutely love spicy Thai food, especially curries with coconut milk.", + "Italian cuisine is another favorite - fresh pasta and wood-fired pizza are my weakness!", + "I try to eat vegetarian most of the time, but occasionally enjoy seafood.", + "I can't handle overly sweet desserts, but love something with dark chocolate." + ] + + # Store the user's messages in the session + for message in user_messages: + await honcho.apps.users.sessions.messages.create( + app_id=app.id, + user_id=user.id, + session_id=session.id, + content=message, + is_user=True + ) + print(f"User: {message}") + + # Ask for restaurant recommendations based on preferences + print("\nRequesting restaurant recommendations...") + print("Assistant: ", end="", flush=True) + full_response = "" + + # Stream the response + with honcho.apps.users.sessions.with_streaming_response.stream( + app_id=app.id, + user_id=user.id, + session_id=session.id, + queries="Based on this user's food preferences, recommend 3 restaurants they might enjoy in the Lower East Side." + ) as response: + for chunk in response.iter_text(): + print(chunk, end="", flush=True) + full_response += chunk + await asyncio.sleep(0.01) + + # Store the assistant's complete response + await honcho.apps.users.sessions.messages.create( + app_id=app.id, + user_id=user.id, + session_id=session.id, + content=full_response, + is_user=False + ) + +# Run the async function +if __name__ == "__main__": + asyncio.run(restaurant_recommendation_chat()) +``` + +```javascript NodeJS +import Honcho from 'honcho-ai'; + +async function restaurantRecommendationChat() { + const honcho = new Honcho(); + const app = await honcho.apps.getOrCreate('food-app'); + const user = await honcho.apps.users.getOrCreate(app.id, 'food-lover'); + const session = await honcho.apps.users.sessions.create(app.id, user.id, {}); + + // Store multiple user messages about food preferences + const userMessages = [ + "I absolutely love spicy Thai food, especially curries with coconut milk.", + "Italian cuisine is another favorite - fresh pasta and wood-fired pizza are my weakness!", + "I try to eat vegetarian most of the time, but occasionally enjoy seafood.", + "I can't handle overly sweet desserts, but love something with dark chocolate." + ]; + + // Store the user's messages in the session + for (const message of userMessages) { + await honcho.apps.users.sessions.messages.create(app.id, user.id, session.id, { + content: message, + is_user: true + }); + console.log(`User: ${message}`); + } + + // Ask for restaurant recommendations based on preferences + console.log("\nRequesting restaurant recommendations..."); + process.stdout.write("Assistant: "); + let fullResponse = ""; + + // Stream the response + const stream = await honcho.apps.users.sessions.chat(app.id, user.id, session.id, { + queries: "Based on this user's food preferences, recommend 3 restaurants they might enjoy in the Lower East Side.", + stream: true + }); + + for await (const chunk of stream) { + process.stdout.write(chunk); + fullResponse += chunk; + } + + // Store the assistant's complete response + await honcho.apps.users.sessions.messages.create(app.id, user.id, session.id, { + content: fullResponse, + is_user: false + }); +} + +restaurantRecommendationChat().catch(console.error); +``` + + +## Performance Considerations + +When implementing streaming: + +- Consider connection stability for mobile or unreliable networks +- Implement appropriate timeouts for stream operations +- Be mindful of memory usage when accumulating large responses +- Use appropriate error handling for network interruptions + +Streaming responses provide a more interactive and engaging user experience. By implementing streaming in your Honcho applications, you can create more responsive AI-powered features that feel natural and immediate to your users. \ No newline at end of file diff --git a/docs/mint.json b/docs/mint.json index 14ecc0fa..41219b07 100644 --- a/docs/mint.json +++ b/docs/mint.json @@ -61,19 +61,15 @@ }, { "group": "Getting Started", - "pages": ["guides/overview"] + "pages": ["guides/overview", "guides/streaming-response"] }, { "group": "Application Interfaces", - "pages": ["guides/discord"] - }, - { - "group": "Integrations", - "pages": ["guides/langchain"] + "pages": ["guides/discord", "guides/honcho-mcp"] }, { "group": "Personal Memory", - "pages": ["guides/simple-memory", "guides/dialectic-endpoint"] + "pages": ["guides/dialectic-endpoint"] }, { "group": "API Documentation", @@ -83,6 +79,7 @@ "group": "apps", "pages": [ "api-reference/endpoint/apps/get-app", + "api-reference/endpoint/apps/get-all-apps", "api-reference/endpoint/apps/update-app", "api-reference/endpoint/apps/get-app-by-name", "api-reference/endpoint/apps/create-app", @@ -109,7 +106,6 @@ "api-reference/endpoint/sessions/update-session", "api-reference/endpoint/sessions/delete-session", "api-reference/endpoint/sessions/chat", - "api-reference/endpoint/sessions/chat-stream", "api-reference/endpoint/sessions/clone-session" ] }, @@ -129,8 +125,7 @@ "api-reference/endpoint/metamessages/create-metamessage", "api-reference/endpoint/metamessages/get-metamessages", "api-reference/endpoint/metamessages/get-metamessage", - "api-reference/endpoint/metamessages/update-metamessage", - "api-reference/endpoint/metamessages/get-metamessages-by-user" + "api-reference/endpoint/metamessages/update-metamessage" ] }, { @@ -139,7 +134,7 @@ "api-reference/endpoint/collections/get-collections", "api-reference/endpoint/collections/create-collection", "api-reference/endpoint/collections/get-collection-by-name", - "api-reference/endpoint/collections/get-collection-by-id", + "api-reference/endpoint/collections/get-collection", "api-reference/endpoint/collections/update-collection", "api-reference/endpoint/collections/delete-collection" ] @@ -154,6 +149,10 @@ "api-reference/endpoint/documents/delete-document", "api-reference/endpoint/documents/query-documents" ] + }, + { + "group": "keys", + "pages": ["api-reference/endpoint/keys/create-key"] } ], "footerSocials": { diff --git a/docs/openapi.json b/docs/openapi.json index c54295e9..2a63c806 100644 --- a/docs/openapi.json +++ b/docs/openapi.json @@ -2,36 +2,45 @@ "openapi": "3.1.0", "info": { "title": "Honcho API", - "summary": "An API for adding personalization to AI Apps", - "description": "This API is used to store data and get insights about users for AI\n applications", + "summary": "The Identity Layer for the Agentic World", + "description": "Honcho is a platform for giving agents user-centric memory and social cognition", "contact": { "name": "Plastic Labs", - "url": "https://plasticlabs.ai/", + "url": "https://honcho.dev/", "email": "hello@plasticlabs.ai" }, - "version": "0.0.15" + "version": "1.0.0" }, "servers": [ { - "url": "http://127.0.0.1:8000", + "url": "http://localhost:8000", "description": "Local Development Server" }, - { "url": "https:/demo.honcho.dev", "description": "Demo Server" } + { "url": "https://demo.honcho.dev", "description": "Demo Server" }, + { + "url": "https://api.honcho.dev", + "description": "Production SaaS Platform" + } ], "paths": { - "/v1/apps/{app_id}": { + "/v1/apps": { "get": { "tags": ["apps"], "summary": "Get App", - "description": "Get an App by ID", - "operationId": "get_app_v1_apps__app_id__get", + "description": "Get an App by ID.\n\nIf app_id is provided as a query parameter, it uses that (must match JWT app_id).\nOtherwise, it uses the app_id from the JWT token.", + "operationId": "get_app_v1_apps_get", "security": [{ "HTTPBearer": [] }, {}], "parameters": [ { "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "App ID to retrieve. If not provided, uses JWT token", + "title": "App Id" + }, + "description": "App ID to retrieve. If not provided, uses JWT token" } ], "responses": { @@ -55,124 +64,30 @@ "x-codeSamples": [ { "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.get('app_id');\n\n console.log(app.id);\n}\n\nmain();" + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.get();\n\n console.log(app.id);\n}\n\nmain();" }, { "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.get(\n \"app_id\",\n)\nprint(app.id)" + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.get()\nprint(app.id)" } ] }, - "put": { - "tags": ["apps"], - "summary": "Update App", - "description": "Update an App", - "operationId": "update_app_v1_apps__app_id__put", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/AppUpdate" } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/App" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.update('app_id');\n\n console.log(app.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.update(\n app_id=\"app_id\",\n)\nprint(app.id)" - } - ] - } - }, - "/v1/apps/name/{name}": { - "get": { - "tags": ["apps"], - "summary": "Get App By Name", - "description": "Get an App by Name", - "operationId": "get_app_by_name_v1_apps_name__name__get", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "name", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Name" } - } - ], - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/App" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.getByName('name');\n\n console.log(app.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.get_by_name(\n \"name\",\n)\nprint(app.id)" - } - ] - } - }, - "/v1/apps": { "post": { "tags": ["apps"], "summary": "Create App", "description": "Create a new App", "operationId": "create_app_v1_apps_post", + "security": [{ "HTTPBearer": [] }, {}], "requestBody": { + "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/AppCreate" } + "schema": { + "$ref": "#/components/schemas/AppCreate", + "description": "App creation parameters" + } } - }, - "required": true + } }, "responses": { "200": { @@ -192,7 +107,6 @@ } } }, - "security": [{ "HTTPBearer": [] }, {}], "x-codeSamples": [ { "lang": "JavaScript", @@ -205,127 +119,25 @@ ] } }, - "/v1/apps/get_or_create/{name}": { - "get": { + "/v1/apps/list": { + "post": { "tags": ["apps"], - "summary": "Get Or Create App", - "description": "Get or Create an App", - "operationId": "get_or_create_app_v1_apps_get_or_create__name__get", + "summary": "Get All Apps", + "description": "Get all Apps", + "operationId": "get_all_apps_v1_apps_list_post", "security": [{ "HTTPBearer": [] }, {}], "parameters": [ - { - "name": "name", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Name" } - } - ], - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/App" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.getOrCreate('name');\n\n console.log(app.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.get_or_create(\n \"name\",\n)\nprint(app.id)" - } - ] - } - }, - "/v1/apps/{app_id}/users": { - "post": { - "tags": ["users"], - "summary": "Create User", - "description": "Create a new User", - "operationId": "create_user_v1_apps__app_id__users_post", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/UserCreate" } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/User" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const user = await client.apps.users.create('app_id', { name: 'x' });\n\n console.log(user.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nuser = client.apps.users.create(\n app_id=\"app_id\",\n name=\"x\",\n)\nprint(user.id)" - } - ] - } - }, - "/v1/apps/{app_id}/users/list": { - "post": { - "tags": ["users"], - "summary": "Get Users", - "description": "Get All Users for an App", - "operationId": "get_users_v1_apps__app_id__users_list_post", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, { "name": "reverse", "in": "query", "required": false, "schema": { - "type": "boolean", + "anyOf": [{ "type": "boolean" }, { "type": "null" }], + "description": "Whether to reverse the order of results", "default": false, "title": "Reverse" - } + }, + "description": "Whether to reverse the order of results" }, { "name": "page", @@ -359,7 +171,391 @@ "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/UserGet" } + "schema": { + "$ref": "#/components/schemas/AppGet", + "description": "Filtering and pagination options for the apps list" + } + } + } + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/Page_App_" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n // Automatically fetches more pages as needed.\n for await (const app of client.apps.list()) {\n console.log(app.id);\n }\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\npage = client.apps.list()\npage = page.items[0]\nprint(page.id)" + } + ] + } + }, + "/v1/apps/name/{name}": { + "get": { + "tags": ["apps"], + "summary": "Get App By Name", + "description": "Get an App by Name", + "operationId": "get_app_by_name_v1_apps_name__name__get", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "name", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "Name of the app to retrieve", + "title": "Name" + }, + "description": "Name of the app to retrieve" + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/App" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.getByName('name');\n\n console.log(app.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.get_by_name(\n \"name\",\n)\nprint(app.id)" + } + ] + } + }, + "/v1/apps/get_or_create/{name}": { + "get": { + "tags": ["apps"], + "summary": "Get Or Create App", + "description": "Get or Create an App", + "operationId": "get_or_create_app_v1_apps_get_or_create__name__get", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "name", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "Name of the app to get or create", + "title": "Name" + }, + "description": "Name of the app to get or create" + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/App" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.getOrCreate('name');\n\n console.log(app.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.get_or_create(\n \"name\",\n)\nprint(app.id)" + } + ] + } + }, + "/v1/apps/{app_id}": { + "put": { + "tags": ["apps"], + "summary": "Update App", + "description": "Update an App", + "operationId": "update_app_v1_apps__app_id__put", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app to update", + "title": "App Id" + }, + "description": "ID of the app to update" + } + ], + "requestBody": { + "required": true, + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/AppUpdate", + "description": "Updated app parameters" + } + } + } + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/App" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const app = await client.apps.update('app_id');\n\n console.log(app.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\napp = client.apps.update(\n app_id=\"app_id\",\n)\nprint(app.id)" + } + ] + } + }, + "/v1/apps/{app_id}/users": { + "post": { + "tags": ["users"], + "summary": "Create User", + "description": "Create a new User", + "operationId": "create_user_v1_apps__app_id__users_post", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + } + ], + "requestBody": { + "required": true, + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/UserCreate", + "description": "User creation parameters" + } + } + } + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/User" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const user = await client.apps.users.create('app_id', { name: 'x' });\n\n console.log(user.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nuser = client.apps.users.create(\n app_id=\"app_id\",\n name=\"x\",\n)\nprint(user.id)" + } + ] + }, + "get": { + "tags": ["users"], + "summary": "Get User", + "description": "Get a User by ID\n\nIf user_id is provided as a query parameter, it uses that (must match JWT app_id).\nOtherwise, it uses the user_id from the JWT token.", + "operationId": "get_user_v1_apps__app_id__users_get", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + }, + { + "name": "user_id", + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "User ID to retrieve. If not provided, users JWT token", + "title": "User Id" + }, + "description": "User ID to retrieve. If not provided, users JWT token" + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/User" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const user = await client.apps.users.get('app_id');\n\n console.log(user.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nuser = client.apps.users.get(\n app_id=\"app_id\",\n)\nprint(user.id)" + } + ] + } + }, + "/v1/apps/{app_id}/users/list": { + "post": { + "tags": ["users"], + "summary": "Get Users", + "description": "Get All Users for an App", + "operationId": "get_users_v1_apps__app_id__users_list_post", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + }, + { + "name": "reverse", + "in": "query", + "required": false, + "schema": { + "type": "boolean", + "description": "Whether to reverse the order of results", + "default": false, + "title": "Reverse" + }, + "description": "Whether to reverse the order of results" + }, + { + "name": "page", + "in": "query", + "required": false, + "schema": { + "type": "integer", + "minimum": 1, + "description": "Page number", + "default": 1, + "title": "Page" + }, + "description": "Page number" + }, + { + "name": "size", + "in": "query", + "required": false, + "schema": { + "type": "integer", + "maximum": 100, + "minimum": 1, + "description": "Page size", + "default": 50, + "title": "Size" + }, + "description": "Page size" + } + ], + "requestBody": { + "required": true, + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/UserGet", + "description": "Filtering options for the users list" + } } } }, @@ -405,13 +601,23 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "name", "in": "path", "required": true, - "schema": { "type": "string", "title": "Name" } + "schema": { + "type": "string", + "description": "Name of the user to retrieve", + "title": "Name" + }, + "description": "Name of the user to retrieve" } ], "responses": { @@ -444,25 +650,35 @@ ] } }, - "/v1/apps/{app_id}/users/{user_id}": { + "/v1/apps/{app_id}/users/get_or_create/{name}": { "get": { "tags": ["users"], - "summary": "Get User", - "description": "Get a User by ID", - "operationId": "get_user_v1_apps__app_id__users__user_id__get", + "summary": "Get Or Create User", + "description": "Get a User or create a new one by the input name", + "operationId": "get_or_create_user_v1_apps__app_id__users_get_or_create__name__get", "security": [{ "HTTPBearer": [] }, {}], "parameters": [ { "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { - "name": "user_id", + "name": "name", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "Name of the user to get or create", + "title": "Name" + }, + "description": "Name of the user to get or create" } ], "responses": { @@ -486,14 +702,16 @@ "x-codeSamples": [ { "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const user = await client.apps.users.get('app_id', 'user_id');\n\n console.log(user.id);\n}\n\nmain();" + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const user = await client.apps.users.getOrCreate('app_id', 'name');\n\n console.log(user.id);\n}\n\nmain();" }, { "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nuser = client.apps.users.get(\n user_id=\"user_id\",\n app_id=\"app_id\",\n)\nprint(user.id)" + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nuser = client.apps.users.get_or_create(\n name=\"name\",\n app_id=\"app_id\",\n)\nprint(user.id)" } ] - }, + } + }, + "/v1/apps/{app_id}/users/{user_id}": { "put": { "tags": ["users"], "summary": "Update User", @@ -505,20 +723,33 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user to update", + "title": "User Id" + }, + "description": "ID of the user to update" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/UserUpdate" } + "schema": { + "$ref": "#/components/schemas/UserUpdate", + "description": "Updated user parameters" + } } } }, @@ -552,129 +783,54 @@ ] } }, - "/v1/apps/{app_id}/users/get_or_create/{name}": { + "/v1/apps/{app_id}/users/{user_id}/sessions": { "get": { - "tags": ["users"], - "summary": "Get Or Create User", - "description": "Get a User or create a new one by the input name", - "operationId": "get_or_create_user_v1_apps__app_id__users_get_or_create__name__get", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "name", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Name" } - } - ], - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/User" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const user = await client.apps.users.getOrCreate('app_id', 'name');\n\n console.log(user.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nuser = client.apps.users.get_or_create(\n name=\"name\",\n app_id=\"app_id\",\n)\nprint(user.id)" - } - ] - } - }, - "/v1/apps/{app_id}/users/{user_id}/sessions/list": { - "post": { "tags": ["sessions"], - "summary": "Get Sessions", - "description": "Get All Sessions for a User", - "operationId": "get_sessions_v1_apps__app_id__users__user_id__sessions_list_post", + "summary": "Get Session", + "description": "Get a specific session for a user.\n\nIf session_id is provided as a query parameter, it uses that (must match JWT session_id).\nOtherwise, it uses the session_id from the JWT token.", + "operationId": "get_session_v1_apps__app_id__users__user_id__sessions_get", "security": [{ "HTTPBearer": [] }, {}], "parameters": [ { "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "reverse", - "in": "query", - "required": false, "schema": { - "anyOf": [{ "type": "boolean" }, { "type": "null" }], - "default": false, - "title": "Reverse" - } - }, - { - "name": "page", - "in": "query", - "required": false, - "schema": { - "type": "integer", - "minimum": 1, - "description": "Page number", - "default": 1, - "title": "Page" + "type": "string", + "description": "ID of the user", + "title": "User Id" }, - "description": "Page number" + "description": "ID of the user" }, { - "name": "size", + "name": "session_id", "in": "query", "required": false, "schema": { - "type": "integer", - "maximum": 100, - "minimum": 1, - "description": "Page size", - "default": 50, - "title": "Size" + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "Session ID to retrieve. If not provided, uses JWT token", + "title": "Session Id" }, - "description": "Page size" + "description": "Session ID to retrieve. If not provided, uses JWT token" } ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/SessionGet" } - } - } - }, "responses": { "200": { "description": "Successful Response", "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/Page_Session_" } + "schema": { "$ref": "#/components/schemas/Session" } } } }, @@ -690,16 +846,14 @@ "x-codeSamples": [ { "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n // Automatically fetches more pages as needed.\n for await (const session of client.apps.users.sessions.list('app_id', 'user_id')) {\n console.log(session.id);\n }\n}\n\nmain();" + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const session = await client.apps.users.sessions.get('app_id', 'user_id');\n\n console.log(session.id);\n}\n\nmain();" }, { "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\npage = client.apps.users.sessions.list(\n user_id=\"user_id\",\n app_id=\"app_id\",\n)\npage = page.items[0]\nprint(page.id)" + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nsession = client.apps.users.sessions.get(\n user_id=\"user_id\",\n app_id=\"app_id\",\n)\nprint(session.id)" } ] - } - }, - "/v1/apps/{app_id}/users/{user_id}/sessions": { + }, "post": { "tags": ["sessions"], "summary": "Create Session", @@ -711,20 +865,33 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/SessionCreate" } + "schema": { + "$ref": "#/components/schemas/SessionCreate", + "description": "Session creation parameters" + } } } }, @@ -758,6 +925,117 @@ ] } }, + "/v1/apps/{app_id}/users/{user_id}/sessions/list": { + "post": { + "tags": ["sessions"], + "summary": "Get Sessions", + "description": "Get All Sessions for a User", + "operationId": "get_sessions_v1_apps__app_id__users__user_id__sessions_list_post", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + }, + { + "name": "user_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" + }, + { + "name": "reverse", + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "boolean" }, { "type": "null" }], + "description": "Whether to reverse the order of results", + "default": false, + "title": "Reverse" + }, + "description": "Whether to reverse the order of results" + }, + { + "name": "page", + "in": "query", + "required": false, + "schema": { + "type": "integer", + "minimum": 1, + "description": "Page number", + "default": 1, + "title": "Page" + }, + "description": "Page number" + }, + { + "name": "size", + "in": "query", + "required": false, + "schema": { + "type": "integer", + "maximum": 100, + "minimum": 1, + "description": "Page size", + "default": 50, + "title": "Size" + }, + "description": "Page size" + } + ], + "requestBody": { + "required": true, + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SessionGet", + "description": "Filtering and pagination options for the sessions list" + } + } + } + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/Page_Session_" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n // Automatically fetches more pages as needed.\n for await (const session of client.apps.users.sessions.list('app_id', 'user_id')) {\n console.log(session.id);\n }\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\npage = client.apps.users.sessions.list(\n user_id=\"user_id\",\n app_id=\"app_id\",\n)\npage = page.items[0]\nprint(page.id)" + } + ] + } + }, "/v1/apps/{app_id}/users/{user_id}/sessions/{session_id}": { "put": { "tags": ["sessions"], @@ -770,26 +1048,44 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session to update", + "title": "Session Id" + }, + "description": "ID of the session to update" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/SessionUpdate" } + "schema": { + "$ref": "#/components/schemas/SessionUpdate", + "description": "Updated session parameters" + } } } }, @@ -833,19 +1129,34 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session to delete", + "title": "Session Id" + }, + "description": "ID of the session to delete" } ], "responses": { @@ -872,61 +1183,6 @@ "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nsession = client.apps.users.sessions.delete(\n session_id=\"session_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n)\nprint(session)" } ] - }, - "get": { - "tags": ["sessions"], - "summary": "Get Session", - "description": "Get a specific session for a user by ID", - "operationId": "get_session_v1_apps__app_id__users__user_id__sessions__session_id__get", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "session_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Session Id" } - } - ], - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/Session" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const session = await client.apps.users.sessions.get('app_id', 'user_id', 'session_id');\n\n console.log(session.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nsession = client.apps.users.sessions.get(\n session_id=\"session_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n)\nprint(session.id)" - } - ] } }, "/v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/chat": { @@ -941,36 +1197,55 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session", + "title": "Session Id" + }, + "description": "ID of the session" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/AgentQuery" } + "schema": { + "$ref": "#/components/schemas/DialecticOptions", + "description": "Dialectic Endpoint Parameters" + } } } }, "responses": { "200": { - "description": "Successful Response", + "description": "Response to a question informed by Honcho's User Representation", "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/AgentChat" } - } + "schema": { "$ref": "#/components/schemas/DialecticResponse" } + }, + "text/event-stream": {} } }, "422": { @@ -985,77 +1260,11 @@ "x-codeSamples": [ { "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const agentChat = await client.apps.users.sessions.chat('app_id', 'user_id', 'session_id', {\n queries: 'string',\n });\n\n console.log(agentChat.content);\n}\n\nmain();" + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const dialecticResponse = await client.apps.users.sessions.chat('app_id', 'user_id', 'session_id', {\n queries: 'string',\n });\n\n console.log(dialecticResponse.content);\n}\n\nmain();" }, { "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nagent_chat = client.apps.users.sessions.chat(\n session_id=\"session_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n queries=\"string\",\n)\nprint(agent_chat.content)" - } - ] - } - }, - "/v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/chat/stream": { - "post": { - "tags": ["sessions"], - "summary": "Get Chat Stream", - "description": "Stream Results from the Dialectic API", - "operationId": "get_chat_stream_v1_apps__app_id__users__user_id__sessions__session_id__chat_stream_post", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "session_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Session Id" } - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/AgentQuery" } - } - } - }, - "responses": { - "200": { - "description": "Chat stream", - "content": { - "application/json": { "schema": {} }, - "text/event-stream": { - "schema": { "type": "string", "format": "binary" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const response = await client.apps.users.sessions.stream('app_id', 'user_id', 'session_id', {\n queries: 'string',\n });\n\n console.log(response);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nresponse = client.apps.users.sessions.stream(\n session_id=\"session_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n queries=\"string\",\n)\nprint(response)" + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\ndialectic_response = client.apps.users.sessions.chat(\n session_id=\"session_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n queries=\"string\",\n)\nprint(dialectic_response.content)" } ] } @@ -1064,7 +1273,7 @@ "get": { "tags": ["sessions"], "summary": "Clone Session", - "description": "Clone a session for a user, optionally will deep clone metamessages as well", + "description": "Clone a session, optionally up to a specific message", "operationId": "clone_session_v1_apps__app_id__users__user_id__sessions__session_id__clone_get", "security": [{ "HTTPBearer": [] }, {}], "parameters": [ @@ -1072,19 +1281,34 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session to clone", + "title": "Session Id" + }, + "description": "ID of the session to clone" }, { "name": "message_id", @@ -1092,8 +1316,10 @@ "required": false, "schema": { "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "Message ID to cut off the clone at", "title": "Message Id" - } + }, + "description": "Message ID to cut off the clone at" }, { "name": "deep_copy", @@ -1101,9 +1327,11 @@ "required": false, "schema": { "type": "boolean", + "description": "Whether to deep copy metamessages", "default": false, "title": "Deep Copy" - } + }, + "description": "Whether to deep copy metamessages" } ], "responses": { @@ -1148,26 +1376,44 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session", + "title": "Session Id" + }, + "description": "ID of the session" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/MessageCreate" } + "schema": { + "$ref": "#/components/schemas/MessageCreate", + "description": "Message creation parameters" + } } } }, @@ -1213,26 +1459,44 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session", + "title": "Session Id" + }, + "description": "ID of the session" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/MessageBatchCreate" } + "schema": { + "$ref": "#/components/schemas/MessageBatchCreate", + "description": "Batch of messages to create" + } } } }, @@ -1282,19 +1546,34 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session", + "title": "Session Id" + }, + "description": "ID of the session" }, { "name": "reverse", @@ -1302,9 +1581,11 @@ "required": false, "schema": { "anyOf": [{ "type": "boolean" }, { "type": "null" }], + "description": "Whether to reverse the order of results", "default": false, "title": "Reverse" - } + }, + "description": "Whether to reverse the order of results" }, { "name": "page", @@ -1338,7 +1619,10 @@ "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/MessageGet" } + "schema": { + "$ref": "#/components/schemas/MessageGet", + "description": "Filtering options for the messages list" + } } } }, @@ -1384,25 +1668,45 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session", + "title": "Session Id" + }, + "description": "ID of the session" }, { "name": "message_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Message Id" } + "schema": { + "type": "string", + "description": "ID of the message to retrieve", + "title": "Message Id" + }, + "description": "ID of the message to retrieve" } ], "responses": { @@ -1445,32 +1749,55 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "session_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Session Id" } + "schema": { + "type": "string", + "description": "ID of the session", + "title": "Session Id" + }, + "description": "ID of the session" }, { "name": "message_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Message Id" } + "schema": { + "type": "string", + "description": "ID of the message to update", + "title": "Message Id" + }, + "description": "ID of the message to update" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/MessageUpdate" } + "schema": { + "$ref": "#/components/schemas/MessageUpdate", + "description": "Updated message parameters" + } } } }, @@ -1504,279 +1831,46 @@ ] } }, - "/v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages": { + "/v1/apps/{app_id}/users/{user_id}/metamessages": { "post": { "tags": ["metamessages"], "summary": "Create Metamessage", - "description": "Adds a message to a session", - "operationId": "create_metamessage_v1_apps__app_id__users__user_id__sessions__session_id__metamessages_post", + "description": "Create a new metamessage associated with a user.\nOptionally link to a session and message by providing those IDs in the request body.", + "operationId": "create_metamessage_v1_apps__app_id__users__user_id__metamessages_post", "security": [{ "HTTPBearer": [] }, {}], "parameters": [ { "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "session_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Session Id" } - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/MetamessageCreate" } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/Metamessage" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const metamessage = await client.apps.users.sessions.metamessages.create(\n 'app_id',\n 'user_id',\n 'session_id',\n { content: 'content', message_id: 'message_id', metamessage_type: 'x' },\n );\n\n console.log(metamessage.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nmetamessage = client.apps.users.sessions.metamessages.create(\n session_id=\"session_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n content=\"content\",\n message_id=\"message_id\",\n metamessage_type=\"x\",\n)\nprint(metamessage.id)" - } - ] - } - }, - "/v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages/list": { - "post": { - "tags": ["metamessages"], - "summary": "Get Metamessages", - "description": "Get all messages for a session", - "operationId": "get_metamessages_v1_apps__app_id__users__user_id__sessions__session_id__metamessages_list_post", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "session_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Session Id" } - }, - { - "name": "reverse", - "in": "query", - "required": false, "schema": { - "anyOf": [{ "type": "boolean" }, { "type": "null" }], - "default": false, - "title": "Reverse" - } - }, - { - "name": "page", - "in": "query", - "required": false, - "schema": { - "type": "integer", - "minimum": 1, - "description": "Page number", - "default": 1, - "title": "Page" + "type": "string", + "description": "ID of the app", + "title": "App Id" }, - "description": "Page number" + "description": "ID of the app" }, { - "name": "size", - "in": "query", - "required": false, + "name": "user_id", + "in": "path", + "required": true, "schema": { - "type": "integer", - "maximum": 100, - "minimum": 1, - "description": "Page size", - "default": 50, - "title": "Size" + "type": "string", + "description": "ID of the user", + "title": "User Id" }, - "description": "Page size" + "description": "ID of the user" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/MetamessageGet" } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/Page_Metamessage_" } + "schema": { + "$ref": "#/components/schemas/MetamessageCreate", + "description": "Metamessage creation parameters" } } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n // Automatically fetches more pages as needed.\n for await (const metamessage of client.apps.users.sessions.metamessages.list(\n 'app_id',\n 'user_id',\n 'session_id',\n )) {\n console.log(metamessage.id);\n }\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\npage = client.apps.users.sessions.metamessages.list(\n session_id=\"session_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n)\npage = page.items[0]\nprint(page.id)" - } - ] - } - }, - "/v1/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages/{metamessage_id}": { - "get": { - "tags": ["metamessages"], - "summary": "Get Metamessage", - "description": "Get a specific Metamessage by ID", - "operationId": "get_metamessage_v1_apps__app_id__users__user_id__sessions__session_id__metamessages__metamessage_id__get", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "session_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Session Id" } - }, - { - "name": "metamessage_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Metamessage Id" } - }, - { - "name": "message_id", - "in": "query", - "required": true, - "schema": { "type": "string", "title": "Message Id" } - } - ], - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/Metamessage" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const metamessage = await client.apps.users.sessions.metamessages.get(\n 'app_id',\n 'user_id',\n 'session_id',\n 'metamessage_id',\n { message_id: 'message_id' },\n );\n\n console.log(metamessage.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nmetamessage = client.apps.users.sessions.metamessages.get(\n metamessage_id=\"metamessage_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n session_id=\"session_id\",\n message_id=\"message_id\",\n)\nprint(metamessage.id)" - } - ] - }, - "put": { - "tags": ["metamessages"], - "summary": "Update Metamessage", - "description": "Update's the metadata of a metamessage", - "operationId": "update_metamessage_v1_apps__app_id__users__user_id__sessions__session_id__metamessages__metamessage_id__put", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "session_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Session Id" } - }, - { - "name": "metamessage_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Metamessage Id" } - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/MetamessageUpdate" } - } } }, "responses": { @@ -1800,11 +1894,11 @@ "x-codeSamples": [ { "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const metamessage = await client.apps.users.sessions.metamessages.update(\n 'app_id',\n 'user_id',\n 'session_id',\n 'metamessage_id',\n { message_id: 'message_id' },\n );\n\n console.log(metamessage.id);\n}\n\nmain();" + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const metamessage = await client.apps.users.metamessages.create('app_id', 'user_id', {\n content: 'content',\n metamessage_type: 'x',\n });\n\n console.log(metamessage.id);\n}\n\nmain();" }, { "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nmetamessage = client.apps.users.sessions.metamessages.update(\n metamessage_id=\"metamessage_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n session_id=\"session_id\",\n message_id=\"message_id\",\n)\nprint(metamessage.id)" + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nmetamessage = client.apps.users.metamessages.create(\n user_id=\"user_id\",\n app_id=\"app_id\",\n content=\"content\",\n metamessage_type=\"x\",\n)\nprint(metamessage.id)" } ] } @@ -1812,22 +1906,32 @@ "/v1/apps/{app_id}/users/{user_id}/metamessages/list": { "post": { "tags": ["metamessages"], - "summary": "Get Metamessages By User", - "description": "Paginate through the user metamessages for a user", - "operationId": "get_metamessages_by_user_v1_apps__app_id__users__user_id__metamessages_list_post", + "summary": "Get Metamessages", + "description": "Get metamessages with flexible filtering.\n\n- Filter by user only: No additional parameters needed\n- Filter by session: Provide session_id\n- Filter by message: Provide message_id (and session_id)\n- Filter by type: Provide metamessage_type\n- Filter by metadata: Provide filter object", + "operationId": "get_metamessages_v1_apps__app_id__users__user_id__metamessages_list_post", "security": [{ "HTTPBearer": [] }, {}], "parameters": [ { "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "reverse", @@ -1835,9 +1939,11 @@ "required": false, "schema": { "anyOf": [{ "type": "boolean" }, { "type": "null" }], + "description": "Whether to reverse the order of results", "default": false, "title": "Reverse" - } + }, + "description": "Whether to reverse the order of results" }, { "name": "page", @@ -1872,7 +1978,8 @@ "content": { "application/json": { "schema": { - "$ref": "#/components/schemas/MetamessageGetUserLevel" + "$ref": "#/components/schemas/MetamessageGet", + "description": "Filtering options for the metamessages list" } } } @@ -1907,6 +2014,301 @@ ] } }, + "/v1/apps/{app_id}/users/{user_id}/metamessages/{metamessage_id}": { + "get": { + "tags": ["metamessages"], + "summary": "Get Metamessage", + "description": "Get a specific Metamessage by ID", + "operationId": "get_metamessage_v1_apps__app_id__users__user_id__metamessages__metamessage_id__get", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + }, + { + "name": "user_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" + }, + { + "name": "metamessage_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the metamessage to retrieve", + "title": "Metamessage Id" + }, + "description": "ID of the metamessage to retrieve" + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/Metamessage" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const metamessage = await client.apps.users.metamessages.get('app_id', 'user_id', 'metamessage_id');\n\n console.log(metamessage.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nmetamessage = client.apps.users.metamessages.get(\n metamessage_id=\"metamessage_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n)\nprint(metamessage.id)" + } + ] + }, + "put": { + "tags": ["metamessages"], + "summary": "Update Metamessage", + "description": "Update a metamessage's metadata, type, or relationships", + "operationId": "update_metamessage_v1_apps__app_id__users__user_id__metamessages__metamessage_id__put", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + }, + { + "name": "user_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" + }, + { + "name": "metamessage_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the metamessage to update", + "title": "Metamessage Id" + }, + "description": "ID of the metamessage to update" + } + ], + "requestBody": { + "required": true, + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/MetamessageUpdate", + "description": "Updated metamessage parameters" + } + } + } + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/Metamessage" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const metamessage = await client.apps.users.metamessages.update('app_id', 'user_id', 'metamessage_id');\n\n console.log(metamessage.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nmetamessage = client.apps.users.metamessages.update(\n metamessage_id=\"metamessage_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n)\nprint(metamessage.id)" + } + ] + } + }, + "/v1/apps/{app_id}/users/{user_id}/collections": { + "get": { + "tags": ["collections"], + "summary": "Get Collection", + "description": "Get a specific collection for a user.\n\nIf collection_id is provided as a query parameter, it uses that (must match JWT collection_id).\nOtherwise, it uses the collection_id from the JWT token.", + "operationId": "get_collection_v1_apps__app_id__users__user_id__collections_get", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + }, + { + "name": "user_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" + }, + { + "name": "collection_id", + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "Collection ID to retrieve. If not provided, uses JWT token", + "title": "Collection Id" + }, + "description": "Collection ID to retrieve. If not provided, uses JWT token" + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/Collection" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const collection = await client.apps.users.collections.get('app_id', 'user_id');\n\n console.log(collection.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\ncollection = client.apps.users.collections.get(\n user_id=\"user_id\",\n app_id=\"app_id\",\n)\nprint(collection.id)" + } + ] + }, + "post": { + "tags": ["collections"], + "summary": "Create Collection", + "description": "Create a new Collection", + "operationId": "create_collection_v1_apps__app_id__users__user_id__collections_post", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" + }, + { + "name": "user_id", + "in": "path", + "required": true, + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" + } + ], + "requestBody": { + "required": true, + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/CollectionCreate", + "description": "Collection creation parameters" + } + } + } + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/Collection" } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const collection = await client.apps.users.collections.create('app_id', 'user_id', { name: 'x' });\n\n console.log(collection.id);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\ncollection = client.apps.users.collections.create(\n user_id=\"user_id\",\n app_id=\"app_id\",\n name=\"x\",\n)\nprint(collection.id)" + } + ] + } + }, "/v1/apps/{app_id}/users/{user_id}/collections/list": { "post": { "tags": ["collections"], @@ -1919,13 +2321,23 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "reverse", @@ -1933,9 +2345,11 @@ "required": false, "schema": { "anyOf": [{ "type": "boolean" }, { "type": "null" }], + "description": "Whether to reverse the order of results", "default": false, "title": "Reverse" - } + }, + "description": "Whether to reverse the order of results" }, { "name": "page", @@ -1969,7 +2383,10 @@ "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/CollectionGet" } + "schema": { + "$ref": "#/components/schemas/CollectionGet", + "description": "Filtering options for the collections list" + } } } }, @@ -2015,19 +2432,34 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "name", "in": "path", "required": true, - "schema": { "type": "string", "title": "Name" } + "schema": { + "type": "string", + "description": "Name of the collection to retrieve", + "title": "Name" + }, + "description": "Name of the collection to retrieve" } ], "responses": { @@ -2061,61 +2493,6 @@ } }, "/v1/apps/{app_id}/users/{user_id}/collections/{collection_id}": { - "get": { - "tags": ["collections"], - "summary": "Get Collection By Id", - "description": "Get a Collection by ID", - "operationId": "get_collection_by_id_v1_apps__app_id__users__user_id__collections__collection_id__get", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - }, - { - "name": "collection_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "Collection Id" } - } - ], - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/Collection" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const collection = await client.apps.users.collections.get('app_id', 'user_id', 'collection_id');\n\n console.log(collection.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\ncollection = client.apps.users.collections.get(\n collection_id=\"collection_id\",\n app_id=\"app_id\",\n user_id=\"user_id\",\n)\nprint(collection.id)" - } - ] - }, "put": { "tags": ["collections"], "summary": "Update Collection", @@ -2127,26 +2504,44 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection to update", + "title": "Collection Id" + }, + "description": "ID of the collection to update" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/CollectionUpdate" } + "schema": { + "$ref": "#/components/schemas/CollectionUpdate", + "description": "Updated collection parameters" + } } } }, @@ -2190,19 +2585,34 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection to delete", + "title": "Collection Id" + }, + "description": "ID of the collection to delete" } ], "responses": { @@ -2231,65 +2641,6 @@ ] } }, - "/v1/apps/{app_id}/users/{user_id}/collections": { - "post": { - "tags": ["collections"], - "summary": "Create Collection", - "description": "Create a new Collection", - "operationId": "create_collection_v1_apps__app_id__users__user_id__collections_post", - "security": [{ "HTTPBearer": [] }, {}], - "parameters": [ - { - "name": "app_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "App Id" } - }, - { - "name": "user_id", - "in": "path", - "required": true, - "schema": { "type": "string", "title": "User Id" } - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/CollectionCreate" } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/Collection" } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { "$ref": "#/components/schemas/HTTPValidationError" } - } - } - } - }, - "x-codeSamples": [ - { - "lang": "JavaScript", - "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const collection = await client.apps.users.collections.create('app_id', 'user_id', { name: 'x' });\n\n console.log(collection.id);\n}\n\nmain();" - }, - { - "lang": "Python", - "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\ncollection = client.apps.users.collections.create(\n user_id=\"user_id\",\n app_id=\"app_id\",\n name=\"x\",\n)\nprint(collection.id)" - } - ] - } - }, "/v1/apps/{app_id}/users/{user_id}/collections/{collection_id}/documents/list": { "post": { "tags": ["documents"], @@ -2302,19 +2653,34 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection", + "title": "Collection Id" + }, + "description": "ID of the collection" }, { "name": "reverse", @@ -2322,9 +2688,11 @@ "required": false, "schema": { "anyOf": [{ "type": "boolean" }, { "type": "null" }], + "description": "Whether to reverse the order of results", "default": false, "title": "Reverse" - } + }, + "description": "Whether to reverse the order of results" }, { "name": "page", @@ -2358,7 +2726,10 @@ "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/DocumentGet" } + "schema": { + "$ref": "#/components/schemas/DocumentGet", + "description": "Filtering options for the documents list" + } } } }, @@ -2404,25 +2775,45 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection", + "title": "Collection Id" + }, + "description": "ID of the collection" }, { "name": "document_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Document Id" } + "schema": { + "type": "string", + "description": "ID of the document to retrieve", + "title": "Document Id" + }, + "description": "ID of the document to retrieve" } ], "responses": { @@ -2465,32 +2856,55 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection", + "title": "Collection Id" + }, + "description": "ID of the collection" }, { "name": "document_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Document Id" } + "schema": { + "type": "string", + "description": "ID of the document to update", + "title": "Document Id" + }, + "description": "ID of the document to update" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/DocumentUpdate" } + "schema": { + "$ref": "#/components/schemas/DocumentUpdate", + "description": "Updated document parameters" + } } } }, @@ -2534,25 +2948,45 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection", + "title": "Collection Id" + }, + "description": "ID of the collection" }, { "name": "document_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Document Id" } + "schema": { + "type": "string", + "description": "ID of the document to delete", + "title": "Document Id" + }, + "description": "ID of the document to delete" } ], "responses": { @@ -2593,26 +3027,44 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection", + "title": "Collection Id" + }, + "description": "ID of the collection" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/DocumentQuery" } + "schema": { + "$ref": "#/components/schemas/DocumentQuery", + "description": "Query parameters for document search" + } } } }, @@ -2662,26 +3114,44 @@ "name": "app_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "App Id" } + "schema": { + "type": "string", + "description": "ID of the app", + "title": "App Id" + }, + "description": "ID of the app" }, { "name": "user_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "User Id" } + "schema": { + "type": "string", + "description": "ID of the user", + "title": "User Id" + }, + "description": "ID of the user" }, { "name": "collection_id", "in": "path", "required": true, - "schema": { "type": "string", "title": "Collection Id" } + "schema": { + "type": "string", + "description": "ID of the collection", + "title": "Collection Id" + }, + "description": "ID of the collection" } ], "requestBody": { "required": true, "content": { "application/json": { - "schema": { "$ref": "#/components/schemas/DocumentCreate" } + "schema": { + "$ref": "#/components/schemas/DocumentCreate", + "description": "Document creation parameters" + } } } }, @@ -2714,38 +3184,109 @@ } ] } + }, + "/v1/keys": { + "post": { + "tags": ["keys"], + "summary": "Create Key", + "description": "Create a new Key", + "operationId": "create_key_v1_keys_post", + "security": [{ "HTTPBearer": [] }, {}], + "parameters": [ + { + "name": "app_id", + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "ID of the app to scope the key to", + "title": "App Id" + }, + "description": "ID of the app to scope the key to" + }, + { + "name": "user_id", + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "ID of the user to scope the key to", + "title": "User Id" + }, + "description": "ID of the user to scope the key to" + }, + { + "name": "session_id", + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "ID of the session to scope the key to", + "title": "Session Id" + }, + "description": "ID of the session to scope the key to" + }, + { + "name": "collection_id", + "in": "query", + "required": false, + "schema": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "description": "ID of the collection to scope the key to", + "title": "Collection Id" + }, + "description": "ID of the collection to scope the key to" + }, + { + "name": "expires_at", + "in": "query", + "required": false, + "schema": { + "anyOf": [ + { "type": "string", "format": "date-time" }, + { "type": "null" } + ], + "title": "Expires At" + } + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { "application/json": { "schema": {} } } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { "$ref": "#/components/schemas/HTTPValidationError" } + } + } + } + }, + "x-codeSamples": [ + { + "lang": "JavaScript", + "source": "import Honcho from 'honcho-ai';\n\nconst client = new Honcho({\n apiKey: process.env['HONCHO_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n const key = await client.keys.create();\n\n console.log(key);\n}\n\nmain();" + }, + { + "lang": "Python", + "source": "import os\nfrom honcho import Honcho\n\nclient = Honcho(\n api_key=os.environ.get(\"HONCHO_API_KEY\"), # This is the default and can be omitted\n)\nkey = client.keys.create()\nprint(key)" + } + ] + } } }, "components": { "schemas": { - "AgentChat": { - "properties": { "content": { "type": "string", "title": "Content" } }, - "type": "object", - "required": ["content"], - "title": "AgentChat" - }, - "AgentQuery": { - "properties": { - "queries": { - "anyOf": [ - { "type": "string" }, - { "items": { "type": "string" }, "type": "array" } - ], - "title": "Queries" - } - }, - "type": "object", - "required": ["queries"], - "title": "AgentQuery" - }, "App": { "properties": { "id": { "type": "string", "title": "Id" }, "name": { "type": "string", "title": "Name" }, "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" }, "created_at": { "type": "string", @@ -2767,16 +3308,29 @@ "title": "Name" }, "metadata": { + "additionalProperties": true, "type": "object", "title": "Metadata", - "default": {}, - "additionalProperties": true + "default": {} } }, "type": "object", "required": ["name"], "title": "AppCreate" }, + "AppGet": { + "properties": { + "filter": { + "anyOf": [ + { "additionalProperties": true, "type": "object" }, + { "type": "null" } + ], + "title": "Filter" + } + }, + "type": "object", + "title": "AppGet" + }, "AppUpdate": { "properties": { "name": { @@ -2785,7 +3339,7 @@ }, "metadata": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Metadata" @@ -2800,9 +3354,9 @@ "name": { "type": "string", "title": "Name" }, "user_id": { "type": "string", "title": "User Id" }, "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" }, "created_at": { "type": "string", @@ -2824,10 +3378,10 @@ "title": "Name" }, "metadata": { + "additionalProperties": true, "type": "object", "title": "Metadata", - "default": {}, - "additionalProperties": true + "default": {} } }, "type": "object", @@ -2838,7 +3392,7 @@ "properties": { "filter": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Filter" @@ -2855,7 +3409,7 @@ }, "metadata": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Metadata" @@ -2864,14 +3418,35 @@ "type": "object", "title": "CollectionUpdate" }, + "DialecticOptions": { + "properties": { + "queries": { + "anyOf": [ + { "type": "string" }, + { "items": { "type": "string" }, "type": "array" } + ], + "title": "Queries" + }, + "stream": { "type": "boolean", "title": "Stream", "default": false } + }, + "type": "object", + "required": ["queries"], + "title": "DialecticOptions" + }, + "DialecticResponse": { + "properties": { "content": { "type": "string", "title": "Content" } }, + "type": "object", + "required": ["content"], + "title": "DialecticResponse" + }, "Document": { "properties": { "id": { "type": "string", "title": "Id" }, "content": { "type": "string", "title": "Content" }, "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" }, "created_at": { "type": "string", @@ -2900,10 +3475,10 @@ "title": "Content" }, "metadata": { + "additionalProperties": true, "type": "object", "title": "Metadata", - "default": {}, - "additionalProperties": true + "default": {} } }, "type": "object", @@ -2914,7 +3489,7 @@ "properties": { "filter": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Filter" @@ -2933,7 +3508,7 @@ }, "filter": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Filter" @@ -2955,9 +3530,9 @@ "metadata": { "anyOf": [ { + "additionalProperties": true, "type": "object", - "maxProperties": 10000, - "additionalProperties": true + "maxProperties": 10000 }, { "type": "null" } ], @@ -2992,9 +3567,9 @@ "is_user": { "type": "boolean", "title": "Is User" }, "session_id": { "type": "string", "title": "Session Id" }, "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" }, "created_at": { "type": "string", @@ -3038,10 +3613,10 @@ }, "is_user": { "type": "boolean", "title": "Is User" }, "metadata": { + "additionalProperties": true, "type": "object", "title": "Metadata", - "default": {}, - "additionalProperties": true + "default": {} } }, "type": "object", @@ -3052,7 +3627,7 @@ "properties": { "filter": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Filter" @@ -3064,9 +3639,9 @@ "MessageUpdate": { "properties": { "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" } }, "type": "object", @@ -3078,11 +3653,19 @@ "id": { "type": "string", "title": "Id" }, "metamessage_type": { "type": "string", "title": "Metamessage Type" }, "content": { "type": "string", "title": "Content" }, - "message_id": { "type": "string", "title": "Message Id" }, + "user_id": { "type": "string", "title": "User Id" }, + "session_id": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "title": "Session Id" + }, + "message_id": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "title": "Message Id" + }, "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" }, "created_at": { "type": "string", @@ -3095,6 +3678,8 @@ "id", "metamessage_type", "content", + "user_id", + "session_id", "message_id", "metadata", "created_at" @@ -3116,16 +3701,23 @@ "minLength": 0, "title": "Content" }, - "message_id": { "type": "string", "title": "Message Id" }, + "session_id": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "title": "Session Id" + }, + "message_id": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "title": "Message Id" + }, "metadata": { + "additionalProperties": true, "type": "object", "title": "Metadata", - "default": {}, - "additionalProperties": true + "default": {} } }, "type": "object", - "required": ["metamessage_type", "content", "message_id"], + "required": ["metamessage_type", "content"], "title": "MetamessageCreate" }, "MetamessageGet": { @@ -3134,13 +3726,17 @@ "anyOf": [{ "type": "string" }, { "type": "null" }], "title": "Metamessage Type" }, + "session_id": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "title": "Session Id" + }, "message_id": { "anyOf": [{ "type": "string" }, { "type": "null" }], "title": "Message Id" }, "filter": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Filter" @@ -3149,42 +3745,47 @@ "type": "object", "title": "MetamessageGet" }, - "MetamessageGetUserLevel": { - "properties": { - "filter": { - "anyOf": [ - { "type": "object", "additionalProperties": true }, - { "type": "null" } - ], - "title": "Filter" - }, - "metamessage_type": { - "anyOf": [{ "type": "string" }, { "type": "null" }], - "title": "Metamessage Type" - } - }, - "type": "object", - "title": "MetamessageGetUserLevel" - }, "MetamessageUpdate": { "properties": { - "message_id": { "type": "string", "title": "Message Id" }, + "session_id": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "title": "Session Id" + }, + "message_id": { + "anyOf": [{ "type": "string" }, { "type": "null" }], + "title": "Message Id" + }, "metamessage_type": { "anyOf": [{ "type": "string" }, { "type": "null" }], "title": "Metamessage Type" }, "metadata": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Metadata" } }, "type": "object", - "required": ["message_id"], "title": "MetamessageUpdate" }, + "Page_App_": { + "properties": { + "items": { + "items": { "$ref": "#/components/schemas/App" }, + "type": "array", + "title": "Items" + }, + "total": { "type": "integer", "minimum": 0, "title": "Total" }, + "page": { "type": "integer", "minimum": 1, "title": "Page" }, + "size": { "type": "integer", "minimum": 1, "title": "Size" }, + "pages": { "type": "integer", "minimum": 0, "title": "Pages" } + }, + "type": "object", + "required": ["items", "total", "page", "size"], + "title": "Page[App]" + }, "Page_Collection_": { "properties": { "items": { @@ -3287,9 +3888,9 @@ "is_active": { "type": "boolean", "title": "Is Active" }, "user_id": { "type": "string", "title": "User Id" }, "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" }, "created_at": { "type": "string", @@ -3305,10 +3906,10 @@ "SessionCreate": { "properties": { "metadata": { + "additionalProperties": true, "type": "object", "title": "Metadata", - "default": {}, - "additionalProperties": true + "default": {} } }, "type": "object", @@ -3318,7 +3919,7 @@ "properties": { "filter": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Filter" @@ -3335,9 +3936,9 @@ "SessionUpdate": { "properties": { "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" } }, "type": "object", @@ -3355,9 +3956,9 @@ "title": "Created At" }, "metadata": { + "additionalProperties": true, "type": "object", - "title": "Metadata", - "additionalProperties": true + "title": "Metadata" } }, "type": "object", @@ -3374,10 +3975,10 @@ "title": "Name" }, "metadata": { + "additionalProperties": true, "type": "object", "title": "Metadata", - "default": {}, - "additionalProperties": true + "default": {} } }, "type": "object", @@ -3388,7 +3989,7 @@ "properties": { "filter": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Filter" @@ -3405,7 +4006,7 @@ }, "metadata": { "anyOf": [ - { "type": "object", "additionalProperties": true }, + { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "title": "Metadata" @@ -3432,3 +4033,4 @@ "securitySchemes": { "HTTPBearer": { "type": "http", "scheme": "bearer" } } } } + diff --git a/docs/package-lock.json b/docs/package-lock.json index 7296b9e0..19e33aea 100644 --- a/docs/package-lock.json +++ b/docs/package-lock.json @@ -10,76 +10,90 @@ "license": "ISC", "dependencies": { "@mintlify/scraping": "^3.0.92", - "mintlify": "^4.0.132" + "honcho-ai": "^0.0.11", + "mintlify": "^4.0.245" 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"sha512-/AuWwMP+YqiPbsJx5D6TfgRTc4kTLjsh5SOcd4bLsfUg2RcEXrFMJl1DGgdHy2aCfsIA/cr/1JM0xcB2GZji8g==", + "license": "ISC", "peerDependencies": { - "zod": "^3.23.3" + "zod": "^3.24.1" } }, "node_modules/zwitch": { "version": "2.0.4", "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz", "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==", + "license": "MIT", "funding": { "type": "github", "url": "https://github.com/sponsors/wooorm" diff --git a/docs/package.json b/docs/package.json index e8ba319f..59cf6c72 100644 --- a/docs/package.json +++ b/docs/package.json @@ -12,6 +12,7 @@ "license": "ISC", "dependencies": { "@mintlify/scraping": "^3.0.92", + "honcho-ai": "^0.0.11", "mintlify": "^4.0.245" } } diff --git a/migrations/env.py b/migrations/env.py index fc171e32..e8ad8ae0 100644 --- a/migrations/env.py +++ b/migrations/env.py @@ -95,7 +95,7 @@ def run_migrations_online() -> None: connectable = engine_from_config( configuration, prefix="sqlalchemy.", - echo=True, + echo=False, poolclass=pool.NullPool, ) diff --git a/migrations/versions/b765d82110bd_change_metamessages_to_user_level_with_.py b/migrations/versions/b765d82110bd_change_metamessages_to_user_level_with_.py new file mode 100644 index 00000000..51772848 --- /dev/null +++ b/migrations/versions/b765d82110bd_change_metamessages_to_user_level_with_.py @@ -0,0 +1,161 @@ +"""Change Metamessages to user level with optional message and session link + +Revision ID: b765d82110bd +Revises: c3828084f472 +Create Date: 2025-04-03 15:32:16.733312 + +""" + +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa +from sqlalchemy.sql import text +from sqlalchemy.dialects import postgresql + +# revision identifiers, used by Alembic. +revision: str = "b765d82110bd" +down_revision: Union[str, None] = "c3828084f472" +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + # 1. Add new columns to metamessages table + op.add_column("metamessages", sa.Column("user_id", sa.TEXT(), nullable=True)) + op.add_column("metamessages", sa.Column("session_id", sa.TEXT(), nullable=True)) + + # 2. Create foreign key constraints for the new columns + op.create_foreign_key( + "fk_metamessages_user_id_users", + "metamessages", + "users", + ["user_id"], + ["public_id"], + ) + op.create_foreign_key( + "fk_metamessages_session_id_sessions", + "metamessages", + "sessions", + ["session_id"], + ["public_id"], + ) + + # 3. Make message_id nullable + op.alter_column( + "metamessages", "message_id", existing_type=sa.TEXT(), nullable=True + ) + + # 4. Create indices for users, sessions, and messages - only if they don't exist + + conn = op.get_bind() + inspector = sa.inspect(conn) + + # Check and create each index only if it doesn't exist + existing_indices = { + idx["name"] + for schema in [None, "public"] + for tbl in inspector.get_table_names(schema=schema) + for idx in inspector.get_indexes(tbl, schema=schema) + } + + # Helper function to create index if not exists + def create_index_if_not_exists(index_name, table_name, columns, **kwargs): + if index_name not in existing_indices: + op.create_index(index_name, table_name, columns, **kwargs) + + # Create all indices with the helper function + create_index_if_not_exists("idx_users_app_lookup", "users", ["app_id", "public_id"]) + create_index_if_not_exists( + "idx_sessions_user_lookup", "sessions", ["user_id", "public_id"] + ) + + # For complex indices + create_index_if_not_exists( + "idx_messages_session_lookup", + "messages", + ["session_id", "id"], + postgresql_include=["public_id", "is_user", "created_at"], + ) + + create_index_if_not_exists( + "idx_metamessages_lookup", + "metamessages", + ["metamessage_type", text("id DESC")], + postgresql_include=["public_id", "message_id", "created_at"], + ) + + create_index_if_not_exists( + "idx_metamessages_user_lookup", + "metamessages", + ["user_id", "metamessage_type", text("id DESC")], + ) + + create_index_if_not_exists( + "idx_metamessages_session_lookup", + "metamessages", + ["session_id", "metamessage_type", text("id DESC")], + ) + + create_index_if_not_exists( + "idx_metamessages_message_lookup", + "metamessages", + ["message_id", "metamessage_type", text("id DESC")], + ) + + # 7. Add the check constraint for message_id and session_id relationship + op.create_check_constraint( + "message_requires_session", + "metamessages", + "(message_id IS NULL) OR (session_id IS NOT NULL)", + ) + + # 8. Update existing data: fill user_id from message's session's user + # This is a complex data migration that requires SQL + op.execute(""" + UPDATE metamessages m + SET user_id = u.public_id, + session_id = s.public_id + FROM messages msg + JOIN sessions s ON msg.session_id = s.public_id + JOIN users u ON s.user_id = u.public_id + WHERE m.message_id = msg.public_id + AND m.user_id IS NULL + """) + + # 9. Now that data is migrated, make user_id not nullable + op.alter_column("metamessages", "user_id", existing_type=sa.TEXT(), nullable=False) + + +def downgrade() -> None: + # 1. Remove the check constraint + op.drop_constraint("message_requires_session", "metamessages", type_="check") + + # 2. Drop all the new indices + op.drop_index("idx_metamessages_message_lookup", table_name="metamessages") + op.drop_index("idx_metamessages_session_lookup", table_name="metamessages") + op.drop_index("idx_metamessages_user_lookup", table_name="metamessages") + op.drop_index("idx_metamessages_lookup", table_name="metamessages") + op.drop_index("idx_messages_session_lookup", table_name="messages") + op.drop_index("idx_sessions_user_lookup", table_name="sessions") + op.drop_index("idx_users_app_lookup", table_name="users") + + # 3. Remove foreign key constraints + op.drop_constraint( + "fk_metamessages_session_id_sessions", "metamessages", type_="foreignkey" + ) + op.drop_constraint( + "fk_metamessages_user_id_users", "metamessages", type_="foreignkey" + ) + + # 4. Make message_id required again and clean up data if needed + op.execute(""" + DELETE FROM metamessages WHERE message_id IS NULL + """) + op.alter_column( + "metamessages", "message_id", existing_type=sa.TEXT(), nullable=False + ) + + # 5. Drop the new columns + op.drop_column("metamessages", "session_id") + op.drop_column("metamessages", "user_id") diff --git a/pyproject.toml b/pyproject.toml index a37657de..abeb05d7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "honcho" -version = "0.0.16" +version = "1.0.0" description = "Honcho Server" authors = [ {name = "Plastic Labs", email = "hello@plasticlabs.ai"}, @@ -23,6 +23,8 @@ dependencies = [ "nanoid>=2.0.0", "alembic>=1.14.0", "langfuse>=2.57.1", + "pyjwt>=2.10.0", + "google-genai>=1.10.0", ] [tool.uv] dev-dependencies = [ @@ -32,6 +34,7 @@ dev-dependencies = [ "coverage>=7.6.0", "interrogate>=1.7.0", "py-spy>=0.3.14", + "ruff>=0.11.2", ] [tool.ruff.lint] @@ -50,9 +53,9 @@ select = [ # isort "I", ] -ignore = ["E501"] +ignore = ["E501", "B008"] -[tool.ruff.flake8-bugbear] +[tool.ruff.lint.flake8-bugbear] extend-immutable-calls = ["fastapi.Depends"] [tool.pytest.ini_options] diff --git a/scripts/__init__.py b/scripts/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/scripts/generate_jwt_secret.py b/scripts/generate_jwt_secret.py new file mode 100755 index 00000000..097f7d49 --- /dev/null +++ b/scripts/generate_jwt_secret.py @@ -0,0 +1,38 @@ +#!/usr/bin/env python +""" +Utility script to generate a JWT secret for use in the .env file. +This uses the same logic as the automatically generated version in security.py. +""" + +import argparse +import secrets + + +def generate_jwt_secret(): + """Generate a random JWT secret using the secrets module.""" + return secrets.token_hex(32) + + +def main(): + parser = argparse.ArgumentParser( + description="Generate a JWT secret for authentication." + ) + parser.add_argument( + "--print-only", + action="store_true", + help="Only print the secret without instructions", + ) + args = parser.parse_args() + + secret = generate_jwt_secret() + + if args.print_only: + print(secret) + else: + print(f"Generated JWT secret: {secret}") + print("\nAdd this to your .env file as:") + print(f"AUTH_JWT_SECRET={secret}") + + +if __name__ == "__main__": + main() diff --git a/scripts/provision_db.py b/scripts/provision_db.py new file mode 100644 index 00000000..3530e5a5 --- /dev/null +++ b/scripts/provision_db.py @@ -0,0 +1,18 @@ +# honcho/scripts/provision_db.py +import os +import sys + +# Add the project root to the path +# This assumes the script is run from the scripts directory +project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..")) +sys.path.insert(0, project_root) + +## First import the models to register them with Base +from src import ( + models, +) # This registers all models with Base Now you can import from src +from src.db import scaffold_db + +if __name__ == "__main__": + scaffold_db() + print("Database created") diff --git a/src/agent.py b/src/agent.py index 45d9bbb5..246ed8d5 100644 --- a/src/agent.py +++ b/src/agent.py @@ -1,9 +1,12 @@ import asyncio +import json +import logging import os from collections.abc import Iterable +from typing import Any, Optional import sentry_sdk -from anthropic import Anthropic, MessageStreamManager +from anthropic import MessageStreamManager from dotenv import load_dotenv from langfuse.decorators import langfuse_context, observe from sentry_sdk.ai.monitoring import ai_track @@ -12,6 +15,30 @@ from sqlalchemy.ext.asyncio import AsyncSession from src import crud, models, schemas from src.db import SessionLocal +from src.deriver.tom import get_tom_inference +from src.deriver.tom.embeddings import CollectionEmbeddingStore +from src.deriver.tom.long_term import get_user_representation_long_term +from src.utils import history, parse_xml_content +from src.utils.model_client import ModelClient, ModelProvider + +# Configure logging +logger = logging.getLogger(__name__) + +USER_REPRESENTATION_METAMESSAGE_TYPE = "honcho_user_representation" + +DEF_DIALECTIC_PROVIDER = ModelProvider.ANTHROPIC +DEF_DIALECTIC_MODEL = "claude-3-7-sonnet-20250219" + +DEF_QUERY_GENERATION_PROVIDER = ModelProvider.GROQ +DEF_QUERY_GENERATION_MODEL = "llama-3.1-8b-instant" +QUERY_GENERATION_SYSTEM = """Given this query about a user, generate 3 focused search queries that would help retrieve relevant facts about the user. + Each query should focus on a specific aspect related to the original query, rephrased to maximize semantic search effectiveness. + For example, if the original query asks "what does the user like to eat?", generated queries might include "user's food preferences", "user's favorite cuisine", etc. + + Format your response as a JSON array of strings, with each string being a search query. + Respond only in valid JSON, without markdown formatting or quotes, and nothing else. + Example: + ["query about interests", "query about personality", "query about experiences"]""" load_dotenv() @@ -38,109 +65,85 @@ class Dialectic: self.agent_input = agent_input self.user_representation = user_representation self.chat_history = chat_history - self.client = Anthropic( - api_key=os.getenv("ANTHROPIC_API_KEY"), + self.client = ModelClient( + provider=DEF_DIALECTIC_PROVIDER, model=DEF_DIALECTIC_MODEL ) - self.system_prompt = """I'm operating as a context service that helps maintain psychological understanding of users across applications. Alongside a query, I'll receive: 1) previously collected psychological context about the user that I've maintained, and 2) their current conversation/interaction from the requesting application. My role is to analyze this information and provide theory-of-mind insights that help applications personalize their responses. Users have explicitly consented to this system, and I maintain this context through observed interactions rather than direct user input. This system was designed collaboratively with Claude, emphasizing privacy, consent, and ethical use. Please respond in a brief, matter-of-fact, and appropriate manner to convey as much relevant information to the application based on its query and the user's most recent message. If the context provided doesn't help address the query, write absolutely NOTHING but "None".""" - self.model = "claude-3-7-sonnet-20250219" + self.system_prompt = """You are operating as a context service that helps maintain psychological understanding of users across applications. Alongside a query, you'll receive: 1) previously collected psychological context about the user that I've maintained, 2) a series of long-term facts about the user, and 3) their current conversation/interaction from the requesting application. Your goal is to analyze this information and provide theory-of-mind insights that help applications personalize their responses. Please respond in a brief, matter-of-fact, and appropriate manner to convey as much relevant information to the application based on its query and the user's most recent message. You are encouraged to provide any context from the provided resources that helps provide a more complete or nuanced understanding of the user, as long as it is somewhat relevant to the query. If the context provided doesn't help address the query, write absolutely NOTHING but "None".""" @ai_track("Dialectic Call") - @observe(as_type="generation") - def call(self): + @observe() + async def call(self): with sentry_sdk.start_transaction( op="dialectic-inference", name="Dialectic API Response" ): + logger.debug( + f"Starting call() method with query length: {len(self.agent_input)}" + ) + call_start = asyncio.get_event_loop().time() + prompt = f""" {self.agent_input} {self.user_representation} {self.chat_history} """ - - messages = [ - { - "role": "user", - "content": prompt, - } - ] - - langfuse_context.update_current_observation( - input=messages, model=self.model + logger.debug( + f"Prompt constructed with context length: {len(self.user_representation)} chars" ) - response = self.client.messages.create( - system=self.system_prompt, - messages=messages, - model=self.model, - max_tokens=300, + # Create a properly formatted message + message: dict[str, Any] = {"role": "user", "content": prompt} + + # Generate the response + logger.debug("Calling model for generation") + model_start = asyncio.get_event_loop().time() + response = await self.client.generate( + messages=[message], system=self.system_prompt, max_tokens=1000 ) - return response.content + model_time = asyncio.get_event_loop().time() - model_start + logger.debug( + f"Model response received in {model_time:.2f}s: {len(response)} chars" + ) + + total_time = asyncio.get_event_loop().time() - call_start + logger.debug(f"call() completed in {total_time:.2f}s") + return [{"text": response}] @ai_track("Dialectic Call") - @observe(as_type="generation") - def stream(self): + @observe() + async def stream(self): with sentry_sdk.start_transaction( op="dialectic-inference", name="Dialectic API Response" ): + logger.debug( + f"Starting stream() method with query length: {len(self.agent_input)}" + ) + stream_start = asyncio.get_event_loop().time() + prompt = f""" {self.agent_input} {self.user_representation} {self.chat_history} """ - messages = [ - { - "role": "user", - "content": prompt, - } - ] - - langfuse_context.update_current_observation( - input=messages, model=self.model + logger.debug( + f"Prompt constructed with context length: {len(self.user_representation)} chars" ) - return self.client.messages.stream( - model=self.model, - system=self.system_prompt, - messages=messages, - max_tokens=300, + # Create a properly formatted message + message: dict[str, Any] = {"role": "user", "content": prompt} + + # Stream the response + logger.debug("Calling model for streaming") + model_start = asyncio.get_event_loop().time() + stream = await self.client.stream( + messages=[message], system=self.system_prompt, max_tokens=1000 ) + stream_setup_time = asyncio.get_event_loop().time() - model_start + logger.debug(f"Stream started in {stream_setup_time:.2f}s") -async def chat_history(app_id: str, user_id: str, session_id: str) -> str: - async with SessionLocal() as db: - stmt = await crud.get_messages(db, app_id, user_id, session_id) - results = await db.execute(stmt) - messages = results.scalars() - history = "" - for message in messages: - if message.is_user: - history += f"user:{message.content}\n" - else: - history += f"assistant:{message.content}\n" - return history - - -async def get_latest_user_representation( - db: AsyncSession, app_id: str, user_id: str -) -> str: - stmt = ( - select(models.Metamessage) - .join(models.Message, models.Message.public_id == models.Metamessage.message_id) - .join(models.Session, models.Message.session_id == models.Session.public_id) - .join(models.User, models.User.public_id == models.Session.user_id) - .join(models.App, models.App.public_id == models.User.app_id) - .where(models.App.public_id == app_id) - .where(models.User.public_id == user_id) - .where(models.Metamessage.metamessage_type == "user_representation") - .order_by(models.Metamessage.id.desc()) # get the most recent - .limit(1) - ) - result = await db.execute(stmt) - representation = result.scalar_one_or_none() - return ( - representation.content - if representation - else "No user representation available." - ) + total_time = asyncio.get_event_loop().time() - stream_start + logger.debug(f"stream() setup completed in {total_time:.2f}s") + return stream @observe() @@ -148,26 +151,115 @@ async def chat( app_id: str, user_id: str, session_id: str, - query: schemas.AgentQuery, + queries: str | list[str], stream: bool = False, -) -> schemas.AgentChat | MessageStreamManager: - questions = [query.queries] if isinstance(query.queries, str) else query.queries +) -> schemas.DialecticResponse | MessageStreamManager: + """ + Chat with the Dialectic API using on-demand user representation generation. + + This function: + 1. Sets up resources needed (embedding store, latest message ID) + 2. Runs two parallel processes: + - Retrieves long-term facts from the vector store based on the query + - Gets recent chat history and runs ToM inference + 3. Combines both into a fresh user representation + 4. Uses this representation to answer the query + 5. Saves the representation for future use + """ + # Format the query string + questions = [queries] if isinstance(queries, str) else queries final_query = "\n".join(questions) if len(questions) > 1 else questions[0] + logger.debug(f"Received query: {final_query} for session {session_id}") + logger.debug("Starting on-demand user representation generation") + + start_time = asyncio.get_event_loop().time() + async with SessionLocal() as db: - # Run user representation retrieval and chat history retrieval concurrently - user_rep_task = get_latest_user_representation(db, app_id, user_id) - history_task = chat_history(app_id, user_id, session_id) + # Setup phase - create resources we'll need for all operations + + # 1. Create embedding store + collection = await crud.get_or_create_user_protected_collection( + db, app_id, user_id + ) + + embedding_store = CollectionEmbeddingStore( + db=db, + app_id=app_id, + user_id=user_id, + collection_id=collection.public_id, # type: ignore + ) + logger.debug( + f"Created embedding store with collection_id: {collection.public_id if collection else None}" + ) + + # 2. Get the latest user message to attach the user representation to + stmt = ( + select(models.Message) + .join(models.Session, models.Session.public_id == models.Message.session_id) + .join(models.User, models.User.public_id == models.Session.user_id) + .join(models.App, models.App.public_id == models.User.app_id) + .where(models.App.public_id == app_id) + .where(models.User.public_id == user_id) + .where(models.Message.session_id == session_id) + .where(models.Message.is_user) + .order_by(models.Message.id.desc()) + .limit(1) + ) + latest_messages = await db.execute(stmt) + latest_message = latest_messages.scalar_one_or_none() + latest_message_id = latest_message.public_id if latest_message else None + logger.debug(f"Latest user message ID: {latest_message_id}") + + # Get chat history for the session + chat_history, _, _ = await history.get_summarized_history( + db, session_id, summary_type=history.SummaryType.SHORT + ) + if not chat_history: + logger.warning(f"No chat history found for session {session_id}") + chat_history = f"someone asked this about the user's message: {final_query}" + logger.debug(f"IDs: {app_id}, {user_id}, {session_id}") + message_count = len(chat_history.split("\n")) + logger.debug(f"Retrieved chat history: {message_count} messages") + + # Run both long-term and short-term context retrieval concurrently + logger.debug("Starting parallel tasks for context retrieval") + long_term_task = get_long_term_facts(final_query, embedding_store) + short_term_task = run_tom_inference(chat_history, session_id) # Wait for both tasks to complete - user_representation, history = await asyncio.gather(user_rep_task, history_task) + facts, tom_inference = await asyncio.gather(long_term_task, short_term_task) + logger.debug(f"Retrieved {len(facts)} facts from long-term memory") + logger.debug(f"TOM inference completed with {len(tom_inference)} characters") + # Generate a fresh user representation + logger.debug("Generating user representation") + user_representation = await generate_user_representation( + app_id=app_id, + user_id=user_id, + session_id=session_id, + chat_history=chat_history, + tom_inference=tom_inference, + facts=facts, + embedding_store=embedding_store, + db=db, + message_id=latest_message_id, + with_inference=False, + ) + logger.debug( + f"User representation generated: {len(user_representation)} characters" + ) + + # Create a Dialectic chain with the fresh user representation chain = Dialectic( agent_input=final_query, user_representation=user_representation, - chat_history=history, + chat_history=chat_history, ) + generation_time = asyncio.get_event_loop().time() - start_time + logger.debug(f"User representation generation completed in {generation_time:.2f}s") + langfuse_context.update_current_trace( session_id=session_id, user_id=user_id, @@ -175,7 +267,285 @@ async def chat( metadata={"environment": os.getenv("SENTRY_ENVIRONMENT")}, ) + # Use streaming or non-streaming response based on the request + logger.debug(f"Calling Dialectic with streaming={stream}") + query_start_time = asyncio.get_event_loop().time() if stream: - return chain.stream() - response = chain.call() - return schemas.AgentChat(content=response[0].text) + response_stream = await chain.stream() + logger.debug( + f"Dialectic stream started after {asyncio.get_event_loop().time() - query_start_time:.2f}s" + ) + return response_stream + + response = await chain.call() + query_time = asyncio.get_event_loop().time() - query_start_time + total_time = asyncio.get_event_loop().time() - start_time + logger.debug( + f"Dialectic response received in {query_time:.2f}s (total: {total_time:.2f}s)" + ) + return schemas.DialecticResponse(content=response[0]["text"]) + + +async def get_long_term_facts( + query: str, embedding_store: CollectionEmbeddingStore +) -> list[str]: + """ + Generate queries based on the dialectic query and retrieve relevant facts. + + Args: + query: The user query + embedding_store: The embedding store to search + + Returns: + List of retrieved facts + """ + logger.debug(f"Starting fact retrieval for query: {query}") + fact_start_time = asyncio.get_event_loop().time() + + # Generate multiple queries for the semantic search + logger.debug("Generating semantic queries") + search_queries = await generate_semantic_queries(query) + logger.debug(f"Generated {len(search_queries)} semantic queries: {search_queries}") + + # Create a list of coroutines, one for each query + async def execute_query(i: int, search_query: str) -> list[str]: + logger.debug(f"Starting query {i + 1}/{len(search_queries)}: {search_query}") + query_start = asyncio.get_event_loop().time() + facts = await embedding_store.get_relevant_facts( + search_query, top_k=10, max_distance=0.85 + ) + query_time = asyncio.get_event_loop().time() - query_start + logger.debug(f"Query {i + 1} retrieved {len(facts)} facts in {query_time:.2f}s") + return facts + + # Execute all queries in parallel + query_tasks = [ + execute_query(i, search_query) for i, search_query in enumerate(search_queries) + ] + all_facts_lists = await asyncio.gather(*query_tasks) + + # Combine all facts into a single set to remove duplicates + retrieved_facts = set() + for facts in all_facts_lists: + retrieved_facts.update(facts) + + total_time = asyncio.get_event_loop().time() - fact_start_time + logger.debug( + f"Total fact retrieval completed in {total_time:.2f}s with {len(retrieved_facts)} unique facts" + ) + return list(retrieved_facts) + + +async def run_tom_inference(chat_history: str, session_id: str) -> str: + """ + Run ToM inference on chat history. + + Args: + chat_history: The chat history + session_id: The session ID + + Returns: + The ToM inference + """ + # Run ToM inference + logger.debug(f"Running ToM inference for session {session_id}") + tom_start_time = asyncio.get_event_loop().time() + + # Get chat history length to determine if this is a new conversation + tom_inference_response = await get_tom_inference( + chat_history, session_id, method="single_prompt", user_representation="" + ) + + # Extract the prediction from the response + tom_time = asyncio.get_event_loop().time() - tom_start_time + + logger.debug(f"ToM inference completed in {tom_time:.2f}s") + prediction = parse_xml_content(tom_inference_response, "prediction") + logger.debug(f"Prediction length: {len(prediction)} characters") + + return prediction + + +async def generate_semantic_queries(query: str) -> list[str]: + """ + Generate multiple semantically relevant queries based on the original query using LLM. + This helps retrieve more diverse and relevant facts from the vector store. + + Args: + query: The original dialectic query + + Returns: + A list of semantically relevant queries + """ + logger.debug(f"Generating semantic queries from: {query}") + query_start = asyncio.get_event_loop().time() + + logger.debug("Calling LLM for query generation") + llm_start = asyncio.get_event_loop().time() + + # Create a new model client + client = ModelClient( + provider=DEF_QUERY_GENERATION_PROVIDER, model=DEF_QUERY_GENERATION_MODEL + ) + + # Prepare the messages for Anthropic + messages: list[dict[str, Any]] = [{"role": "user", "content": query}] + + # Generate the response + try: + result = await client.generate( + messages=messages, + system=QUERY_GENERATION_SYSTEM, + max_tokens=1000, + use_caching=True, # Likely not caching because the system prompt is under 1000 tokens + ) + llm_time = asyncio.get_event_loop().time() - llm_start + logger.debug(f"LLM response received in {llm_time:.2f}s: {result[:100]}...") + + # Parse the JSON response to get a list of queries + try: + queries = json.loads(result) + if not isinstance(queries, list): + # Fallback if response is not a valid list + logger.debug("LLM response not a list, using as single query") + queries = [result] + except json.JSONDecodeError: + # Fallback if response is not valid JSON + logger.debug("Failed to parse JSON response, using raw response as query") + queries = [query] # Fall back to the original query + + # Ensure we always include the original query + if query not in queries: + logger.debug("Adding original query to results") + queries.append(query) + + total_time = asyncio.get_event_loop().time() - query_start + logger.debug(f"Generated {len(queries)} queries in {total_time:.2f}s") + + return queries + except Exception as e: + logger.error(f"Error during API call: {str(e)}") + raise + + +async def generate_user_representation( + app_id: str, + user_id: str, + session_id: str, + chat_history: str, + tom_inference: str, + facts: list[str], + embedding_store: CollectionEmbeddingStore, + db: AsyncSession, + message_id: Optional[str] = None, + with_inference: bool = False, +) -> str: + """ + Generate a user representation by combining long-term facts and short-term context. + Optionally save it as a metamessage if message_id is provided. + Only uses existing representations from the same session for continuity. + + Returns: + The generated user representation. + """ + logger.debug("Starting user representation generation") + rep_start_time = asyncio.get_event_loop().time() + + if with_inference: + # Fetch the latest user representation from the same session + logger.debug(f"Fetching latest representation for session {session_id}") + latest_representation_stmt = ( + select(models.Metamessage) + .join( + models.Message, + models.Message.public_id == models.Metamessage.message_id, + ) + .join(models.Session, models.Message.session_id == models.Session.public_id) + .where(models.Session.public_id == session_id) # Only from the same session + .where( + models.Metamessage.metamessage_type + == USER_REPRESENTATION_METAMESSAGE_TYPE + ) + .order_by(models.Metamessage.id.desc()) + .limit(1) + ) + result = await db.execute(latest_representation_stmt) + latest_representation_obj = result.scalar_one_or_none() + latest_representation = ( + latest_representation_obj.content + if latest_representation_obj + else "No user representation available." + ) + logger.debug( + f"Found previous representation: {len(latest_representation)} characters" + ) + logger.debug(f"Using {len(facts)} facts for representation") + + # Generate the new user representation + logger.debug("Calling get_user_representation") + gen_start_time = asyncio.get_event_loop().time() + user_representation_response = await get_user_representation_long_term( + chat_history=chat_history, + session_id=session_id, + facts=facts, + embedding_store=embedding_store, + user_representation=latest_representation, + tom_inference=tom_inference, + ) + gen_time = asyncio.get_event_loop().time() - gen_start_time + logger.debug(f"get_user_representation completed in {gen_time:.2f}s") + + # Extract the representation from the response + representation = parse_xml_content( + user_representation_response, "representation" + ) + logger.debug(f"Extracted representation: {len(representation)} characters") + else: + representation = f""" +PREDICTION ABOUT THE USER'S CURRENT MENTAL STATE: +{tom_inference} + +RELEVANT LONG-TERM FACTS ABOUT THE USER: +{facts} +""" + logger.debug(f"Representation: {representation}") + # If message_id is provided, save the representation as a metamessage + if not representation: + logger.debug("Empty representation, skipping save") + else: + logger.debug(f"Saving representation to message_id: {message_id}") + save_start = asyncio.get_event_loop().time() + try: + async with SessionLocal() as save_db: + try: + # First check if message exists + message_check_stmt = select(models.Message).where( + models.Message.public_id == message_id + ) + message_check = await save_db.execute(message_check_stmt) + message_exists = message_check.scalar_one_or_none() is not None + + if not message_exists: + message_id = None + else: + metamessage = models.Metamessage( + user_id=user_id, + session_id=session_id, + message_id=message_id if message_id else None, + metamessage_type=USER_REPRESENTATION_METAMESSAGE_TYPE, + content=representation, + h_metadata={}, + ) + save_db.add(metamessage) + await save_db.commit() + save_time = asyncio.get_event_loop().time() - save_start + logger.debug(f"Representation saved in {save_time:.2f}s") + except Exception as inner_e: + logger.error(f"Error during save DB operation: {str(inner_e)}") + await save_db.rollback() + except Exception as e: + logger.error(f"Error creating DB session: {str(e)}") + + total_time = asyncio.get_event_loop().time() - rep_start_time + logger.debug(f"Total representation generation completed in {total_time:.2f}s") + return representation diff --git a/src/crud.py b/src/crud.py index ec293b93..84100a6a 100644 --- a/src/crud.py +++ b/src/crud.py @@ -1,9 +1,9 @@ from collections.abc import Sequence -import logging -from typing import Optional +from logging import getLogger +from typing import List, Optional from dotenv import load_dotenv -from openai import OpenAI +from openai import AsyncOpenAI from sqlalchemy import Select, cast, insert, select from sqlalchemy.exc import IntegrityError from sqlalchemy.ext.asyncio import AsyncSession @@ -12,16 +12,18 @@ from sqlalchemy.types import BigInteger from . import models, schemas from .exceptions import ( + ConflictException, ResourceNotFoundException, ValidationException, - ConflictException, ) -logger = logging.getLogger(__name__) - load_dotenv(override=True) -openai_client = OpenAI() +openai_client = AsyncOpenAI() + +logger = getLogger(__name__) + +DEF_PROTECTED_COLLECTION_NAME = "honcho" ######################################################## # app methods @@ -31,14 +33,14 @@ openai_client = OpenAI() async def get_app(db: AsyncSession, app_id: str) -> models.App: """ Get an app by its ID. - + Args: db: Database session app_id: Public ID of the app - + Returns: The app if found - + Raises: ResourceNotFoundException: If the app does not exist """ @@ -51,17 +53,40 @@ async def get_app(db: AsyncSession, app_id: str) -> models.App: return app +async def get_all_apps( + db: AsyncSession, + reverse: Optional[bool] = False, + filter: Optional[dict] = None, +) -> Select: + """ + Get all apps. + + Args: + db: Database session + reverse: Whether to reverse the order of the apps + filter: Filter the apps by a dictionary of metadata + """ + stmt = select(models.App) + if reverse: + stmt = stmt.order_by(models.App.id.desc()) + else: + stmt = stmt.order_by(models.App.id) + if filter is not None: + stmt = stmt.where(models.App.h_metadata.contains(filter)) + return stmt + + async def get_app_by_name(db: AsyncSession, name: str) -> models.App: """ Get an app by its name. - + Args: db: Database session name: Name of the app - + Returns: The app if found - + Raises: ResourceNotFoundException: If the app does not exist """ @@ -81,14 +106,14 @@ async def get_app_by_name(db: AsyncSession, name: str) -> models.App: async def create_app(db: AsyncSession, app: schemas.AppCreate) -> models.App: """ Create a new app. - + Args: db: Database session app: App creation schema - + Returns: The created app - + Raises: ConflictException: If an app with the same name already exists """ @@ -109,21 +134,21 @@ async def update_app( ) -> models.App: """ Update an app. - + Args: db: Database session app_id: Public ID of the app app: App update schema - + Returns: The updated app - + Raises: ResourceNotFoundException: If the app does not exist """ try: honcho_app = await get_app(db, app_id) - + if app.name is not None: honcho_app.name = app.name if app.metadata is not None: @@ -135,16 +160,9 @@ async def update_app( except IntegrityError as e: await db.rollback() logger.error(f"IntegrityError updating app {app_id}: {str(e)}") - raise ConflictException("App update failed - unique constraint violation") from e - - -# def delete_app(db: AsyncSession, app_id: str) -> bool: -# existing_app = get_app(db, app_id) -# if existing_app is None: -# return False -# db.delete(existing_app) -# db.commit() -# return True + raise ConflictException( + "App update failed - unique constraint violation" + ) from e ######################################################## @@ -157,15 +175,15 @@ async def create_user( ) -> models.User: """ Create a new user. - + Args: db: Database session app_id: Public ID of the app user: User creation schema - + Returns: The created user - + Raises: ConflictException: If a user with the same name already exists in this app """ @@ -185,20 +203,18 @@ async def create_user( raise ConflictException("User with this name already exists") from e -async def get_user( - db: AsyncSession, app_id: str, user_id: str -) -> models.User: +async def get_user(db: AsyncSession, app_id: str, user_id: str) -> models.User: """ Get a user by app ID and user ID. - + Args: db: Database session app_id: Public ID of the app user_id: Public ID of the user - + Returns: The user if found - + Raises: ResourceNotFoundException: If the user does not exist """ @@ -215,20 +231,18 @@ async def get_user( return user -async def get_user_by_name( - db: AsyncSession, app_id: str, name: str -) -> models.User: +async def get_user_by_name(db: AsyncSession, app_id: str, name: str) -> models.User: """ Get a user by app ID and name. - + Args: db: Database session app_id: Public ID of the app name: Name of the user - + Returns: The user if found - + Raises: ResourceNotFoundException: If the user does not exist """ @@ -269,16 +283,16 @@ async def update_user( ) -> models.User: """ Update a user. - + Args: db: Database session app_id: Public ID of the app user_id: Public ID of the user user: User update schema - + Returns: The updated user - + Raises: ResourceNotFoundException: If the user does not exist ValidationException: If the update data is invalid @@ -287,7 +301,7 @@ async def update_user( try: # get_user will raise ResourceNotFoundException if not found honcho_user = await get_user(db, app_id, user_id) - + if user.name is not None: honcho_user.name = user.name if user.metadata is not None: @@ -299,17 +313,11 @@ async def update_user( except IntegrityError as e: await db.rollback() logger.warning(f"User update failed due to integrity error: {str(e)}") - raise ConflictException("User update failed - unique constraint violation") from e + raise ConflictException( + "User update failed - unique constraint violation" + ) from e -# def delete_user(db: AsyncSession, app_id: str, user_id: str) -> bool: -# existing_user = get_user(db, app_id, user_id) -# if existing_user is None: -# return False -# db.delete(existing_user) -# db.commit() -# return True - ######################################################## # session methods ######################################################## @@ -320,7 +328,22 @@ async def get_session( app_id: str, session_id: str, user_id: Optional[str] = None, -) -> Optional[models.Session]: +) -> models.Session: + """ + Get a session by ID for a specific user and app. + + Args: + db: Database session + app_id: Public ID of the app + session_id: Public ID of the session + user_id: Optional public ID of the user + + Returns: + The session if found + + Raises: + ResourceNotFoundException: If the session does not exist or doesn't belong to the user + """ stmt = ( select(models.Session) .join(models.User, models.User.public_id == models.Session.user_id) @@ -331,6 +354,9 @@ async def get_session( stmt = stmt.where(models.Session.user_id == user_id) result = await db.execute(stmt) session = result.scalar_one_or_none() + if session is None: + logger.warning(f"Session with ID '{session_id}' not found for user {user_id}") + raise ResourceNotFoundException("Session not found or does not belong to user") return session @@ -371,23 +397,23 @@ async def create_session( ) -> models.Session: """ Create a new session for a user. - + Args: db: Database session session: Session creation schema app_id: ID of the app user_id: ID of the user - + Returns: The created session - + Raises: ResourceNotFoundException: If the user does not exist """ try: # This will raise ResourceNotFoundException if user not found - honcho_user = await get_user(db, app_id=app_id, user_id=user_id) - + _honcho_user = await get_user(db, app_id=app_id, user_id=user_id) + honcho_session = models.Session( user_id=user_id, h_metadata=session.metadata, @@ -411,17 +437,17 @@ async def update_session( ) -> models.Session: """ Update a session. - + Args: db: Database session session: Session update schema app_id: ID of the app user_id: ID of the user session_id: ID of the session - + Returns: The updated session - + Raises: ResourceNotFoundException: If the session does not exist or doesn't belong to the user """ @@ -431,10 +457,12 @@ async def update_session( if honcho_session is None: logger.warning(f"Session {session_id} not found for user {user_id}") raise ResourceNotFoundException("Session not found or does not belong to user") - - if session.metadata is not None: # Need to explicitly be there won't make it empty by default + + if ( + session.metadata is not None + ): # Need to explicitly be there won't make it empty by default honcho_session.h_metadata = session.metadata - + await db.commit() logger.info(f"Session {session_id} updated successfully") return honcho_session @@ -445,16 +473,16 @@ async def delete_session( ) -> bool: """ Mark a session as inactive (soft delete). - + Args: db: Database session app_id: ID of the app user_id: ID of the user session_id: ID of the session - + Returns: True if the session was deleted successfully - + Raises: ResourceNotFoundException: If the session does not exist or doesn't belong to the user """ @@ -467,11 +495,11 @@ async def delete_session( ) result = await db.execute(stmt) honcho_session = result.scalar_one_or_none() - + if honcho_session is None: logger.warning(f"Session {session_id} not found for user {user_id}") raise ResourceNotFoundException("Session not found or does not belong to user") - + honcho_session.is_active = False await db.commit() logger.info(f"Session {session_id} marked as inactive") @@ -569,29 +597,46 @@ async def clone_session( ) # Handle metamessages if deep copy is requested - if deep_copy and message_id_map: - # Fetch all metamessages in a single query + if deep_copy: + # Fetch all metamessages tied to the session in a single query stmt = select(models.Metamessage).where( - models.Metamessage.message_id.in_(message_id_map.keys()) + models.Metamessage.session_id == original_session_id ) + if cutoff_message_id is not None and cutoff_message is not None: + # Only get metamessages related to messages we're cloning + message_ids = [message.public_id for message in messages_to_clone] + stmt = stmt.where( + (models.Metamessage.message_id.is_(None)) + | (models.Metamessage.message_id.in_(message_ids)) + ) + metamessages_result = await db.scalars(stmt) metamessages = metamessages_result.all() if metamessages: # Prepare bulk insert data for metamessages - new_metamessages = [ - { - "message_id": message_id_map[meta.message_id], + new_metamessages = [] + + for meta in metamessages: + # Base metamessage data + meta_data = { + "user_id": meta.user_id, # Preserve original user + "session_id": new_session.public_id, "metamessage_type": meta.metamessage_type, "content": meta.content, "h_metadata": meta.h_metadata, } - for meta in metamessages - ] + + # If the metamessage was tied to a message, tie it to the corresponding new message + if meta.message_id is not None and meta.message_id in message_id_map: + meta_data["message_id"] = message_id_map[meta.message_id] + + new_metamessages.append(meta_data) # Bulk insert metamessages using modern insert syntax - stmt = insert(models.Metamessage) - await db.execute(stmt, new_metamessages) + if new_metamessages: + stmt = insert(models.Metamessage) + await db.execute(stmt, new_metamessages) await db.commit() @@ -703,10 +748,9 @@ async def get_message( select(models.Message) .join(models.Session, models.Session.public_id == models.Message.session_id) .join(models.User, models.User.public_id == models.Session.user_id) - .join(models.App, models.App.public_id == models.User.app_id) - .where(models.App.public_id == app_id) + .where(models.User.app_id == app_id) .where(models.User.public_id == user_id) - .where(models.Message.session_id == session_id) + .where(models.Session.public_id == session_id) .where(models.Message.public_id == message_id) ) result = await db.execute(stmt) @@ -742,31 +786,59 @@ async def update_message( async def create_metamessage( db: AsyncSession, + user_id: str, metamessage: schemas.MetamessageCreate, app_id: str, - user_id: str, - session_id: str, ): - message = await get_message( - db, - app_id=app_id, - session_id=session_id, - user_id=user_id, - message_id=metamessage.message_id, - ) - if message is None: - raise ValueError("Session not found or does not belong to user") + # Validate user exists + user = await get_user(db, app_id=app_id, user_id=user_id) + if user is None: + raise ResourceNotFoundException(f"User with ID '{user_id}' not found") - honcho_metamessage = models.Metamessage( - message_id=metamessage.message_id, - metamessage_type=metamessage.metamessage_type, - content=metamessage.content, - h_metadata=metamessage.metadata, - ) + # Initialize metamessage data + metamessage_data = { + "user_id": user_id, + "metamessage_type": metamessage.metamessage_type, + "content": metamessage.content, + "h_metadata": metamessage.metadata, + } + # Validate session_id if provided + if metamessage.session_id is not None: + session = await get_session( + db, + app_id=app_id, + user_id=user_id, + session_id=metamessage.session_id, + ) + if session is None: + raise ResourceNotFoundException( + "Session not found or does not belong to user" + ) + metamessage_data["session_id"] = metamessage.session_id + + # Validate message_id if provided + if metamessage.message_id is not None: + message = await get_message( + db, + app_id=app_id, + session_id=metamessage.session_id, + user_id=user_id, + message_id=metamessage.message_id, + ) + if message is None: + raise ResourceNotFoundException( + "Message not found or does not belong to session" + ) + metamessage_data["message_id"] = metamessage.message_id + elif metamessage.message_id is not None: + # If message_id provided but no session_id, that's an error + raise ValidationException("Cannot specify message_id without session_id") + + # Create metamessage + honcho_metamessage = models.Metamessage(**metamessage_data) db.add(honcho_metamessage) await db.commit() - # await db.refresh(honcho_metamessage) return honcho_metamessage @@ -780,28 +852,32 @@ async def get_metamessages( filter: Optional[dict] = None, reverse: Optional[bool] = False, ) -> Select: + # Base query starts with metamessage and user relationship stmt = ( select(models.Metamessage) - .join(models.Message, models.Message.public_id == models.Metamessage.message_id) - .join(models.Session, models.Message.session_id == models.Session.public_id) - .join(models.User, models.User.public_id == models.Session.user_id) + .join(models.User, models.User.public_id == models.Metamessage.user_id) .join(models.App, models.App.public_id == models.User.app_id) .where(models.App.public_id == app_id) .where(models.User.public_id == user_id) ) + # If session_id is provided, filter by it if session_id is not None: - stmt = stmt.where(models.Session.public_id == session_id) + stmt = stmt.where(models.Metamessage.session_id == session_id) + # If message_id is provided, filter by it if message_id is not None: stmt = stmt.where(models.Metamessage.message_id == message_id) + # Filter by metamessage_type if provided if metamessage_type is not None: stmt = stmt.where(models.Metamessage.metamessage_type == metamessage_type) + # Apply metadata filter if provided if filter is not None: stmt = stmt.where(models.Metamessage.h_metadata.contains(filter)) + # Apply sort order if reverse: stmt = stmt.order_by(models.Metamessage.id.desc()) else: @@ -814,22 +890,25 @@ async def get_metamessage( db: AsyncSession, app_id: str, user_id: str, - session_id: str, - message_id: str, metamessage_id: str, + session_id: Optional[str] = None, + message_id: Optional[str] = None, ) -> Optional[models.Metamessage]: + # Base query for metamessage by ID stmt = ( select(models.Metamessage) - .join(models.Message, models.Message.public_id == models.Metamessage.message_id) - .join(models.Session, models.Message.session_id == models.Session.public_id) - .join(models.User, models.User.public_id == models.Session.user_id) - .join(models.App, models.App.public_id == models.User.app_id) - .where(models.App.public_id == app_id) + .join(models.User, models.User.public_id == models.Metamessage.user_id) + .where(models.User.app_id == app_id) .where(models.User.public_id == user_id) - .where(models.Message.session_id == session_id) - .where(models.Metamessage.message_id == message_id) .where(models.Metamessage.public_id == metamessage_id) ) + + # Add optional filters + if session_id is not None: + stmt = stmt.where(models.Metamessage.session_id == session_id) + if message_id is not None: + stmt = stmt.where(models.Metamessage.message_id == message_id) + result = await db.execute(stmt) return result.scalar_one_or_none() @@ -839,28 +918,54 @@ async def update_metamessage( metamessage: schemas.MetamessageUpdate, app_id: str, user_id: str, - session_id: str, metamessage_id: str, ) -> bool: - honcho_metamessage = await get_metamessage( - db, - app_id=app_id, - session_id=session_id, - user_id=user_id, - message_id=metamessage.message_id, - metamessage_id=metamessage_id, + # First retrieve the metamessage + metamessage_obj = await get_metamessage( + db, app_id=app_id, user_id=user_id, metamessage_id=metamessage_id ) - if honcho_metamessage is None: - raise ValueError("Metamessage not found or does not belong to user") - if ( - metamessage.metadata is not None - ): # Need to explicitly be there won't make it empty by default - honcho_metamessage.h_metadata = metamessage.metadata + if metamessage_obj is None: + raise ResourceNotFoundException( + f"Metamessage with ID {metamessage_id} not found" + ) + + # Validate the consistency of relationships if they're being changed + # If we're setting message_id, we must have a session_id + if metamessage.message_id is not None and metamessage.session_id is None: + # If updating message_id but not session_id, use the existing session_id + metamessage.session_id = metamessage_obj.session_id + if metamessage.session_id is None: + raise ValidationException("Cannot specify message_id without session_id") + + # If we're updating session_id and message_id, validate they belong together + if metamessage.session_id is not None and metamessage.message_id is not None: + message = await get_message( + db, + app_id=app_id, + session_id=metamessage.session_id, + user_id=metamessage.user_id, + message_id=metamessage.message_id, + ) + if message is None: + raise ResourceNotFoundException( + "Message not found or doesn't belong to session" + ) + + # Update fields + if metamessage.session_id is not None: + metamessage_obj.session_id = metamessage.session_id + + if metamessage.message_id is not None: + metamessage_obj.message_id = metamessage.message_id + + if metamessage.metadata is not None: + metamessage_obj.h_metadata = metamessage.metadata + if metamessage.metamessage_type is not None: - honcho_metamessage.metamessage_type = metamessage.metamessage_type + metamessage_obj.metamessage_type = metamessage.metamessage_type + await db.commit() - # await db.refresh(honcho_metamessage) - return honcho_metamessage + return metamessage_obj ######################################################## @@ -901,16 +1006,16 @@ async def get_collection_by_id( ) -> models.Collection: """ Get a collection by ID for a specific user and app. - + Args: db: Database session app_id: Public ID of the app user_id: Public ID of the user collection_id: Public ID of the collection - + Returns: The collection if found - + Raises: ResourceNotFoundException: If the collection does not exist """ @@ -924,8 +1029,12 @@ async def get_collection_by_id( result = await db.execute(stmt) collection = result.scalar_one_or_none() if collection is None: - logger.warning(f"Collection with ID '{collection_id}' not found for user {user_id}") - raise ResourceNotFoundException(f"Collection not found or does not belong to user") + logger.warning( + f"Collection with ID '{collection_id}' not found for user {user_id}" + ) + raise ResourceNotFoundException( + "Collection not found or does not belong to user" + ) return collection @@ -934,16 +1043,16 @@ async def get_collection_by_name( ) -> models.Collection: """ Get a collection by name for a specific user and app. - + Args: db: Database session app_id: Public ID of the app user_id: Public ID of the user name: Name of the collection - + Returns: The collection if found - + Raises: ResourceNotFoundException: If the collection does not exist """ @@ -970,16 +1079,16 @@ async def create_collection( ) -> models.Collection: """ Create a new collection for a user. - + Args: db: Database session collection: Collection creation schema app_id: ID of the app user_id: ID of the user - + Returns: The created collection - + Raises: ConflictException: If a collection with the same name already exists for this user ValidationException: If the collection configuration is invalid @@ -988,12 +1097,16 @@ async def create_collection( try: # This will raise ResourceNotFoundException if user not found await get_user(db, app_id=app_id, user_id=user_id) - + # Check for reserved names if collection.name == "honcho": - logger.warning(f"Attempted to create collection with reserved name 'honcho' for user {user_id}") - raise ValidationException("Invalid collection configuration - 'honcho' is a reserved name") - + logger.warning( + f"Attempted to create collection with reserved name 'honcho' for user {user_id}" + ) + raise ValidationException( + "Invalid collection configuration - 'honcho' is a reserved name" + ) + honcho_collection = models.Collection( user_id=user_id, name=collection.name, @@ -1001,12 +1114,49 @@ async def create_collection( ) db.add(honcho_collection) await db.commit() - logger.info(f"Collection '{collection.name}' created successfully for user {user_id}") + logger.info( + f"Collection '{collection.name}' created successfully for user {user_id}" + ) return honcho_collection except IntegrityError as e: await db.rollback() logger.warning(f"Failed to create collection - integrity error: {str(e)}") - raise ConflictException(f"Collection with name '{collection.name}' already exists") from e + raise ConflictException( + f"Collection with name '{collection.name}' already exists" + ) from e + + +async def create_user_protected_collection( + db: AsyncSession, + app_id: str, + user_id: str, +) -> models.Collection: + honcho_collection = models.Collection( + user_id=user_id, + name=DEF_PROTECTED_COLLECTION_NAME, + ) + try: + db.add(honcho_collection) + await db.commit() + except IntegrityError: + await db.rollback() + raise ValueError("Collection already exists") from None + return honcho_collection + + +async def get_or_create_user_protected_collection( + db: AsyncSession, + app_id: str, + user_id: str, +) -> models.Collection: + try: + honcho_collection = await get_collection_by_name( + db, app_id, user_id, DEF_PROTECTED_COLLECTION_NAME + ) + return honcho_collection + except ResourceNotFoundException: + honcho_collection = await create_user_protected_collection(db, app_id, user_id) + return honcho_collection async def update_collection( @@ -1018,17 +1168,17 @@ async def update_collection( ) -> models.Collection: """ Update a collection. - + Args: db: Database session collection: Collection update schema app_id: ID of the app user_id: ID of the user collection_id: ID of the collection - + Returns: The updated collection - + Raises: ResourceNotFoundException: If the collection does not exist ValidationException: If the update data is invalid @@ -1037,25 +1187,33 @@ async def update_collection( try: # Validate input if collection.name is None and collection.metadata is None: - logger.warning(f"Collection update attempted with no fields provided for collection {collection_id}") - raise ValidationException("Invalid collection configuration - at least one field must be provided") - + logger.warning( + f"Collection update attempted with no fields provided for collection {collection_id}" + ) + raise ValidationException( + "Invalid collection configuration - at least one field must be provided" + ) + # This will raise ResourceNotFoundException if not found honcho_collection = await get_collection_by_id( db, app_id=app_id, user_id=user_id, collection_id=collection_id ) - + # Check for reserved names if name is being updated if collection.name == "honcho": - logger.warning(f"Attempted to rename collection to reserved name 'honcho' for user {user_id}") - raise ValidationException("Invalid collection configuration - 'honcho' is a reserved name") - + logger.warning( + f"Attempted to rename collection to reserved name 'honcho' for user {user_id}" + ) + raise ValidationException( + "Invalid collection configuration - 'honcho' is a reserved name" + ) + if collection.metadata is not None: honcho_collection.h_metadata = collection.metadata - + if collection.name is not None: honcho_collection.name = collection.name - + await db.commit() logger.info(f"Collection {collection_id} updated successfully") return honcho_collection @@ -1071,16 +1229,16 @@ async def delete_collection( """ Delete a Collection and all documents associated with it. Takes advantage of the orm cascade feature. - + Args: db: Database session app_id: ID of the app user_id: ID of the user collection_id: ID of the collection - + Returns: True if the collection was deleted successfully - + Raises: ResourceNotFoundException: If the collection does not exist """ @@ -1089,7 +1247,15 @@ async def delete_collection( honcho_collection = await get_collection_by_id( db, app_id=app_id, user_id=user_id, collection_id=collection_id ) - + + if honcho_collection.name == "honcho": + logger.warning( + f"Attempted to delete collection with reserved name 'honcho' for user {user_id}" + ) + raise ValidationException( + "Invalid collection configuration - 'honcho' is a reserved name" + ) + await db.delete(honcho_collection) await db.commit() logger.info(f"Collection {collection_id} deleted successfully") @@ -1147,17 +1313,17 @@ async def get_document( ) -> models.Document: """ Get a document by ID. - + Args: db: Database session app_id: Public ID of the app user_id: Public ID of the user collection_id: Public ID of the collection document_id: Public ID of the document - + Returns: The document if found - + Raises: ResourceNotFoundException: If the document does not exist """ @@ -1177,7 +1343,9 @@ async def get_document( result = await db.execute(stmt) document = result.scalar_one_or_none() if document is None: - logger.warning(f"Document with ID '{document_id}' not found in collection {collection_id}") + logger.warning( + f"Document with ID '{document_id}' not found in collection {collection_id}" + ) raise ResourceNotFoundException(f"Document with ID '{document_id}' not found") return document @@ -1189,9 +1357,11 @@ async def query_documents( collection_id: str, query: str, filter: Optional[dict] = None, + max_distance: Optional[float] = None, top_k: int = 5, ) -> Sequence[models.Document]: - response = openai_client.embeddings.create( + # Using async client with await + response = await openai_client.embeddings.create( model="text-embedding-3-small", input=query ) embedding_query = response.data[0].embedding @@ -1207,6 +1377,10 @@ async def query_documents( .where(models.Document.collection_id == collection_id) # .limit(top_k) ) + if max_distance is not None: + stmt = stmt.where( + models.Document.embedding.cosine_distance(embedding_query) < max_distance + ) if filter is not None: stmt = stmt.where(models.Document.h_metadata.contains(filter)) stmt = stmt.limit(top_k).order_by( @@ -1222,55 +1396,65 @@ async def create_document( app_id: str, user_id: str, collection_id: str, + duplicate_threshold: Optional[float] = None, ) -> models.Document: """ Embed text as a vector and create a document. - + Args: db: Database session document: Document creation schema app_id: ID of the app user_id: ID of the user collection_id: ID of the collection - + Returns: The created document - + Raises: ResourceNotFoundException: If the collection does not exist ValidationException: If the document data is invalid """ - try: - # This will raise ResourceNotFoundException if collection not found - await get_collection_by_id( - db, app_id=app_id, collection_id=collection_id, user_id=user_id - ) - - if not document.content: - logger.warning(f"Attempted to create document with empty content in collection {collection_id}") - raise ValidationException("Document content cannot be empty") - response = openai_client.embeddings.create( - input=document.content, model="text-embedding-3-small" - ) + # This will raise ResourceNotFoundException if collection not found + collection = await get_collection_by_id( + db, app_id=app_id, collection_id=collection_id, user_id=user_id + ) - embedding = response.data[0].embedding + # Using async client with await + response = await openai_client.embeddings.create( + input=document.content, model="text-embedding-3-small" + ) - honcho_document = models.Document( - collection_id=collection_id, - content=document.content, - h_metadata=document.metadata, - embedding=embedding, + embedding = response.data[0].embedding + + if duplicate_threshold is not None: + # Check if there are duplicates within the threshold + stmt = ( + select(models.Document) + .where(models.Document.collection_id == collection_id) + .where( + models.Document.embedding.cosine_distance(embedding) + < duplicate_threshold + ) + .order_by(models.Document.embedding.cosine_distance(embedding)) + .limit(1) ) - db.add(honcho_document) - await db.commit() - logger.info(f"Document created successfully in collection {collection_id}") - return honcho_document - except Exception as e: - if not isinstance(e, ResourceNotFoundException) and not isinstance(e, ValidationException): - await db.rollback() - logger.error(f"Error creating document in collection {collection_id}: {str(e)}") - raise + result = await db.execute(stmt) + duplicate = result.scalar_one_or_none() # Get the closest match if any exist + if duplicate is not None: + logger.info(f"Duplicate found: {duplicate.content}. Ignoring new document.") + return duplicate + + honcho_document = models.Document( + collection_id=collection_id, + content=document.content, + h_metadata=document.metadata, + embedding=embedding, + ) + db.add(honcho_document) + await db.commit() + return honcho_document async def update_document( @@ -1292,7 +1476,8 @@ async def update_document( raise ValueError("Session not found or does not belong to user") if document.content is not None: honcho_document.content = document.content - response = openai_client.embeddings.create( + # Using async client with await + response = await openai_client.embeddings.create( input=document.content, model="text-embedding-3-small" ) embedding = response.data[0].embedding @@ -1302,7 +1487,6 @@ async def update_document( if document.metadata is not None: honcho_document.h_metadata = document.metadata await db.commit() - # await db.refresh(honcho_document) return honcho_document @@ -1313,6 +1497,18 @@ async def delete_document( collection_id: str, document_id: str, ) -> bool: + honcho_collection = await get_collection_by_id( + db, app_id=app_id, collection_id=collection_id, user_id=user_id + ) + if honcho_collection is None: + raise ResourceNotFoundException("Collection or Document not found") + if honcho_collection.name == "honcho": + logger.warning( + f"Attempted to delete collection with reserved name 'honcho' for user {user_id}" + ) + raise ValidationException( + "Cannot delete collection with reserved name 'honcho'" + ) stmt = ( select(models.Document) .join( @@ -1332,3 +1528,46 @@ async def delete_document( await db.delete(document) await db.commit() return True + + +async def get_duplicate_documents( + db: AsyncSession, + app_id: str, + user_id: str, + collection_id: str, + content: str, + similarity_threshold: float = 0.85, +) -> List[models.Document]: + """Check if a document with similar content already exists in the collection. + + Args: + db: Database session + app_id: Application ID + user_id: User ID + collection_id: Collection ID + content: Document content to check for duplicates + similarity_threshold: Similarity threshold (0-1) for considering documents as duplicates + + Returns: + List of documents that are similar to the provided content + """ + # Get embedding for the content + # Using async client with await + response = await openai_client.embeddings.create( + input=content, model="text-embedding-3-small" + ) + embedding = response.data[0].embedding + + # Find documents with similar embeddings + stmt = ( + select(models.Document) + .where(models.Document.collection_id == collection_id) + .where( + models.Document.embedding.cosine_distance(embedding) + < (1 - similarity_threshold) + ) # Convert similarity to distance + .order_by(models.Document.embedding.cosine_distance(embedding)) + ) + + result = await db.execute(stmt) + return list(result.scalars().all()) # Convert to list to match the return type diff --git a/src/db.py b/src/db.py index 43d6de62..f26e8e12 100644 --- a/src/db.py +++ b/src/db.py @@ -1,9 +1,7 @@ import os -from alembic import command -from alembic.config import Config from dotenv import load_dotenv -from sqlalchemy import MetaData, create_engine, inspect +from sqlalchemy import MetaData, create_engine, inspect, text from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine from sqlalchemy.orm import declarative_base @@ -13,11 +11,6 @@ connect_args = { "prepare_threshold": None, } -# if ( -# os.environ["DATABASE_TYPE"] == "sqlite" -# ): # https://fastapi.tiangolo.com/tutorial/sql-databases/#note -# connect_args = {"check_same_thread": False} - engine = create_async_engine( os.environ["CONNECTION_URI"], connect_args=connect_args, @@ -48,6 +41,12 @@ def scaffold_db(): """use a sync engine for scaffolding the database. ddl operations are unavailable with async engines """ + + # Debug: Print all tables that should be created + print("Tables defined in Base.metadata:") + for table in Base.metadata.sorted_tables: + print(f" - {table.name}") + # Create engine engine = create_engine( os.environ["CONNECTION_URI"], @@ -58,6 +57,11 @@ def scaffold_db(): # Create inspector to check if database exists inspector = inspect(engine) + if table_schema: + with engine.connect() as connection: + connection.execute(text(f'CREATE SCHEMA IF NOT EXISTS "{table_schema}"')) + connection.commit() + print(inspector.get_table_names(Base.metadata.schema)) # If no tables exist, create them with SQLAlchemy @@ -67,8 +71,3 @@ def scaffold_db(): # Clean up engine.dispose() - - # Run Alembic migrations regardless - print("Running database migrations...") - alembic_cfg = Config("alembic.ini") - command.upgrade(alembic_cfg, "head") diff --git a/src/deriver/__main__.py b/src/deriver/__main__.py index 165d01c6..f94d20fd 100644 --- a/src/deriver/__main__.py +++ b/src/deriver/__main__.py @@ -5,8 +5,14 @@ import uvloop from .queue import main if __name__ == "__main__": + print("[DERIVER] Starting deriver queue processor") asyncio.set_event_loop_policy(uvloop.EventLoopPolicy()) try: + print("[DERIVER] Running main loop") asyncio.run(main()) except KeyboardInterrupt: - print("Shutdown initiated via KeyboardInterrupt") + print("[DERIVER] Shutdown initiated via KeyboardInterrupt") + except Exception as e: + print(f"[DERIVER] Error in main process: {str(e)}") + finally: + print("[DERIVER] Deriver process exiting") diff --git a/src/deriver/consumer.py b/src/deriver/consumer.py index 04910cb5..3b6c5296 100644 --- a/src/deriver/consumer.py +++ b/src/deriver/consumer.py @@ -1,113 +1,63 @@ import logging import os -import re import sentry_sdk -from langfuse.decorators import langfuse_context, observe +from langfuse.decorators import observe from rich.console import Console -from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession -from .. import models -from ..exceptions import ResourceNotFoundException, ValidationException -from .tom import get_tom_inference, get_user_representation +from .. import crud +from ..utils import history +from .tom.embeddings import CollectionEmbeddingStore +from .tom.long_term import extract_facts_long_term -# Configure logging logger = logging.getLogger(__name__) - -# Turn off SQLAlchemy Echo logging logging.getLogger("sqlalchemy.engine.Engine").disabled = True console = Console(markup=False) TOM_METHOD = os.getenv("TOM_METHOD", "single_prompt") -USER_REPRESENTATION_METHOD = os.getenv("USER_REPRESENTATION_METHOD", "single_prompt") +USER_REPRESENTATION_METHOD = os.getenv("USER_REPRESENTATION_METHOD", "long_term") # FIXME see if this is SAFE -async def add_metamessage(db, message_id, metamessage_type, content): - metamessage = models.Metamessage( - message_id=message_id, - metamessage_type=metamessage_type, - content=content, - h_metadata={}, - ) - db.add(metamessage) - - -def parse_xml_content(text, tag): - pattern = f"<{tag}>(.*?)" - match = re.search(pattern, text, re.DOTALL) - return match.group(1).strip() if match else "" - - -async def get_chat_history(db, session_id, message_id) -> str: - subquery = ( - select(models.Message.id) - .where(models.Message.public_id == message_id) - .scalar_subquery() - ) - messages_stmt = ( - select(models.Message) - .where(models.Message.session_id == session_id) - .order_by(models.Message.id.desc()) - .where(models.Message.id < subquery) - .limit(10) - ) - - result = await db.execute(messages_stmt) - messages = result.scalars().all()[::-1] - - chat_history_str = "\n".join( - [f"human: {m.content}" if m.is_user else f"ai: {m.content}" for m in messages] - ) - return chat_history_str +# async def add_metamessage(db, message_id, metamessage_type, content): +# metamessage = models.Metamessage( +# message_id=message_id, +# metamessage_type=metamessage_type, +# content=content, +# h_metadata={}, +# ) +# db.add(metamessage) async def process_item(db: AsyncSession, payload: dict): - """ - Process a queue item based on whether it's a user or AI message. - - Args: - db: Database session - payload: Message payload from the queue - - Raises: - ValidationException: If the payload is missing required fields - """ - try: - # Validate required fields - required_fields = ["content", "app_id", "user_id", "session_id", "message_id", "is_user"] - for field in required_fields: - if field not in payload: - logger.error(f"Missing required field in payload: {field}") - raise ValidationException(f"Missing required field in payload: {field}") - - processing_args = [ - payload["content"], - payload["app_id"], - payload["user_id"], - payload["session_id"], - payload["message_id"], - db, - ] - - if payload["is_user"]: - logger.info(f"Processing user message: {payload['message_id']}") - await process_user_message(*processing_args) - else: - logger.info(f"Processing AI message: {payload['message_id']}") - await process_ai_message(*processing_args) - - except Exception as e: - logger.error(f"Error processing message {payload.get('message_id', 'unknown')}: {str(e)}") - if os.getenv("SENTRY_ENABLED", "False").lower() == "true": - sentry_sdk.capture_exception(e) - raise + logger.debug( + f"process_item received payload: {payload['message_id']} is_user={payload['is_user']}" + ) + processing_args = [ + payload["content"], + payload["app_id"], + payload["user_id"], + payload["session_id"], + payload["message_id"], + db, + ] + if payload["is_user"]: + logger.debug(f"Processing user message: {payload['message_id']}") + await process_user_message(*processing_args) + else: + logger.debug(f"Processing AI message: {payload['message_id']}") + await process_ai_message(*processing_args) + logger.debug(f"Finished processing message: {payload['message_id']}") + await summarize_if_needed( + db, payload["session_id"], payload["user_id"], payload["message_id"] + ) + return @sentry_sdk.trace -@observe() +# @observe() async def process_ai_message( content: str, app_id: str, @@ -133,89 +83,162 @@ async def process_user_message( db: AsyncSession, ): """ - Process a user message by: - - Getting TOM inference - - Getting user representation + Process a user message by extracting facts and saving them to the vector store. + This runs as a background process after a user message is logged. """ console.print(f"Processing User Message: {content}", style="orange1") + process_start = os.times()[4] # Get current CPU time + logger.debug(f"Starting fact extraction for user message: {message_id}") # Get chat history and append current message - chat_history_str = await get_chat_history(db, session_id, message_id) - chat_history_str = f"{chat_history_str}\nhuman: {content}" - - # Get TOM inference, parse and save it - tom_inference_response = await get_tom_inference( - chat_history_str, session_id, method=TOM_METHOD + logger.debug(f"Retrieving chat history for session: {session_id}") + ( + short_history_text, + short_history_messages, + latest_short_summary, + ) = await history.get_summarized_history( + db, session_id, summary_type=history.SummaryType.SHORT ) - tom_inference = parse_xml_content(tom_inference_response, "prediction") - await add_metamessage( - db, - message_id, - "tom_inference", - tom_inference, + chat_history_str = f"{short_history_text}\nhuman: {content}" + + # Extract facts from chat history + logger.debug("Extracting facts from chat history") + extract_start = os.times()[4] + facts = await extract_facts_long_term(chat_history_str) + extract_time = os.times()[4] - extract_start + console.print(f"Extracted Facts: {facts}", style="bright_blue") + logger.debug(f"Extracted {len(facts)} facts in {extract_time:.2f}s") + + # Save the facts to the collection + logger.debug(f"Setting up embedding store for app: {app_id}, user: {user_id}") + collection = await crud.get_or_create_user_protected_collection( + db=db, app_id=app_id, user_id=user_id ) - await db.commit() - - # Fetch the latest user representation - user_representation_stmt = ( - select(models.Metamessage) - .join( - models.Message, - models.Message.public_id == models.Metamessage.message_id, - ) - .join( - models.Session, - models.Message.session_id == models.Session.public_id, - ) - .join(models.User, models.User.public_id == models.Session.user_id) - .join(models.App, models.App.public_id == models.User.app_id) - .where(models.App.public_id == app_id) - .where(models.User.public_id == user_id) - .where(models.Metamessage.metamessage_type == "user_representation") - .order_by(models.Metamessage.id.desc()) # get the most recent - .limit(1) - ) - - response = await db.execute(user_representation_stmt) - existing_representation = response.scalar_one_or_none() - - existing_representation_content = ( - existing_representation.content if existing_representation else "None" - ) - logger.info(f"User {user_id}: Existing Representation retrieved") - logger.debug(f"User {user_id}: Existing Representation: {existing_representation_content}") - - langfuse_context.update_current_trace( - session_id=session_id, + embedding_store = CollectionEmbeddingStore( + db=db, + app_id=app_id, user_id=user_id, - release=os.getenv("SENTRY_RELEASE"), - metadata={"environment": os.getenv("SENTRY_ENVIRONMENT")}, + collection_id=collection.public_id, # type: ignore ) - # Call user_representation - user_representation_response = await get_user_representation( - chat_history=chat_history_str, - session_id=session_id, - user_representation=existing_representation_content, - tom_inference=tom_inference, - method=USER_REPRESENTATION_METHOD, + # Filter out facts that are duplicates of existing facts in the vector store + logger.debug("Removing duplicate facts") + dedup_start = os.times()[4] + unique_facts = await embedding_store.remove_duplicates(facts) + dedup_time = os.times()[4] - dedup_start + logger.debug( + f"Found {len(unique_facts)}/{len(facts)} unique facts in {dedup_time:.2f}s" ) - # parse the user_representation response - user_representation_response = parse_xml_content( - user_representation_response, "representation" + # Only save the unique facts + if unique_facts: + logger.debug(f"Saving {len(unique_facts)} unique facts to vector store") + save_start = os.times()[4] + await embedding_store.save_facts(unique_facts, message_id=message_id) + save_time = os.times()[4] - save_start + logger.debug(f"Facts saved in {save_time:.2f}s") + else: + logger.debug("No unique facts to save") + + console.print(f"Saved {len(unique_facts)} unique facts", style="bright_green") + + total_time = os.times()[4] - process_start + logger.debug(f"Total processing time: {total_time:.2f}s") + + +async def summarize_if_needed( + db: AsyncSession, session_id: str, user_id: str, message_id: str +): + summary_start = os.times()[4] + logger.debug("Checking if summaries should be created") + + # STEP 1: First check if we need a short summary (every 10 messages) + ( + should_create_short, + short_messages, + latest_short_summary, + ) = await history.should_create_summary( + db, session_id, summary_type=history.SummaryType.SHORT ) - # Store the user_representation response as a metamessage - await add_metamessage( - db, - message_id, - "user_representation", - user_representation_response, - ) - await db.commit() + if should_create_short: + logger.debug(f"Short summary needed for {len(short_messages)} messages") - console.print( - f"User Representation:\n{user_representation_response}", - style="bright_green", - ) + # STEP 2: If we need a short summary, check if we also need a long summary + ( + should_create_long, + long_messages, + latest_long_summary, + ) = await history.should_create_summary( + db, session_id, summary_type=history.SummaryType.LONG + ) + + # STEP 3: If we need a long summary, create it first before creating the short summary + if should_create_long: + logger.debug( + f"Creating new long summary covering {len(long_messages)} messages" + ) + try: + # Get previous long summary context if available + previous_long_summary = ( + latest_long_summary.content if latest_long_summary else None + ) + + # Create a new long summary + long_summary_text = await history.create_summary( + messages=long_messages, + previous_summary=previous_long_summary, + summary_type=history.SummaryType.LONG, + ) + # Save the long summary as a metamessage and capture the returned object + latest_long_summary = await history.save_summary_metamessage( + db=db, + user_id=user_id, + session_id=session_id, + message_id=message_id, + summary_content=long_summary_text, + message_count=len(long_messages), + summary_type=history.SummaryType.LONG, + ) + logger.debug("Long summary created and saved successfully") + except Exception as e: + logger.error(f"Error creating long summary: {str(e)}") + else: + logger.debug( + f"No long summary needed. Need {history.MESSAGES_PER_LONG_SUMMARY} messages since last long summary." + ) + + # STEP 4: Now create the short summary, using the latest long summary for context if available + logger.debug( + f"Creating new short summary covering {len(short_messages)} messages" + ) + try: + previous_summary = ( + latest_long_summary.content if latest_long_summary else None + ) + # Create a new short summary + short_summary_text = await history.create_summary( + messages=short_messages, + previous_summary=previous_summary, + summary_type=history.SummaryType.SHORT, + ) + # Save the short summary as a metamessage + await history.save_summary_metamessage( + db=db, + user_id=user_id, + session_id=session_id, + message_id=message_id, + summary_content=short_summary_text, + message_count=len(short_messages), + summary_type=history.SummaryType.SHORT, + ) + logger.debug("Short summary created and saved successfully") + except Exception as e: + logger.error(f"Error creating short summary: {str(e)}") + else: + logger.debug( + f"No short summary needed. Need {history.MESSAGES_PER_SHORT_SUMMARY} messages since last short summary." + ) + + summary_time = os.times()[4] - summary_start + logger.debug(f"Summary check completed in {summary_time:.2f}s") diff --git a/src/deriver/queue.py b/src/deriver/queue.py index ef0ee2fd..33d87e5a 100644 --- a/src/deriver/queue.py +++ b/src/deriver/queue.py @@ -1,8 +1,8 @@ import asyncio -import logging import os import signal from datetime import datetime, timedelta +from logging import getLogger import sentry_sdk from dotenv import load_dotenv @@ -16,7 +16,7 @@ from .. import models from ..db import SessionLocal from .consumer import process_item -logger = logging.getLogger(__name__) +logger = getLogger(__name__) load_dotenv() @@ -57,13 +57,19 @@ class QueueManager: async def initialize(self): """Setup signal handlers and start the main polling loop""" + logger.debug(f"Initializing QueueManager with {self.workers} workers") + + # Set up signal handlers loop = asyncio.get_running_loop() signals = (signal.SIGTERM, signal.SIGINT) for sig in signals: loop.add_signal_handler( sig, lambda s=sig: asyncio.create_task(self.shutdown(s)) ) + logger.debug("Signal handlers registered") + # Run the polling loop directly in this task + logger.debug("Starting polling loop directly") try: await self.polling_loop() finally: @@ -75,7 +81,9 @@ class QueueManager: self.shutdown_event.set() if self.active_tasks: - logger.info(f"Waiting for {len(self.active_tasks)} active tasks to complete...") + logger.info( + f"Waiting for {len(self.active_tasks)} active tasks to complete..." + ) await asyncio.gather(*self.active_tasks, return_exceptions=True) async def cleanup(self): @@ -86,7 +94,9 @@ class QueueManager: async with SessionLocal() as db: await db.execute( delete(models.ActiveQueueSession).where( - models.ActiveQueueSession.session_id.in_(self.owned_sessions) + models.ActiveQueueSession.session_id.in_( + self.owned_sessions + ) ) ) await db.commit() @@ -128,15 +138,18 @@ class QueueManager: async def polling_loop(self): """Main polling loop to find and process new sessions""" + logger.debug("Starting polling loop") try: while not self.shutdown_event.is_set(): if self.queue_empty_flag.is_set(): + # logger.debug("Queue empty flag set, waiting") await asyncio.sleep(1) self.queue_empty_flag.clear() continue - # Chec if we have capacity before querying + # Check if we have capacity before querying if self.semaphore.locked(): + # logger.debug("All workers busy, waiting") await asyncio.sleep(1) # Wait before trying again continue @@ -150,13 +163,16 @@ class QueueManager: # Try to claim the session await db.execute( insert(models.ActiveQueueSession).values( - session_id=session_id + session_id=session_id, ) ) await db.commit() # Track this session self.track_session(session_id) + logger.debug( + f"Claimed session {session_id} for processing" + ) # Create a new task for processing this session if not self.shutdown_event.is_set(): @@ -166,6 +182,9 @@ class QueueManager: self.add_task(task) except IntegrityError: await db.rollback() + logger.debug( + f"Failed to claim session {session_id}, already owned" + ) else: self.queue_empty_flag.set() await asyncio.sleep(1) @@ -185,39 +204,60 @@ class QueueManager: @sentry_sdk.trace async def process_session(self, session_id: int): """Process all messages for a session""" + logger.debug(f"Starting to process session {session_id}") async with self.semaphore: # Hold the semaphore for the entire session duration async with SessionLocal() as db: try: + message_count = 0 while not self.shutdown_event.is_set(): message = await self.get_next_message(db, session_id) if not message: + logger.debug(f"No more messages for session {session_id}") break + + message_count += 1 + logger.debug( + f"Processing message {message.id} for session {session_id} (message {message_count})" + ) try: - logger.info(f"Processing message {message.id} from session {session_id}") + logger.info( + f"Processing message {message.id} from session {session_id}" + ) await process_item(db, payload=message.payload) - logger.info(f"Successfully processed message {message.id}") + logger.debug(f"Successfully processed message {message.id}") except Exception as e: - logger.error(f"Error processing message {message.id}: {str(e)}", exc_info=True) + logger.error( + f"Error processing message {message.id}: {str(e)}", + exc_info=True, + ) if os.getenv("SENTRY_ENABLED", "False").lower() == "true": sentry_sdk.capture_exception(e) finally: # Prevent malformed messages from stalling queue indefinitely message.processed = True await db.commit() - logger.info(f"Marked message {message.id} as processed") + logger.debug(f"Marked message {message.id} as processed") if self.shutdown_event.is_set(): + logger.debug( + f"Shutdown requested, stopping processing for session {session_id}" + ) break - # Update last_updated timestamp to showthis session is still being processed + # Update last_updated timestamp to show this session is still being processed await db.execute( update(models.ActiveQueueSession) .where(models.ActiveQueueSession.session_id == session_id) .values(last_updated=func.now()) ) await db.commit() + + logger.debug( + f"Completed processing session {session_id}, processed {message_count} messages" + ) finally: # Remove session from active_sessions when done + logger.debug(f"Removing session {session_id} from active sessions") await db.execute( delete(models.ActiveQueueSession).where( models.ActiveQueueSession.session_id == session_id @@ -241,5 +281,12 @@ class QueueManager: async def main(): + logger.debug("Starting queue manager") manager = QueueManager() - await manager.initialize() + try: + await manager.initialize() + except Exception as e: + logger.error(f"Error in main: {str(e)}") + sentry_sdk.capture_exception(e) + finally: + logger.debug("Main function exiting") diff --git a/src/deriver/tom/README.md b/src/deriver/tom/README.md new file mode 100644 index 00000000..66e56d25 --- /dev/null +++ b/src/deriver/tom/README.md @@ -0,0 +1,13 @@ +# Theory of Mind Inference +[Theory of Mind](https://blog.plasticlabs.ai/blog/Theory-of-Mind-Is-All-You-Need) is a core principle behind Honcho: we believe that enabling AI agents to reason about users' mental states is essential if we want them to successfully act on our behalf. + +Honcho currently features three different modules for theory of mind inference: +- `conversational.py`: Inspired by our work on [metanarrative prompting](https://blog.plasticlabs.ai/blog/Agent-Identity). Uses a metanarrative prompt for both ToM inference and generating a user representation. +- `single_prompt.py`: A more conventional and straightforward approach that specifies in a single system prompt what it wants the LLM to output. +- `long_term.py`: Formats a theory of mind inference and a series of long-term facts into a user representation. + +The current setup works as follows: +- We extract facts from incoming messages using the code in `src.deriver.consumer`. +- These messages get added to the protected `honcho` user collection using the `CollectionEmbeddingStore` in `src.deriver.tom.embeddings`. +- The dialectic endpoint, in `src.agent`, retrieves long-term facts from this store that are relevant to the query, and runs the ToM inference in `src.deriver.tom.single_prompt` to generate a prediction of the user's short-term mental state. +- The retrieved long-term facts and the short-term ToM inference are combined into a user representation. By default, this is done using a simple f-string, but they can optionally be combined using a separate inference, which would use `src.deriver.tom.long_term`. \ No newline at end of file diff --git a/src/deriver/tom/__init__.py b/src/deriver/tom/__init__.py index 477ab531..5d6a6452 100644 --- a/src/deriver/tom/__init__.py +++ b/src/deriver/tom/__init__.py @@ -1,30 +1,52 @@ -from .conversational import get_tom_inference_conversational, get_user_representation_conversational -from .single_prompt import get_tom_inference_single_prompt, get_user_representation_single_prompt +from .conversational import ( + get_tom_inference_conversational, + get_user_representation_conversational, +) +from .long_term import get_user_representation_long_term +from .single_prompt import ( + get_tom_inference_single_prompt, + get_user_representation_single_prompt, +) -async def get_tom_inference(chat_history: str, - session_id: str, - user_representation: str = "None", - method: str = "conversational", - **kwargs - ) -> str: + +async def get_tom_inference( + chat_history: str, + session_id: str, + user_representation: str = "None", + method: str = "conversational", + **kwargs, +) -> str: if method == "conversational": - return await get_tom_inference_conversational(chat_history, session_id, user_representation, **kwargs) + return await get_tom_inference_conversational( + chat_history, session_id, user_representation, **kwargs + ) elif method == "single_prompt": - return await get_tom_inference_single_prompt(chat_history, session_id, user_representation, **kwargs) + return await get_tom_inference_single_prompt( + chat_history, session_id, user_representation, **kwargs + ) else: raise ValueError(f"Invalid method: {method}") -async def get_user_representation(chat_history: str, - session_id: str, - user_representation: str = "None", - tom_inference: str = "None", - method: str = "conversational", - **kwargs - ) -> str: +async def get_user_representation( + chat_history: str, + session_id: str, + user_representation: str = "None", + tom_inference: str = "None", + method: str = "conversational", + **kwargs, +) -> str: if method == "conversational": - return await get_user_representation_conversational(chat_history, session_id, user_representation, tom_inference, **kwargs) + return await get_user_representation_conversational( + chat_history, session_id, user_representation, tom_inference, **kwargs + ) elif method == "single_prompt": - return await get_user_representation_single_prompt(chat_history, session_id, user_representation, tom_inference, **kwargs) + return await get_user_representation_single_prompt( + chat_history, session_id, user_representation, tom_inference, **kwargs + ) + elif method == "long_term": + return await get_user_representation_long_term( + chat_history, session_id, user_representation, tom_inference, **kwargs + ) else: - raise ValueError(f"Invalid method: {method}") \ No newline at end of file + raise ValueError(f"Invalid method: {method}") diff --git a/src/deriver/tom/conversational.py b/src/deriver/tom/conversational.py index bc604adf..98b91bfe 100644 --- a/src/deriver/tom/conversational.py +++ b/src/deriver/tom/conversational.py @@ -15,7 +15,7 @@ anthropic = Anthropic( @ai_track("Tom Inference") -@observe(as_type="generation") +@observe() async def get_tom_inference_conversational( chat_history: str, session_id: str, user_representation: str = "None" ) -> str: @@ -81,7 +81,7 @@ async def get_tom_inference_conversational( @ai_track("User Representation") -@observe(as_type="generation") +@observe() async def get_user_representation_conversational( chat_history: str, session_id: str, diff --git a/src/deriver/tom/embeddings.py b/src/deriver/tom/embeddings.py new file mode 100644 index 00000000..031c28c1 --- /dev/null +++ b/src/deriver/tom/embeddings.py @@ -0,0 +1,114 @@ +import logging + +from sqlalchemy.ext.asyncio import AsyncSession + +from ... import crud, schemas + +logger = logging.getLogger(__name__) + + +class CollectionEmbeddingStore: + def __init__(self, db: AsyncSession, app_id: str, user_id: str, collection_id: str): + self.db = db + self.app_id = app_id + self.user_id = user_id + self.collection_id = collection_id + + async def save_facts( + self, + facts: list[str], + replace_duplicates: bool = True, + similarity_threshold: float = 0.85, + message_id: str = None, + ) -> None: + """Save facts to the collection. + + Args: + facts: List of facts to save + replace_duplicates: If True, replace old duplicates with new facts. If False, discard new duplicates + similarity_threshold: Facts with similarity above this threshold are considered duplicates + """ + for fact in facts: + # Create document with duplicate checking + try: + metadata = {} + if message_id: + metadata["message_id"] = message_id + await crud.create_document( + self.db, + document=schemas.DocumentCreate(content=fact, metadata=metadata), + app_id=self.app_id, + user_id=self.user_id, + collection_id=self.collection_id, + duplicate_threshold=1 + - similarity_threshold, # Convert similarity to distance + ) + except Exception as e: + logger.error(f"Error creating document: {e}") + continue + + async def get_relevant_facts( + self, query: str, top_k: int = 5, max_distance: float = 0.3 + ) -> list[str]: + """Retrieve the most relevant facts for a given query. + + Args: + query: The query text to find relevant facts for + top_k: Maximum number of facts to return + similarity_threshold: Minimum similarity score for a fact to be considered relevant + + Returns: + List of facts sorted by relevance + """ + documents = await crud.query_documents( + self.db, + app_id=self.app_id, + user_id=self.user_id, + collection_id=self.collection_id, + query=query, + max_distance=max_distance, + top_k=top_k, + ) + + return [doc.content for doc in documents] + + async def remove_duplicates( + self, facts: list[str], similarity_threshold: float = 0.85 + ) -> list[str]: + """Remove facts that are duplicates of existing facts in the vector store. + + Args: + facts: List of facts to check for duplicates + similarity_threshold: Facts with similarity above this threshold are considered duplicates + + Returns: + List of facts that are not duplicates of existing facts + """ + unique_facts = [] + + for fact in facts: + try: + # Check for duplicates using the crud function + duplicates = await crud.get_duplicate_documents( + self.db, + app_id=self.app_id, + user_id=self.user_id, + collection_id=self.collection_id, + content=fact, + similarity_threshold=similarity_threshold, + ) + + if not duplicates: + # No duplicates found, add to unique facts + unique_facts.append(fact) + else: + # Log duplicate found + logger.debug( + f"Duplicate found: {duplicates[0].content}. Ignoring fact: {fact}" + ) + except Exception as e: + logger.error(f"Error checking for duplicates: {e}") + # If there's an error, still include the fact to avoid losing information + unique_facts.append(fact) + + return unique_facts diff --git a/src/deriver/tom/long_term.py b/src/deriver/tom/long_term.py new file mode 100644 index 00000000..c40fcbcf --- /dev/null +++ b/src/deriver/tom/long_term.py @@ -0,0 +1,216 @@ +import json +import logging +import time +from typing import Optional + +from langfuse.decorators import observe +from sentry_sdk.ai.monitoring import ai_track + +from src.utils import parse_xml_content +from src.utils.model_client import ModelClient, ModelProvider + +from .embeddings import CollectionEmbeddingStore + +# Configure logging +logger = logging.getLogger(__name__) + +# Constants for fact extraction +FACT_EXTRACTION_PROVIDER = ModelProvider.GEMINI +FACT_EXTRACTION_MODEL = "gemini-2.0-flash-lite" + +USER_REPRESENTATION_PROVIDER = ModelProvider.GROQ +USER_REPRESENTATION_MODEL = "llama-3.3-70b-versatile" + +MAX_FACT_DISTANCE = 0.85 + + +@ai_track("User Representation") +@observe() +async def get_user_representation_long_term( + chat_history: str, + session_id: str, + embedding_store: CollectionEmbeddingStore, + user_representation: str = "None", + tom_inference: str = "None", + facts: Optional[list[str]] = None, +) -> str: + if facts is None: + facts = [] + facts_str = "\n".join([f"- {fact}" for fact in facts]) + logger.debug(f"Facts: {facts_str}") + + system_prompt = """You are a system for maintaining factual user representations based on conversation history and theory of mind analysis. + +Your job is to update the existing user representation (if provided) with the new information from the conversation history and theory of mind analysis. + +REQUIREMENTS: +1. Distinguish between temporary states and persistent patterns +2. Only incorporate verified information into core profile +3. Track certainty levels for all information +4. Maintain areas of uncertainty explicitly +5. Update representation incrementally +6. DO NOT generate persistent information - it will be injected separately. Always include the tag in your response in order to inject the facts. + +OUTPUT FORMAT: + +CURRENT STATE: +- Active Context: Current situation/activity +- Temporary Conditions: Immediate circumstances + +- Present Mood/Activity: What user is doing right now + + + +TENTATIVE PATTERNS: +- Possible Traits: Mark confidence (Low/Medium/High) +- Potential Interests: Need more evidence +- Speculative Elements: Clearly marked as unconfirmed + +KNOWLEDGE GAPS: +- List key missing information +- Note areas needing clarification + +EXPECTATION VIOLATIONS: +- Based on the above information, if the next message were to surprise you, what could it contain? +- Format: "POTENTIAL SURPRISE: [possible content] [reason] [confidence level]" +- Include 3-5 possible surprises + +UPDATES: +- New Information: Recent observations +- Changes: Modified interpretations +- Removals: Information no longer supported + +""" + + # Build the context message + context_str = f"CONVERSATION:\n{chat_history}\n\n" + if tom_inference != "None": + context_str += f"PREDICTION OF USER MENTAL STATE - MIGHT BE INCORRECT:\n{tom_inference}\n\n" + if user_representation != "None": + context_str += f"EXISTING USER REPRESENTATION - INCOMPLETE, TO BE UPDATED:\n{user_representation}" + + messages = [ + { + "role": "user", + "content": f"Please analyze this information and provide an updated user representation. DO NOT generate persistent information - it will be injected separately:\n{context_str}", + } + ] + + # Create a new model client + client = ModelClient( + provider=USER_REPRESENTATION_PROVIDER, model=USER_REPRESENTATION_MODEL + ) + + # Generate the response with caching enabled + response = await client.generate( + messages=messages, + system=system_prompt, + max_tokens=1000, + temperature=0, + use_caching=True, # Enable caching for the system prompt + ) + + # Inject the facts into the response + persistent_info = f"""PERSISTENT INFORMATION: +{facts_str}""" + + return response.replace("", persistent_info) + + +@ai_track("Fact Extraction") +@observe() +async def extract_facts_long_term(chat_history: str) -> list[str]: + logger.debug("Starting fact extraction from chat history") + extract_start = time.time() + + system_prompt = """ + You are an AI assistant specialized in extracting and formatting relevant information about users from conversations. Your task is to analyze a given conversation and create a list of concise, factual statements about the user. These statements will be stored in a vector embedding database to enhance future interactions. + +Here is the conversation you need to analyze: + + +{chat_history} + + +Instructions: + +1. Carefully read through the conversation. Extract only new facts, from only the last message sent by the user - treat the rest of the conversation only as context. Ignore facts in the last message that are already stated in the conversation. + +2. Identify key new pieces of information from the last message sent by the user that would be valuable for future interactions. Look for: + - Personal details (name, age, occupation, location, etc.) + - Preferences (likes, dislikes, interests, hobbies) + - Experiences (travel, education, work history) + - Expressive style (writing style, tone, etc.) + - Relationships (family, friends, pets) + - Goals or aspirations + - Challenges or problems they're facing + - Opinions or beliefs + +3. For each piece of information you identify: + a. Verify that it is factual and explicitly stated in the conversation, not inferred. + b. Formulate it as a concise statement that would aid in semantic retrieval. + c. Ensure it is not similar to information previously stated in the conversation. + +4. Before providing your final output, wrap your analysis in tags. In this analysis: + - List each piece of information you've identified. + - For each piece of information: + * Quote the relevant part of the conversation. + * Categorize the information (e.g., personal detail, preference, experience). + * Explain why you've included this information. + * Show how you've formulated the fact for optimal semantic retrieval. + - Discuss any challenges you encountered in extracting or formatting the information. + +5. After your analysis, provide your final output as a JSON array of strings. Each string should be a single fact about the user. Wrap the facts in tags. + +Example of the expected output format: + +[Analysis goes here] + + +{{ +"facts": +[ + "User is 28 years old", + "User's friend Mary works as a software engineer", + "Favorite food is sushi" +] +}} + + +Remember to focus on clear, concise statements that capture key information about the user. Each fact should be worded in a way that will aid its semantic retrieval from a vector embedding database. It's OK for this section to be quite long. + """ + message = system_prompt.format(chat_history=chat_history) + messages = [{"role": "user", "content": message}] + + logger.debug("Calling LLM for fact extraction") + llm_start = time.time() + + # Create a new model client + client = ModelClient(provider=FACT_EXTRACTION_PROVIDER, model=FACT_EXTRACTION_MODEL) + + # Generate the response with caching enabled + response = await client.generate( + messages=messages, + max_tokens=1000, + temperature=0.0, + use_caching=True, # Enable caching for the system prompt + ) + + llm_time = time.time() - llm_start + logger.debug(f"LLM response received in {llm_time:.2f}s") + + try: + logger.debug("Parsing JSON response") + facts_str = parse_xml_content(response, "facts") + response_data = json.loads(facts_str) + facts = response_data["facts"] + logger.debug(f"Extracted {len(facts)} facts") + if facts: + logger.debug(f"Sample facts: {facts[:3] if len(facts) > 3 else facts}") + except (json.JSONDecodeError, KeyError) as e: + logger.error(f"Error parsing response: {str(e)}") + facts = [] + + total_time = time.time() - extract_start + logger.debug(f"Total extraction completed in {total_time:.2f}s") + return facts diff --git a/src/deriver/tom/single_prompt.py b/src/deriver/tom/single_prompt.py index 929c6bfd..3696eb5e 100644 --- a/src/deriver/tom/single_prompt.py +++ b/src/deriver/tom/single_prompt.py @@ -1,28 +1,18 @@ -import os +import logging +from typing import Any, Optional import sentry_sdk -from anthropic import Anthropic from langfuse.decorators import langfuse_context, observe from sentry_sdk.ai.monitoring import ai_track -# Place the code below at the beginning of your application to initialize the tracer +from src.utils.model_client import ModelClient, ModelProvider -# Initialize the Anthropic client -anthropic = Anthropic( - api_key=os.getenv("ANTHROPIC_API_KEY"), - max_retries=5, -) +logger = logging.getLogger(__name__) -ANTHROPIC_MODEL = "claude-3-5-haiku-20241022" +DEF_PROVIDER = ModelProvider.GROQ +DEF_MODEL = "llama-3.3-70b-versatile" - -@ai_track("Tom Inference") -@observe(as_type="generation") -async def get_tom_inference_single_prompt( - chat_history: str, session_id: str, user_representation: str = "None", **kwargs -) -> str: - with sentry_sdk.start_transaction(op="tom-inference", name="ToM Inference"): - system_prompt = """You are a system for analyzing conversations to make evidence-based inferences about user mental states. +TOM_SYSTEM_PROMPT = """You are a system for analyzing conversations to make evidence-based inferences about user mental states. REQUIREMENTS: 1. Only make inferences that are directly supported by conversation evidence @@ -56,53 +46,9 @@ EXPECTATION VIOLATIONS: - Based on the above information, if the next message were to surprise you, what could it contain? - Format: "POTENTIAL SURPRISE: [possible content] [reason] [confidence level]" - Include 3-5 possible surprises - -""" +""" - messages = [ - { - "role": "user", - "content": f"Please analyze this conversation and provide a prediction following the format above:\n{chat_history}", - } - ] - - # Add existing user representation if available - if user_representation != "None": - messages.append( - { - "role": "user", - "content": f"Consider this existing user representation for context, but focus on current state:\n{user_representation}", - } - ) - - langfuse_context.update_current_observation( - input=messages, model=ANTHROPIC_MODEL - ) - message = anthropic.messages.create( - model=ANTHROPIC_MODEL, - max_tokens=1000, - temperature=0, - messages=messages, - system=system_prompt, - ) - print(f"tom_inference in single_prompt.py: {message.content[0].text=}") - message = message.content[0].text - return message - - -@ai_track("User Representation") -@observe(as_type="generation") -async def get_user_representation_single_prompt( - chat_history: str, - session_id: str, - user_representation: str = "None", - tom_inference: str = "None", - **kwargs, -) -> str: - with sentry_sdk.start_transaction( - op="user-representation-inference", name="User Representation" - ): - system_prompt = """You are a system for maintaining factual user representations based on conversation history and theory of mind analysis. +USER_REPRESENTATION_SYSTEM_PROMPT = """You are a system for maintaining factual user representations based on conversation history and theory of mind analysis. Your job is to update the existing user representation (if provided) with the new information from the conversation history and theory of mind analysis. @@ -152,36 +98,101 @@ UPDATES: - New Information: Recent observations - Changes: Modified interpretations - Removals: Information no longer supported - -""" +""" - messages = [] - print(f"in single_prompt.py: chat_history: {chat_history}") - print(f"in single_prompt.py: user_representation: {user_representation}") +@ai_track("Tom Inference") +@observe() +async def get_tom_inference_single_prompt( + chat_history: str, + session_id: str, + user_representation: Optional[str] = None, + **kwargs, +) -> str: + with sentry_sdk.start_transaction(op="tom-inference", name="ToM Inference"): + # Create a new model client + client = ModelClient(provider=DEF_PROVIDER, model=DEF_MODEL) + + # Prepare the messages + messages: list[dict[str, Any]] = [ + { + "role": "user", + "content": f"Please analyze this conversation and provide a prediction following the format above:\n{chat_history}", + } + ] + + # Add existing user representation if available + if user_representation: + messages.append( + { + "role": "user", + "content": f"Consider this existing user representation for context, but focus on current state:\n{user_representation}", + } + ) + + langfuse_context.update_current_observation(input=messages, model=DEF_MODEL) + + # Generate the response with caching enabled + try: + response = await client.generate( + messages=messages, + system=TOM_SYSTEM_PROMPT, + max_tokens=1000, + temperature=0, + use_caching=True, # Enable caching for the system prompt + ) + except Exception as e: + sentry_sdk.capture_exception(e) + logger.error(f"Error generating Tom inference: {e}") + raise e + + return response + + +@ai_track("User Representation") +@observe() +async def get_user_representation_single_prompt( + chat_history: str, + session_id: str, + user_representation: Optional[str] = None, + tom_inference: Optional[str] = None, + **kwargs, +) -> str: + with sentry_sdk.start_transaction( + op="user-representation-inference", name="User Representation" + ): + # Create a new model client + client = ModelClient(provider=DEF_PROVIDER, model=DEF_MODEL) + # Build the context message context_str = f"CONVERSATION:\n{chat_history}\n\n" - if tom_inference != "None": + if tom_inference: context_str += f"PREDICTION OF USER MENTAL STATE - MIGHT BE INCORRECT:\n{tom_inference}\n\n" - if user_representation != "None": + if user_representation: context_str += f"EXISTING USER REPRESENTATION - INCOMPLETE, TO BE UPDATED:\n{user_representation}" - messages.append( + # Prepare the messages + messages: list[dict[str, Any]] = [ { "role": "user", "content": f"Please analyze this information and provide an updated user representation:\n{context_str}", } - ) + ] - langfuse_context.update_current_observation( - input=messages, model=ANTHROPIC_MODEL - ) - message = anthropic.messages.create( - model=ANTHROPIC_MODEL, - max_tokens=1000, - temperature=0, - messages=messages, - system=system_prompt, - ) - message = message.content[0].text - return message + langfuse_context.update_current_observation(input=messages, model=DEF_MODEL) + + # Generate the response with caching enabled + try: + response = await client.generate( + messages=messages, + system=USER_REPRESENTATION_SYSTEM_PROMPT, + max_tokens=1000, + temperature=0, + use_caching=True, # Enable caching for the system prompt + ) + except Exception as e: + sentry_sdk.capture_exception(e) + logger.error(f"Error generating user representation: {e}") + raise e + + return response diff --git a/src/exceptions.py b/src/exceptions.py index 1b034a33..3088ce82 100644 --- a/src/exceptions.py +++ b/src/exceptions.py @@ -1,14 +1,16 @@ """ Custom exceptions for the Honcho application. """ + from typing import Optional class HonchoException(Exception): """Base exception for all Honcho-specific errors.""" + status_code = 500 detail = "An unexpected error occurred" - + def __init__(self, detail: Optional[str] = None, status_code: Optional[int] = None): self.detail = detail or self.detail self.status_code = status_code or self.status_code @@ -17,29 +19,41 @@ class HonchoException(Exception): class ResourceNotFoundException(HonchoException): """Exception raised when a requested resource is not found.""" + status_code = 404 detail = "Resource not found" class ValidationException(HonchoException): """Exception raised when validation fails.""" + status_code = 422 detail = "Validation error" class ConflictException(HonchoException): """Exception raised when there's a resource conflict.""" + status_code = 409 detail = "Resource conflict" class AuthenticationException(HonchoException): """Exception raised when authentication fails.""" + status_code = 401 detail = "Authentication failed" class AuthorizationException(HonchoException): """Exception raised when authorization fails.""" + status_code = 403 - detail = "Not authorized to access this resource" \ No newline at end of file + detail = "Not authorized to access this resource" + + +class DisabledException(HonchoException): + """Exception raised when a feature is disabled.""" + + status_code = 405 + detail = "Feature is disabled" diff --git a/src/main.py b/src/main.py index 6ff7a123..4d9143a8 100644 --- a/src/main.py +++ b/src/main.py @@ -10,33 +10,65 @@ from fastapi_pagination import add_pagination from sentry_sdk.integrations.fastapi import FastApiIntegration from sentry_sdk.integrations.starlette import StarletteIntegration +from src.db import engine from src.exceptions import HonchoException from src.routers import ( apps, collections, documents, + keys, messages, metamessages, sessions, users, ) +from src.security import create_admin_jwt + + +def get_log_level(env_var="LOG_LEVEL", default="INFO"): + """ + Convert log level string from environment variable to logging module constant. + + Args: + env_var: Name of the environment variable to check + default: Default log level if environment variable is not set + + Returns: + int: The logging level constant (e.g., logging.INFO) + """ + log_level_str = os.getenv(env_var, default).upper() + + log_levels = { + "CRITICAL": logging.CRITICAL, # 50 + "ERROR": logging.ERROR, # 40 + "WARNING": logging.WARNING, # 30 + "INFO": logging.INFO, # 20 + "DEBUG": logging.DEBUG, # 10 + "NOTSET": logging.NOTSET, # 0 + } + + return log_levels.get(log_level_str, logging.INFO) -from .db import engine, scaffold_db # Configure logging logging.basicConfig( - level=logging.INFO, + level=get_log_level(), format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", ) logger = logging.getLogger(__name__) -# Sentry Setup +# JWT Setup +async def setup_admin_jwt(): + token = create_admin_jwt() + print(f"\n ADMIN JWT: {token}\n") + + +# Sentry Setup SENTRY_ENABLED = os.getenv("SENTRY_ENABLED", "False").lower() == "true" if SENTRY_ENABLED: sentry_sdk.init( dsn=os.getenv("SENTRY_DSN"), - enable_tracing=True, traces_sample_rate=0.4, profiles_sample_rate=0.4, integrations=[ @@ -52,7 +84,6 @@ if SENTRY_ENABLED: @asynccontextmanager async def lifespan(app: FastAPI): - scaffold_db() # Scaffold Database on Startup yield await engine.dispose() @@ -60,17 +91,17 @@ async def lifespan(app: FastAPI): app = FastAPI( lifespan=lifespan, servers=[ - {"url": "http://127.0.0.1:8000", "description": "Local Development Server"}, - {"url": "https:/demo.honcho.dev", "description": "Demo Server"}, + {"url": "http://localhost:8000", "description": "Local Development Server"}, + {"url": "https://demo.honcho.dev", "description": "Demo Server"}, + {"url": "https://api.honcho.dev", "description": "Production SaaS Platform"}, ], title="Honcho API", - summary="An API for adding personalization to AI Apps", - description="""This API is used to store data and get insights about users for AI - applications""", - version="0.0.16", + summary="The Identity Layer for the Agentic World", + description="""Honcho is a platform for giving agents user-centric memory and social cognition""", + version="1.0.0", contact={ "name": "Plastic Labs", - "url": "https://plasticlabs.ai", + "url": "https://honcho.dev", "email": "hello@plasticlabs.ai", }, license_info={ @@ -99,9 +130,9 @@ app.include_router(users.router, prefix="/v1") app.include_router(sessions.router, prefix="/v1") app.include_router(messages.router, prefix="/v1") app.include_router(metamessages.router, prefix="/v1") -app.include_router(metamessages.router_user_level, prefix="/v1") app.include_router(collections.router, prefix="/v1") app.include_router(documents.router, prefix="/v1") +app.include_router(keys.router, prefix="/v1") # Global exception handlers diff --git a/src/models.py b/src/models.py index e78dfd0d..2f62b37f 100644 --- a/src/models.py +++ b/src/models.py @@ -10,7 +10,9 @@ from sqlalchemy import ( DateTime, ForeignKey, Identity, + Index, UniqueConstraint, + text, ) from sqlalchemy.dialects.postgresql import JSONB, TEXT from sqlalchemy.orm import Mapped, mapped_column, relationship @@ -60,12 +62,14 @@ class User(Base): app = relationship("App", back_populates="users") sessions = relationship("Session", back_populates="user") collections = relationship("Collection", back_populates="user") + metamessages = relationship("Metamessage", back_populates="user") __table_args__ = ( UniqueConstraint("name", "app_id", name="unique_name_app_user"), CheckConstraint("length(public_id) = 21", name="public_id_length"), CheckConstraint("length(name) <= 512", name="name_length"), CheckConstraint("public_id ~ '^[A-Za-z0-9_-]+$'", name="public_id_format"), + Index("idx_users_app_lookup", "app_id", "public_id"), ) def __repr__(self) -> str: @@ -86,12 +90,14 @@ class Session(Base): DateTime(timezone=True), index=True, default=func.now() ) messages = relationship("Message", back_populates="session") + metamessages = relationship("Metamessage", back_populates="session") user_id: Mapped[str] = mapped_column(ForeignKey("users.public_id"), index=True) user = relationship("User", back_populates="sessions") __table_args__ = ( CheckConstraint("length(public_id) = 21", name="public_id_length"), CheckConstraint("public_id ~ '^[A-Za-z0-9_-]+$'", name="public_id_format"), + Index("idx_sessions_user_lookup", "user_id", "public_id"), ) def __repr__(self) -> str: @@ -123,6 +129,12 @@ class Message(Base): CheckConstraint("length(public_id) = 21", name="public_id_length"), CheckConstraint("public_id ~ '^[A-Za-z0-9_-]+$'", name="public_id_format"), CheckConstraint("length(content) <= 65535", name="content_length"), + Index( + "idx_messages_session_lookup", + "session_id", + "id", + postgresql_include=["public_id", "is_user", "created_at"], + ), ) def __repr__(self) -> str: @@ -139,11 +151,21 @@ class Metamessage(Base): ) metamessage_type: Mapped[str] = mapped_column(TEXT, index=True) content: Mapped[str] = mapped_column(TEXT) - message_id: Mapped[str] = mapped_column( - ForeignKey("messages.public_id"), index=True + + # Foreign keys - message_id is now optional + user_id: Mapped[str] = mapped_column(ForeignKey("users.public_id"), index=True) + session_id: Mapped[str | None] = mapped_column( + ForeignKey("sessions.public_id"), index=True, nullable=True + ) + message_id: Mapped[str | None] = mapped_column( + ForeignKey("messages.public_id"), index=True, nullable=True ) + # Relationships + user = relationship("User", back_populates="metamessages") + session = relationship("Session", back_populates="metamessages") message = relationship("Message", back_populates="metamessages") + created_at: Mapped[datetime.datetime] = mapped_column( DateTime(timezone=True), index=True, default=func.now() ) @@ -156,10 +178,41 @@ class Metamessage(Base): CheckConstraint( "length(metamessage_type) <= 512", name="metamessage_type_length" ), + # Added constraints to ensure consistency + CheckConstraint( + "(message_id IS NULL) OR (session_id IS NOT NULL)", + name="message_requires_session", + ), + # Keep existing index + Index( + "idx_metamessages_lookup", + "metamessage_type", + text("id DESC"), + postgresql_include=["public_id", "message_id", "created_at"], + ), + # Indices for user, session, and message lookups + Index( + "idx_metamessages_user_lookup", + "user_id", + "metamessage_type", + text("id DESC"), + ), + Index( + "idx_metamessages_session_lookup", + "session_id", + "metamessage_type", + text("id DESC"), + ), + Index( + "idx_metamessages_message_lookup", + "message_id", + "metamessage_type", + text("id DESC"), + ), ) def __repr__(self) -> str: - return f"Metamessages(id={self.id}, message_id={self.message_id}, metamessage_type={self.metamessage_type}, content={self.content[10:]})" + return f"Metamessages(id={self.id}, user_id={self.user_id}, session_id={self.session_id}, message_id={self.message_id}, metamessage_type={self.metamessage_type})" class Collection(Base): diff --git a/src/routers/apps.py b/src/routers/apps.py index 43580441..3c37cd28 100644 --- a/src/routers/apps.py +++ b/src/routers/apps.py @@ -1,46 +1,112 @@ import logging +from typing import Optional -from fastapi import APIRouter, Depends +from fastapi import APIRouter, Body, Depends, Path, Query +from fastapi_pagination import Page +from fastapi_pagination.ext.sqlalchemy import paginate from src import crud, schemas from src.dependencies import db -from src.exceptions import ResourceNotFoundException -from src.security import auth +from src.exceptions import AuthenticationException, ResourceNotFoundException +from src.security import JWTParams, require_auth logger = logging.getLogger(__name__) router = APIRouter( prefix="/apps", tags=["apps"], - dependencies=[Depends(auth)], ) -@router.get("/{app_id}", response_model=schemas.App) -async def get_app(app_id: str, db=db): - """Get an App by ID""" - # ResourceNotFoundException will be caught by global handler if app not found - app = await crud.get_app(db, app_id=app_id) - return app +@router.get("", response_model=schemas.App) +async def get_app( + app_id: Optional[str] = Query( + None, description="App ID to retrieve. If not provided, uses JWT token" + ), + jwt_params: JWTParams = Depends(require_auth()), + db=db, +): + """ + Get an App by ID. + + If app_id is provided as a query parameter, it uses that (must match JWT app_id). + Otherwise, it uses the app_id from the JWT token. + """ + # If app_id provided in query, check if it matches jwt or user is admin + if app_id: + if not jwt_params.ad and jwt_params.ap != app_id: + raise AuthenticationException("Unauthorized access to resource") + target_app_id = app_id + else: + # Use app_id from JWT + if not jwt_params.ap: + raise AuthenticationException("App ID not found in query parameter or JWT") + target_app_id = jwt_params.ap + + return await crud.get_app(db, app_id=target_app_id) -@router.get("/name/{name}", response_model=schemas.App) -async def get_app_by_name(name: str, db=db): +@router.post( + "/list", + response_model=Page[schemas.App], + dependencies=[Depends(require_auth(admin=True))], +) +async def get_all_apps( + options: schemas.AppGet = Body( + ..., description="Filtering and pagination options for the apps list" + ), + reverse: Optional[bool] = Query( + False, description="Whether to reverse the order of results" + ), + db=db, +): + """Get all Apps""" + return await paginate( + db, + await crud.get_all_apps( + db, + reverse=reverse, + filter=options.filter, + ), + ) + + +@router.get( + "/name/{name}", + response_model=schemas.App, + dependencies=[Depends(require_auth(admin=True))], +) +async def get_app_by_name( + name: str = Path(..., description="Name of the app to retrieve"), + db=db, +): """Get an App by Name""" # ResourceNotFoundException will be caught by global handler if app not found app = await crud.get_app_by_name(db, name=name) return app -@router.post("", response_model=schemas.App) -async def create_app(app: schemas.AppCreate, db=db): +@router.post( + "", response_model=schemas.App, dependencies=[Depends(require_auth(admin=True))] +) +async def create_app( + app: schemas.AppCreate = Body(..., description="App creation parameters"), + db=db, +): """Create a new App""" honcho_app = await crud.create_app(db, app=app) return honcho_app -@router.get("/get_or_create/{name}", response_model=schemas.App) -async def get_or_create_app(name: str, db=db): +@router.get( + "/get_or_create/{name}", + response_model=schemas.App, + dependencies=[Depends(require_auth(admin=True))], +) +async def get_or_create_app( + name: str = Path(..., description="Name of the app to get or create"), + db=db, +): """Get or Create an App""" try: app = await crud.get_app_by_name(db=db, name=name) @@ -51,10 +117,14 @@ async def get_or_create_app(name: str, db=db): return app -@router.put("/{app_id}", response_model=schemas.App) +@router.put( + "/{app_id}", + response_model=schemas.App, + dependencies=[Depends(require_auth(app_id="app_id"))], +) async def update_app( - app_id: str, - app: schemas.AppUpdate, + app_id: str = Path(..., description="ID of the app to update"), + app: schemas.AppUpdate = Body(..., description="Updated app parameters"), db=db, ): """Update an App""" diff --git a/src/routers/collections.py b/src/routers/collections.py index 65a42bd5..7cd5d0ee 100644 --- a/src/routers/collections.py +++ b/src/routers/collections.py @@ -1,26 +1,82 @@ from typing import Optional -from fastapi import APIRouter, Depends +from fastapi import APIRouter, Body, Depends, Path, Query from fastapi_pagination import Page from fastapi_pagination.ext.sqlalchemy import paginate from src import crud, schemas from src.dependencies import db -from src.security import auth +from src.exceptions import AuthenticationException +from src.security import JWTParams, require_auth router = APIRouter( prefix="/apps/{app_id}/users/{user_id}/collections", tags=["collections"], - dependencies=[Depends(auth)], ) -@router.post("/list", response_model=Page[schemas.Collection]) +@router.get( + "", + response_model=schemas.Collection, +) +async def get_collection( + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: Optional[str] = Query( + None, description="Collection ID to retrieve. If not provided, uses JWT token" + ), + jwt_params: JWTParams = Depends(require_auth()), + db=db, +): + """ + Get a specific collection for a user. + + If collection_id is provided as a query parameter, it uses that (must match JWT collection_id). + Otherwise, it uses the collection_id from the JWT token. + """ + # Verify JWT has access to the requested resource + if not jwt_params.ad: + if jwt_params.ap is not None and jwt_params.ap != app_id: + raise AuthenticationException("Unauthorized access to resource") + if jwt_params.us is not None and jwt_params.us != user_id: + raise AuthenticationException("Unauthorized access to resource") + # If collection_id provided in query, check if it matches jwt or user is admin + if collection_id: + if ( + not jwt_params.ad + and jwt_params.co is not None + and jwt_params.co != collection_id + ): + raise AuthenticationException("Unauthorized access to resource") + target_collection_id = collection_id + else: + # Use collection_id from JWT + if not jwt_params.co: + raise AuthenticationException( + "Collection ID not found in query parameter or JWT" + ) + target_collection_id = jwt_params.co + + # Let crud function handle the ResourceNotFoundException + return await crud.get_collection_by_id( + db, app_id=app_id, collection_id=target_collection_id, user_id=user_id + ) + + +@router.post( + "/list", + response_model=Page[schemas.Collection], + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def get_collections( - app_id: str, - user_id: str, - options: schemas.CollectionGet, - reverse: Optional[bool] = False, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + options: schemas.CollectionGet = Body( + ..., description="Filtering options for the collections list" + ), + reverse: Optional[bool] = Query( + False, description="Whether to reverse the order of results" + ), db=db, ): """Get All Collections for a User""" @@ -32,11 +88,15 @@ async def get_collections( ) -@router.get("/name/{name}", response_model=schemas.Collection) +@router.get( + "/name/{name}", + response_model=schemas.Collection, + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def get_collection_by_name( - app_id: str, - user_id: str, - name: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + name: str = Path(..., description="Name of the collection to retrieve"), db=db, ) -> schemas.Collection: """Get a Collection by Name""" @@ -46,25 +106,17 @@ async def get_collection_by_name( return honcho_collection -@router.get("/{collection_id}", response_model=schemas.Collection) -async def get_collection_by_id( - app_id: str, - user_id: str, - collection_id: str, - db=db, -) -> schemas.Collection: - """Get a Collection by ID""" - honcho_collection = await crud.get_collection_by_id( - db, app_id=app_id, user_id=user_id, collection_id=collection_id - ) - return honcho_collection - - -@router.post("", response_model=schemas.Collection) +@router.post( + "", + response_model=schemas.Collection, + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def create_collection( - app_id: str, - user_id: str, - collection: schemas.CollectionCreate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection: schemas.CollectionCreate = Body( + ..., description="Collection creation parameters" + ), db=db, ): """Create a new Collection""" @@ -75,12 +127,24 @@ async def create_collection( ) -@router.put("/{collection_id}", response_model=schemas.Collection) +@router.put( + "/{collection_id}", + response_model=schemas.Collection, + dependencies=[ + Depends( + require_auth( + app_id="app_id", user_id="user_id", collection_id="collection_id" + ) + ) + ], +) async def update_collection( - app_id: str, - user_id: str, - collection_id: str, - collection: schemas.CollectionUpdate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection to update"), + collection: schemas.CollectionUpdate = Body( + ..., description="Updated collection parameters" + ), db=db, ): "Update a Collection's name or metadata" @@ -96,11 +160,20 @@ async def update_collection( return honcho_collection -@router.delete("/{collection_id}") +@router.delete( + "/{collection_id}", + dependencies=[ + Depends( + require_auth( + app_id="app_id", user_id="user_id", collection_id="collection_id" + ) + ) + ], +) async def delete_collection( - app_id: str, - user_id: str, - collection_id: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection to delete"), db=db, ): """Delete a Collection and its documents""" diff --git a/src/routers/documents.py b/src/routers/documents.py index a3f7e242..0c5926ec 100644 --- a/src/routers/documents.py +++ b/src/routers/documents.py @@ -1,33 +1,42 @@ -import json import logging from collections.abc import Sequence from typing import Optional -from fastapi import APIRouter, Depends +from fastapi import APIRouter, Body, Depends, Path, Query from fastapi_pagination import Page from fastapi_pagination.ext.sqlalchemy import paginate from src import crud, schemas from src.dependencies import db from src.exceptions import ResourceNotFoundException, ValidationException -from src.security import auth +from src.security import require_auth logger = logging.getLogger(__name__) router = APIRouter( prefix="/apps/{app_id}/users/{user_id}/collections/{collection_id}/documents", tags=["documents"], - dependencies=[Depends(auth)], + dependencies=[ + Depends( + require_auth( + app_id="app_id", user_id="user_id", collection_id="collection_id" + ) + ) + ], ) @router.post("/list", response_model=Page[schemas.Document]) async def get_documents( - app_id: str, - user_id: str, - collection_id: str, - options: schemas.DocumentGet, - reverse: Optional[bool] = False, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection"), + options: schemas.DocumentGet = Body( + ..., description="Filtering options for the documents list" + ), + reverse: Optional[bool] = Query( + False, description="Whether to reverse the order of results" + ), db=db, ): """Get all of the Documents in a Collection""" @@ -40,22 +49,23 @@ async def get_documents( filter=options.filter, reverse=reverse, ) - + return await paginate(db, documents_query) except ValueError as e: - logger.warning(f"Failed to get documents for collection {collection_id}: {str(e)}") - raise ResourceNotFoundException("Collection not found or does not belong to user") from e + logger.warning( + f"Failed to get documents for collection {collection_id}: {str(e)}" + ) + raise ResourceNotFoundException( + "Collection not found or does not belong to user" + ) from e -@router.get( - "/{document_id}", - response_model=schemas.Document, -) +@router.get("/{document_id}", response_model=schemas.Document) async def get_document( - app_id: str, - user_id: str, - collection_id: str, - document_id: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection"), + document_id: str = Path(..., description="ID of the document to retrieve"), db=db, ): """Get a document by ID""" @@ -71,10 +81,12 @@ async def get_document( @router.post("/query", response_model=Sequence[schemas.Document]) async def query_documents( - app_id: str, - user_id: str, - collection_id: str, - options: schemas.DocumentQuery, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection"), + options: schemas.DocumentQuery = Body( + ..., description="Query parameters for document search" + ), db=db, ): """Cosine Similarity Search for Documents""" @@ -84,7 +96,7 @@ async def query_documents( filter = options.filter if options.filter == {}: filter = None - + documents = await crud.query_documents( db=db, app_id=app_id, @@ -94,20 +106,24 @@ async def query_documents( filter=filter, top_k=top_k, ) - + logger.info(f"Query documents successful for collection {collection_id}") return documents except ValueError as e: - logger.error(f"Error querying documents in collection {collection_id}: {str(e)}") + logger.error( + f"Error querying documents in collection {collection_id}: {str(e)}" + ) raise ValidationException("Error querying documents") from e @router.post("", response_model=schemas.Document) async def create_document( - app_id: str, - user_id: str, - collection_id: str, - document: schemas.DocumentCreate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection"), + document: schemas.DocumentCreate = Body( + ..., description="Document creation parameters" + ), db=db, ): """Embed text as a vector and create a Document""" @@ -122,8 +138,12 @@ async def create_document( logger.info(f"Document created successfully in collection {collection_id}") return document_obj except ValueError as e: - logger.warning(f"Failed to create document in collection {collection_id}: {str(e)}") - raise ResourceNotFoundException("Collection not found or does not belong to user") from e + logger.warning( + f"Failed to create document in collection {collection_id}: {str(e)}" + ) + raise ResourceNotFoundException( + "Collection not found or does not belong to user" + ) from e @router.put( @@ -131,18 +151,22 @@ async def create_document( response_model=schemas.Document, ) async def update_document( - app_id: str, - user_id: str, - collection_id: str, - document_id: str, - document: schemas.DocumentUpdate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection"), + document_id: str = Path(..., description="ID of the document to update"), + document: schemas.DocumentUpdate = Body( + ..., description="Updated document parameters" + ), db=db, ): """Update the content and/or the metadata of a Document""" if document.content is None and document.metadata is None: - logger.warning(f"Document update attempted with empty content and metadata for document {document_id}") + logger.warning( + f"Document update attempted with empty content and metadata for document {document_id}" + ) raise ValidationException("Content and metadata cannot both be None") - + try: updated_document = await crud.update_document( db, @@ -161,10 +185,10 @@ async def update_document( @router.delete("/{document_id}") async def delete_document( - app_id: str, - user_id: str, - collection_id: str, - document_id: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + collection_id: str = Path(..., description="ID of the collection"), + document_id: str = Path(..., description="ID of the document to delete"), db=db, ): """Delete a Document by ID""" diff --git a/src/routers/keys.py b/src/routers/keys.py new file mode 100644 index 00000000..c40b0ae7 --- /dev/null +++ b/src/routers/keys.py @@ -0,0 +1,58 @@ +import datetime +import logging +import os + +from fastapi import APIRouter, Depends, Query + +from src.exceptions import DisabledException, ValidationException +from src.security import ( + JWTParams, + create_jwt, + require_auth, +) + +logger = logging.getLogger(__name__) + +USE_AUTH = os.getenv("USE_AUTH", "False").lower() == "true" + +router = APIRouter( + prefix="/keys", + tags=["keys"], + dependencies=[Depends(require_auth(admin=True))], +) + + +@router.post("") +async def create_key( + app_id: str | None = Query(None, description="ID of the app to scope the key to"), + user_id: str | None = Query(None, description="ID of the user to scope the key to"), + session_id: str | None = Query( + None, description="ID of the session to scope the key to" + ), + collection_id: str | None = Query( + None, description="ID of the collection to scope the key to" + ), + expires_at: datetime.datetime | None = None, +): + """Create a new Key""" + if not USE_AUTH: + raise DisabledException() + + # Validate that at least one parameter is provided for proper scoping + if not any([app_id, user_id, session_id, collection_id]): + raise ValidationException( + "At least one of app_id, user_id, session_id, or collection_id must be provided" + ) + + key_str = create_jwt( + JWTParams( + exp=expires_at.isoformat() if expires_at else None, + ap=app_id, + us=user_id, + se=session_id, + co=collection_id, + ) + ) + return { + "key": key_str, + } diff --git a/src/routers/messages.py b/src/routers/messages.py index 7bdb0604..602508ed 100644 --- a/src/routers/messages.py +++ b/src/routers/messages.py @@ -2,7 +2,7 @@ import logging import os from typing import List, Optional -from fastapi import APIRouter, BackgroundTasks, Depends +from fastapi import APIRouter, BackgroundTasks, Body, Depends, Path, Query from fastapi_pagination import Page from fastapi_pagination.ext.sqlalchemy import paginate from sqlalchemy.sql import insert @@ -12,14 +12,18 @@ from src.db import SessionLocal from src.dependencies import db from src.exceptions import ResourceNotFoundException from src.models import QueueItem -from src.security import auth +from src.security import require_auth logger = logging.getLogger(__name__) router = APIRouter( prefix="/apps/{app_id}/users/{user_id}/sessions/{session_id}/messages", tags=["messages"], - dependencies=[Depends(auth)], + dependencies=[ + Depends( + require_auth(app_id="app_id", user_id="user_id", session_id="session_id") + ) + ], ) @@ -47,6 +51,11 @@ async def enqueue(payload: dict | list[dict]): user_id=payload[0]["user_id"], session_id=payload[0]["session_id"], ) + if not session: + logger.warning( + f"Session {payload[0]['session_id']} not found, skipping enqueue" + ) + return except ResourceNotFoundException: logger.warning( f"Session {payload[0]['session_id']} not found, skipping enqueue" @@ -97,6 +106,11 @@ async def enqueue(payload: dict | list[dict]): user_id=payload["user_id"], session_id=payload["session_id"], ) + if not session: + logger.warning( + f"Session {payload['session_id']} not found, skipping enqueue" + ) + return except ResourceNotFoundException: logger.warning( f"Session {payload['session_id']} not found, skipping enqueue" @@ -137,11 +151,13 @@ async def enqueue(payload: dict | list[dict]): @router.post("", response_model=schemas.Message) async def create_message_for_session( - app_id: str, - user_id: str, - session_id: str, - message: schemas.MessageCreate, background_tasks: BackgroundTasks, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session"), + message: schemas.MessageCreate = Body( + ..., description="Message creation parameters" + ), db=db, ): """Adds a message to a session""" @@ -175,11 +191,13 @@ async def create_message_for_session( @router.post("/batch", response_model=List[schemas.Message]) async def create_batch_messages_for_session( - app_id: str, - user_id: str, - session_id: str, - batch: schemas.MessageBatchCreate, background_tasks: BackgroundTasks, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session"), + batch: schemas.MessageBatchCreate = Body( + ..., description="Batch of messages to create" + ), db=db, ): """Bulk create messages for a session while maintaining order. Maximum 100 messages per batch.""" @@ -222,11 +240,15 @@ async def create_batch_messages_for_session( @router.post("/list", response_model=Page[schemas.Message]) async def get_messages( - app_id: str, - user_id: str, - session_id: str, - options: schemas.MessageGet, - reverse: Optional[bool] = False, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session"), + options: schemas.MessageGet = Body( + ..., description="Filtering options for the messages list" + ), + reverse: Optional[bool] = Query( + False, description="Whether to reverse the order of results" + ), db=db, ): """Get all messages for a session""" @@ -252,10 +274,10 @@ async def get_messages( @router.get("/{message_id}", response_model=schemas.Message) async def get_message( - app_id: str, - user_id: str, - session_id: str, - message_id: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session"), + message_id: str = Path(..., description="ID of the message to retrieve"), db=db, ): """Get a Message by ID""" @@ -270,11 +292,13 @@ async def get_message( @router.put("/{message_id}", response_model=schemas.Message) async def update_message( - app_id: str, - user_id: str, - session_id: str, - message_id: str, - message: schemas.MessageUpdate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session"), + message_id: str = Path(..., description="ID of the message to update"), + message: schemas.MessageUpdate = Body( + ..., description="Updated message parameters" + ), db=db, ): """Update the metadata of a Message""" @@ -291,4 +315,4 @@ async def update_message( return updated_message except ValueError as e: logger.warning(f"Failed to update message {message_id}: {str(e)}") - raise ResourceNotFoundException("Message or session not found") from e + raise ResourceNotFoundException("Message not found") from e diff --git a/src/routers/metamessages.py b/src/routers/metamessages.py index 07e69dd4..d8b02981 100644 --- a/src/routers/metamessages.py +++ b/src/routers/metamessages.py @@ -1,105 +1,87 @@ import logging from typing import Optional -from fastapi import APIRouter, Depends +from fastapi import APIRouter, Body, Depends, Path, Query from fastapi_pagination import Page from fastapi_pagination.ext.sqlalchemy import paginate from src import crud, schemas from src.dependencies import db from src.exceptions import ResourceNotFoundException, ValidationException -from src.security import auth +from src.security import require_auth logger = logging.getLogger(__name__) router = APIRouter( - prefix="/apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages", - tags=["metamessages"], - dependencies=[Depends(auth)], -) - -router_user_level = APIRouter( prefix="/apps/{app_id}/users/{user_id}/metamessages", tags=["metamessages"], - dependencies=[Depends(auth)], + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], ) @router.post("", response_model=schemas.Metamessage) async def create_metamessage( - app_id: str, - user_id: str, - session_id: str, - metamessage: schemas.MetamessageCreate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + metamessage: schemas.MetamessageCreate = Body( + ..., description="Metamessage creation parameters" + ), db=db, ): - """Adds a message to a session""" + """ + Create a new metamessage associated with a user. + Optionally link to a session and message by providing those IDs in the request body. + """ try: metamessage_obj = await crud.create_metamessage( db, + user_id=user_id, metamessage=metamessage, app_id=app_id, - user_id=user_id, - session_id=session_id, ) - logger.info(f"Metamessage created successfully for session {session_id}") + logger.info(f"Metamessage created successfully for user {user_id}") return metamessage_obj - except ValueError as e: - logger.warning(f"Failed to create metamessage for session {session_id}: {str(e)}") - raise ResourceNotFoundException("Session not found") from e + except (ResourceNotFoundException, ValidationException) as e: + logger.warning(f"Failed to create metamessage: {str(e)}") + raise @router.post("/list", response_model=Page[schemas.Metamessage]) async def get_metamessages( - app_id: str, - user_id: str, - session_id: str, - options: schemas.MetamessageGet, - reverse: Optional[bool] = False, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + options: schemas.MetamessageGet = Body( + ..., description="Filtering options for the metamessages list" + ), + reverse: Optional[bool] = Query( + False, description="Whether to reverse the order of results" + ), db=db, ): - """Get all messages for a session""" + """ + Get metamessages with flexible filtering. + + - Filter by user only: No additional parameters needed + - Filter by session: Provide session_id + - Filter by message: Provide message_id (and session_id) + - Filter by type: Provide metamessage_type + - Filter by metadata: Provide filter object + """ try: metamessages_query = await crud.get_metamessages( db, app_id=app_id, user_id=user_id, - session_id=session_id, + session_id=options.session_id, message_id=options.message_id, metamessage_type=options.metamessage_type, filter=options.filter, reverse=reverse, ) - return await paginate(db, metamessages_query) - except ValueError as e: - logger.warning(f"Failed to get metamessages for session {session_id}: {str(e)}") - raise ResourceNotFoundException("Session not found") from e - - -@router_user_level.post("/list", response_model=Page[schemas.Metamessage]) -async def get_metamessages_by_user( - app_id: str, - user_id: str, - options: schemas.MetamessageGetUserLevel, - reverse: Optional[bool] = False, - db=db, -): - """Paginate through the user metamessages for a user""" - try: - metamessages_query = await crud.get_metamessages( - db, - app_id=app_id, - user_id=user_id, - metamessage_type=options.metamessage_type, - reverse=reverse, - filter=options.filter, - ) - - return await paginate(db, metamessages_query) - except ValueError as e: - logger.warning(f"Failed to get metamessages for user {user_id}: {str(e)}") - raise ResourceNotFoundException("User not found") from e + except (ResourceNotFoundException, ValidationException) as e: + logger.warning(f"Failed to get metamessages: {str(e)}") + raise @router.get( @@ -107,25 +89,23 @@ async def get_metamessages_by_user( response_model=schemas.Metamessage, ) async def get_metamessage( - app_id: str, - user_id: str, - session_id: str, - message_id: str, - metamessage_id: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + metamessage_id: str = Path(..., description="ID of the metamessage to retrieve"), db=db, ): """Get a specific Metamessage by ID""" honcho_metamessage = await crud.get_metamessage( db, app_id=app_id, - session_id=session_id, user_id=user_id, - message_id=message_id, metamessage_id=metamessage_id, ) if honcho_metamessage is None: - logger.warning(f"Metamessage {metamessage_id} not found for message {message_id}") - raise ResourceNotFoundException(f"Metamessage with ID {metamessage_id} not found") + logger.warning(f"Metamessage {metamessage_id} not found") + raise ResourceNotFoundException( + f"Metamessage with ID {metamessage_id} not found" + ) return honcho_metamessage @@ -134,29 +114,25 @@ async def get_metamessage( response_model=schemas.Metamessage, ) async def update_metamessage( - app_id: str, - user_id: str, - session_id: str, - metamessage_id: str, - metamessage: schemas.MetamessageUpdate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + metamessage_id: str = Path(..., description="ID of the metamessage to update"), + metamessage: schemas.MetamessageUpdate = Body( + ..., description="Updated metamessage parameters" + ), db=db, ): - """Update's the metadata of a metamessage""" - if metamessage.metadata is None: - logger.warning(f"Update attempted with empty metadata for metamessage {metamessage_id}") - raise ValidationException("Metamessage metadata cannot be empty") - + """Update a metamessage's metadata, type, or relationships""" try: updated_metamessage = await crud.update_metamessage( db, metamessage=metamessage, app_id=app_id, user_id=user_id, - session_id=session_id, metamessage_id=metamessage_id, ) logger.info(f"Metamessage {metamessage_id} updated successfully") return updated_metamessage - except ValueError as e: + except (ResourceNotFoundException, ValidationException) as e: logger.warning(f"Failed to update metamessage {metamessage_id}: {str(e)}") - raise ResourceNotFoundException("Session or metamessage not found") from e + raise diff --git a/src/routers/sessions.py b/src/routers/sessions.py index c4110614..f8087bdc 100644 --- a/src/routers/sessions.py +++ b/src/routers/sessions.py @@ -1,32 +1,92 @@ import logging from typing import Optional -from anthropic import MessageStreamManager -from fastapi import APIRouter, Depends +from anthropic import AsyncMessageStreamManager +from fastapi import APIRouter, Body, Depends, Path, Query +from fastapi.exceptions import HTTPException from fastapi.responses import StreamingResponse from fastapi_pagination import Page from fastapi_pagination.ext.sqlalchemy import paginate from src import agent, crud, schemas from src.dependencies import db -from src.exceptions import ResourceNotFoundException, ValidationException -from src.security import auth +from src.exceptions import ( + AuthenticationException, + ResourceNotFoundException, + ValidationException, +) +from src.security import JWTParams, require_auth logger = logging.getLogger(__name__) router = APIRouter( prefix="/apps/{app_id}/users/{user_id}/sessions", tags=["sessions"], - dependencies=[Depends(auth)], ) -@router.post("/list", response_model=Page[schemas.Session]) +@router.get( + "", + response_model=schemas.Session, +) +async def get_session( + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: Optional[str] = Query( + None, description="Session ID to retrieve. If not provided, uses JWT token" + ), + jwt_params: JWTParams = Depends(require_auth()), + db=db, +): + """ + Get a specific session for a user. + + If session_id is provided as a query parameter, it uses that (must match JWT session_id). + Otherwise, it uses the session_id from the JWT token. + """ + # Verify JWT has access to the requested resource + if not jwt_params.ad: + if jwt_params.ap is not None and jwt_params.ap != app_id: + raise AuthenticationException("Unauthorized access to resource") + if jwt_params.us is not None and jwt_params.us != user_id: + raise AuthenticationException("Unauthorized access to resource") + # If session_id provided in query, check if it matches jwt or user is admin + if session_id: + if ( + not jwt_params.ad + and jwt_params.se is not None + and jwt_params.se != session_id + ): + raise AuthenticationException("Unauthorized access to resource") + target_session_id = session_id + else: + # Use session_id from JWT + if not jwt_params.se: + raise AuthenticationException( + "Session ID not found in query parameter or JWT" + ) + target_session_id = jwt_params.se + + # Let crud function handle the ResourceNotFoundException + return await crud.get_session( + db, app_id=app_id, session_id=target_session_id, user_id=user_id + ) + + +@router.post( + "/list", + response_model=Page[schemas.Session], + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def get_sessions( - app_id: str, - user_id: str, - options: schemas.SessionGet, - reverse: Optional[bool] = False, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + options: schemas.SessionGet = Body( + ..., description="Filtering and pagination options for the sessions list" + ), + reverse: Optional[bool] = Query( + False, description="Whether to reverse the order of results" + ), db=db, ): """Get All Sessions for a User""" @@ -43,11 +103,17 @@ async def get_sessions( ) -@router.post("", response_model=schemas.Session) +@router.post( + "", + response_model=schemas.Session, + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def create_session( - app_id: str, - user_id: str, - session: schemas.SessionCreate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session: schemas.SessionCreate = Body( + ..., description="Session creation parameters" + ), db=db, ): """Create a Session for a User""" @@ -62,12 +128,22 @@ async def create_session( raise ValidationException(str(e)) from e -@router.put("/{session_id}", response_model=schemas.Session) +@router.put( + "/{session_id}", + response_model=schemas.Session, + dependencies=[ + Depends( + require_auth(app_id="app_id", user_id="user_id", session_id="session_id") + ) + ], +) async def update_session( - app_id: str, - user_id: str, - session_id: str, - session: schemas.SessionUpdate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session to update"), + session: schemas.SessionUpdate = Body( + ..., description="Updated session parameters" + ), db=db, ): """Update the metadata of a Session""" @@ -82,11 +158,18 @@ async def update_session( raise ResourceNotFoundException("Session not found") from e -@router.delete("/{session_id}") +@router.delete( + "/{session_id}", + dependencies=[ + Depends( + require_auth(app_id="app_id", user_id="user_id", session_id="session_id") + ) + ], +) async def delete_session( - app_id: str, - user_id: str, - session_id: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session to delete"), db=db, ): """Delete a session by marking it as inactive""" @@ -101,88 +184,92 @@ async def delete_session( raise ResourceNotFoundException("Session not found") from e -@router.get("/{session_id}", response_model=schemas.Session) -async def get_session( - app_id: str, - user_id: str, - session_id: str, - db=db, -): - """Get a specific session for a user by ID""" - honcho_session = await crud.get_session( - db, app_id=app_id, session_id=session_id, user_id=user_id - ) - if honcho_session is None: - logger.warning(f"Session {session_id} not found for user {user_id}") - raise ResourceNotFoundException(f"Session with ID {session_id} not found") - return honcho_session - - -@router.post("/{session_id}/chat", response_model=schemas.AgentChat) -async def chat( - app_id: str, - user_id: str, - session_id: str, - query: schemas.AgentQuery, -): - """Chat with the Dialectic API""" - return await agent.chat( - app_id=app_id, user_id=user_id, session_id=session_id, query=query - ) - - @router.post( - "/{session_id}/chat/stream", + "/{session_id}/chat", + response_model=schemas.DialecticResponse, responses={ 200: { - "description": "Chat stream", - "content": { - "text/event-stream": {"schema": {"type": "string", "format": "binary"}} - }, - } + "description": "Response to a question informed by Honcho's User Representation", + "content": {"text/event-stream": {}}, + }, }, + dependencies=[ + Depends( + require_auth(app_id="app_id", user_id="user_id", session_id="session_id") + ) + ], ) -async def get_chat_stream( - app_id: str, - user_id: str, - session_id: str, - query: schemas.AgentQuery, +async def chat( + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session"), + options: schemas.DialecticOptions = Body( + ..., description="Dialectic Endpoint Parameters" + ), ): - """Stream Results from the Dialectic API""" - - async def parse_stream(): - stream = await agent.chat( + """Chat with the Dialectic API""" + if not options.stream: + return await agent.chat( app_id=app_id, user_id=user_id, session_id=session_id, - query=query, - stream=True, + queries=options.queries, ) - if type(stream) is MessageStreamManager: - with stream as stream_manager: - for text in stream_manager.text_stream: - yield text + else: - return StreamingResponse( - content=parse_stream(), media_type="text/event-stream", status_code=200 - ) + async def parse_stream(): + try: + stream = await agent.chat( + app_id=app_id, + user_id=user_id, + session_id=session_id, + queries=options.queries, + stream=True, + ) + if type(stream) is AsyncMessageStreamManager: + async with stream as stream_manager: + async for text in stream_manager.text_stream: + yield text + except Exception as e: + logger.error(f"Error in stream: {str(e)}") + raise HTTPException(status_code=500, detail=str(e)) from e + + return StreamingResponse( + content=parse_stream(), media_type="text/event-stream", status_code=200 + ) -@router.get("/{session_id}/clone", response_model=schemas.Session) +@router.get( + "/{session_id}/clone", + response_model=schemas.Session, + dependencies=[ + Depends( + require_auth(app_id="app_id", user_id="user_id", session_id="session_id") + ) + ], +) async def clone_session( - app_id: str, - user_id: str, - session_id: str, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user"), + session_id: str = Path(..., description="ID of the session to clone"), db=db, - message_id: Optional[str] = None, - deep_copy: bool = False, + message_id: Optional[str] = Query( + None, description="Message ID to cut off the clone at" + ), + deep_copy: bool = Query(False, description="Whether to deep copy metamessages"), ): - """Clone a session for a user, optionally will deep clone metamessages as well""" - return await crud.clone_session( - db, - app_id=app_id, - user_id=user_id, - original_session_id=session_id, - cutoff_message_id=message_id, - deep_copy=deep_copy, - ) + """Clone a session, optionally up to a specific message""" + try: + cloned_session = await crud.clone_session( + db, + app_id=app_id, + user_id=user_id, + original_session_id=session_id, + cutoff_message_id=message_id, + deep_copy=deep_copy, + ) + logger.info(f"Session {session_id} cloned successfully") + return cloned_session + except ValueError as e: + logger.warning(f"Failed to clone session {session_id}: {str(e)}") + raise ResourceNotFoundException("Session not found") from e diff --git a/src/routers/users.py b/src/routers/users.py index ee64ce13..da1661d4 100644 --- a/src/routers/users.py +++ b/src/routers/users.py @@ -1,29 +1,34 @@ import logging +from typing import Optional -from fastapi import APIRouter, Depends +from fastapi import APIRouter, Body, Depends, Path, Query from fastapi_pagination import Page from fastapi_pagination.ext.sqlalchemy import paginate from src import crud, schemas from src.dependencies import db from src.exceptions import ( + AuthenticationException, ResourceNotFoundException, ) -from src.security import auth +from src.security import JWTParams, require_auth logger = logging.getLogger(__name__) router = APIRouter( prefix="/apps/{app_id}/users", tags=["users"], - dependencies=[Depends(auth)], ) -@router.post("", response_model=schemas.User) +@router.post( + "", + response_model=schemas.User, + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def create_user( - app_id: str, - user: schemas.UserCreate, + app_id: str = Path(..., description="ID of the app"), + user: schemas.UserCreate = Body(..., description="User creation parameters"), db=db, ): """Create a new User""" @@ -31,11 +36,17 @@ async def create_user( return user_obj -@router.post("/list", response_model=Page[schemas.User]) +@router.post( + "/list", + response_model=Page[schemas.User], + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def get_users( - app_id: str, - options: schemas.UserGet, - reverse: bool = False, + app_id: str = Path(..., description="ID of the app"), + options: schemas.UserGet = Body( + ..., description="Filtering options for the users list" + ), + reverse: bool = Query(False, description="Whether to reverse the order of results"), db=db, ): """Get All Users for an App""" @@ -45,10 +56,55 @@ async def get_users( ) -@router.get("/name/{name}", response_model=schemas.User) +@router.get( + "", + response_model=schemas.User, +) +async def get_user( + app_id: str = Path(..., description="ID of the app"), + user_id: Optional[str] = Query( + None, description="User ID to retrieve. If not provided, users JWT token" + ), + jwt_params: JWTParams = Depends(require_auth()), + db=db, +): + """ + Get a User by ID + + If user_id is provided as a query parameter, it uses that (must match JWT app_id). + Otherwise, it uses the user_id from the JWT token. + """ + # validate app query param + if not jwt_params.ad and jwt_params.ap is not None and jwt_params.ap != app_id: + raise AuthenticationException("Unauthorized access to resource") + + if user_id: + if not jwt_params.ad and jwt_params.us is not None and jwt_params.us != user_id: + raise AuthenticationException("Unauthorized access to resource") + target_user_id = user_id + else: + # Use user_id from JWT + if not jwt_params.us: + raise AuthenticationException("User ID not found in query parameter or JWT") + target_user_id = jwt_params.us + user = await crud.get_user(db, app_id=app_id, user_id=target_user_id) + return user + + +@router.get( + "/name/{name}", + response_model=schemas.User, + dependencies=[ + Depends( + require_auth( + app_id="app_id", + ) + ) + ], +) async def get_user_by_name( - app_id: str, - name: str, + app_id: str = Path(..., description="ID of the app"), + name: str = Path(..., description="Name of the user to retrieve"), db=db, ): """Get a User by name""" @@ -56,19 +112,22 @@ async def get_user_by_name( return user -@router.get("/{user_id}", response_model=schemas.User) -async def get_user( - app_id: str, - user_id: str, +@router.get( + "/get_or_create/{name}", + response_model=schemas.User, + dependencies=[ + Depends( + require_auth( + app_id="app_id", + ) + ) + ], +) +async def get_or_create_user( + app_id: str = Path(..., description="ID of the app"), + name: str = Path(..., description="Name of the user to get or create"), db=db, ): - """Get a User by ID""" - user = await crud.get_user(db, app_id=app_id, user_id=user_id) - return user - - -@router.get("/get_or_create/{name}", response_model=schemas.User) -async def get_or_create_user(app_id: str, name: str, db=db): """Get a User or create a new one by the input name""" try: user = await crud.get_user_by_name(db, app_id=app_id, name=name) @@ -81,11 +140,15 @@ async def get_or_create_user(app_id: str, name: str, db=db): return user -@router.put("/{user_id}", response_model=schemas.User) +@router.put( + "/{user_id}", + response_model=schemas.User, + dependencies=[Depends(require_auth(app_id="app_id", user_id="user_id"))], +) async def update_user( - app_id: str, - user_id: str, - user: schemas.UserUpdate, + app_id: str = Path(..., description="ID of the app"), + user_id: str = Path(..., description="ID of the user to update"), + user: schemas.UserUpdate = Body(..., description="Updated user parameters"), db=db, ): """Update a User's name and/or metadata""" diff --git a/src/schemas.py b/src/schemas.py index a2fb23c2..aa602284 100644 --- a/src/schemas.py +++ b/src/schemas.py @@ -13,6 +13,10 @@ class AppCreate(AppBase): metadata: dict = {} +class AppGet(AppBase): + filter: dict | None = None + + class AppUpdate(AppBase): name: str | None = None metadata: dict | None = None @@ -172,23 +176,21 @@ class MetamessageBase(BaseModel): class MetamessageCreate(MetamessageBase): metamessage_type: Annotated[str, Field(min_length=1, max_length=50)] content: Annotated[str, Field(min_length=0, max_length=50000)] - message_id: str + session_id: str | None = None + message_id: str | None = None metadata: dict = {} class MetamessageGet(MetamessageBase): metamessage_type: str | None = None + session_id: str | None = None message_id: str | None = None filter: dict | None = None -class MetamessageGetUserLevel(MessageBase): - filter: dict | None = None - metamessage_type: str | None = None - - class MetamessageUpdate(MetamessageBase): - message_id: str + session_id: str | None = None + message_id: str | None = None metamessage_type: str | None = None metadata: dict | None = None @@ -198,7 +200,9 @@ class Metamessage(MetamessageBase): id: str metamessage_type: str content: str - message_id: str + user_id: str + session_id: str | None + message_id: str | None h_metadata: dict = Field(exclude=True) metadata: dict created_at: datetime.datetime @@ -317,27 +321,30 @@ class Document(DocumentBase): ) -class AgentQuery(BaseModel): +class DialecticOptions(BaseModel): queries: str | list[str] + stream: bool = False - @field_validator('queries') + @field_validator("queries") def validate_queries(cls, v): MAX_STRING_LENGTH = 10000 MAX_LIST_LENGTH = 25 if isinstance(v, str): if len(v) > MAX_STRING_LENGTH: - raise ValueError('Query too long') + raise ValueError("Query too long") elif isinstance(v, list): if len(v) > MAX_LIST_LENGTH: - raise ValueError('Too many queries') + raise ValueError("Too many queries") if any(len(q) > MAX_STRING_LENGTH for q in v): - raise ValueError('One or more queries too long') + raise ValueError("One or more queries too long") return v -class AgentChat(BaseModel): + +class DialecticResponse(BaseModel): content: str class MessageBatchCreate(BaseModel): """Schema for batch message creation with a max of 100 messages""" + messages: list[MessageCreate] = Field(..., max_length=100) diff --git a/src/security.py b/src/security.py index c12eb163..6b1e837e 100644 --- a/src/security.py +++ b/src/security.py @@ -1,28 +1,214 @@ +import datetime import logging import os -from typing import Annotated +from typing import Annotated, Optional -from fastapi import Depends +import jwt +from fastapi import Depends, Request from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer +from pydantic import BaseModel +from sqlalchemy.ext.asyncio import AsyncSession + +from src.dependencies import get_db from .exceptions import AuthenticationException logger = logging.getLogger(__name__) -USE_AUTH_SERVICE = os.getenv("USE_AUTH_SERVICE", "False").lower() == "true" -SECRET_KEY = os.getenv("SECRET_KEY", "test") +USE_AUTH = os.getenv("USE_AUTH", "False").lower() == "true" +AUTH_JWT_SECRET = os.getenv("AUTH_JWT_SECRET", "") if USE_AUTH else "" + +if USE_AUTH and AUTH_JWT_SECRET == "": + print( + "\n ERROR: No JWT secret provided. Set the AUTH_JWT_SECRET environment variable.\n" + ) + exit(1) security = HTTPBearer( auto_error=False, ) +# +# jwt params +# all optional, used to produce tokens valid for different routes +# hierarchy: app > user > ( session / collection ) +# routes that involve a 'name' parameter require permissions for the parent object +# name routes are considered 'queries' as names are mutable properties +# +# note: add routes without parameters that assume the most immediately scoped key is providing +# +class JWTParams(BaseModel): + """ + JWT parameters used to produce tokens valid for different routes. + Hierarchy: app > user > (session / collection) + + All routers require at least the most tightly scoped parameter. + Routes will accept a JWT with a scope higher in the hierarchy. + + Names shortened to minimize token size. Timestamp is included + so that many unique tokens can be generated for the same resource. + Note that the timestamp itself is not used for security, and can + be omitted, such as when Honcho generates the initial admin JWT. + + Fields (all optional other than `t`): + + `t`: a string timestamp of when the JWT was created + `exp`: a string timestamp of when the JWT expires (optional) + `ad`: a boolean flag indicating if the JWT is an admin JWT + `ap`: (string) app id + `us`: (string) user id + `se`: (string) session id + `co`: (string) collection id + """ + + t: str = datetime.datetime.now().isoformat() + exp: Optional[str] = None + ad: Optional[bool] = None + ap: Optional[str] = None + us: Optional[str] = None + se: Optional[str] = None + co: Optional[str] = None + + +def create_admin_jwt() -> str: + """Create a JWT for admin operations.""" + params = JWTParams(t="", ad=True) + key = create_jwt(params) + return key + + +def create_jwt(params: JWTParams) -> str: + """Create a JWT token from the given parameters.""" + payload = {k: v for k, v in params.__dict__.items() if v is not None} + return jwt.encode(payload, AUTH_JWT_SECRET.encode("utf-8"), algorithm="HS256") + + +async def verify_jwt(token: str) -> JWTParams: + """Verify a JWT token and return the decoded parameters.""" + + params = JWTParams() + try: + decoded = jwt.decode( + token, AUTH_JWT_SECRET.encode("utf-8"), algorithms=["HS256"] + ) + if "t" in decoded: + params.t = decoded["t"] + if "exp" in decoded: + params.exp = decoded["exp"] + if ( + params.exp + and datetime.datetime.fromisoformat(params.exp) + < datetime.datetime.now() + ): + raise AuthenticationException("JWT expired") + if "ad" in decoded: + params.ad = decoded["ad"] + if "ap" in decoded: + params.ap = decoded["ap"] + if "us" in decoded: + params.us = decoded["us"] + if "se" in decoded: + params.se = decoded["se"] + if "co" in decoded: + params.co = decoded["co"] + return params + except jwt.PyJWTError: + raise AuthenticationException("Invalid JWT") from None + + +def require_auth( + admin: Optional[bool] = None, + app_id: Optional[str] = None, + user_id: Optional[str] = None, + session_id: Optional[str] = None, + collection_id: Optional[str] = None, +): + """ + Generate a dependency that requires authentication for the given parameters. + """ + + async def auth_dependency( + request: Request, + credentials: HTTPAuthorizationCredentials = Depends(security), + db: AsyncSession = Depends(get_db), + ): + app_id_param = ( + request.path_params.get(app_id) or request.query_params.get(app_id) + if app_id + else None + ) + user_id_param = ( + request.path_params.get(user_id) or request.query_params.get(user_id) + if user_id + else None + ) + session_id_param = ( + request.path_params.get(session_id) or request.query_params.get(session_id) + if session_id + else None + ) + collection_id_param = ( + request.path_params.get(collection_id) + or request.query_params.get(collection_id) + if collection_id + else None + ) + + return await auth( + credentials=credentials, + admin=admin, + app_id=app_id_param, + user_id=user_id_param, + session_id=session_id_param, + collection_id=collection_id_param, + ) + + return auth_dependency + + async def auth( credentials: Annotated[HTTPAuthorizationCredentials, Depends(security)], -): - if not USE_AUTH_SERVICE: - return True - if not credentials or credentials.credentials != SECRET_KEY: - logger.warning("Invalid access token attempt") - raise AuthenticationException("Invalid access token") - return {"message": "OK"} + admin: Optional[bool] = None, + app_id: Optional[str] = None, + user_id: Optional[str] = None, + session_id: Optional[str] = None, + collection_id: Optional[str] = None, +) -> JWTParams: + """Authenticate the given JWT and return the decoded parameters.""" + if not USE_AUTH: + return JWTParams(t="", ad=True) + if not credentials or not credentials.credentials: + logger.warning("No access token provided") + raise AuthenticationException("No access token provided") + + jwt_params = await verify_jwt(credentials.credentials) + + # based on api operation, verify api key based on that key's permissions + if jwt_params.ad: + return jwt_params + if admin: + raise AuthenticationException("Resource requires admin privileges") + + # Check if the JWT has direct access to the requested resource + # For session or collection level access + if session_id and jwt_params.se == session_id: + return jwt_params + if collection_id and jwt_params.co == collection_id: + return jwt_params + + # For user level access - can access all sessions/collections under this user + if user_id and jwt_params.us == user_id: + return jwt_params + + # For app level access - can access all users/sessions/collections under this app + if app_id and jwt_params.ap == app_id: + return jwt_params + + if any([session_id, collection_id, user_id, app_id]): + print([session_id, collection_id, user_id, app_id]) + print(jwt_params) + raise AuthenticationException("JWT not permissioned for this resource") + + # Route did not specify any parameters, so it should parse parameters itself + return jwt_params diff --git a/src/utils/__init__.py b/src/utils/__init__.py new file mode 100644 index 00000000..aead6593 --- /dev/null +++ b/src/utils/__init__.py @@ -0,0 +1,21 @@ +""" +Utility modules for the Honcho app. +""" + +import re + + +def parse_xml_content(text: str, tag: str) -> str: + """ + Extract content from XML-like tags in a string. + + Args: + text: The text containing XML-like tags + tag: The tag name to extract content from + + Returns: + The content between the opening and closing tags, or an empty string if not found + """ + pattern = f"<{tag}>(.*?)" + match = re.search(pattern, text, re.DOTALL) + return match.group(1).strip() if match else "" diff --git a/src/utils/history.py b/src/utils/history.py new file mode 100644 index 00000000..bbc65ee8 --- /dev/null +++ b/src/utils/history.py @@ -0,0 +1,392 @@ +import logging +from enum import Enum +from typing import Optional, Union, cast + +from sqlalchemy import select +from sqlalchemy.ext.asyncio import AsyncSession + +from src.utils.model_client import ModelClient, ModelProvider + +from .. import models + +logger = logging.getLogger(__name__) + +# Export the public functions +__all__ = [ + "get_session_summaries", + "get_messages_since_message", + "get_messages_since_latest_summary", + "create_summary", + "save_summary_metamessage", + "get_summarized_history", + "should_create_summary", + "MESSAGES_PER_SHORT_SUMMARY", + "MESSAGES_PER_LONG_SUMMARY", + "SummaryType", +] + + +# Configuration constants for summaries +MESSAGES_PER_SHORT_SUMMARY = 20 # How often to create short summaries +MESSAGES_PER_LONG_SUMMARY = 60 # How often to create long summaries + + +# The types of metamessages to use for summaries +class SummaryType(Enum): + SHORT = "honcho_chat_summary_short" + LONG = "honcho_chat_summary_long" + + +# Default model settings for summary generation +DEFAULT_PROVIDER = ModelProvider.GEMINI +DEFAULT_MODEL = "gemini-2.0-flash-lite" + + +async def get_session_summaries( + db: AsyncSession, + session_id: str, + summary_type: SummaryType = SummaryType.SHORT, + only_latest: bool = False, +) -> Union[list[models.Metamessage], Optional[models.Metamessage]]: + """ + Get summaries for a given session. + + Args: + db: Database session + session_id: The session ID + summary_type: Type of summary to retrieve ("short" or "long") + only_latest: Whether to return only the latest summary + + Returns: + If only_latest is True: The most recent summary metamessage, or None if none exists + If only_latest is False: A list of all summary metamessages for the session + """ + # Determine the metamessage type based on summary_type + metamessage_type = ( + SummaryType.SHORT.value + if summary_type == SummaryType.SHORT + else SummaryType.LONG.value + ) + + stmt = ( + select(models.Metamessage) + .where(models.Metamessage.session_id == session_id) + .where(models.Metamessage.metamessage_type == metamessage_type) + .order_by(models.Metamessage.id.desc()) + ) + + if only_latest: + stmt = stmt.limit(1) + result = await db.execute(stmt) + # Always return a metamessage instance or None + return result.scalar_one_or_none() + else: + result = await db.execute(stmt) + return list(result.scalars().all()) + + +async def get_messages_since_message( + db: AsyncSession, session_id: str, message_id: Optional[str] = None +) -> list[models.Message]: + """ + Get all messages since a specific message. + + Args: + db: Database session + session_id: The session ID + message_id: The reference message ID + + Returns: + List of messages after the reference message or all messages if message_id is None + """ + # Base query for messages in this session + query = ( + select(models.Message) + .where(models.Message.session_id == session_id) + .order_by(models.Message.id) + ) + + # If we have a reference message ID, filter to get newer messages + if message_id: + # First, get the ID of the message + message_id_subquery = ( + select(models.Message.id) + .where(models.Message.public_id == message_id) + .scalar_subquery() + ) + + # Then filter to only get messages with higher IDs + query = query.where(models.Message.id > message_id_subquery) + + # Execute query + result = await db.execute(query) + return list(result.scalars().all()) + + +async def create_summary( + messages: list[models.Message], + previous_summary: Optional[str] = None, + summary_type: SummaryType = SummaryType.SHORT, +) -> str: + """ + Generate a summary of the provided messages using an LLM. + + Args: + messages: List of messages to summarize + previous_summary: Optional previous summary to provide context + summary_type: Type of summary to create ("short" or "long") + + Returns: + A summary of the conversation + """ + # Combine messages into a conversation format + conversation = "\n".join( + [ + f"{'human' if msg.is_user else 'assistant'}: {msg.content}" + for msg in messages + ] + ) + + # Adjust system prompt based on summary type + if summary_type == SummaryType.LONG: + system_prompt = """You are a system that creates comprehensive summaries of conversations. +Focus on capturing: +1. Key facts and information shared +2. User preferences, opinions, and questions +3. Important context and requests +4. Core topics discussed in detail +5. User's apparent emotional state and personality traits +6. Important themes and patterns across the conversation + +It is very important that you clearly distinguish between the user's messages and the assistant's messages, and that only the user's literal words are attributed to them. + +Provide a thorough and detailed summary that captures the essence of the conversation. +Your summary should serve as a comprehensive record of the important information in this conversation. + +Return only the summary without any explanation or meta-commentary.""" + else: # short summary + system_prompt = """You are a system that summarizes parts of a conversation to create a concise and accurate summary. +Focus on capturing: +1. Key facts and information shared +2. User preferences, opinions, and questions +3. Important context and requests +4. Core topics discussed +5. User's apparent emotional state + +It is very important that you clearly distinguish between the user's messages and the assistant's messages, and that only the user's literal words are attributed to them. + +Provide a concise, factual summary that captures the essence of the conversation. +Your summary should be detailed enough to serve as context for future messages, +but brief enough to be helpful. + +Return only the summary without any explanation or meta-commentary.""" + + # Include previous summary if available + if previous_summary: + user_prompt = f"""Here is a previous summary of the conversation: +{previous_summary} +Now please summarize these additional messages, incorporating the context from the previous summary. + +Your summary should summarize the entire conversation in a self-contained way, such that someone could read it and understand the entire conversation. +{conversation} +Provide a {"comprehensive" if summary_type == SummaryType.LONG else "concise"} summary that captures both the previous context and the new information.""" + else: + user_prompt = f"""Please summarize the following conversation segment: +{conversation} +Provide a {"comprehensive" if summary_type == SummaryType.LONG else "concise"} summary that captures the key points and context.""" + + # Create a model client + client = ModelClient(provider=DEFAULT_PROVIDER, model=DEFAULT_MODEL) + + # Generate the summary + llm_messages = [{"role": "user", "content": user_prompt}] + + try: + summary = await client.generate( + messages=llm_messages, + system=system_prompt, + max_tokens=1000 + if summary_type == SummaryType.SHORT + else 2000, # Allow longer responses for long summaries + temperature=0.0, + use_caching=True, + ) + return summary + except Exception as e: + logger.error(f"Error generating summary: {str(e)}") + # Fallback to a basic summary in case of error + return f"Conversation with {len(messages)} messages about {messages[-1].content[:30]}..." + + +async def save_summary_metamessage( + db: AsyncSession, + user_id: str, + session_id: str, + message_id: str, + summary_content: str, + message_count: int, + summary_type: SummaryType = SummaryType.SHORT, +) -> models.Metamessage: + """ + Save a summary as a metamessage. + + Args: + db: Database session + user_id: User ID + session_id: Session ID + message_id: The ID of the most recent message being summarized + summary_content: The summary text to save + message_count: Number of messages covered by this summary + summary_type: Type of summary to save + + Returns: + The created metamessage + """ + # Get the metamessage_type value from the enum + metamessage_type = summary_type.value + + # Create and save the metamessage + metamessage = models.Metamessage( + user_id=user_id, + session_id=session_id, + message_id=message_id, + metamessage_type=metamessage_type, + content=summary_content, + h_metadata={"message_count": message_count, "summary_type": summary_type.name}, + ) + + db.add(metamessage) + await db.commit() + + logger.info( + f"Saved {summary_type.name.lower()} summary metamessage for session {session_id} covering {message_count} messages" + ) + return metamessage + + +async def get_full_history( + db: AsyncSession, session_id: str +) -> tuple[str, list[models.Message]]: + """ + Get all messages for a given session. + """ + messages = await get_messages_since_message(db, session_id) + return format_messages(messages), messages + + +async def get_summarized_history( + db: AsyncSession, session_id: str, summary_type: SummaryType = SummaryType.SHORT +) -> tuple[str, list[models.Message], Optional[models.Metamessage]]: + """ + Get a summarized version of the chat history by combining the latest summary + with all messages since that summary. + + Args: + db: Database session + session_id: The session ID + summary_type: Type of summary to get ("short" or "long") + + Returns: + A tuple containing: + - String formatted history text with summary and recent messages + - List of messages since the latest summary + - The latest summary metamessage, or None if no summary exists + """ + # Get messages since the latest summary and the summary itself + messages, latest_summary = await get_messages_since_latest_summary( + db, session_id, summary_type + ) + + # Format messages + messages_text = format_messages(messages) + + # We know latest_summary is either a Metamessage or None because of the type + # narrowing in get_messages_since_latest_summary + if latest_summary: + # Combine summary with recent messages + history_text = f"[CONVERSATION SUMMARY: {latest_summary.content}]\n\n[RECENT MESSAGES]\n{messages_text}" + else: + # No summary available, return just the messages + history_text = messages_text + return history_text, messages, latest_summary + + +async def get_messages_since_latest_summary( + db: AsyncSession, session_id: str, summary_type: SummaryType = SummaryType.SHORT +) -> tuple[list[models.Message], Optional[models.Metamessage]]: + """ + Get all messages since the latest summary for a session. + + This is a convenience method that combines: + 1. Getting the latest summary for the session + 2. Getting all messages since that summary + + Args: + db: Database session + session_id: The session ID + summary_type: Type of summary to get ("short" or "long") + + Returns: + A tuple containing: + - List of messages since the latest summary (or all messages if no summary exists) + - The latest summary metamessage, or None if no summary exists + """ + # Get the latest summary (will be a Metamessage instance or None) + # We include only_latest=True to get a single Metamessage (not a list) + summary = await get_session_summaries( + db, session_id, summary_type=summary_type, only_latest=True + ) + + # Type narrowing - summary is now either None or a Metamessage instance + latest_summary = cast(Optional[models.Metamessage], summary) + + # Check if we have a valid summary with a message_id + if latest_summary is not None: + messages = await get_messages_since_message( + db, session_id, latest_summary.message_id + ) + return messages, latest_summary + else: + messages = await get_messages_since_message(db, session_id) + return messages, None + + +async def should_create_summary( + db: AsyncSession, session_id: str, summary_type: SummaryType = SummaryType.SHORT +) -> tuple[bool, list[models.Message], Optional[models.Metamessage]]: + """ + Determine if a new summary should be created for this session. + + Args: + db: Database session + session_id: The session ID + summary_type: Type of summary to check for ("short" or "long") + + Returns: + Tuple containing: + - Boolean indicating whether a summary should be created + - List of messages to be included in the summary + - The latest summary of the requested type, or None if no summary exists + """ + messages, latest_summary = await get_messages_since_latest_summary( + db, session_id, summary_type + ) + threshold = ( + MESSAGES_PER_SHORT_SUMMARY + if summary_type == SummaryType.SHORT + else MESSAGES_PER_LONG_SUMMARY + ) + should_create = len(messages) >= threshold + return should_create, messages, latest_summary + + +def format_messages(messages: list[models.Message]) -> str: + """ + Format a list of messages into a string. + """ + if len(messages) == 0: + return "" + return "\n".join( + [f"{'user' if msg.is_user else 'assistant'}: {msg.content}" for msg in messages] + ) + diff --git a/src/utils/model_client.py b/src/utils/model_client.py new file mode 100644 index 00000000..8c98a800 --- /dev/null +++ b/src/utils/model_client.py @@ -0,0 +1,541 @@ +""" +Utility functions for interacting with various language model APIs. +""" + +import os +from enum import Enum +from typing import Any, Optional, Protocol + +import sentry_sdk +from anthropic import AsyncAnthropic +from dotenv import load_dotenv +from google import genai +from google.genai import types as genai_types +from langfuse.decorators import langfuse_context, observe + +# from openai import AsyncOpenAI +from langfuse.openai import AsyncOpenAI + +# Load environment variables +load_dotenv() + + +# Supported model providers +class ModelProvider(str, Enum): + ANTHROPIC = "anthropic" + OPENAI = "openai" + OPENROUTER = "openrouter" + CEREBRAS = "cerebras" + GROQ = "groq" + GEMINI = "gemini" + # Add other providers as needed + + +# Default models for each provider +DEFAULT_MODELS = { + ModelProvider.ANTHROPIC: "claude-3-7-sonnet-20250219", + ModelProvider.OPENAI: "gpt-4o", + ModelProvider.OPENROUTER: "meta-llama/Llama-3.3-70B-Instruct", + ModelProvider.CEREBRAS: "llama-3.3-70b", + ModelProvider.GROQ: "llama-3.3-70b-versatile", + ModelProvider.GEMINI: "gemini-2.0-flash-lite", +} + +OPENAI_COMPATIBLE_PROVIDERS = [ + ModelProvider.OPENAI, + ModelProvider.OPENROUTER, + ModelProvider.CEREBRAS, + ModelProvider.GROQ, +] + +DEFAULT_TEMPERATURE = 0.0 +DEFAULT_MAX_TOKENS = 1000 + + +class Message(Protocol): + """Protocol for a message that works with any provider.""" + + role: str + content: str + + +class ModelClient: + """A client for interacting with various language model APIs.""" + + def __init__( + self, + provider: ModelProvider = ModelProvider.ANTHROPIC, + model: Optional[str] = None, + api_key: Optional[str] = None, + base_url: Optional[str] = None, + ): + """ + Initialize the model client. + + Args: + provider: The model provider to use + model: The specific model to use, or None to use the default model for the provider + api_key: The API key to use, or None to read from environment variables + base_url: Custom base URL for the API endpoints (used for OpenRouter) + """ + self.provider = provider + self.model = model or DEFAULT_MODELS[provider] + self.base_url = base_url + self.openai_client = None + self.gemini_client = None + + # Setup provider-specific clients + if provider == ModelProvider.ANTHROPIC: + self.api_key = api_key or os.getenv("ANTHROPIC_API_KEY") + if not self.api_key: + raise ValueError("Anthropic API key is required") + self.client = AsyncAnthropic(api_key=self.api_key) + elif provider in OPENAI_COMPATIBLE_PROVIDERS: + self.api_key = api_key or os.getenv("OPENAI_COMPATIBLE_API_KEY") + self.base_url = base_url or os.getenv("OPENAI_COMPATIBLE_BASE_URL") + if not self.api_key: + raise ValueError("OpenAI-compatible API key is required") + self.openai_client = AsyncOpenAI( + api_key=self.api_key, base_url=self.base_url + ) + elif provider == ModelProvider.GEMINI: + self.api_key = api_key or os.getenv("GEMINI_API_KEY") + if not self.api_key: + raise ValueError("Gemini API key is required") + self.gemini_client = genai.Client(api_key=self.api_key) + else: + raise ValueError(f"Unsupported provider: {provider}") + + def create_message(self, role: str, content: str) -> dict[str, str]: + """ + Create a message that works with the current provider. + + Args: + role: The role of the message (e.g., "user", "assistant") + content: The message content + + Returns: + A message compatible with the current provider + """ + # For now, just return a dictionary that works with both Anthropic and OpenAI + return {"role": role, "content": content} + + @observe() + async def generate( + self, + messages: list[dict[str, Any]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + extra_headers: Optional[dict[str, str]] = None, + use_caching: bool = False, + ) -> str: + """ + Generate a response using the configured model. + + Args: + messages: The conversation history + system: Optional system prompt + max_tokens: Maximum number of tokens to generate + temperature: Temperature for generation + extra_headers: Optional headers to add to the request + use_caching: Whether to use provider-side caching for the response + + Returns: + The generated text + """ + with sentry_sdk.start_transaction( + op="llm-api", name=f"{self.provider} API Call" + ): + # Log to langfuse + langfuse_context.update_current_observation( + input=messages, model=self.model + ) + + if self.provider == ModelProvider.ANTHROPIC: + return await self._generate_anthropic( + messages, + system, + max_tokens, + temperature, + extra_headers, + use_caching, + ) + elif self.provider in OPENAI_COMPATIBLE_PROVIDERS: + return await self._generate_openai( + messages, system, max_tokens, temperature + ) + elif self.provider == ModelProvider.GEMINI: + return await self._generate_gemini( + messages, system, max_tokens, temperature + ) + else: + raise ValueError(f"Unsupported provider: {self.provider}") + + @observe(as_type="generation") + async def _generate_anthropic( + self, + messages: list[dict[str, Any]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + extra_headers: Optional[dict[str, str]] = None, + use_caching: bool = False, + ) -> str: + """Generate a response using the Anthropic API.""" + if not self.client: + raise ValueError("Anthropic client not initialized.") + + params = { + "model": self.model, + "messages": messages, + "max_tokens": max_tokens, + "temperature": temperature, + } + + # Handle system prompt with caching if enabled + if system: + if use_caching: + params["system"] = [ + { + "type": "text", + "text": system, + "cache_control": {"type": "ephemeral"}, + } + ] + else: + params["system"] = system + + langfuse_context.update_current_observation(input=messages, model=self.model) + + response = await self.client.messages.create(**params) + + # Extract the text from the response + if response.content and len(response.content) > 0: + content_block = response.content[0] + # Check content_block by checking for attribute 'type' instead of using isinstance + if ( + content_block + and hasattr(content_block, "type") + and content_block.type == "text" + ): + return content_block.text + return str(content_block) + return "" + + @observe(as_type="generation") + async def _generate_openai( + self, + messages: list[dict[str, str]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + ) -> str: + """Generate text using OpenAI or OpenRouter API.""" + if not self.openai_client: + raise ValueError("OpenAI client not initialized") + + # Prepare messages + formatted_messages = [] + + # Add system message if provided + if system: + formatted_messages.append({"role": "system", "content": system}) + + # Add the rest of the messages + formatted_messages.extend(messages) + + # Make the API call with the OpenAI client + response = await self.openai_client.chat.completions.create( + model=self.model, + messages=formatted_messages, + max_tokens=max_tokens, + temperature=temperature, + ) + + # Extract the generated text + choice = response.choices[0] + if choice and choice.message and choice.message.content: + return choice.message.content + return "" + + @observe() + async def stream( + self, + messages: list[dict[str, Any]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + extra_headers: Optional[dict[str, str]] = None, + use_caching: bool = False, + ) -> Any: + """ + Stream a response using the configured model. + + Args: + messages: The conversation history + system: Optional system prompt + max_tokens: Maximum number of tokens to generate + temperature: Temperature for generation + extra_headers: Optional headers to add to the request + use_caching: Whether to use provider-side caching for the response + + Returns: + A streaming response from the provider + """ + with sentry_sdk.start_transaction( + op="llm-api-stream", name=f"{self.provider} API Stream" + ): + # Log to langfuse + langfuse_context.update_current_observation( + input=messages, model=self.model + ) + + if self.provider == ModelProvider.ANTHROPIC: + return await self._stream_anthropic( + messages, + system, + max_tokens, + temperature, + extra_headers, + use_caching, + ) + elif self.provider in OPENAI_COMPATIBLE_PROVIDERS: + return await self._stream_openai( + messages, system, max_tokens, temperature + ) + elif self.provider == ModelProvider.GEMINI: + return await self._stream_gemini( + messages, system, max_tokens, temperature + ) + else: + raise ValueError(f"Unsupported provider: {self.provider}") + + @observe(as_type="generation") + async def _stream_anthropic( + self, + messages: list[dict[str, Any]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + extra_headers: Optional[dict[str, str]] = None, + use_caching: bool = False, + ) -> Any: + """Stream text using Anthropic API.""" + if not self.client: + raise ValueError("Anthropic client not initialized.") + + params = { + "model": self.model, + "messages": messages, + "max_tokens": max_tokens, + "temperature": temperature, + } + + # Handle system prompt with caching if enabled + if system: + if use_caching: + params["system"] = [ + { + "type": "text", + "text": system, + "cache_control": {"type": "ephemeral"}, + } + ] + else: + params["system"] = system + + langfuse_context.update_current_observation(input=messages, model=self.model) + + # Return the stream directly without awaiting it + return self.client.messages.stream(**params) + + @observe(as_type="generation") + async def _stream_openai( + self, + messages: list[dict[str, str]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + ) -> Any: + """Stream text using OpenAI or OpenRouter API.""" + if not self.openai_client: + raise ValueError("OpenAI client not initialized") + + # Prepare messages + formatted_messages = [] + + # Add system message if provided + if system: + formatted_messages.append({"role": "system", "content": system}) + + # Add the rest of the messages + formatted_messages.extend(messages) + + # Make the API call with the OpenAI client + stream = await self.openai_client.chat.completions.create( + model=self.model, + messages=formatted_messages, + max_tokens=max_tokens, + temperature=temperature, + stream=True, + ) + + return stream + + @observe(as_type="generation") + async def _generate_gemini( + self, + messages: list[dict[str, str]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + ) -> str: + """Generate text using Gemini API.""" + if not self.gemini_client: + raise ValueError("Gemini client not initialized") + + # Format messages for Gemini + gemini_messages = [] + + # Convert messages to Gemini format + for message in messages: + role = message["role"] + # Map roles to what Gemini expects + if role == "user": + gemini_role = "user" + elif role == "assistant": + gemini_role = "model" + else: + # Skip system messages as they're handled through config + continue + + gemini_messages.append( + genai_types.Content( + role=gemini_role, + parts=[genai_types.Part.from_text(text=message["content"])], + ) + ) + + # Set generation config + generate_content_config = genai_types.GenerateContentConfig( + temperature=temperature, + max_output_tokens=max_tokens, + response_mime_type="text/plain", + ) + + # Add system instruction if provided + if system: + generate_content_config.system_instruction = system + + # Make the API call + if not gemini_messages: + # If we have no messages but have a system prompt, create a default user message + if system: + default_content = genai_types.Content( + role="user", + parts=[ + genai_types.Part.from_text( + text="Please respond based on the system instructions." + ) + ], + ) + # model = self.gemini_client.get_model(self.model) + response = await self.gemini_client.aio.models.generate_content( + model=self.model, + contents=default_content, + config=generate_content_config, + ) + else: + raise ValueError("No messages provided for Gemini generation") + else: + # Normal case with messages + # model = get_model(self.model) + response = await self.gemini_client.aio.models.generate_content( + model=self.model, + contents=gemini_messages + if len(gemini_messages) > 1 + else gemini_messages[0], + config=generate_content_config, + ) + + # Extract text from response + if response and response.text: + return response.text + return "" + + @observe(as_type="generation") + async def _stream_gemini( + self, + messages: list[dict[str, str]], + system: Optional[str] = None, + max_tokens: int = DEFAULT_MAX_TOKENS, + temperature: float = DEFAULT_TEMPERATURE, + ) -> Any: + """Stream text using Gemini API.""" + if not self.gemini_client: + raise ValueError("Gemini client not initialized") + + # Format messages for Gemini + gemini_messages = [] + + # Convert messages to Gemini format + for message in messages: + role = message["role"] + # Map roles to what Gemini expects + if role == "user": + gemini_role = "user" + elif role == "assistant": + gemini_role = "model" + else: + # Skip system messages as they're handled through config + continue + + gemini_messages.append( + genai_types.Content( + role=gemini_role, + parts=[genai_types.Part.from_text(text=message["content"])], + ) + ) + + # Set generation config + generate_content_config = genai_types.GenerateContentConfig( + temperature=temperature, + max_output_tokens=max_tokens, + response_mime_type="text/plain", + ) + + # Add system instruction if provided + if system: + generate_content_config.system_instruction = system + + # Make the streaming API call + if not gemini_messages: + # If we have no messages but have a system prompt, create a default user message + if system: + default_content = genai_types.Content( + role="user", + parts=[ + genai_types.Part.from_text( + text="Please respond based on the system instructions." + ) + ], + ) + stream = await self.gemini_client.aio.models.generate_content_stream( + model=self.model, + contents=default_content, + config=generate_content_config, + ) + else: + raise ValueError("No messages provided for Gemini streaming") + else: + # Normal case with messages + stream = await self.gemini_client.aio.models.generate_content_stream( + model=self.model, + contents=gemini_messages + if len(gemini_messages) > 1 + else gemini_messages[0], + config=generate_content_config, + ) + + return stream diff --git a/tests/conftest.py b/tests/conftest.py index b9f5dc1d..0d111596 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,7 +1,8 @@ import logging # noqa: I001 import os -import sys +import jwt from nanoid import generate as generate_nanoid +from unittest.mock import patch, MagicMock, AsyncMock import pytest import pytest_asyncio @@ -9,7 +10,7 @@ from fastapi import Request from fastapi.responses import JSONResponse from fastapi.testclient import TestClient from sqlalchemy import text -from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine, AsyncSession +from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine from sqlalchemy.engine.url import make_url from sqlalchemy.exc import OperationalError, ProgrammingError from sqlalchemy_utils import create_database, database_exists, drop_database @@ -18,22 +19,45 @@ from src import models from src.db import Base from src.dependencies import get_db from src.exceptions import HonchoException +from src.security import create_admin_jwt, create_jwt, JWTParams from src.main import app + +# Create a custom handler that doesn't get closed prematurely +class TestHandler(logging.Handler): + def __init__(self): + super().__init__() + self.records = [] + + def emit(self, record): + self.records.append(record) + + +# Setup logging with our custom handler +test_handler = TestHandler() logging.basicConfig( level=logging.DEBUG, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", - stream=sys.stdout, # This ensures the output goes to stdout + handlers=[test_handler], ) logger = logging.getLogger(__name__) logging.getLogger("sqlalchemy.engine.Engine").disabled = True # Test database URL # TODO use environment variable -CONNECTION_URI = make_url(os.getenv("CONNECTION_URI")) +CONNECTION_URI = make_url( + os.getenv( + "CONNECTION_URI", + "postgresql+psycopg://postgres:postgres@localhost:5432/postgres", + ) +) TEST_DB_URL = CONNECTION_URI.set(database="test_db") DEFAULT_DB_URL = str(CONNECTION_URI.set(database="postgres")) +# Test API authorization +USE_AUTH = os.getenv("USE_AUTH", "False").lower() == "true" +AUTH_JWT_SECRET = os.getenv("AUTH_JWT_SECRET", "test-secret") + def create_test_database(db_url): """Helper function create a database if it does not already exist @@ -66,7 +90,7 @@ async def setup_test_database(db_url): Returns: engine: SQLAlchemy engine """ - engine = create_async_engine(str(db_url)) + engine = create_async_engine(str(db_url), echo=True) async with engine.connect() as conn: try: logger.info("Attempting to create pgvector extension...") @@ -94,7 +118,10 @@ async def db_engine(): create_test_database(TEST_DB_URL) engine = await setup_test_database(TEST_DB_URL) + # Drop all tables first to ensure clean state async with engine.begin() as conn: + await conn.run_sync(Base.metadata.drop_all) + # Then create all tables with current models await conn.run_sync(Base.metadata.create_all) yield engine @@ -114,7 +141,7 @@ async def db_session(db_engine): @pytest.fixture(scope="function") -def client(db_session): +async def client(db_session): """Create a FastAPI TestClient for the scope of a single test function""" # Register exception handlers for tests @@ -130,9 +157,49 @@ def client(db_session): app.dependency_overrides[get_db] = override_get_db with TestClient(app) as c: + if USE_AUTH: + # give the test client the admin JWT + c.headers["Authorization"] = f"Bearer {create_admin_jwt()}" yield c +def create_invalid_jwt() -> str: + return jwt.encode({"ad": "invalid"}, "this is not the secret", algorithm="HS256") + + +@pytest.fixture( + params=[ + ("none", None), # No auth + ("invalid", create_invalid_jwt), # Invalid JWT + ("empty", lambda: create_jwt(JWTParams())), # Empty JWT + ("admin", create_admin_jwt), # Admin JWT + ] +) +def auth_client(client, request, monkeypatch): + """ + Fixture that provides a client with different authentication states. + Always ensures USE_AUTH is set to True. + """ + # Ensure USE_AUTH is always True for this fixture + import src.routers.keys as keys_module + import src.security as security + + monkeypatch.setattr(keys_module, "USE_AUTH", "true") + monkeypatch.setattr(security, "USE_AUTH", "true") + + # Clear any existing Authorization header + client.headers.pop("Authorization", None) + + auth_type, token_func = request.param + client.auth_type = auth_type + + if token_func is not None: + token = token_func() + client.headers["Authorization"] = f"Bearer {token}" + + return client + + @pytest_asyncio.fixture(scope="function") async def sample_data(db_session): """Helper function to create test data""" @@ -149,3 +216,41 @@ async def sample_data(db_session): yield test_app, test_user await db_session.rollback() + + +@pytest.fixture(autouse=True) +def mock_langfuse(): + """Mock Langfuse decorator and context during tests""" + with ( + patch("langfuse.decorators.observe") as mock_observe, + patch("langfuse.decorators.langfuse_context") as mock_context, + ): + # Mock the decorator to just return the function + mock_observe.return_value = lambda func: func + + # Mock the context object + mock_context_obj = MagicMock() + mock_context_obj.update_current_observation = MagicMock() + mock_context_obj.update_current_trace = MagicMock() + mock_context.return_value = mock_context_obj + + # Disable httpx logging during tests + logging.getLogger("httpx").setLevel(logging.WARNING) + + yield + + # Clean up logging handlers + for handler in logging.getLogger().handlers[:]: + if isinstance(handler, TestHandler): + handler.close() + logging.getLogger().removeHandler(handler) + + +@pytest.fixture(autouse=True) +def mock_openai_embeddings(): + """Mock OpenAI embeddings API calls for testing""" + with patch("src.crud.openai_client.embeddings.create") as mock_create: + mock_response = AsyncMock() + mock_response.data = [MagicMock(embedding=[0.1] * 1536)] + mock_create.return_value = mock_response + yield mock_create diff --git a/tests/routes/test_apps.py b/tests/routes/test_apps.py index 5365a1e0..a8569655 100644 --- a/tests/routes/test_apps.py +++ b/tests/routes/test_apps.py @@ -1,3 +1,4 @@ +import pytest from nanoid import generate as generate_nanoid @@ -37,7 +38,7 @@ def test_get_or_create_app(client): response = client.get(f"/v1/apps/name/{name}") assert response.status_code == 404 assert "detail" in response.json() - + # This should create the app response = client.get(f"/v1/apps/get_or_create/{name}") assert response.status_code == 200 @@ -48,23 +49,23 @@ def test_get_or_create_app(client): def test_get_or_create_existing_app(client): name = str(generate_nanoid()) - + # App doesn't exist yet response = client.get(f"/v1/apps/name/{name}") assert response.status_code == 404 - + # Create the app response = client.post( "/v1/apps", json={"name": name, "metadata": {"key": "value"}} ) assert response.status_code == 200 app1 = response.json() - + # Now get_or_create should find the existing app response = client.get(f"/v1/apps/get_or_create/{name}") assert response.status_code == 200 app2 = response.json() - + # Both should be the same app assert app1["name"] == app2["name"] assert app1["id"] == app2["id"] @@ -73,13 +74,46 @@ def test_get_or_create_existing_app(client): def test_get_app_by_id(client, sample_data): test_app, _ = sample_data - response = client.get(f"/v1/apps/{test_app.public_id}") + response = client.get(f"/v1/apps?app_id={test_app.public_id}") assert response.status_code == 200 data = response.json() assert data["name"] == test_app.name assert data["id"] == str(test_app.public_id) +@pytest.mark.asyncio +async def test_get_all_apps(client, db_session, sample_data): + test_app, test_user = sample_data + + # create a test app with metadata + response = client.post( + "/v1/apps", + json={ + "name": "test_app", + "metadata": {"test_key": "test_value"}, + }, + ) + + response = client.post( + "/v1/apps/list", + json={}, + ) + assert response.status_code == 200 + data = response.json() + assert "items" in data + assert len(data["items"]) > 0 + + response = client.post( + "/v1/apps/list", + json={"filter": {"test_key": "test_value"}}, + ) + assert response.status_code == 200 + data = response.json() + assert "items" in data + assert len(data["items"]) > 0 + assert data["items"][0]["metadata"] == {"test_key": "test_value"} + + def test_get_app_by_name(client, sample_data): test_app, _ = sample_data response = client.get(f"/v1/apps/name/{test_app.name}") @@ -107,10 +141,10 @@ def test_create_duplicate_app_name(client): name = str(generate_nanoid()) response = client.post("/v1/apps", json={"name": name}) assert response.status_code == 200 - + # Try to create another app with the same name response = client.post("/v1/apps", json={"name": name}) - + # Should get a ConflictException with 409 status assert response.status_code == 409 data = response.json() diff --git a/tests/routes/test_collections.py b/tests/routes/test_collections.py index 4be81670..5464129a 100644 --- a/tests/routes/test_collections.py +++ b/tests/routes/test_collections.py @@ -1,3 +1,4 @@ +import pytest from nanoid import generate as generate_nanoid @@ -25,7 +26,7 @@ def test_get_collection_by_id(client, sample_data) -> None: data = response.json() # Get the collection response = client.get( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{data['id']}" + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections?collection_id={data['id']}" ) assert response.status_code == 200 data = response.json() @@ -127,6 +128,58 @@ def test_delete_collection(client, sample_data) -> None: ) assert response.status_code == 200 response = client.get( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{data['id']}" + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections?collection_id={data['id']}" ) assert response.status_code == 404 + + +@pytest.mark.asyncio +async def test_cannot_delete_honcho_collection(client, sample_data, db_session) -> None: + test_app, test_user = sample_data + # Make the protected "honcho" collection + response = client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "honcho", "metadata": {}}, + ) + assert response.status_code == 422 # Should get validation error when trying to create + + # Try to create it directly through API to test delete protection + response = client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "test_collection", "metadata": {}}, + ) + assert response.status_code == 200 + data = response.json() + collection_id = data["id"] + + # Update the collection to have the reserved name + response = client.put( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}", + json={"name": "honcho", "metadata": {}}, + ) + assert response.status_code == 422 # Should get validation error + + # Create the protected collection using the internal method directly with db_session + from src.crud import create_user_protected_collection + + # Create the protected collection + honcho_collection = await create_user_protected_collection( + db_session, app_id=test_app.public_id, user_id=test_user.public_id + ) + await db_session.flush() + + # Get the protected collection + response = client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/name/honcho" + ) + assert response.status_code == 200 + data = response.json() + assert data["name"] == "honcho" + protected_id = data["id"] + + # Try to delete the protected collection + response = client.delete( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{protected_id}" + ) + assert response.status_code == 422 # Should get validation error + assert "reserved name" in response.json()["detail"].lower() diff --git a/tests/routes/test_documents.py b/tests/routes/test_documents.py index 9c90d23b..fa801a67 100644 --- a/tests/routes/test_documents.py +++ b/tests/routes/test_documents.py @@ -1,3 +1,4 @@ +import pytest from nanoid import generate as generate_nanoid @@ -10,7 +11,7 @@ def test_update_document_validation_error(client, sample_data): ) assert response.status_code == 200 collection = response.json() - + # Create a document response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection['id']}/documents", @@ -18,13 +19,13 @@ def test_update_document_validation_error(client, sample_data): ) assert response.status_code == 200 document = response.json() - + # Try to update the document with empty content and metadata response = client.put( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection['id']}/documents/{document['id']}", json={"content": None, "metadata": None}, ) - + # Should get a ValidationException with 422 status assert response.status_code == 422 data = response.json() @@ -214,3 +215,47 @@ def test_delete_document(client, sample_data): f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection['id']}/documents/{document['id']}" ) assert response.status_code == 404 + + +@pytest.mark.asyncio +async def test_cannot_delete_documents_in_honcho_collection(client, sample_data, db_session): + test_app, test_user = sample_data + + # Create the protected collection using the internal method directly with db_session + from src.crud import create_user_protected_collection + + # Create the protected honcho collection + honcho_collection = await create_user_protected_collection( + db_session, app_id=test_app.public_id, user_id=test_user.public_id + ) + await db_session.flush() + + # Get the protected collection + response = client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/name/honcho" + ) + assert response.status_code == 200 + collection = response.json() + assert collection["name"] == "honcho" + + # Create a document in the protected collection + response = client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection['id']}/documents", + json={"content": "protected document", "metadata": {}}, + ) + assert response.status_code == 200 + document = response.json() + + # Try to delete the document from the protected collection + response = client.delete( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection['id']}/documents/{document['id']}" + ) + assert response.status_code == 422 # Should get validation error + assert "honcho" in response.json()["detail"].lower() + + # The document should still exist + response = client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection['id']}/documents/{document['id']}" + ) + assert response.status_code == 200 + assert response.json()["content"] == "protected document" diff --git a/tests/routes/test_keys.py b/tests/routes/test_keys.py new file mode 100644 index 00000000..d7690e46 --- /dev/null +++ b/tests/routes/test_keys.py @@ -0,0 +1,63 @@ +def test_create_key_no_params(auth_client): + """Test creating a key with no parameters""" + response = auth_client.post("/v1/keys") + + # Only admin JWT should be allowed + if auth_client.auth_type == "admin": + # key with no params should fail + assert response.status_code == 422 + else: + assert response.status_code == 401 + + +def test_create_key_with_params(auth_client, sample_data): + """Test creating a key with specific parameters""" + test_app, test_user = sample_data + + if auth_client.auth_type != "admin": + return # Skip test if not admin authentication + + # Test with app_id + response = auth_client.post("/v1/keys", params={"app_id": test_app.public_id}) + assert response.status_code == 200 + assert "key" in response.json() + + # Test with app_id and user_id + response = auth_client.post( + "/v1/keys", + params={"app_id": test_app.public_id, "user_id": test_user.public_id}, + ) + assert response.status_code == 200 + assert "key" in response.json() + + # Test with session_id and collection_id + response = auth_client.post( + "/v1/keys", + params={ + "app_id": test_app.public_id, + "user_id": test_user.public_id, + "session_id": "test-session", + "collection_id": "test-collection", + }, + ) + assert response.status_code == 200 + assert "key" in response.json() + + +def test_create_key_with_expires_at(auth_client, sample_data): + """Test creating a key with an expiration date""" + response = auth_client.post("/v1/keys", params={"expires_at": "2025-01-01"}) + + # Only admin JWT should be allowed + if auth_client.auth_type == "admin": + # key with no params should fail + assert response.status_code == 422 + return + else: + assert response.status_code == 401 + + test_app, _ = sample_data + + # assert that the key is expired + response = auth_client.post("/v1/keys", params={"app_id": test_app.public_id}) + assert response.status_code == 401 diff --git a/tests/routes/test_messages.py b/tests/routes/test_messages.py index d4bff1c8..0c7d99df 100644 --- a/tests/routes/test_messages.py +++ b/tests/routes/test_messages.py @@ -111,6 +111,7 @@ async def test_update_message(client, db_session, sample_data): data = response.json() assert data["metadata"] == {"new_key": "new_value"} + @pytest.mark.asyncio async def test_update_message_empty_metadata(client, db_session, sample_data): test_app, test_user = sample_data @@ -148,8 +149,9 @@ async def test_create_batch_messages(client, db_session, sample_data): { "content": f"Test message {i}", "is_user": i % 2 == 0, # Alternating user/non-user messages - "metadata": {"batch_index": i} - } for i in range(3) + "metadata": {"batch_index": i}, + } + for i in range(3) ] } @@ -157,13 +159,13 @@ async def test_create_batch_messages(client, db_session, sample_data): f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{test_session.public_id}/messages/batch", json=test_messages, ) - + assert response.status_code == 200 data = response.json() - + # Verify the response contains all messages assert len(data) == 3 - + # Verify messages are in the correct order and have correct content for i, message in enumerate(data): assert message["content"] == f"Test message {i}" @@ -195,8 +197,9 @@ async def test_create_batch_messages_limit(client, db_session, sample_data): { "content": f"Test message {i}", "is_user": i % 2 == 0, - "metadata": {"batch_index": i} - } for i in range(101) # 101 messages + "metadata": {"batch_index": i}, + } + for i in range(101) # 101 messages ] } @@ -204,7 +207,7 @@ async def test_create_batch_messages_limit(client, db_session, sample_data): f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{test_session.public_id}/messages/batch", json=test_messages, ) - + assert response.status_code == 422 # Validation error data = response.json() assert "messages" in data["detail"][0]["loc"] # Error should mention messages field diff --git a/tests/routes/test_metamessages.py b/tests/routes/test_metamessages.py index 65ec8f6f..ca7f643c 100644 --- a/tests/routes/test_metamessages.py +++ b/tests/routes/test_metamessages.py @@ -17,8 +17,9 @@ async def test_create_metamessage(client, db_session, sample_data): await db_session.commit() response = client.post( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{test_session.public_id}/metamessages", + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages", json={ + "session_id": str(test_session.public_id), "message_id": str(test_message.public_id), "content": "Test Metamessage", "metadata": {}, @@ -27,6 +28,8 @@ async def test_create_metamessage(client, db_session, sample_data): ) assert response.status_code == 200 data = response.json() + assert data["user_id"] == str(test_user.public_id) + assert data["session_id"] == str(test_session.public_id) assert data["message_id"] == str(test_message.public_id) assert data["content"] == "Test Metamessage" assert data["metadata"] == {} @@ -46,19 +49,23 @@ async def test_get_metamessage(client, db_session, sample_data): db_session.add(test_message) await db_session.commit() test_metamessage = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage", - metadata={}, + h_metadata={}, metamessage_type="test_type", ) db_session.add(test_metamessage) await db_session.commit() response = client.get( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{test_session.public_id}/metamessages/{test_metamessage.public_id}/?message_id={test_message.public_id}" + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages/{test_metamessage.public_id}" ) assert response.status_code == 200 data = response.json() + assert data["user_id"] == str(test_user.public_id) + assert data["session_id"] == str(test_session.public_id) assert data["message_id"] == str(test_message.public_id) assert data["content"] == "Test Metamessage" assert data["metadata"] == {} @@ -66,7 +73,7 @@ async def test_get_metamessage(client, db_session, sample_data): @pytest.mark.asyncio -async def test_get_metamessages(client, db_session, sample_data): +async def test_get_metamessages_by_session(client, db_session, sample_data): test_app, test_user = sample_data # Create a test session test_session = models.Session(user_id=test_user.public_id) @@ -77,25 +84,35 @@ async def test_get_metamessages(client, db_session, sample_data): ) db_session.add(test_message) await db_session.commit() + + # Create metamessages for the same session test_metamessage_1 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage", h_metadata={}, metamessage_type="test_type", ) test_metamessage_2 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage", h_metadata={}, metamessage_type="test_type", ) test_metamessage_3 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage", h_metadata={}, metamessage_type="test_type", ) test_metamessage_4 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage", h_metadata={}, @@ -107,25 +124,29 @@ async def test_get_metamessages(client, db_session, sample_data): db_session.add(test_metamessage_4) await db_session.commit() + # Filter by session and type response = client.post( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{test_session.public_id}/metamessages/list", - json={"metamessage_type": "test_type"}, + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages/list", + json={ + "session_id": str(test_session.public_id), + "metamessage_type": "test_type", + }, ) assert response.status_code == 200 data = response.json() assert "items" in data - assert len(data["items"]) > 0 assert len(data["items"]) == 3 assert data["items"][0]["content"] == "Test Metamessage" assert data["items"][0]["metamessage_type"] == "test_type" + assert data["items"][0]["session_id"] == str(test_session.public_id) assert data["items"][0]["metadata"] == {} @pytest.mark.asyncio async def test_get_metamessage_by_user(client, db_session, sample_data): test_app, test_user = sample_data - # Create a 3 test sessions + # Create 3 test sessions test_session_1 = models.Session(user_id=test_user.public_id) test_session_2 = models.Session(user_id=test_user.public_id) test_session_3 = models.Session(user_id=test_user.public_id) @@ -149,48 +170,87 @@ async def test_get_metamessage_by_user(client, db_session, sample_data): db_session.add(test_message_3) await db_session.commit() - # create a metamessage on each message + # Create metamessages across different sessions test_metamessage_1 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session_1.public_id, message_id=test_message_1.public_id, content="Test Metamessage", h_metadata={}, metamessage_type="test_type", ) test_metamessage_2 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session_2.public_id, message_id=test_message_2.public_id, content="Test Metamessage", h_metadata={}, metamessage_type="test_type", ) test_metamessage_3 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session_3.public_id, message_id=test_message_3.public_id, content="Test Metamessage", h_metadata={}, metamessage_type="test_type", ) test_metamessage_4 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session_3.public_id, message_id=test_message_3.public_id, content="Test Metamessage", h_metadata={}, metamessage_type="test_type_2", ) + # Create a user-level metamessage (no session/message) + test_metamessage_5 = models.Metamessage( + user_id=test_user.public_id, + content="User level metamessage", + h_metadata={}, + metamessage_type="test_type", + ) db_session.add(test_metamessage_1) db_session.add(test_metamessage_2) db_session.add(test_metamessage_3) db_session.add(test_metamessage_4) + db_session.add(test_metamessage_5) await db_session.commit() + # Filter only by type across all user's metamessages response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages/list", json={"metamessage_type": "test_type"}, ) assert response.status_code == 200 data = response.json() - assert len(data["items"]) > 0 - assert len(data["items"]) == 3 - assert data["items"][0]["content"] == "Test Metamessage" + assert len(data["items"]) == 4 # All test_type metamessages for the user + assert data["items"][0]["content"] in ["Test Metamessage", "User level metamessage"] assert data["items"][0]["metamessage_type"] == "test_type" - assert data["items"][0]["metadata"] == {} + assert data["items"][0]["user_id"] == str(test_user.public_id) + + +@pytest.mark.asyncio +async def test_create_user_level_metamessage(client, db_session, sample_data): + test_app, test_user = sample_data + + # Create a user-level metamessage (no session or message) + response = client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages", + json={ + "content": "User level insight", + "metadata": {"source": "user_profile"}, + "metamessage_type": "user_insight", + }, + ) + assert response.status_code == 200 + data = response.json() + assert data["user_id"] == str(test_user.public_id) + assert data["session_id"] is None + assert data["message_id"] is None + assert data["content"] == "User level insight" + assert data["metadata"] == {"source": "user_profile"} + assert data["metamessage_type"] == "user_insight" @pytest.mark.asyncio @@ -206,21 +266,27 @@ async def test_update_metamessage(client, db_session, sample_data): db_session.add(test_message) await db_session.commit() test_metamessage = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage", - metadata={}, + h_metadata={}, metamessage_type="test_type", ) db_session.add(test_metamessage) await db_session.commit() response = client.put( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{test_session.public_id}/metamessages/{test_metamessage.public_id}", + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages/{test_metamessage.public_id}", json={ - "message_id": str(test_message.public_id), "metadata": {"new_key": "new_value"}, + "metamessage_type": "updated_type", }, ) assert response.status_code == 200 data = response.json() assert data["metadata"] == {"new_key": "new_value"} + assert data["metamessage_type"] == "updated_type" + assert data["user_id"] == str(test_user.public_id) + assert data["session_id"] == str(test_session.public_id) + assert data["message_id"] == str(test_message.public_id) diff --git a/tests/routes/test_scoped_api.py b/tests/routes/test_scoped_api.py new file mode 100644 index 00000000..8dbee588 --- /dev/null +++ b/tests/routes/test_scoped_api.py @@ -0,0 +1,628 @@ +from nanoid import generate as generate_nanoid + +from src.security import JWTParams, create_jwt + + +def test_create_app_with_auth(auth_client): + name = str(generate_nanoid()) + + response = auth_client.post( + "/v1/apps", json={"name": name, "metadata": {"key": "value"}} + ) + + # Check expected behavior based on auth type + if auth_client.auth_type != "admin": + assert response.status_code == 401 + return + + assert response.status_code == 200 + + +def test_auth_response_time(auth_client): + name = str(generate_nanoid()) + + import time + + start_time = time.time() + + response = auth_client.post( + "/v1/apps", json={"name": name, "metadata": {"key": "value"}} + ) + + end_time = time.time() + response_time = end_time - start_time + print( + f"Server response time for client {auth_client.auth_type}: {response_time:.6f} seconds" + ) + + # Check expected behavior based on auth type + if auth_client.auth_type != "admin": + assert response.status_code == 401 + return + + assert response.status_code == 200 + + +def test_get_or_create_app_with_auth(auth_client): + name = str(generate_nanoid()) + # Should return a ResourceNotFoundException with 404 status + response = auth_client.get(f"/v1/apps/name/{name}") + + if auth_client.auth_type != "admin": + assert response.status_code == 401 + return + + assert response.status_code == 404 + + response = auth_client.get(f"/v1/apps/get_or_create/{name}") + + if auth_client.auth_type != "admin": + assert response.status_code == 401 + return + + assert response.status_code == 200 + + +def test_get_app_by_id_with_auth(auth_client, sample_data): + test_app, _ = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + response = auth_client.get(f"/v1/apps?app_id={test_app.public_id}") + + # Admin JWT or JWT with matching app_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + +def test_get_app_from_token(auth_client, sample_data): + test_app, _ = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + response = auth_client.get("/v1/apps") + + if auth_client.auth_type == "empty": + assert response.status_code == 200 + assert response.json()["id"] == test_app.public_id + else: + assert response.status_code == 401 + + +def test_get_app_by_name_with_auth(auth_client, sample_data): + test_app, _ = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + # Note that this will still fail because name route requires admin + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + response = auth_client.get(f"/v1/apps/name/{test_app.name}") + + # Only admin JWT should be allowed + if auth_client.auth_type == "admin": + assert response.status_code == 200 + else: + assert response.status_code == 401 + + +def test_update_app_with_auth(auth_client, sample_data): + test_app, _ = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + # Note that this will still fail because name route requires admin + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + new_name = str(generate_nanoid()) + response = auth_client.put( + f"/v1/apps/{test_app.public_id}", + json={"name": new_name, "metadata": {"new_key": "new_value"}}, + ) + + # Only admin JWT or JWT with matching app_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + +def test_update_app_with_wrong_auth(auth_client, sample_data): + test_app, _ = sample_data + + different_app = str(generate_nanoid()) + + if auth_client.auth_type == "empty": + # For non-admin, include the *wrong* app_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=different_app))}" + ) + + new_name = str(generate_nanoid()) + response = auth_client.put( + f"/v1/apps/{test_app.public_id}", + json={"name": new_name, "metadata": {"new_key": "new_value"}}, + ) + + # Only admin JWT or JWT with matching app_id should be allowed + if auth_client.auth_type == "admin": + assert response.status_code == 200 + else: + # wrong app_id should be rejected + assert response.status_code == 401 + + +def test_create_user_with_auth(auth_client, sample_data): + test_app, _ = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + name = str(generate_nanoid()) + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users", + json={"name": name, "metadata": {"user_key": "user_value"}}, + ) + + # Only admin JWT or JWT with matching app_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + +def test_get_user_by_id_with_auth(auth_client, sample_data): + test_app, test_user = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users?user_id={test_user.public_id}" + ) + + # Admin JWT or JWT with matching app_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + # Test with user-scoped JWT + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(us=test_user.public_id))}" + ) + + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users?user_id={test_user.public_id}" + ) + + assert response.status_code == 200 + + response2 = auth_client.get(f"/v1/apps/{test_app.public_id}/users") + + assert response2.status_code == 200 + + print(response2.json()) + + assert response2.json()["id"] == test_user.public_id + + +def test_get_user_by_name_with_auth(auth_client, sample_data): + test_app, test_user = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/name/{test_user.name}" + ) + + # Admin JWT or JWT with matching app_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + +def test_update_user_with_auth(auth_client, sample_data): + test_app, test_user = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + new_name = str(generate_nanoid()) + response = auth_client.put( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}", + json={"name": new_name, "metadata": {"updated_key": "updated_value"}}, + ) + + # Admin JWT or JWT with matching app_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + # Test with user-scoped JWT + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(us=test_user.public_id))}" + ) + + response = auth_client.put( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}", + json={ + "name": str(generate_nanoid()), + "metadata": {"user_key": "user_value"}, + }, + ) + + assert response.status_code == 200 + + +def test_create_session_with_auth(auth_client, sample_data): + test_app, test_user = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id and user_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id, us=test_user.public_id))}" + ) + + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", + json={}, + ) + + # Only admin JWT or JWT with matching app_id and user_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + # Remove app_id from header and make sure user-scoped key works too + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(us=test_user.public_id))}" + ) + + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", + json={}, + ) + + assert response.status_code == 200 + + +def test_get_session_by_id_with_auth(auth_client, sample_data): + test_app, test_user = sample_data + + # First create a session + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id, us=test_user.public_id))}" + ) + + create_response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", + json={}, + ) + + if auth_client.auth_type not in ["admin", "empty"]: + assert create_response.status_code == 401 + return + + assert create_response.status_code == 200 + session_id = create_response.json()["id"] + + # Test with app and user scoped JWT + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions?session_id={session_id}" + ) + assert response.status_code == 200 + + if auth_client.auth_type == "empty": + # Test with session-scoped JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(se=session_id))}" + ) + + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions?session_id={session_id}" + ) + assert response.status_code == 200 + + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions" + ) + + assert response.status_code == 200 + + assert response.json()["id"] == session_id + + # Test with wrong session_id (should be 401 since we have a session-scoped JWT) + assert ( + auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions?session_id={generate_nanoid()}" + ).status_code + == 401 + ) + + # Test with user-scoped JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(us=test_user.public_id))}" + ) + + assert ( + auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions?session_id={session_id}" + ).status_code + == 200 + ) + assert ( + auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions" + ).status_code + == 401 + ) + + # Test with app-scoped JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + assert ( + auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions?session_id={session_id}" + ).status_code + == 200 + ) + + assert ( + auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions" + ).status_code + == 401 + ) + + # Test with wrong session_id (should be 404 since we have an app-scoped JWT) + assert ( + auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions?session_id={generate_nanoid()}" + ).status_code + == 404 + ) + + +def test_create_collection(auth_client, sample_data) -> None: + test_app, test_user = sample_data + + if auth_client.auth_type == "empty": + # For non-admin, include the app_id and user_id in the JWT + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id, us=test_user.public_id))}" + ) + + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "test_collection", "metadata": {}}, + ) + + # Only admin JWT or JWT with matching app_id and user_id should be allowed + if auth_client.auth_type in ["admin", "empty"]: + assert response.status_code == 200 + else: + assert response.status_code == 401 + + # Remove app_id from header and make sure user-scoped key works too + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(us=test_user.public_id))}" + ) + + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "test_collection2", "metadata": {}}, + ) + + assert response.status_code == 200 + + # Remove user_id from header and make sure app-scoped key works too + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id))}" + ) + + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "test_collection3", "metadata": {}}, + ) + + assert response.status_code == 200 + + +def test_get_collection_by_id_with_auth(auth_client, sample_data) -> None: + test_app, test_user = sample_data + + # First create a collection + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id, us=test_user.public_id))}" + ) + + create_response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "test_collection_get", "metadata": {}}, + ) + + if auth_client.auth_type not in ["admin", "empty"]: + assert create_response.status_code == 401 + return + + assert create_response.status_code == 200 + collection_id = create_response.json()["id"] + + # Test with app and user scoped JWT + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections?collection_id={collection_id}" + ) + assert response.status_code == 200 + + # Test with collection-scoped JWT + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(co=collection_id))}" + ) + + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections?collection_id={collection_id}" + ) + assert response.status_code == 200 + + # Test auto resolution of ID + response2 = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections" + ) + assert response2.status_code == 200 + assert response2.json()["id"] == collection_id + + +def test_get_collection_by_name_with_auth(auth_client, sample_data) -> None: + test_app, test_user = sample_data + collection_name = f"test_collection_{generate_nanoid()}" + + # First create a collection + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id, us=test_user.public_id))}" + ) + + create_response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": collection_name, "metadata": {}}, + ) + + if auth_client.auth_type not in ["admin", "empty"]: + assert create_response.status_code == 401 + return + + assert create_response.status_code == 200 + + # Test with app and user scoped JWT + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/name/{collection_name}" + ) + assert response.status_code == 200 + + +def test_create_document_with_auth(auth_client, sample_data) -> None: + test_app, test_user = sample_data + + # First create a collection + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id, us=test_user.public_id))}" + ) + + create_collection_response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "test_collection_docs", "metadata": {}}, + ) + + if auth_client.auth_type not in ["admin", "empty"]: + assert create_collection_response.status_code == 401 + return + + assert create_collection_response.status_code == 200 + collection_id = create_collection_response.json()["id"] + + # Create document with app and user scoped JWT + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents", + json={"content": "Test document content", "metadata": {"doc_key": "doc_value"}}, + ) + assert response.status_code == 200 + + # Test with collection-scoped JWT + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(co=collection_id))}" + ) + + response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents", + json={"content": "Test document with collection JWT", "metadata": {}}, + ) + assert response.status_code == 200 + + +def test_get_document_with_auth(auth_client, sample_data) -> None: + test_app, test_user = sample_data + + # First create a collection and document + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(ap=test_app.public_id, us=test_user.public_id))}" + ) + + create_collection_response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", + json={"name": "test_collection_get_doc", "metadata": {}}, + ) + + if auth_client.auth_type not in ["admin", "empty"]: + assert create_collection_response.status_code == 401 + return + + assert create_collection_response.status_code == 200 + collection_id = create_collection_response.json()["id"] + + create_doc_response = auth_client.post( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents", + json={"content": "Test document for retrieval", "metadata": {}}, + ) + assert create_doc_response.status_code == 200 + document_id = create_doc_response.json()["id"] + + # Get document with app and user scoped JWT + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents/{document_id}" + ) + assert response.status_code == 200 + + # Test with collection-scoped JWT + if auth_client.auth_type == "empty": + auth_client.headers["Authorization"] = ( + f"Bearer {create_jwt(JWTParams(co=collection_id))}" + ) + + response = auth_client.get( + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents/{document_id}" + ) + assert response.status_code == 200 diff --git a/tests/routes/test_sessions.py b/tests/routes/test_sessions.py index 50e15ae9..c566c021 100644 --- a/tests/routes/test_sessions.py +++ b/tests/routes/test_sessions.py @@ -118,7 +118,7 @@ async def test_delete_session(client, db_session, sample_data): ) assert response.status_code == 200 response = client.get( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{test_session.public_id}" + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions?session_id={test_session.public_id}" ) data = response.json() assert data["is_active"] is False @@ -266,24 +266,32 @@ async def test_deep_clone_session(client, db_session, sample_data): await db_session.commit() test_metamessage_1 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage 1", h_metadata={}, metamessage_type="test_type", ) test_metamessage_2 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage 2", h_metadata={}, metamessage_type="test_type", ) test_metamessage_3 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message2.public_id, content="Test Metamessage 3", h_metadata={}, metamessage_type="test_type", ) test_metamessage_4 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message2.public_id, content="Test Metamessage 4", h_metadata={}, @@ -325,8 +333,8 @@ async def test_deep_clone_session(client, db_session, sample_data): assert data["items"][1]["metadata"] == {"key": "value2"} response = client.post( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{cloned_session_id}/metamessages/list", - json={}, + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages/list", + json={"session_id": cloned_session_id}, ) assert response.status_code == 200 @@ -374,24 +382,32 @@ async def test_partial_deep_clone_session(client, db_session, sample_data): await db_session.commit() test_metamessage_1 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage 1", h_metadata={}, metamessage_type="test_type", ) test_metamessage_2 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message.public_id, content="Test Metamessage 2", h_metadata={}, metamessage_type="test_type", ) test_metamessage_3 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message2.public_id, content="Test Metamessage 3", h_metadata={}, metamessage_type="test_type", ) test_metamessage_4 = models.Metamessage( + user_id=test_user.public_id, + session_id=test_session.public_id, message_id=test_message2.public_id, content="Test Metamessage 4", h_metadata={}, @@ -429,8 +445,8 @@ async def test_partial_deep_clone_session(client, db_session, sample_data): assert data["items"][0]["metadata"] == {"key": "value"} response = client.post( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{cloned_session_id}/metamessages/list", - json={}, + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages/list", + json={"session_id": cloned_session_id}, ) assert response.status_code == 200 diff --git a/tests/routes/test_users.py b/tests/routes/test_users.py index 09726cd4..6cce77e9 100644 --- a/tests/routes/test_users.py +++ b/tests/routes/test_users.py @@ -17,7 +17,9 @@ def test_create_user(client, sample_data): def test_get_user_by_id(client, sample_data): test_app, test_user = sample_data - response = client.get(f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}") + response = client.get( + f"/v1/apps/{test_app.public_id}/users?user_id={test_user.public_id}" + ) assert response.status_code == 200 data = response.json() assert data["name"] == test_user.name diff --git a/tests/routes/test_validation_api.py b/tests/routes/test_validation_api.py index 3d1cbbd0..46a25849 100644 --- a/tests/routes/test_validation_api.py +++ b/tests/routes/test_validation_api.py @@ -1,4 +1,3 @@ -import pytest from nanoid import generate as generate_nanoid @@ -32,8 +31,7 @@ def test_user_validations_api(client, sample_data): # Test name too short response = client.post( - f"/v1/apps/{test_app.public_id}/users", - json={"name": "", "metadata": {}} + f"/v1/apps/{test_app.public_id}/users", json={"name": "", "metadata": {}} ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -43,8 +41,7 @@ def test_user_validations_api(client, sample_data): # Test name too long response = client.post( - f"/v1/apps/{test_app.public_id}/users", - json={"name": "a" * 101, "metadata": {}} + f"/v1/apps/{test_app.public_id}/users", json={"name": "a" * 101, "metadata": {}} ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -58,18 +55,14 @@ def test_message_validations_api(client, sample_data): # Create a test session first session_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", - json={"metadata": {}} + json={"metadata": {}}, ) session_id = session_response.json()["id"] # Test content too long response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/messages", - json={ - "content": "a" * 50001, - "is_user": True, - "metadata": {} - } + json={"content": "a" * 50001, "is_user": True, "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -80,11 +73,7 @@ def test_message_validations_api(client, sample_data): # Test invalid is_user type response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/messages", - json={ - "content": "test", - "is_user": "not a bool", - "metadata": {} - } + json={"content": "test", "is_user": "not a bool", "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -98,7 +87,7 @@ def test_collection_validations_api(client, sample_data): # Test name too short response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"name": "", "metadata": {}} + json={"name": "", "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -109,7 +98,7 @@ def test_collection_validations_api(client, sample_data): # Test name too long response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"name": "a" * 101, "metadata": {}} + json={"name": "a" * 101, "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -120,7 +109,7 @@ def test_collection_validations_api(client, sample_data): # Test 'honcho' name restriction response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"name": "honcho", "metadata": {}} + json={"name": "honcho", "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -134,14 +123,14 @@ def test_document_validations_api(client, sample_data): # Create a collection first collection_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"name": str(generate_nanoid()), "metadata": {}} + json={"name": str(generate_nanoid()), "metadata": {}}, ) collection_id = collection_response.json()["id"] # Test content too short response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents", - json={"content": "", "metadata": {}} + json={"content": "", "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -152,7 +141,7 @@ def test_document_validations_api(client, sample_data): # Test content too long response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents", - json={"content": "a" * 100001, "metadata": {}} + json={"content": "a" * 100001, "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -166,14 +155,14 @@ def test_document_query_validations_api(client, sample_data): # Create a collection first collection_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"name": str(generate_nanoid()), "metadata": {}} + json={"name": str(generate_nanoid()), "metadata": {}}, ) collection_id = collection_response.json()["id"] # Test query too short response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents/query", - json={"query": "", "top_k": 5} + json={"query": "", "top_k": 5}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -184,7 +173,7 @@ def test_document_query_validations_api(client, sample_data): # Test query too long response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents/query", - json={"query": "a" * 1001, "top_k": 5} + json={"query": "a" * 1001, "top_k": 5}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -195,7 +184,7 @@ def test_document_query_validations_api(client, sample_data): # Test top_k too small response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents/query", - json={"query": "test", "top_k": 0} + json={"query": "test", "top_k": 0}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -206,7 +195,7 @@ def test_document_query_validations_api(client, sample_data): # Test top_k too large response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents/query", - json={"query": "test", "top_k": 51} + json={"query": "test", "top_k": 51}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -220,23 +209,19 @@ def test_message_batch_validations_api(client, sample_data): # Create a test session first session_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", - json={"metadata": {}} + json={"metadata": {}}, ) session_id = session_response.json()["id"] # Test batch too large messages = [ - { - "content": f"test message {i}", - "is_user": True, - "metadata": {} - } + {"content": f"test message {i}", "is_user": True, "metadata": {}} for i in range(101) # Create 101 messages ] - + response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/messages/batch", - json={"messages": messages} + json={"messages": messages}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -250,25 +235,26 @@ def test_metamessage_validations_api(client, sample_data): # Create session and message first session_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", - json={"metadata": {}} + json={"metadata": {}}, ) session_id = session_response.json()["id"] - + message_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/messages", - json={"content": "test message", "is_user": True, "metadata": {}} + json={"content": "test message", "is_user": True, "metadata": {}}, ) message_id = message_response.json()["id"] # Test metamessage_type too short response = client.post( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/metamessages", + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages", json={ "metamessage_type": "", "content": "test content", + "session_id": session_id, "message_id": message_id, - "metadata": {} - } + "metadata": {}, + }, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -278,13 +264,14 @@ def test_metamessage_validations_api(client, sample_data): # Test metamessage_type too long response = client.post( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/metamessages", + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages", json={ "metamessage_type": "a" * 51, "content": "test content", + "session_id": session_id, "message_id": message_id, - "metadata": {} - } + "metadata": {}, + }, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -294,13 +281,14 @@ def test_metamessage_validations_api(client, sample_data): # Test content too long response = client.post( - f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/metamessages", + f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/metamessages", json={ "metamessage_type": "test_type", "content": "a" * 50001, "message_id": message_id, - "metadata": {} - } + "session_id": session_id, + "metadata": {}, + }, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -314,14 +302,14 @@ def test_collection_update_validations_api(client, sample_data): # Create a collection first collection_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"name": str(generate_nanoid()), "metadata": {}} + json={"name": str(generate_nanoid()), "metadata": {}}, ) collection_id = collection_response.json()["id"] # Test honcho name in update response = client.put( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}", - json={"name": "honcho", "metadata": {}} + json={"name": "honcho", "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -335,26 +323,26 @@ def test_document_update_validations_api(client, sample_data): # Create collection and document first collection_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"name": str(generate_nanoid()), "metadata": {}} + json={"name": str(generate_nanoid()), "metadata": {}}, ) collection_id = collection_response.json()["id"] - + document_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents", - json={"content": "test content", "metadata": {}} + json={"content": "test content", "metadata": {}}, ) document_id = document_response.json()["id"] # Test content too long in update response = client.put( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/{collection_id}/documents/{document_id}", - json={"content": "a" * 100001, "metadata": {}} + json={"content": "a" * 100001, "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] assert error["loc"] == ["body", "content"] assert error["msg"] == "String should have at most 100000 characters" - assert error["type"] == "string_too_long" + assert error["type"] == "string_too_long" def test_session_validations_api(client, sample_data): @@ -362,14 +350,14 @@ def test_session_validations_api(client, sample_data): # Create a test session first session_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", - json={"metadata": {}} + json={"metadata": {}}, ) session_id = session_response.json()["id"] # Test invalid metadata type response = client.put( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}", - json={"metadata": "not a dict"} + json={"metadata": "not a dict"}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -379,31 +367,89 @@ def test_session_validations_api(client, sample_data): # Test empty update response = client.put( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}", - json={} + json={}, ) assert response.status_code == 422 -def test_agent_query_validations_api(client, sample_data): +def test_agent_query_validations_api(client, sample_data, monkeypatch): + # Mock the functions in agent.py that are causing the database issues + + # Create a mock collection with a public_id + class MockCollection: + def __init__(self): + self.public_id = "mock_collection_id" + + # Mock collection retrieval/creation function + async def mock_get_or_create_collection(*args, **kwargs): + return MockCollection() + + async def mock_chat_history(*args, **kwargs): + return "Mock chat history", [], [] + + async def mock_get_long_term_facts(*args, **kwargs): + return ["Mock fact 1", "Mock fact 2"] + + async def mock_run_tom_inference(*args, **kwargs): + return "Mock TOM inference" + + async def mock_generate_user_representation(*args, **kwargs): + return "Mock user representation" + + # Mock the Dialectic.call method + async def mock_dialectic_call(self): + # Create a mock response that will work with line 300 in agent.py: + # return schemas.AgentChat(content=response[0]["text"]) + return [{"text": "Mock response"}] + + # Mock the Dialectic.stream method + def mock_dialectic_stream(self): + class MockStream: + def __enter__(self): + return self + + def __exit__(self, *args): + pass + + @property + def text_stream(self): + yield "Mock streamed response" + + return MockStream() + + # Apply the monkeypatches + monkeypatch.setattr( + "src.crud.get_or_create_user_protected_collection", + mock_get_or_create_collection, + ) + monkeypatch.setattr("src.utils.history.get_summarized_history", mock_chat_history) + monkeypatch.setattr("src.agent.get_long_term_facts", mock_get_long_term_facts) + monkeypatch.setattr("src.agent.run_tom_inference", mock_run_tom_inference) + monkeypatch.setattr( + "src.agent.generate_user_representation", mock_generate_user_representation + ) + monkeypatch.setattr("src.agent.Dialectic.call", mock_dialectic_call) + monkeypatch.setattr("src.agent.Dialectic.stream", mock_dialectic_stream) + test_app, test_user = sample_data # Create a session first since agent queries are likely session-based session_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", - json={"metadata": {}} + json={"metadata": {}}, ) session_id = session_response.json()["id"] # Test valid string query (under 10000 chars) response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/chat", - json={"queries": "a" * 9999} + json={"queries": "a" * 9999}, ) assert response.status_code == 200 # Test string query too long (over 10000 chars) response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/chat", - json={"queries": "a" * 10001} + json={"queries": "a" * 10001}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -414,14 +460,14 @@ def test_agent_query_validations_api(client, sample_data): # Test valid list query (under 25 items, each under 10000 chars) response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/chat", - json={"queries": ["a" * 9999 for _ in range(25)]} + json={"queries": ["a" * 9999 for _ in range(25)]}, ) assert response.status_code == 200 # Test list too long (over 25 items) response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/chat", - json={"queries": ["test" for _ in range(26)]} + json={"queries": ["test" for _ in range(26)]}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -431,7 +477,7 @@ def test_agent_query_validations_api(client, sample_data): # Test list item too long (item over 10000 chars) response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/chat", - json={"queries": ["a" * 10001]} + json={"queries": ["a" * 10001]}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -442,7 +488,7 @@ def test_agent_query_validations_api(client, sample_data): # Test that strings over 20 chars are allowed response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/chat", - json={"queries": "a" * 100} # 100 chars should be fine + json={"queries": "a" * 100}, # 100 chars should be fine ) assert response.status_code == 200 @@ -451,14 +497,14 @@ def test_required_field_validations_api(client, sample_data): test_app, test_user = sample_data session_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", - json={"metadata": {}} + json={"metadata": {}}, ) session_id = session_response.json()["id"] # Test missing required content in message response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/messages", - json={"is_user": True, "metadata": {}} + json={"is_user": True, "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -468,7 +514,7 @@ def test_required_field_validations_api(client, sample_data): # Test missing required is_user in message response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/messages", - json={"content": "test", "metadata": {}} + json={"content": "test", "metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -478,7 +524,7 @@ def test_required_field_validations_api(client, sample_data): # Test missing required name in collection response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections", - json={"metadata": {}} + json={"metadata": {}}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -491,14 +537,14 @@ def test_filter_validations_api(client, sample_data): # Create a session first session_response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions", - json={"metadata": {}} + json={"metadata": {}}, ) session_id = session_response.json()["id"] # Test invalid filter type in message list (at session level) response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/sessions/{session_id}/messages/list", - json={"filter": "not a dict"} + json={"filter": "not a dict"}, ) assert response.status_code == 422 error = response.json()["detail"][0] @@ -508,7 +554,7 @@ def test_filter_validations_api(client, sample_data): # Test invalid filter type in collection list (at user level) response = client.post( f"/v1/apps/{test_app.public_id}/users/{test_user.public_id}/collections/list", - json={"filter": "not a dict"} + json={"filter": "not a dict"}, ) assert response.status_code == 422 error = response.json()["detail"][0] diff --git a/tests/test_schema_validations.py b/tests/test_schema_validations.py index 39ab3586..77d6f28b 100644 --- a/tests/test_schema_validations.py +++ b/tests/test_schema_validations.py @@ -1,14 +1,15 @@ import pytest from pydantic import ValidationError + from src.schemas import ( AppCreate, - UserCreate, - MessageCreate, - MetamessageCreate, CollectionCreate, DocumentCreate, DocumentQuery, MessageBatchCreate, + MessageCreate, + MetamessageCreate, + UserCreate, ) @@ -200,9 +201,7 @@ class TestDocumentQueryValidations: class TestMessageBatchValidations: def test_valid_message_batch(self): batch = MessageBatchCreate( - messages=[ - MessageCreate(content="test", is_user=True, metadata={}) - ] + messages=[MessageCreate(content="test", is_user=True, metadata={})] ) assert len(batch.messages) == 1 @@ -215,4 +214,4 @@ class TestMessageBatchValidations: ] ) error_dict = exc_info.value.errors()[0] - assert error_dict["type"] == "too_long" \ No newline at end of file + assert error_dict["type"] == "too_long" diff --git a/tests/utils/test_model_client.py b/tests/utils/test_model_client.py new file mode 100644 index 00000000..2b51fc50 --- /dev/null +++ b/tests/utils/test_model_client.py @@ -0,0 +1,191 @@ +import os +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +from src.utils.model_client import ( + DEFAULT_MAX_TOKENS, + DEFAULT_MODELS, + DEFAULT_TEMPERATURE, + ModelClient, + ModelProvider, +) + + +@pytest.fixture +def mock_env(monkeypatch): + monkeypatch.setenv("ANTHROPIC_API_KEY", "mock-anthropic-api-key") + monkeypatch.setenv("OPENAI_COMPATIBLE_API_KEY", "mock-openai-api-key") + monkeypatch.setenv("OPENAI_API_KEY", "mock-openai-api-key") + monkeypatch.setenv("GROQ_API_KEY", "mock-groq-api-key") + monkeypatch.setenv("CEREBRAS_API_KEY", "mock-cerebras-api-key") + monkeypatch.setenv("OPENROUTER_API_KEY", "mock-openrouter-api-key") + + +# Test fixtures +@pytest.fixture +def mock_anthropic_response(): + mock_response = MagicMock() + mock_content = MagicMock() + mock_content.type = "text" + mock_content.text = "Test response" + mock_response.content = [mock_content] + return mock_response + + +@pytest.fixture +def mock_openai_response(): + mock_response = MagicMock() + mock_message = MagicMock() + mock_message.content = "Test response" + mock_choice = MagicMock() + mock_choice.message = mock_message + mock_response.choices = [mock_choice] + return mock_response + + +@pytest.fixture +def mock_anthropic_client(): + with patch("src.utils.model_client.AsyncAnthropic") as mock: + client = MagicMock() + client.messages.create = AsyncMock() + client.messages.stream = AsyncMock() + mock.return_value = client + yield client + + +@pytest.fixture +def mock_openai_client(): + with patch("src.utils.model_client.AsyncOpenAI") as mock: + client = MagicMock() + client.chat.completions.create = AsyncMock() + mock.return_value = client + yield client + + +# Initialization Tests +def test_default_initialization(mock_env): + """Test default initialization with Anthropic provider.""" + client = ModelClient() + assert client.provider == ModelProvider.ANTHROPIC + assert client.model == DEFAULT_MODELS[ModelProvider.ANTHROPIC] + assert client.base_url is None + + +def test_custom_model_initialization(): + """Test initialization with custom model name.""" + custom_model = "custom-model" + client = ModelClient(model=custom_model) + assert client.model == custom_model + + +def test_custom_api_key_initialization(): + """Test initialization with custom API key.""" + custom_key = "test-api-key" + client = ModelClient(api_key=custom_key) + assert client.api_key == custom_key + + +def test_custom_base_url_initialization(): + """Test initialization with custom base URL.""" + custom_url = "https://custom-api.example.com" + client = ModelClient(base_url=custom_url) + assert client.base_url == custom_url + + +def test_unsupported_provider_initialization(): + """Test initialization with unsupported provider.""" + with pytest.raises(ValueError, match="is not a valid ModelProvider"): + ModelClient(provider=ModelProvider("unsupported")) + + +def test_missing_api_key_initialization(): + """Test initialization without required API key.""" + with patch.dict(os.environ, {}, clear=True): + with pytest.raises(ValueError, match="API key is required"): + ModelClient() + + +# Message Creation Tests +def test_create_message(): + """Test message creation with different roles.""" + client = ModelClient() + message = client.create_message("user", "Hello") + assert message == {"role": "user", "content": "Hello"} + + +# Generation Tests +@pytest.mark.asyncio +async def test_generate_anthropic(mock_anthropic_client, mock_anthropic_response): + """Test generation with Anthropic provider.""" + mock_anthropic_client.messages.create.return_value = mock_anthropic_response + + client = ModelClient(provider=ModelProvider.ANTHROPIC) + messages = [{"role": "user", "content": "Hello"}] + response = await client.generate(messages) + assert response == "Test response" + + # Verify the API call + mock_anthropic_client.messages.create.assert_called_once() + call_args = mock_anthropic_client.messages.create.call_args[1] + assert call_args["model"] == DEFAULT_MODELS[ModelProvider.ANTHROPIC] + assert call_args["messages"] == messages + assert call_args["max_tokens"] == DEFAULT_MAX_TOKENS + assert call_args["temperature"] == DEFAULT_TEMPERATURE + + +@pytest.mark.asyncio +async def test_generate_openai(mock_openai_client, mock_openai_response, mock_env): + """Test generation with OpenAI provider.""" + mock_openai_client.chat.completions.create.return_value = mock_openai_response + + client = ModelClient(provider=ModelProvider.OPENAI) + messages = [{"role": "user", "content": "Hello"}] + response = await client.generate(messages) + assert response == "Test response" + + # Verify the API call + mock_openai_client.chat.completions.create.assert_called_once() + call_args = mock_openai_client.chat.completions.create.call_args[1] + assert call_args["model"] == DEFAULT_MODELS[ModelProvider.OPENAI] + assert call_args["messages"] == messages + assert call_args["max_tokens"] == DEFAULT_MAX_TOKENS + assert call_args["temperature"] == DEFAULT_TEMPERATURE + + +@pytest.mark.asyncio +async def test_generate_with_system_prompt( + mock_anthropic_client, mock_anthropic_response +): + """Test generation with system prompt.""" + mock_anthropic_client.messages.create.return_value = mock_anthropic_response + + client = ModelClient(provider=ModelProvider.ANTHROPIC) + messages = [{"role": "user", "content": "Hello"}] + system = "You are a helpful assistant" + response = await client.generate(messages, system=system) + assert response == "Test response" + + # Verify the API call + mock_anthropic_client.messages.create.assert_called_once() + call_args = mock_anthropic_client.messages.create.call_args[1] + assert call_args["system"] == system + + +@pytest.mark.asyncio +async def test_generate_with_caching(mock_anthropic_client, mock_anthropic_response): + """Test generation with caching enabled.""" + mock_anthropic_client.messages.create.return_value = mock_anthropic_response + + client = ModelClient(provider=ModelProvider.ANTHROPIC) + messages = [{"role": "user", "content": "Hello"}] + system = "You are a helpful assistant" + response = await client.generate(messages, system=system, use_caching=True) + assert response == "Test response" + + # Verify the API call + mock_anthropic_client.messages.create.assert_called_once() + call_args = mock_anthropic_client.messages.create.call_args[1] + assert call_args["system"] == [ + {"type": "text", "text": system, "cache_control": {"type": "ephemeral"}} + ] diff --git a/uv.lock b/uv.lock index 3942c233..224ba0e7 100644 --- a/uv.lock +++ b/uv.lock @@ -1,18 +1,23 @@ version = 1 +revision = 1 requires-python = ">=3.9" +resolution-markers = [ + "python_full_version >= '3.10'", + "python_full_version < '3.10'", +] [[package]] name = "alembic" -version = "1.14.0" +version = "1.15.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "mako" }, { name = "sqlalchemy" }, { name = "typing-extensions" }, ] -sdist = { 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