[0.0.7] — 2024-04-01 (#50)
* 🧪 asyncify tests * ✨ asyncify client * Basic Test for Page based pagination * add sync buildstep and client * add vscode DX * Added Testing for generators and updated examples * feat: example updates * readme exists now * Stylistic changes and generic message * Metamessages with other refactoring - untested * Work with unit tests * Fix Examples * MEME-78 Update Changelogs * Docstrings to client * 🧪 autogenerate sync tests * test one * add db type * sync client * add status badge * add coverage * add file * give perms * properly output coverage * split test and coverage * rename action * 🧪 autogenerate sync tests (#16) * Vector Support (#18) * Scaffold for PGVector support * Buggy crud with logic skeleton on api * Crud logic and schema definition for pgvector * Populate all routes and refactor to name Collection * vince's progress * AsyncCollection progress * Local PGVector Docker Container * client methods for sdk except document delete and update * Vector Support Passing All Test Cases * Docs Updates --------- Co-authored-by: vintro <vince@plasticlabs.ai> * Add reverse parameters for paginated routes * Address dependabot * Formatting * initial commit on honcho dspy personas * working, hit token limit and can't test dspy optimization * initial version working, need to test optimization * optimizers working, but appending any example * ready for user object (tbomk) * Revert "add test actions and coverage" * Refactor to add User and App Tables * User Object passing test cases * Update examples * DSPy Todo and documentation updates * Add is_active filtering * Add is_active filtering to the generator * Fix update user metadata * working, but weird compiler error * fixed str error in optimizer * ship * sentry * Open Telemetry * optional logging with environment variables * add actions again? (#29) * add postgres * add openai key * readd coverage * desyncify and add detailed coverage * ⚙️ chore: update start script in VS Code to include poetry install --no-root before running uvicorn (#33) * Refactored code but need to tweak asyncpg * Working Async API using Psycopg3 * Update Workflow Connection URI * Update Workflow Connection URI in coverage test as well * Skeleton for Dialectic API * Fixes DEV-217 URL Encoding * Add Built-in Langchain Utility function * Sphinx Docs MVP * Metadata filtering for all fixes dev-261 * Basic Dialectic Endpoint fixes dev-253 * Working Fact Deriver * 0.0.5 Docs and README updates * Cloudflare Sphinx * update example to use right function (#36) * 🚀 feat: add support for running API using docker-compose with configurable environment variables and update docker-compose.yml for API and database services. (#34) Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com> * add interrogate * routerify everything * full docstring coverage * remove unused imports and fix env issue * Update docker-compose connection uri and remove auto-stop to deriver process * Docstrings and langchain message converter in reverse * Sentry, OTEL, langchain both directions, fly.toml for deriver * Rename to deriver * Fix favicon and remove metadata from schema * 0.0.6 Notes * Changelog edit * Route bug fix * Route bug fix again * Langchain Utilities Refactor (#48) * [0.0.6] - 3-21-2024 Bug Fixes (#47) * 🧪 asyncify tests * ✨ asyncify client * Basic Test for Page based pagination * add sync buildstep and client * add vscode DX * Added Testing for generators and updated examples * feat: example updates * readme exists now * Stylistic changes and generic message * Metamessages with other refactoring - untested * Work with unit tests * Fix Examples * MEME-78 Update Changelogs * Docstrings to client * 🧪 autogenerate sync tests * test one * add db type * sync client * add status badge * add coverage * add file * give perms * properly output coverage * split test and coverage * rename action * 🧪 autogenerate sync tests (#16) * Vector Support (#18) * Scaffold for PGVector support * Buggy crud with logic skeleton on api * Crud logic and schema definition for pgvector * Populate all routes and refactor to name Collection * vince's progress * AsyncCollection progress * Local PGVector Docker Container * client methods for sdk except document delete and update * Vector Support Passing All Test Cases * Docs Updates --------- Co-authored-by: vintro <vince@plasticlabs.ai> * Add reverse parameters for paginated routes * Address dependabot * Formatting * initial commit on honcho dspy personas * working, hit token limit and can't test dspy optimization * initial version working, need to test optimization * optimizers working, but appending any example * ready for user object (tbomk) * Revert "add test actions and coverage" * Refactor to add User and App Tables * User Object passing test cases * Update examples * DSPy Todo and documentation updates * Add is_active filtering * Add is_active filtering to the generator * Fix update user metadata * working, but weird compiler error * fixed str error in optimizer * ship * sentry * Open Telemetry * optional logging with environment variables * add actions again? (#29) * add postgres * add openai key * readd coverage * desyncify and add detailed coverage * ⚙️ chore: update start script in VS Code to include poetry install --no-root before running uvicorn (#33) * Refactored code but need to tweak asyncpg * Working Async API using Psycopg3 * Update Workflow Connection URI * Update Workflow Connection URI in coverage test as well * Skeleton for Dialectic API * Fixes DEV-217 URL Encoding * Add Built-in Langchain Utility function * Sphinx Docs MVP * Metadata filtering for all fixes dev-261 * Basic Dialectic Endpoint fixes dev-253 * Working Fact Deriver * 0.0.5 Docs and README updates * Cloudflare Sphinx * update example to use right function (#36) * 🚀 feat: add support for running API using docker-compose with configurable environment variables and update docker-compose.yml for API and database services. (#34) Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com> * add interrogate * routerify everything * full docstring coverage * remove unused imports and fix env issue * Update docker-compose connection uri and remove auto-stop to deriver process * Docstrings and langchain message converter in reverse * Sentry, OTEL, langchain both directions, fly.toml for deriver * Rename to deriver * Fix favicon and remove metadata from schema * 0.0.6 Notes * Changelog edit * Route bug fix * Route bug fix again --------- Co-authored-by: hyusap <paulayush@gmail.com> Co-authored-by: vintro <vince@plasticlabs.ai> Co-authored-by: vintro <77507980+vintrocode@users.noreply.github.com> * Port Docs * Update Examples with new langchain utilites * Rename decorator * Synchronize * Fix API SessionLocal --------- Co-authored-by: hyusap <paulayush@gmail.com> Co-authored-by: vintro <vince@plasticlabs.ai> Co-authored-by: vintro <77507980+vintrocode@users.noreply.github.com> * Basic Auth Header validation * Basic Auth Service * Deriver reliability and default auth revoke * .env.template * 0.0.7 Updates --------- Co-authored-by: hyusap <paulayush@gmail.com> Co-authored-by: vintro <vince@plasticlabs.ai> Co-authored-by: vintro <77507980+vintrocode@users.noreply.github.com>
This commit is contained in:
Vineeth Voruganti
GitHub
parent
29cd37bc90
commit
179ee31b25
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@ -168,3 +168,5 @@ cython_debug/
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.DS_Store
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supabase/
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docs/node_modules
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38
README.md
38
README.md
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@ -1,10 +1,12 @@
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# 🫡 Honcho
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[](https://discord.gg/plasticlabs)
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[](https://twitter.com/plastic_labs)
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Honcho is a platform for making AI agents and LLM powered applications that are personalized
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to their end users.
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Honcho is a platform for making AI agents and LLM powered applications that are personalized
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to their end users.
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@ -25,6 +27,19 @@ Read the user documenation [here](https://docs.honcho.dev)
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- [Contributing](#contributing)
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- [License](#license)
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## Table of Contents
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- [Project Structure](#project-structure)
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- [Usage](#usage)
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- [API](#api)
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- [Docker](#docker)
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- [Manually](#manually)
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- [Deploying on Fly.io](#deploy-on-fly)
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- [Client SDK](#client-sdk)
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- [Use Locally](#use-locally)
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- [Contributing](#contributing)
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- [License](#license)
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## Project Structure
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The Honcho repo is a monorepo containing the server/API that manages database
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@ -61,6 +76,19 @@ docker compose up -d
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#### Manually
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#### Docker
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The API can be run using docker-compose. The `docker-compose.yml.example` file can be copied to `docker-compose.yml` and the environment variables can be set in the `.env` file.
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```bash
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cd honcho/api
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cp docker-compose.yml.example docker-compose.yml
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[ update the file with openai key and other wanted environment variables ]
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docker compose up -d
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```
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#### Manually
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The API can be run either by installing the necessary dependencies and then
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specifying the appropriate environment variables.
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@ -75,6 +103,7 @@ poetry install # install dependencies
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2. Copy the `.env.template` file and specify the type of database and
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connection_uri. For testing sqlite is fine. The below example uses an
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in-memory sqlite database.
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in-memory sqlite database.
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> Honcho has been tested with Postgresql and PGVector
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@ -103,6 +132,7 @@ python -m uvicorn src.main:app --reload
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The API can also be deployed on fly.io. Follow the [Fly.io
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Docs](https://fly.io/docs/getting-started/) to setup your environment and the
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`flyctl`.
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`flyctl`.
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Once `flyctl` is set up use the following commands to launch the application:
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@ -130,6 +160,10 @@ poetry add honcho-ai
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checkout the [SDK Reference](https://api.python.honcho.dev) for a detailed
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look at the different methods and how to use them.
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Also, check out the[example folder](./example/) for examples of how to use the sdk
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checkout the [SDK Reference](https://api.python.honcho.dev) for a detailed
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look at the different methods and how to use them.
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Also, check out the[example folder](./example/) for examples of how to use the sdk
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#### Use Locally
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@ -149,11 +183,13 @@ This project is completely open source and welcomes any and all open source
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contributions. The workflow for contributing is to make a fork of the
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repository. You can claim an issue in the issues tab or start a new thread to
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indicate a feature or bug fix you are working on.
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indicate a feature or bug fix you are working on.
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Once you have finished your contribution make a PR pointed at the `staging`
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branch, and it will be reviewed by a project manager. Feel free to join us in
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our [discord](http://discord.gg/plasticlabs) to discuss your changes or get
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help.
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help.
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Once your changes are accepted and merged into staging they will undergo a
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period of live testing before entering the upstream into `main`
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@ -8,6 +8,11 @@ OPENAI_API_KEY=
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OPENTELEMETRY_ENABLED=false # Set to true to enable OpenTelemetry logging and tracing
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SENTRY_ENABLED=false # Set to true to enable Sentry logging and tracing
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# Auth
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USE_AUTH_SERVICE=false
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AUTH_SERVICE_URL=http://localhost:8001
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## Sentry
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SENTRY_DSN=
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@ -4,6 +4,12 @@ All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](http://keepachangelog.com/)
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and this project adheres to [Semantic Versioning](http://semver.org/).
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## [0.0.7] — 2024-04-01
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### Added
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* Authentication Middleware Interface
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## [0.0.6] — 2024-03-21
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### Added
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@ -25,6 +25,7 @@ services:
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- OTEL_RESOURCE_ATTRIBUTES=
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- DEBUG_LOG_OTEL_TO_PROVIDER=false
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- DEBUG_LOG_OTEL_TO_CONSOLE=true
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- USE_AUTH_SERVICE=false
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database:
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image: ankane/pgvector
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restart: always
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15
api/fly.toml
15
api/fly.toml
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@ -7,25 +7,10 @@ app = "honcho"
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kill_signal = "SIGINT"
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kill_timeout = "5s"
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[experimental]
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auto_rollback = true
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[build]
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[processes]
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api = "python -m uvicorn src.main:app --host 0.0.0.0 --port 8000"
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deriver = "python -m src.deriver"
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[[services]]
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auto_stop_machines = false
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auto_start_machines = true
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min_machines_running = 1
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processes = ["deriver"]
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protocol = "tcp"
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[services.concurrency]
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hard_limit = 250
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soft_limit = 200
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[http_service]
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internal_port = 8000
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auto_stop_machines = false
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@ -2696,4 +2696,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
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[metadata]
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lock-version = "2.0"
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python-versions = "^3.8.1"
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content-hash = "aa7928d0a259d20dd9805ab5b159eebb293eac0b2e46a40d5df55f797222a8f3"
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content-hash = "d2b0e968cff39082c16334498a3571c90b10fec28268f89821f13e2764990393"
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|
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "honcho"
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version = "0.0.6"
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version = "0.0.7"
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description = "Honcho Server"
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authors = ["Plastic Labs <hello@plasticlabs.ai>"]
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readme = "README.md"
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@ -27,6 +27,7 @@ realtime = "^1.0.2"
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psycopg = {extras = ["binary"], version = "^3.1.18"}
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langchain = "^0.1.12"
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langchain-openai = "^0.0.8"
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httpx = "^0.27.0"
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[tool.ruff.lint]
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# from https://docs.astral.sh/ruff/linter/#rule-selection example
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@ -23,8 +23,8 @@ Base = declarative_base()
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def scaffold_db():
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"""Use a Sync Engine for scaffolding the database. DDL operations are unavailable
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with Async Engines
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"""use a sync engine for scaffolding the database. ddl operations are unavailable
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with async engines
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"""
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engine = create_engine(os.environ["CONNECTION_URI"], echo=True)
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Base.metadata.create_all(bind=engine)
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@ -1,7 +1,8 @@
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from fastapi import Depends
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from .db import SessionLocal
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from sqlalchemy.ext.asyncio import AsyncSession
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from .db import SessionLocal
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async def get_db():
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"""FastAPI Dependency Generator for Database"""
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@ -1,5 +1,6 @@
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import asyncio
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import os
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import time
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import uuid
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from typing import List
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@ -15,6 +16,7 @@ from langchain_openai import ChatOpenAI
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from realtime.connection import Socket
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from sqlalchemy import select
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from sqlalchemy.orm import selectinload
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from websockets.exceptions import ConnectionClosedError
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from . import crud, models, schemas
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from .db import SessionLocal
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@ -32,7 +34,7 @@ if SENTRY_ENABLED:
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SUPABASE_ID = os.getenv("SUPABASE_ID")
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SUPABASE_API_KEY = os.getenv("SUPABASE_API_KEY")
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llm = ChatOpenAI(model_name="gpt-4")
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llm = ChatOpenAI(model_name="gpt-3.5")
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output_parser = NumberedListOutputParser()
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SYSTEM_DERIVE_FACTS = load_prompt(
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@ -200,9 +202,26 @@ async def check_dups(
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return new_facts
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# def listen_to_websocket(url):
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# while True:
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# try:
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# s = Socket(url)
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# s.connect()
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# channel = s.set_channel("realtime:public:messages")
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# channel.join().on(
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# "INSERT", lambda payload: asyncio.create_task(callback(payload))
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# )
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# s.listen()
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# except ConnectionClosedError:
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# print("Connection closed, attempting to reconnect...")
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# time.sleep(5)
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if __name__ == "__main__":
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URL = f"wss://{SUPABASE_ID}.supabase.co/realtime/v1/websocket?apikey={SUPABASE_API_KEY}&vsn=1.0.0"
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# URL = f"ws://127.0.0.1:54321/realtime/v1/websocket?apikey={SUPABASE_API_KEY}" # For local Supabase
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# listen_to_websocket(URL)
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s = Socket(URL)
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s.connect()
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@ -1,203 +0,0 @@
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import asyncio
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import os
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import uuid
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from typing import List
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from dotenv import load_dotenv
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from langchain_core.output_parsers import NumberedListOutputParser
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from langchain_core.prompts import (
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ChatPromptTemplate,
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SystemMessagePromptTemplate,
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load_prompt,
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)
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from langchain_openai import ChatOpenAI
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from realtime.connection import Socket
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from sqlalchemy import select
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from sqlalchemy.orm import selectinload
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from . import crud, models, schemas
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from .db import SessionLocal
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load_dotenv()
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SUPABASE_ID = os.getenv("SUPABASE_ID")
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SUPABASE_API_KEY = os.getenv("SUPABASE_API_KEY")
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llm = ChatOpenAI(model_name="gpt-4")
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output_parser = NumberedListOutputParser()
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SYSTEM_DERIVE_FACTS = load_prompt(
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os.path.join(os.path.dirname(__file__), "prompts/derive_facts.yaml")
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)
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SYSTEM_CHECK_DUPS = load_prompt(
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os.path.join(os.path.dirname(__file__), "prompts/check_dup_facts.yaml")
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)
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system_check_dups: SystemMessagePromptTemplate = SystemMessagePromptTemplate(
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prompt=SYSTEM_CHECK_DUPS
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)
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system_derive_facts: SystemMessagePromptTemplate = SystemMessagePromptTemplate(
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prompt=SYSTEM_DERIVE_FACTS
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)
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async def callback(payload):
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# print(payload["record"]["is_user"])
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# print(type(payload["record"]["is_user"]))
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if payload["record"]["is_user"]: # Check if the message is from a user
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session_id = payload["record"]["session_id"]
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message_id = payload["record"]["id"]
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content = payload["record"]["content"]
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# Example of querying for a user_id based on session_id, adjust according to your schema
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session: models.Session
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user_id: uuid.UUID
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app_id: uuid.UUID
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async with SessionLocal() as db:
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stmt = (
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select(models.Session)
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.join(models.Session.messages)
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.where(models.Message.id == message_id)
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.where(models.Session.id == session_id)
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.options(selectinload(models.Session.user))
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)
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result = await db.execute(stmt)
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session = result.scalars().one()
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user = session.user
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user_id = user.id
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app_id = user.app_id
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collection: models.Collection
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async with SessionLocal() as db:
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collection = await crud.get_collection_by_name(
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db, app_id, user_id, "honcho"
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)
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if collection is None:
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collection_create = schemas.CollectionCreate(name="honcho", metadata={})
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collection = await crud.create_collection(
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db,
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collection=collection_create,
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app_id=app_id,
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user_id=user_id,
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)
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collection_id = collection.id
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await process_user_message(
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content, app_id, user_id, session_id, collection_id, message_id
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)
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return
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async def process_user_message(
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content: str,
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app_id: uuid.UUID,
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user_id: uuid.UUID,
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session_id: uuid.UUID,
|
||||
collection_id: uuid.UUID,
|
||||
message_id: uuid.UUID,
|
||||
):
|
||||
# TODO get messages for the session
|
||||
async with SessionLocal() as db:
|
||||
messages_stmt = await crud.get_messages(
|
||||
db=db, app_id=app_id, user_id=user_id, session_id=session_id, reverse=True
|
||||
)
|
||||
messages_stmt = messages_stmt.limit(10)
|
||||
response = await db.execute(messages_stmt)
|
||||
messages = response.scalars().all()
|
||||
messages = messages[::-1]
|
||||
contents = [m.content for m in messages]
|
||||
# print(contents)
|
||||
|
||||
facts = await derive_facts(messages, content)
|
||||
print("===================")
|
||||
print(f"DERIVED FACTS: {facts}")
|
||||
print("===================")
|
||||
new_facts = await check_dups(app_id, user_id, collection_id, facts)
|
||||
|
||||
print("===================")
|
||||
print(f"CHECKED FOR DUPLICATES: {new_facts}")
|
||||
print("===================")
|
||||
|
||||
for fact in new_facts:
|
||||
create_document = schemas.DocumentCreate(content=fact)
|
||||
async with SessionLocal() as db:
|
||||
doc = await crud.create_document(
|
||||
db,
|
||||
document=create_document,
|
||||
app_id=app_id,
|
||||
user_id=user_id,
|
||||
collection_id=collection_id,
|
||||
)
|
||||
print(f"Returned Document: {doc}")
|
||||
# doc = crud.create_document(content=fact)
|
||||
# for fact in new_facts:
|
||||
# session.create_metamessage(
|
||||
# message=user_message, metamessage_type="fact", content=fact
|
||||
# )
|
||||
# print(f"Created fact: {fact}")
|
||||
|
||||
|
||||
async def derive_facts(chat_history, input: str) -> List[str]:
|
||||
"""Derive facts from the user input"""
|
||||
|
||||
fact_derivation = ChatPromptTemplate.from_messages([system_derive_facts])
|
||||
chain = fact_derivation | llm
|
||||
response = await chain.ainvoke(
|
||||
{
|
||||
"chat_history": [
|
||||
(
|
||||
"user: " + message.content
|
||||
if message.is_user
|
||||
else "ai: " + message.content
|
||||
)
|
||||
for message in chat_history
|
||||
],
|
||||
"user_input": input,
|
||||
}
|
||||
)
|
||||
facts = output_parser.parse(response.content)
|
||||
|
||||
return facts
|
||||
|
||||
|
||||
async def check_dups(
|
||||
app_id: uuid.UUID, user_id: uuid.UUID, collection_id: uuid.UUID, facts: List[str]
|
||||
):
|
||||
"""Check that we're not storing duplicate facts"""
|
||||
|
||||
check_duplication = ChatPromptTemplate.from_messages([system_check_dups])
|
||||
query = " ".join(facts)
|
||||
result = None
|
||||
async with SessionLocal() as db:
|
||||
result = await crud.query_documents(
|
||||
db=db,
|
||||
app_id=app_id,
|
||||
user_id=user_id,
|
||||
collection_id=collection_id,
|
||||
query=query,
|
||||
top_k=10,
|
||||
)
|
||||
# result = collection.query(query=query, top_k=10)
|
||||
existing_facts = [document.content for document in result]
|
||||
print("===================")
|
||||
print(f"Existing Facts {existing_facts}")
|
||||
print("===================")
|
||||
if len(existing_facts) == 0:
|
||||
return facts
|
||||
chain = check_duplication | llm
|
||||
response = await chain.ainvoke({"existing_facts": existing_facts, "facts": facts})
|
||||
new_facts = output_parser.parse(response.content)
|
||||
print("===================")
|
||||
print(f"New Facts {facts}")
|
||||
print("===================")
|
||||
return new_facts
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
URL = f"wss://{SUPABASE_ID}.supabase.co/realtime/v1/websocket?apikey={SUPABASE_API_KEY}&vsn=1.0.0"
|
||||
# URL = f"ws://127.0.0.1:54321/realtime/v1/websocket?apikey={SUPABASE_API_KEY}" # For local Supabase
|
||||
s = Socket(URL)
|
||||
s.connect()
|
||||
|
||||
channel = s.set_channel("realtime:public:messages")
|
||||
channel.join().on("INSERT", lambda payload: asyncio.create_task(callback(payload)))
|
||||
s.listen()
|
||||
|
|
@ -1,14 +1,17 @@
|
|||
import json
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
import uuid
|
||||
from contextlib import asynccontextmanager
|
||||
from typing import Optional, Sequence
|
||||
|
||||
import httpx
|
||||
import sentry_sdk
|
||||
from fastapi import (
|
||||
APIRouter,
|
||||
FastAPI,
|
||||
Request,
|
||||
)
|
||||
from fastapi.responses import PlainTextResponse
|
||||
from fastapi_pagination import add_pagination
|
||||
|
|
@ -43,6 +46,8 @@ from slowapi.errors import RateLimitExceeded
|
|||
from slowapi.middleware import SlowAPIMiddleware
|
||||
from slowapi.util import get_remote_address
|
||||
from starlette.exceptions import HTTPException as StarletteHTTPException
|
||||
from starlette.middleware.base import BaseHTTPMiddleware
|
||||
from starlette.responses import Response
|
||||
|
||||
from src.routers import (
|
||||
apps,
|
||||
|
|
@ -216,6 +221,56 @@ app.add_middleware(SlowAPIMiddleware)
|
|||
|
||||
add_pagination(app)
|
||||
|
||||
USE_AUTH_SERVICE = os.getenv("USE_AUTH_SERVICE", "False").lower() == "true"
|
||||
AUTH_SERVICE_URL = os.getenv("AUTH_SERVICE_URL", "http://localhost:8001")
|
||||
|
||||
|
||||
class BearerTokenMiddleware(BaseHTTPMiddleware):
|
||||
async def dispatch(self, request: Request, call_next):
|
||||
authorization: Optional[str] = request.headers.get("Authorization")
|
||||
if authorization:
|
||||
scheme, _, token = authorization.partition(" ")
|
||||
if scheme.lower() == "bearer" and token:
|
||||
id_pattern = r"\/apps\/([^\/]+)"
|
||||
name_pattern = r"\/apps\/name\/([^\/]+)|\/apps\/get_or_create\/([^\/]+)"
|
||||
match_id = re.search(id_pattern, request.url.path)
|
||||
match_name = re.search(name_pattern, request.url.path)
|
||||
payload = {"token": token}
|
||||
if match_name:
|
||||
payload["name"] = match_name.group(1)
|
||||
elif match_id:
|
||||
payload["app_id"] = match_id.group(1)
|
||||
|
||||
res = httpx.get(
|
||||
f"{AUTH_SERVICE_URL}/validate",
|
||||
params=payload,
|
||||
)
|
||||
data = res.json()
|
||||
if (
|
||||
data["app_id"] or data["name"]
|
||||
): # Anything that checks app_id if True is valid
|
||||
return await call_next(request)
|
||||
if data["token"]:
|
||||
check_pattern = r"^\/apps$|^\/apps\/get_or_create"
|
||||
match = re.search(check_pattern, request.url.path)
|
||||
if match:
|
||||
return await call_next(request)
|
||||
|
||||
return Response(content="Invalid token.", status_code=400)
|
||||
else:
|
||||
return Response(
|
||||
content="Invalid authentication scheme.", status_code=400
|
||||
)
|
||||
|
||||
exclude_paths = ["/docs", "/redoc", "/openapi.json"]
|
||||
if request.url.path in exclude_paths:
|
||||
return await call_next(request)
|
||||
return Response(content="Authorization header missing.", status_code=401)
|
||||
|
||||
|
||||
if USE_AUTH_SERVICE:
|
||||
app.add_middleware(BearerTokenMiddleware)
|
||||
|
||||
|
||||
@app.exception_handler(StarletteHTTPException)
|
||||
async def http_exception_handler(request, exc):
|
||||
|
|
|
|||
|
|
@ -1,5 +1,8 @@
|
|||
import os
|
||||
import uuid
|
||||
from typing import Optional
|
||||
|
||||
import httpx
|
||||
from fastapi import APIRouter, HTTPException, Request
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
|
|
@ -57,8 +60,30 @@ async def create_app(request: Request, app: schemas.AppCreate, db=db):
|
|||
schemas.App: Created App object
|
||||
|
||||
"""
|
||||
|
||||
return await crud.create_app(db, app=app)
|
||||
USE_AUTH_SERVICE = os.getenv("USE_AUTH_SERVICE", "False").lower() == "true"
|
||||
if USE_AUTH_SERVICE:
|
||||
AUTH_SERVICE_URL = os.getenv("AUTH_SERVICE_URL", "http://localhost:8001")
|
||||
authorization: Optional[str] = request.headers.get("Authorization")
|
||||
if authorization:
|
||||
scheme, _, token = authorization.partition(" ")
|
||||
if token is not None:
|
||||
honcho_app = await crud.create_app(db, app=app)
|
||||
# if token == "default":
|
||||
# return honcho_app
|
||||
res = httpx.put(
|
||||
f"{AUTH_SERVICE_URL}/organizations",
|
||||
json={
|
||||
"id": str(honcho_app.id),
|
||||
"name": honcho_app.name,
|
||||
"token": token,
|
||||
},
|
||||
)
|
||||
data = res.json()
|
||||
if data:
|
||||
return honcho_app
|
||||
else:
|
||||
honcho_app = await crud.create_app(db, app=app)
|
||||
return honcho_app
|
||||
|
||||
|
||||
@router.get("/get_or_create/{name}", response_model=schemas.App)
|
||||
|
|
@ -73,9 +98,9 @@ async def get_or_create_app(request: Request, name: str, db=db):
|
|||
|
||||
"""
|
||||
print("name", name)
|
||||
app = await crud.get_app_by_name(db, name=name)
|
||||
app = await crud.get_app_by_name(db=db, name=name)
|
||||
if app is None:
|
||||
app = await crud.create_app(db, app=schemas.AppCreate(name=name))
|
||||
app = await create_app(request=request, db=db, app=schemas.AppCreate(name=name))
|
||||
return app
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,43 @@
|
|||
# honcho-docs
|
||||
|
||||
## Setting Up `honcho-docs` Locally
|
||||
|
||||
1. Clone the repository:
|
||||
```
|
||||
git clone git@github.com:plastic-labs/honcho-docs.git
|
||||
```
|
||||
|
||||
2. Navigate into the `honcho-docs` folder:
|
||||
```
|
||||
cd honcho-docs/
|
||||
```
|
||||
The docs folder contains the markdown files that make up the documentation. The majority of the files are in the pages directory. Some notable files in this folder include:
|
||||
|
||||
`index.mdx`: The main documentation file.
|
||||
`_app.js`: This file is used to customize the default Next.js application shell.
|
||||
`theme.config.jsx`: This file is for configuring the Nextra theme for the documentation.
|
||||
|
||||
3. Verify that you have Node.js and npm installed in your system. You can check by running:
|
||||
```
|
||||
node --version
|
||||
npm --version
|
||||
```
|
||||
|
||||
4. If not installed, download Node.js and npm from the respective official websites.
|
||||
|
||||
5. Once you have Node.js and npm running, proceed to install `pnpm` - another package manager that helps to manage project dependencies:
|
||||
```
|
||||
npm install -g pnpm
|
||||
```
|
||||
|
||||
6. Install the project dependencies using yarn:
|
||||
```
|
||||
pnpm i
|
||||
```
|
||||
|
||||
7. After the successful installation of the project dependencies, start the local server:
|
||||
```
|
||||
pnpm dev
|
||||
```
|
||||
|
||||
Now, you should be able to view the docs on your local environment by visiting `http://localhost:3000`. You can explore the different markdown files and make changes as you see fit.
|
||||
|
|
@ -0,0 +1,63 @@
|
|||
<div
|
||||
style={{
|
||||
display: "flex"
|
||||
}}
|
||||
class="justify-center"
|
||||
>
|
||||
<a
|
||||
style={{
|
||||
borderStyle: "none",
|
||||
marginTop: "0.125rem",
|
||||
marginBottom: "0.125rem",
|
||||
}}
|
||||
href="https://pypi.org/project/honcho-ai/"
|
||||
>
|
||||
<img
|
||||
style={{
|
||||
margin: 0,
|
||||
cursor: "pointer",
|
||||
}}
|
||||
noZoom
|
||||
src="https://img.shields.io/pypi/v/honcho-ai?color=orange"
|
||||
alt="Python package version"
|
||||
/>
|
||||
</a>
|
||||
<a
|
||||
style={{
|
||||
borderStyle: "none",
|
||||
marginTop: "0.125rem",
|
||||
marginBottom: "0.125rem",
|
||||
marginLeft: "0.25rem",
|
||||
}}
|
||||
href="https://github.com/plastic-labs/honcho"
|
||||
>
|
||||
<img
|
||||
style={{
|
||||
margin: 0,
|
||||
cursor: "pointer",
|
||||
}}
|
||||
noZoom
|
||||
src="https://img.shields.io/github/stars/plastic-labs/honcho?logo=github"
|
||||
alt="GitHub Stars"
|
||||
/>
|
||||
</a>
|
||||
<a
|
||||
style={{
|
||||
borderStyle: "none",
|
||||
marginTop: "0.125rem",
|
||||
marginBottom: "0.125rem",
|
||||
marginLeft: "0.25rem",
|
||||
}}
|
||||
href="https://pepy.tech/project/honcho-ai"
|
||||
>
|
||||
<img
|
||||
style={{
|
||||
margin: 0,
|
||||
cursor: "pointer",
|
||||
}}
|
||||
noZoom
|
||||
src="https://static.pepy.tech/personalized-badge/honcho-ai?period=total&units=international_system&left_color=grey&right_color=blue&left_text=pip%20installs"
|
||||
alt="pip installs"
|
||||
/>
|
||||
</a>
|
||||
</div>
|
||||
|
|
@ -0,0 +1,18 @@
|
|||
---
|
||||
title: 'Contributing'
|
||||
description: 'Guidelines for contributing to the Honcho Project'
|
||||
icon: 'handshake-angle'
|
||||
---
|
||||
|
||||
This project is completely open source and welcomes any and all open source
|
||||
contributions. The workflow for contributing is to make a fork of the
|
||||
repository. You can claim an issue in the issues tab or start a new thread to
|
||||
indicate a feature or bug fix you are working on.
|
||||
|
||||
Once you have finished your contribution make a PR pointed at the `staging`
|
||||
branch, and it will be reviewed by a project manager. Feel free to join us in
|
||||
our [discord](http://discord.gg/plasticlabs) to discuss your changes or get
|
||||
help.
|
||||
|
||||
Once your changes are accepted and merged into staging they will undergo a
|
||||
period of live testing before entering the upstream into `main`
|
||||
|
|
@ -0,0 +1,671 @@
|
|||
---
|
||||
title: 'License'
|
||||
icon: 'scroll'
|
||||
---
|
||||
|
||||
Honcho is licensed under the AGPL-3.0 License. This is copied below for convenience and also present in the
|
||||
[GitHub Repository](https://github.com/plastic-labs/honcho)
|
||||
|
||||
```
|
||||
GNU AFFERO GENERAL PUBLIC LICENSE
|
||||
Version 3, 19 November 2007
|
||||
|
||||
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
|
||||
Everyone is permitted to copy and distribute verbatim copies
|
||||
of this license document, but changing it is not allowed.
|
||||
|
||||
Preamble
|
||||
|
||||
The GNU Affero General Public License is a free, copyleft license for
|
||||
software and other kinds of works, specifically designed to ensure
|
||||
cooperation with the community in the case of network server software.
|
||||
|
||||
The licenses for most software and other practical works are designed
|
||||
to take away your freedom to share and change the works. By contrast,
|
||||
our General Public Licenses are intended to guarantee your freedom to
|
||||
share and change all versions of a program--to make sure it remains free
|
||||
software for all its users.
|
||||
|
||||
When we speak of free software, we are referring to freedom, not
|
||||
price. Our General Public Licenses are designed to make sure that you
|
||||
have the freedom to distribute copies of free software (and charge for
|
||||
them if you wish), that you receive source code or can get it if you
|
||||
want it, that you can change the software or use pieces of it in new
|
||||
free programs, and that you know you can do these things.
|
||||
|
||||
Developers that use our General Public Licenses protect your rights
|
||||
with two steps: (1) assert copyright on the software, and (2) offer
|
||||
you this License which gives you legal permission to copy, distribute
|
||||
and/or modify the software.
|
||||
|
||||
A secondary benefit of defending all users' freedom is that
|
||||
improvements made in alternate versions of the program, if they
|
||||
receive widespread use, become available for other developers to
|
||||
incorporate. Many developers of free software are heartened and
|
||||
encouraged by the resulting cooperation. However, in the case of
|
||||
software used on network servers, this result may fail to come about.
|
||||
The GNU General Public License permits making a modified version and
|
||||
letting the public access it on a server without ever releasing its
|
||||
source code to the public.
|
||||
|
||||
The GNU Affero General Public License is designed specifically to
|
||||
ensure that, in such cases, the modified source code becomes available
|
||||
to the community. It requires the operator of a network server to
|
||||
provide the source code of the modified version running there to the
|
||||
users of that server. Therefore, public use of a modified version, on
|
||||
a publicly accessible server, gives the public access to the source
|
||||
code of the modified version.
|
||||
|
||||
An older license, called the Affero General Public License and
|
||||
published by Affero, was designed to accomplish similar goals. This is
|
||||
a different license, not a version of the Affero GPL, but Affero has
|
||||
released a new version of the Affero GPL which permits relicensing under
|
||||
this license.
|
||||
|
||||
The precise terms and conditions for copying, distribution and
|
||||
modification follow.
|
||||
|
||||
TERMS AND CONDITIONS
|
||||
|
||||
0. Definitions.
|
||||
|
||||
"This License" refers to version 3 of the GNU Affero General Public License.
|
||||
|
||||
"Copyright" also means copyright-like laws that apply to other kinds of
|
||||
works, such as semiconductor masks.
|
||||
|
||||
"The Program" refers to any copyrightable work licensed under this
|
||||
License. Each licensee is addressed as "you". "Licensees" and
|
||||
"recipients" may be individuals or organizations.
|
||||
|
||||
To "modify" a work means to copy from or adapt all or part of the work
|
||||
in a fashion requiring copyright permission, other than the making of an
|
||||
exact copy. The resulting work is called a "modified version" of the
|
||||
earlier work or a work "based on" the earlier work.
|
||||
|
||||
A "covered work" means either the unmodified Program or a work based
|
||||
on the Program.
|
||||
|
||||
To "propagate" a work means to do anything with it that, without
|
||||
permission, would make you directly or secondarily liable for
|
||||
infringement under applicable copyright law, except executing it on a
|
||||
computer or modifying a private copy. Propagation includes copying,
|
||||
distribution (with or without modification), making available to the
|
||||
public, and in some countries other activities as well.
|
||||
|
||||
To "convey" a work means any kind of propagation that enables other
|
||||
parties to make or receive copies. Mere interaction with a user through
|
||||
a computer network, with no transfer of a copy, is not conveying.
|
||||
|
||||
An interactive user interface displays "Appropriate Legal Notices"
|
||||
to the extent that it includes a convenient and prominently visible
|
||||
feature that (1) displays an appropriate copyright notice, and (2)
|
||||
tells the user that there is no warranty for the work (except to the
|
||||
extent that warranties are provided), that licensees may convey the
|
||||
work under this License, and how to view a copy of this License. If
|
||||
the interface presents a list of user commands or options, such as a
|
||||
menu, a prominent item in the list meets this criterion.
|
||||
|
||||
1. Source Code.
|
||||
|
||||
The "source code" for a work means the preferred form of the work
|
||||
for making modifications to it. "Object code" means any non-source
|
||||
form of a work.
|
||||
|
||||
A "Standard Interface" means an interface that either is an official
|
||||
standard defined by a recognized standards body, or, in the case of
|
||||
interfaces specified for a particular programming language, one that
|
||||
is widely used among developers working in that language.
|
||||
|
||||
The "System Libraries" of an executable work include anything, other
|
||||
than the work as a whole, that (a) is included in the normal form of
|
||||
packaging a Major Component, but which is not part of that Major
|
||||
Component, and (b) serves only to enable use of the work with that
|
||||
Major Component, or to implement a Standard Interface for which an
|
||||
implementation is available to the public in source code form. A
|
||||
"Major Component", in this context, means a major essential component
|
||||
(kernel, window system, and so on) of the specific operating system
|
||||
(if any) on which the executable work runs, or a compiler used to
|
||||
produce the work, or an object code interpreter used to run it.
|
||||
|
||||
The "Corresponding Source" for a work in object code form means all
|
||||
the source code needed to generate, install, and (for an executable
|
||||
work) run the object code and to modify the work, including scripts to
|
||||
control those activities. However, it does not include the work's
|
||||
System Libraries, or general-purpose tools or generally available free
|
||||
programs which are used unmodified in performing those activities but
|
||||
which are not part of the work. For example, Corresponding Source
|
||||
includes interface definition files associated with source files for
|
||||
the work, and the source code for shared libraries and dynamically
|
||||
linked subprograms that the work is specifically designed to require,
|
||||
such as by intimate data communication or control flow between those
|
||||
subprograms and other parts of the work.
|
||||
|
||||
The Corresponding Source need not include anything that users
|
||||
can regenerate automatically from other parts of the Corresponding
|
||||
Source.
|
||||
|
||||
The Corresponding Source for a work in source code form is that
|
||||
same work.
|
||||
|
||||
2. Basic Permissions.
|
||||
|
||||
All rights granted under this License are granted for the term of
|
||||
copyright on the Program, and are irrevocable provided the stated
|
||||
conditions are met. This License explicitly affirms your unlimited
|
||||
permission to run the unmodified Program. The output from running a
|
||||
covered work is covered by this License only if the output, given its
|
||||
content, constitutes a covered work. This License acknowledges your
|
||||
rights of fair use or other equivalent, as provided by copyright law.
|
||||
|
||||
You may make, run and propagate covered works that you do not
|
||||
convey, without conditions so long as your license otherwise remains
|
||||
in force. You may convey covered works to others for the sole purpose
|
||||
of having them make modifications exclusively for you, or provide you
|
||||
with facilities for running those works, provided that you comply with
|
||||
the terms of this License in conveying all material for which you do
|
||||
not control copyright. Those thus making or running the covered works
|
||||
for you must do so exclusively on your behalf, under your direction
|
||||
and control, on terms that prohibit them from making any copies of
|
||||
your copyrighted material outside their relationship with you.
|
||||
|
||||
Conveying under any other circumstances is permitted solely under
|
||||
the conditions stated below. Sublicensing is not allowed; section 10
|
||||
makes it unnecessary.
|
||||
|
||||
3. Protecting Users' Legal Rights From Anti-Circumvention Law.
|
||||
|
||||
No covered work shall be deemed part of an effective technological
|
||||
measure under any applicable law fulfilling obligations under article
|
||||
11 of the WIPO copyright treaty adopted on 20 December 1996, or
|
||||
similar laws prohibiting or restricting circumvention of such
|
||||
measures.
|
||||
|
||||
When you convey a covered work, you waive any legal power to forbid
|
||||
circumvention of technological measures to the extent such circumvention
|
||||
is effected by exercising rights under this License with respect to
|
||||
the covered work, and you disclaim any intention to limit operation or
|
||||
modification of the work as a means of enforcing, against the work's
|
||||
users, your or third parties' legal rights to forbid circumvention of
|
||||
technological measures.
|
||||
|
||||
4. Conveying Verbatim Copies.
|
||||
|
||||
You may convey verbatim copies of the Program's source code as you
|
||||
receive it, in any medium, provided that you conspicuously and
|
||||
appropriately publish on each copy an appropriate copyright notice;
|
||||
keep intact all notices stating that this License and any
|
||||
non-permissive terms added in accord with section 7 apply to the code;
|
||||
keep intact all notices of the absence of any warranty; and give all
|
||||
recipients a copy of this License along with the Program.
|
||||
|
||||
You may charge any price or no price for each copy that you convey,
|
||||
and you may offer support or warranty protection for a fee.
|
||||
|
||||
5. Conveying Modified Source Versions.
|
||||
|
||||
You may convey a work based on the Program, or the modifications to
|
||||
produce it from the Program, in the form of source code under the
|
||||
terms of section 4, provided that you also meet all of these conditions:
|
||||
|
||||
a) The work must carry prominent notices stating that you modified
|
||||
it, and giving a relevant date.
|
||||
|
||||
b) The work must carry prominent notices stating that it is
|
||||
released under this License and any conditions added under section
|
||||
7. This requirement modifies the requirement in section 4 to
|
||||
"keep intact all notices".
|
||||
|
||||
c) You must license the entire work, as a whole, under this
|
||||
License to anyone who comes into possession of a copy. This
|
||||
License will therefore apply, along with any applicable section 7
|
||||
additional terms, to the whole of the work, and all its parts,
|
||||
regardless of how they are packaged. This License gives no
|
||||
permission to license the work in any other way, but it does not
|
||||
invalidate such permission if you have separately received it.
|
||||
|
||||
d) If the work has interactive user interfaces, each must display
|
||||
Appropriate Legal Notices; however, if the Program has interactive
|
||||
interfaces that do not display Appropriate Legal Notices, your
|
||||
work need not make them do so.
|
||||
|
||||
A compilation of a covered work with other separate and independent
|
||||
works, which are not by their nature extensions of the covered work,
|
||||
and which are not combined with it such as to form a larger program,
|
||||
in or on a volume of a storage or distribution medium, is called an
|
||||
"aggregate" if the compilation and its resulting copyright are not
|
||||
used to limit the access or legal rights of the compilation's users
|
||||
beyond what the individual works permit. Inclusion of a covered work
|
||||
in an aggregate does not cause this License to apply to the other
|
||||
parts of the aggregate.
|
||||
|
||||
6. Conveying Non-Source Forms.
|
||||
|
||||
You may convey a covered work in object code form under the terms
|
||||
of sections 4 and 5, provided that you also convey the
|
||||
machine-readable Corresponding Source under the terms of this License,
|
||||
in one of these ways:
|
||||
|
||||
a) Convey the object code in, or embodied in, a physical product
|
||||
(including a physical distribution medium), accompanied by the
|
||||
Corresponding Source fixed on a durable physical medium
|
||||
customarily used for software interchange.
|
||||
|
||||
b) Convey the object code in, or embodied in, a physical product
|
||||
(including a physical distribution medium), accompanied by a
|
||||
written offer, valid for at least three years and valid for as
|
||||
long as you offer spare parts or customer support for that product
|
||||
model, to give anyone who possesses the object code either (1) a
|
||||
copy of the Corresponding Source for all the software in the
|
||||
product that is covered by this License, on a durable physical
|
||||
medium customarily used for software interchange, for a price no
|
||||
more than your reasonable cost of physically performing this
|
||||
conveying of source, or (2) access to copy the
|
||||
Corresponding Source from a network server at no charge.
|
||||
|
||||
c) Convey individual copies of the object code with a copy of the
|
||||
written offer to provide the Corresponding Source. This
|
||||
alternative is allowed only occasionally and noncommercially, and
|
||||
only if you received the object code with such an offer, in accord
|
||||
with subsection 6b.
|
||||
|
||||
d) Convey the object code by offering access from a designated
|
||||
place (gratis or for a charge), and offer equivalent access to the
|
||||
Corresponding Source in the same way through the same place at no
|
||||
further charge. You need not require recipients to copy the
|
||||
Corresponding Source along with the object code. If the place to
|
||||
copy the object code is a network server, the Corresponding Source
|
||||
may be on a different server (operated by you or a third party)
|
||||
that supports equivalent copying facilities, provided you maintain
|
||||
clear directions next to the object code saying where to find the
|
||||
Corresponding Source. Regardless of what server hosts the
|
||||
Corresponding Source, you remain obligated to ensure that it is
|
||||
available for as long as needed to satisfy these requirements.
|
||||
|
||||
e) Convey the object code using peer-to-peer transmission, provided
|
||||
you inform other peers where the object code and Corresponding
|
||||
Source of the work are being offered to the general public at no
|
||||
charge under subsection 6d.
|
||||
|
||||
A separable portion of the object code, whose source code is excluded
|
||||
from the Corresponding Source as a System Library, need not be
|
||||
included in conveying the object code work.
|
||||
|
||||
A "User Product" is either (1) a "consumer product", which means any
|
||||
tangible personal property which is normally used for personal, family,
|
||||
or household purposes, or (2) anything designed or sold for incorporation
|
||||
into a dwelling. In determining whether a product is a consumer product,
|
||||
doubtful cases shall be resolved in favor of coverage. For a particular
|
||||
product received by a particular user, "normally used" refers to a
|
||||
typical or common use of that class of product, regardless of the status
|
||||
of the particular user or of the way in which the particular user
|
||||
actually uses, or expects or is expected to use, the product. A product
|
||||
is a consumer product regardless of whether the product has substantial
|
||||
commercial, industrial or non-consumer uses, unless such uses represent
|
||||
the only significant mode of use of the product.
|
||||
|
||||
"Installation Information" for a User Product means any methods,
|
||||
procedures, authorization keys, or other information required to install
|
||||
and execute modified versions of a covered work in that User Product from
|
||||
a modified version of its Corresponding Source. The information must
|
||||
suffice to ensure that the continued functioning of the modified object
|
||||
code is in no case prevented or interfered with solely because
|
||||
modification has been made.
|
||||
|
||||
If you convey an object code work under this section in, or with, or
|
||||
specifically for use in, a User Product, and the conveying occurs as
|
||||
part of a transaction in which the right of possession and use of the
|
||||
User Product is transferred to the recipient in perpetuity or for a
|
||||
fixed term (regardless of how the transaction is characterized), the
|
||||
Corresponding Source conveyed under this section must be accompanied
|
||||
by the Installation Information. But this requirement does not apply
|
||||
if neither you nor any third party retains the ability to install
|
||||
modified object code on the User Product (for example, the work has
|
||||
been installed in ROM).
|
||||
|
||||
The requirement to provide Installation Information does not include a
|
||||
requirement to continue to provide support service, warranty, or updates
|
||||
for a work that has been modified or installed by the recipient, or for
|
||||
the User Product in which it has been modified or installed. Access to a
|
||||
network may be denied when the modification itself materially and
|
||||
adversely affects the operation of the network or violates the rules and
|
||||
protocols for communication across the network.
|
||||
|
||||
Corresponding Source conveyed, and Installation Information provided,
|
||||
in accord with this section must be in a format that is publicly
|
||||
documented (and with an implementation available to the public in
|
||||
source code form), and must require no special password or key for
|
||||
unpacking, reading or copying.
|
||||
|
||||
7. Additional Terms.
|
||||
|
||||
"Additional permissions" are terms that supplement the terms of this
|
||||
License by making exceptions from one or more of its conditions.
|
||||
Additional permissions that are applicable to the entire Program shall
|
||||
be treated as though they were included in this License, to the extent
|
||||
that they are valid under applicable law. If additional permissions
|
||||
apply only to part of the Program, that part may be used separately
|
||||
under those permissions, but the entire Program remains governed by
|
||||
this License without regard to the additional permissions.
|
||||
|
||||
When you convey a copy of a covered work, you may at your option
|
||||
remove any additional permissions from that copy, or from any part of
|
||||
it. (Additional permissions may be written to require their own
|
||||
removal in certain cases when you modify the work.) You may place
|
||||
additional permissions on material, added by you to a covered work,
|
||||
for which you have or can give appropriate copyright permission.
|
||||
|
||||
Notwithstanding any other provision of this License, for material you
|
||||
add to a covered work, you may (if authorized by the copyright holders of
|
||||
that material) supplement the terms of this License with terms:
|
||||
|
||||
a) Disclaiming warranty or limiting liability differently from the
|
||||
terms of sections 15 and 16 of this License; or
|
||||
|
||||
b) Requiring preservation of specified reasonable legal notices or
|
||||
author attributions in that material or in the Appropriate Legal
|
||||
Notices displayed by works containing it; or
|
||||
|
||||
c) Prohibiting misrepresentation of the origin of that material, or
|
||||
requiring that modified versions of such material be marked in
|
||||
reasonable ways as different from the original version; or
|
||||
|
||||
d) Limiting the use for publicity purposes of names of licensors or
|
||||
authors of the material; or
|
||||
|
||||
e) Declining to grant rights under trademark law for use of some
|
||||
trade names, trademarks, or service marks; or
|
||||
|
||||
f) Requiring indemnification of licensors and authors of that
|
||||
material by anyone who conveys the material (or modified versions of
|
||||
it) with contractual assumptions of liability to the recipient, for
|
||||
any liability that these contractual assumptions directly impose on
|
||||
those licensors and authors.
|
||||
|
||||
All other non-permissive additional terms are considered "further
|
||||
restrictions" within the meaning of section 10. If the Program as you
|
||||
received it, or any part of it, contains a notice stating that it is
|
||||
governed by this License along with a term that is a further
|
||||
restriction, you may remove that term. If a license document contains
|
||||
a further restriction but permits relicensing or conveying under this
|
||||
License, you may add to a covered work material governed by the terms
|
||||
of that license document, provided that the further restriction does
|
||||
not survive such relicensing or conveying.
|
||||
|
||||
If you add terms to a covered work in accord with this section, you
|
||||
must place, in the relevant source files, a statement of the
|
||||
additional terms that apply to those files, or a notice indicating
|
||||
where to find the applicable terms.
|
||||
|
||||
Additional terms, permissive or non-permissive, may be stated in the
|
||||
form of a separately written license, or stated as exceptions;
|
||||
the above requirements apply either way.
|
||||
|
||||
8. Termination.
|
||||
|
||||
You may not propagate or modify a covered work except as expressly
|
||||
provided under this License. Any attempt otherwise to propagate or
|
||||
modify it is void, and will automatically terminate your rights under
|
||||
this License (including any patent licenses granted under the third
|
||||
paragraph of section 11).
|
||||
|
||||
However, if you cease all violation of this License, then your
|
||||
license from a particular copyright holder is reinstated (a)
|
||||
provisionally, unless and until the copyright holder explicitly and
|
||||
finally terminates your license, and (b) permanently, if the copyright
|
||||
holder fails to notify you of the violation by some reasonable means
|
||||
prior to 60 days after the cessation.
|
||||
|
||||
Moreover, your license from a particular copyright holder is
|
||||
reinstated permanently if the copyright holder notifies you of the
|
||||
violation by some reasonable means, this is the first time you have
|
||||
received notice of violation of this License (for any work) from that
|
||||
copyright holder, and you cure the violation prior to 30 days after
|
||||
your receipt of the notice.
|
||||
|
||||
Termination of your rights under this section does not terminate the
|
||||
licenses of parties who have received copies or rights from you under
|
||||
this License. If your rights have been terminated and not permanently
|
||||
reinstated, you do not qualify to receive new licenses for the same
|
||||
material under section 10.
|
||||
|
||||
9. Acceptance Not Required for Having Copies.
|
||||
|
||||
You are not required to accept this License in order to receive or
|
||||
run a copy of the Program. Ancillary propagation of a covered work
|
||||
occurring solely as a consequence of using peer-to-peer transmission
|
||||
to receive a copy likewise does not require acceptance. However,
|
||||
nothing other than this License grants you permission to propagate or
|
||||
modify any covered work. These actions infringe copyright if you do
|
||||
not accept this License. Therefore, by modifying or propagating a
|
||||
covered work, you indicate your acceptance of this License to do so.
|
||||
|
||||
10. Automatic Licensing of Downstream Recipients.
|
||||
|
||||
Each time you convey a covered work, the recipient automatically
|
||||
receives a license from the original licensors, to run, modify and
|
||||
propagate that work, subject to this License. You are not responsible
|
||||
for enforcing compliance by third parties with this License.
|
||||
|
||||
An "entity transaction" is a transaction transferring control of an
|
||||
organization, or substantially all assets of one, or subdividing an
|
||||
organization, or merging organizations. If propagation of a covered
|
||||
work results from an entity transaction, each party to that
|
||||
transaction who receives a copy of the work also receives whatever
|
||||
licenses to the work the party's predecessor in interest had or could
|
||||
give under the previous paragraph, plus a right to possession of the
|
||||
Corresponding Source of the work from the predecessor in interest, if
|
||||
the predecessor has it or can get it with reasonable efforts.
|
||||
|
||||
You may not impose any further restrictions on the exercise of the
|
||||
rights granted or affirmed under this License. For example, you may
|
||||
not impose a license fee, royalty, or other charge for exercise of
|
||||
rights granted under this License, and you may not initiate litigation
|
||||
(including a cross-claim or counterclaim in a lawsuit) alleging that
|
||||
any patent claim is infringed by making, using, selling, offering for
|
||||
sale, or importing the Program or any portion of it.
|
||||
|
||||
11. Patents.
|
||||
|
||||
A "contributor" is a copyright holder who authorizes use under this
|
||||
License of the Program or a work on which the Program is based. The
|
||||
work thus licensed is called the contributor's "contributor version".
|
||||
|
||||
A contributor's "essential patent claims" are all patent claims
|
||||
owned or controlled by the contributor, whether already acquired or
|
||||
hereafter acquired, that would be infringed by some manner, permitted
|
||||
by this License, of making, using, or selling its contributor version,
|
||||
but do not include claims that would be infringed only as a
|
||||
consequence of further modification of the contributor version. For
|
||||
purposes of this definition, "control" includes the right to grant
|
||||
patent sublicenses in a manner consistent with the requirements of
|
||||
this License.
|
||||
|
||||
Each contributor grants you a non-exclusive, worldwide, royalty-free
|
||||
patent license under the contributor's essential patent claims, to
|
||||
make, use, sell, offer for sale, import and otherwise run, modify and
|
||||
propagate the contents of its contributor version.
|
||||
|
||||
In the following three paragraphs, a "patent license" is any express
|
||||
agreement or commitment, however denominated, not to enforce a patent
|
||||
(such as an express permission to practice a patent or covenant not to
|
||||
sue for patent infringement). To "grant" such a patent license to a
|
||||
party means to make such an agreement or commitment not to enforce a
|
||||
patent against the party.
|
||||
|
||||
If you convey a covered work, knowingly relying on a patent license,
|
||||
and the Corresponding Source of the work is not available for anyone
|
||||
to copy, free of charge and under the terms of this License, through a
|
||||
publicly available network server or other readily accessible means,
|
||||
then you must either (1) cause the Corresponding Source to be so
|
||||
available, or (2) arrange to deprive yourself of the benefit of the
|
||||
patent license for this particular work, or (3) arrange, in a manner
|
||||
consistent with the requirements of this License, to extend the patent
|
||||
license to downstream recipients. "Knowingly relying" means you have
|
||||
actual knowledge that, but for the patent license, your conveying the
|
||||
covered work in a country, or your recipient's use of the covered work
|
||||
in a country, would infringe one or more identifiable patents in that
|
||||
country that you have reason to believe are valid.
|
||||
|
||||
If, pursuant to or in connection with a single transaction or
|
||||
arrangement, you convey, or propagate by procuring conveyance of, a
|
||||
covered work, and grant a patent license to some of the parties
|
||||
receiving the covered work authorizing them to use, propagate, modify
|
||||
or convey a specific copy of the covered work, then the patent license
|
||||
you grant is automatically extended to all recipients of the covered
|
||||
work and works based on it.
|
||||
|
||||
A patent license is "discriminatory" if it does not include within
|
||||
the scope of its coverage, prohibits the exercise of, or is
|
||||
conditioned on the non-exercise of one or more of the rights that are
|
||||
specifically granted under this License. You may not convey a covered
|
||||
work if you are a party to an arrangement with a third party that is
|
||||
in the business of distributing software, under which you make payment
|
||||
to the third party based on the extent of your activity of conveying
|
||||
the work, and under which the third party grants, to any of the
|
||||
parties who would receive the covered work from you, a discriminatory
|
||||
patent license (a) in connection with copies of the covered work
|
||||
conveyed by you (or copies made from those copies), or (b) primarily
|
||||
for and in connection with specific products or compilations that
|
||||
contain the covered work, unless you entered into that arrangement,
|
||||
or that patent license was granted, prior to 28 March 2007.
|
||||
|
||||
Nothing in this License shall be construed as excluding or limiting
|
||||
any implied license or other defenses to infringement that may
|
||||
otherwise be available to you under applicable patent law.
|
||||
|
||||
12. No Surrender of Others' Freedom.
|
||||
|
||||
If conditions are imposed on you (whether by court order, agreement or
|
||||
otherwise) that contradict the conditions of this License, they do not
|
||||
excuse you from the conditions of this License. If you cannot convey a
|
||||
covered work so as to satisfy simultaneously your obligations under this
|
||||
License and any other pertinent obligations, then as a consequence you may
|
||||
not convey it at all. For example, if you agree to terms that obligate you
|
||||
to collect a royalty for further conveying from those to whom you convey
|
||||
the Program, the only way you could satisfy both those terms and this
|
||||
License would be to refrain entirely from conveying the Program.
|
||||
|
||||
13. Remote Network Interaction; Use with the GNU General Public License.
|
||||
|
||||
Notwithstanding any other provision of this License, if you modify the
|
||||
Program, your modified version must prominently offer all users
|
||||
interacting with it remotely through a computer network (if your version
|
||||
supports such interaction) an opportunity to receive the Corresponding
|
||||
Source of your version by providing access to the Corresponding Source
|
||||
from a network server at no charge, through some standard or customary
|
||||
means of facilitating copying of software. This Corresponding Source
|
||||
shall include the Corresponding Source for any work covered by version 3
|
||||
of the GNU General Public License that is incorporated pursuant to the
|
||||
following paragraph.
|
||||
|
||||
Notwithstanding any other provision of this License, you have
|
||||
permission to link or combine any covered work with a work licensed
|
||||
under version 3 of the GNU General Public License into a single
|
||||
combined work, and to convey the resulting work. The terms of this
|
||||
License will continue to apply to the part which is the covered work,
|
||||
but the work with which it is combined will remain governed by version
|
||||
3 of the GNU General Public License.
|
||||
|
||||
14. Revised Versions of this License.
|
||||
|
||||
The Free Software Foundation may publish revised and/or new versions of
|
||||
the GNU Affero General Public License from time to time. Such new versions
|
||||
will be similar in spirit to the present version, but may differ in detail to
|
||||
address new problems or concerns.
|
||||
|
||||
Each version is given a distinguishing version number. If the
|
||||
Program specifies that a certain numbered version of the GNU Affero General
|
||||
Public License "or any later version" applies to it, you have the
|
||||
option of following the terms and conditions either of that numbered
|
||||
version or of any later version published by the Free Software
|
||||
Foundation. If the Program does not specify a version number of the
|
||||
GNU Affero General Public License, you may choose any version ever published
|
||||
by the Free Software Foundation.
|
||||
|
||||
If the Program specifies that a proxy can decide which future
|
||||
versions of the GNU Affero General Public License can be used, that proxy's
|
||||
public statement of acceptance of a version permanently authorizes you
|
||||
to choose that version for the Program.
|
||||
|
||||
Later license versions may give you additional or different
|
||||
permissions. However, no additional obligations are imposed on any
|
||||
author or copyright holder as a result of your choosing to follow a
|
||||
later version.
|
||||
|
||||
15. Disclaimer of Warranty.
|
||||
|
||||
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
|
||||
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
|
||||
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
|
||||
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
|
||||
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
||||
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
|
||||
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
|
||||
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
|
||||
|
||||
16. Limitation of Liability.
|
||||
|
||||
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
|
||||
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
|
||||
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
|
||||
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
|
||||
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
|
||||
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
|
||||
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
|
||||
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
|
||||
SUCH DAMAGES.
|
||||
|
||||
17. Interpretation of Sections 15 and 16.
|
||||
|
||||
If the disclaimer of warranty and limitation of liability provided
|
||||
above cannot be given local legal effect according to their terms,
|
||||
reviewing courts shall apply local law that most closely approximates
|
||||
an absolute waiver of all civil liability in connection with the
|
||||
Program, unless a warranty or assumption of liability accompanies a
|
||||
copy of the Program in return for a fee.
|
||||
|
||||
END OF TERMS AND CONDITIONS
|
||||
|
||||
How to Apply These Terms to Your New Programs
|
||||
|
||||
If you develop a new program, and you want it to be of the greatest
|
||||
possible use to the public, the best way to achieve this is to make it
|
||||
free software which everyone can redistribute and change under these terms.
|
||||
|
||||
To do so, attach the following notices to the program. It is safest
|
||||
to attach them to the start of each source file to most effectively
|
||||
state the exclusion of warranty; and each file should have at least
|
||||
the "copyright" line and a pointer to where the full notice is found.
|
||||
|
||||
<one line to give the program's name and a brief idea of what it does.>
|
||||
Copyright (C) <year> <name of author>
|
||||
|
||||
This program is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU Affero General Public License as published
|
||||
by the Free Software Foundation, either version 3 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
This program is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU Affero General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU Affero General Public License
|
||||
along with this program. If not, see <https://www.gnu.org/licenses/>.
|
||||
|
||||
Also add information on how to contact you by electronic and paper mail.
|
||||
|
||||
If your software can interact with users remotely through a computer
|
||||
network, you should also make sure that it provides a way for users to
|
||||
get its source. For example, if your program is a web application, its
|
||||
interface could display a "Source" link that leads users to an archive
|
||||
of the code. There are many ways you could offer source, and different
|
||||
solutions will be better for different programs; see section 13 for the
|
||||
specific requirements.
|
||||
|
||||
You should also get your employer (if you work as a programmer) or school,
|
||||
if any, to sign a "copyright disclaimer" for the program, if necessary.
|
||||
For more information on this, and how to apply and follow the GNU AGPL, see
|
||||
<https://www.gnu.org/licenses/>.
|
||||
```
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: post /apps
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/name/{name}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/get_or_create/{name}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: put /apps/{app_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: post /apps/{app_id}/users/{user_id}/collections
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: delete /apps/{app_id}/users/{user_id}/collections/{collection_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/collections/{name}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/collections
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: put /apps/{app_id}/users/{user_id}/collections/{collection_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: post /apps/{app_id}/users/{user_id}/collections/{collection_id}/documents
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: delete /apps/{app_id}/users/{user_id}/collections/{collection_id}/documents/{document_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/collections/{collection_id}/documents/{document_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/collections/{collection_id}/documents
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/collections/{collection_id}/query
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: put /apps/{app_id}/users/{user_id}/collections/{collection_id}/documents/{document_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: post /apps/{app_id}/users/{user_id}/sessions/{session_id}/messages
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: post /apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/sessions/{session_id}/messages/{message_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/sessions/{session_id}/messages
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages/{metamessage_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: put /apps/{app_id}/users/{user_id}/sessions/{session_id}/messages/{message_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: put /apps/{app_id}/users/{user_id}/sessions/{session_id}/metamessages/{metamessage_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: post /apps/{app_id}/users/{user_id}/sessions
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: delete /apps/{app_id}/users/{user_id}/sessions/{session_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/sessions/{session_id}/chat
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/sessions/{session_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{user_id}/sessions
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: put /apps/{app_id}/users/{user_id}/sessions/{session_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: post /apps/{app_id}/users
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/get_or_create/{name}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users/{name}
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: get /apps/{app_id}/users
|
||||
---
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
---
|
||||
openapi: put /apps/{app_id}/users/{user_id}
|
||||
---
|
||||
|
|
@ -0,0 +1,17 @@
|
|||
---
|
||||
title: 'Introduction'
|
||||
---
|
||||
|
||||
<Note>
|
||||
If you're using the Python SDK you shouldn't need to interface directly with the
|
||||
API. The SDK reference may be more helpful
|
||||
</Note>
|
||||
|
||||
This section of the documentation goes over all of the different API endpoints available in the Honcho
|
||||
Server. They largely map to CRUD operations for each of the core primitives. For information about the core
|
||||
primitives consult [Architecture](/getting-started/Architecture)
|
||||
|
||||
<Warning>
|
||||
This part of the documentation is autogenerated for the most up to date and accurate API spec view the
|
||||
[Redoc](https://demo.honcho.dev/redoc) or [Swagger](https://demo.honcho.dev/docs) directly.
|
||||
</Warning>
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,28 @@
|
|||
<svg width="650" height="650" viewBox="0 0 650 650" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<rect width="650" height="650" fill="#101447"/>
|
||||
<g filter="url(#filter0_dd_11_8)">
|
||||
<path d="M325.56 80C238.59 80 157.54 126.59 113.62 201.69C94.1801 213.51 81.0001 221.78 80.7301 221.92C42.8201 242.58 23.9001 262.29 14.6201 277.9C7.41011 278.03 1.1701 283.37 0.150101 290.73C-1.0099 298.88 4.6801 306.44 12.8401 307.58C21.0101 308.74 28.5501 303.05 29.7101 294.88C30.3101 290.68 29.0701 286.63 26.6301 283.55C40.3601 261.4 69.3201 243.18 87.0601 233.52C90.1101 231.86 261.89 127.81 274.74 130.38C276.89 130.81 280.03 131.97 282.5 137.08C289.3 151.18 226.78 192.95 214.03 200.59C201.82 207.9 191.06 215.71 181.75 224.01C162.02 241.59 148.85 261.32 142.45 282.97C138.6 296.02 127.63 333.6 101.02 342.94C99.1301 338.74 95.3301 335.46 90.4701 334.46C82.4001 332.77 74.4901 337.95 72.8201 346.02C71.2201 353.66 75.7801 361.14 83.1201 363.34C101.49 482.47 203.51 570.77 325.56 570.77C460.86 570.77 570.95 460.69 570.95 325.38C570.95 190.07 460.87 80 325.56 80ZM187.7 236.51C187.12 244.15 185.37 252.9 181.07 258.61C176.54 264.61 167.95 269.71 160.23 273.31C166.33 260.21 175.51 247.92 187.7 236.51ZM325.56 557.54C210.02 557.54 113.46 473.91 96.1601 361.12C97.9201 359.84 99.4201 358.2 100.48 356.25C122.53 348.38 139.19 337.49 154.08 290.08C162.07 287.28 182.01 279.35 191.64 266.56C201.32 253.69 201.46 233.61 201.05 225.28C207.1 220.67 213.7 216.22 220.83 211.95C261.59 187.55 305.55 154.35 294.41 131.32C290.74 123.73 284.83 118.92 277.34 117.43C263.23 114.63 192.72 154.44 140.15 185.73C183.7 128.08 252.41 93.24 325.56 93.24C453.57 93.24 557.71 197.39 557.71 325.39C557.71 453.39 453.57 557.55 325.56 557.55V557.54Z" fill="white"/>
|
||||
<path d="M247.34 325.38C261.296 325.38 272.61 307.843 272.61 286.21C272.61 264.577 261.296 247.04 247.34 247.04C233.384 247.04 222.07 264.577 222.07 286.21C222.07 307.843 233.384 325.38 247.34 325.38Z" fill="white"/>
|
||||
<path d="M403.78 325.38C417.736 325.38 429.05 307.843 429.05 286.21C429.05 264.577 417.736 247.04 403.78 247.04C389.824 247.04 378.51 264.577 378.51 286.21C378.51 307.843 389.824 325.38 403.78 325.38Z" fill="white"/>
|
||||
<path d="M386.18 406.91H264.94C258.48 406.91 253.25 412.14 253.25 418.6C253.25 425.06 258.48 430.29 264.94 430.29H386.18C392.64 430.29 397.87 425.06 397.87 418.6C397.87 412.14 392.64 406.91 386.18 406.91Z" fill="white"/>
|
||||
<path d="M93.9401 333.61L93.9701 333.58L93.9401 333.6V333.62V333.61Z" fill="white"/>
|
||||
</g>
|
||||
<defs>
|
||||
<filter id="filter0_dd_11_8" x="0" y="80" width="594.95" height="514.77" filterUnits="userSpaceOnUse" color-interpolation-filters="sRGB">
|
||||
<feFlood flood-opacity="0" result="BackgroundImageFix"/>
|
||||
<feColorMatrix in="SourceAlpha" type="matrix" values="0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 127 0" result="hardAlpha"/>
|
||||
<feOffset dx="20" dy="20"/>
|
||||
<feGaussianBlur stdDeviation="2"/>
|
||||
<feComposite in2="hardAlpha" operator="out"/>
|
||||
<feColorMatrix type="matrix" values="0 0 0 0 1 0 0 0 0 0.352941 0 0 0 0 0.494118 0 0 0 1 0"/>
|
||||
<feBlend mode="normal" in2="BackgroundImageFix" result="effect1_dropShadow_11_8"/>
|
||||
<feColorMatrix in="SourceAlpha" type="matrix" values="0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 127 0" result="hardAlpha"/>
|
||||
<feOffset dx="10" dy="10"/>
|
||||
<feGaussianBlur stdDeviation="2"/>
|
||||
<feComposite in2="hardAlpha" operator="out"/>
|
||||
<feColorMatrix type="matrix" values="0 0 0 0 0.0352941 0 0 0 0 0.996078 0 0 0 0 0.972549 0 0 0 1 0"/>
|
||||
<feBlend mode="normal" in2="effect1_dropShadow_11_8" result="effect2_dropShadow_11_8"/>
|
||||
<feBlend mode="normal" in="SourceGraphic" in2="effect2_dropShadow_11_8" result="shape"/>
|
||||
</filter>
|
||||
</defs>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 3.5 KiB |
|
|
@ -0,0 +1,83 @@
|
|||
---
|
||||
title: 'Architecture'
|
||||
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 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).
|
||||
|
||||
## Core Primitives
|
||||
|
||||
Using Honcho has the following flow:
|
||||
1. Initialize your `Honcho` instance and `App`
|
||||
2. Create a `User`
|
||||
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
|
||||
7. Add `Document`s to a `User`'s `Collection`
|
||||
|
||||
|
||||
|
||||
|
||||
### Users
|
||||
|
||||
The `User` object is the main interface for managing a User's context. With it
|
||||
you can interface with the `User`'s `Session`s and `Collections`s directly.
|
||||
|
||||
### Sessions
|
||||
|
||||
The `Session` object is useful for organizing your interactions with `User`s.
|
||||
Different `User`s can have different sessions enabling you to neatly segment user
|
||||
context. It also accepts a `location_id` parameter which can specifically
|
||||
denote *where* users' sessions are taking place.
|
||||
|
||||
### Messages
|
||||
|
||||
Sessions are made up of `Message` objects. You can append them to sessions.
|
||||
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.
|
||||
|
||||
### Collections
|
||||
|
||||
`Collections` are used to organize information about the `User`. These can be
|
||||
thought of as stores for more global data about the `User` that spans sessions
|
||||
while `Metamessages` are local to a session and the message they are linked to.
|
||||
|
||||
### Documents
|
||||
|
||||
`Documents` are the individual facts that are stored in the `Collection`. They
|
||||
are stored as vector embeddings to allow for a RAG like interface. Using honcho
|
||||
a developer can query a collection of documents using methods like cosine
|
||||
similarity search
|
||||
|
||||
## Conclusion
|
||||
|
||||
Too often we hear developers enjoying a certain framework for building
|
||||
LLM-powered applications only to see their codebase reach a level of complexity
|
||||
that hits the limits of said framework. It ultimately gets abandoned and
|
||||
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!
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
---
|
||||
title: 'Deploying Honcho'
|
||||
sidebarTitle: 'Deploying'
|
||||
description: 'Deploying the Honcho API Server with Docker'
|
||||
icon: 'rocket'
|
||||
---
|
||||
|
||||
If you're happy with how things are working locally, deploying your Honcho instance is a breeze with [Fly](https://fly.io). Follow the [Fly.io Docs](https://fly.io/docs/getting-started/) to setup your environment and the `flyctl`.
|
||||
|
||||
Once `flyctl` is set up use the the following commands to launch the application:
|
||||
|
||||
```bash
|
||||
cd honcho/api
|
||||
flyctl launch --no-deploy # Follow the prompts and edit as you see fit
|
||||
cat .env | flyctl secrets import # Load in your secrets
|
||||
flyctl deploy # Deploy with appropriate environment variables
|
||||
```
|
||||
|
||||
Then you should have a new URL to initialize your Honcho client with! Consider your user context managed 🪄.`
|
||||
|
|
@ -0,0 +1,98 @@
|
|||
---
|
||||
title: 'Development'
|
||||
description: 'Learn how to preview changes locally'
|
||||
---
|
||||
|
||||
<Info>
|
||||
**Prerequisite** You should have installed Node.js (version 18.10.0 or
|
||||
higher).
|
||||
</Info>
|
||||
|
||||
Step 1. Install Mintlify on your OS:
|
||||
|
||||
<CodeGroup>
|
||||
|
||||
```bash npm
|
||||
npm i -g mintlify
|
||||
```
|
||||
|
||||
```bash yarn
|
||||
yarn global add mintlify
|
||||
```
|
||||
|
||||
</CodeGroup>
|
||||
|
||||
Step 2. Go to the docs are located (where you can find `mint.json`) and run the following command:
|
||||
|
||||
```bash
|
||||
mintlify dev
|
||||
```
|
||||
|
||||
The documentation website is now available at `http://localhost:3000`.
|
||||
|
||||
### Custom Ports
|
||||
|
||||
Mintlify uses port 3000 by default. You can use the `--port` flag to customize the port Mintlify runs on. For example, use this command to run in port 3333:
|
||||
|
||||
```bash
|
||||
mintlify dev --port 3333
|
||||
```
|
||||
|
||||
You will see an error like this if you try to run Mintlify in a port that's already taken:
|
||||
|
||||
```md
|
||||
Error: listen EADDRINUSE: address already in use :::3000
|
||||
```
|
||||
|
||||
## Mintlify Versions
|
||||
|
||||
Each CLI is linked to a specific version of Mintlify. Please update the CLI if your local website looks different than production.
|
||||
|
||||
<CodeGroup>
|
||||
|
||||
```bash npm
|
||||
npm i -g mintlify@latest
|
||||
```
|
||||
|
||||
```bash yarn
|
||||
yarn global upgrade mintlify
|
||||
```
|
||||
|
||||
</CodeGroup>
|
||||
|
||||
## Deployment
|
||||
|
||||
<Tip>
|
||||
Unlimited editors available under the [Startup
|
||||
Plan](https://mintlify.com/pricing)
|
||||
</Tip>
|
||||
|
||||
You should see the following if the deploy successfully went through:
|
||||
|
||||
<Frame>
|
||||
<img src="/images/checks-passed.png" style={{ borderRadius: '0.5rem' }} />
|
||||
</Frame>
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
Here's how to solve some common problems when working with the CLI.
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="Mintlify is not loading">
|
||||
Update to Node v18. Run `mintlify install` and try again.
|
||||
</Accordion>
|
||||
<Accordion title="No such file or directory on Windows">
|
||||
Go to the `C:/Users/Username/.mintlify/` directory and remove the `mint`
|
||||
folder. Then Open the Git Bash in this location and run `git clone
|
||||
https://github.com/mintlify/mint.git`.
|
||||
|
||||
Repeat step 3.
|
||||
|
||||
</Accordion>
|
||||
<Accordion title="Getting an unknown error">
|
||||
Try navigating to the root of your device and delete the ~/.mintlify folder.
|
||||
Then run `mintlify dev` again.
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
Curious about what changed in a CLI version? [Check out the CLI changelog.](/changelog/command-line)
|
||||
|
|
@ -0,0 +1,37 @@
|
|||
---
|
||||
title: 🫡 Welcome to Honcho
|
||||
sidebarTitle: 'Overview'
|
||||
description: 'Honcho is an open source framework for building personalized AI experiences.'
|
||||
icon: 'face-saluting'
|
||||
---
|
||||
|
||||
<Snippet file="overview-shields.mdx" />
|
||||
|
||||
Honcho provides a simple API for managing multiple concurrent sessions across numerous users.
|
||||
Now you can focus on improving your service instead of spending countless hours figuring out how to get it to scale. To learn more about the project, check out our blog post.
|
||||
|
||||
Get started below!
|
||||
|
||||
<CardGroup cols={3}>
|
||||
<Card
|
||||
title="Quickstart"
|
||||
icon="bolt"
|
||||
href="/quickstart"
|
||||
>
|
||||
Quickly set up a local environment to interface with the Honcho API
|
||||
</Card>
|
||||
<Card
|
||||
title="Architecture"
|
||||
icon="building"
|
||||
href="/architecture"
|
||||
>
|
||||
Get an overview of the different primitives and structure of Honcho
|
||||
</Card>
|
||||
<Card
|
||||
title="Integrate with Langchain"
|
||||
icon="bird"
|
||||
href="/guides/langchain"
|
||||
>
|
||||
Learn how to use LangChain and Honcho together to quickly scale your agents to many users
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
|
@ -0,0 +1,72 @@
|
|||
---
|
||||
title: 'Quickstart'
|
||||
description: 'Start building awesome documentation in under 5 minutes'
|
||||
icon: 'bolt'
|
||||
---
|
||||
|
||||
To make things easy, there's an instance of Honcho up and running on a demo
|
||||
server at [https://demo.honcho.dev](https://demo.honcho.dev/docs). The python
|
||||
package defaults to this instance, so let's dive into how to get up and
|
||||
running!
|
||||
|
||||
|
||||
Install the Honcho client SDK with the following command:
|
||||
```bash
|
||||
pip install honcho-ai
|
||||
```
|
||||
Alternatively, if you're using [Poetry](https://python-poetry.org/), run:
|
||||
```bash
|
||||
poetry add honcho-ai
|
||||
```
|
||||
|
||||
Let's walk through simple Python steps. First, import the `Client` from the package:
|
||||
|
||||
```python
|
||||
from honcho import Honcho
|
||||
```
|
||||
|
||||
Next, we want to register an application with the Honcho client:
|
||||
```python
|
||||
from uuid import uuid4
|
||||
|
||||
app_name = str(uuid4()) # random int for the app_name, but this can be any string
|
||||
honcho = Honcho(app_name=app_name)
|
||||
honcho.initialize()
|
||||
```
|
||||
|
||||
This will create an application with the above name if it does not already exist or retrieve it if it does. After we have our application
|
||||
initialized, we can make a user with the following:
|
||||
|
||||
```python
|
||||
user_name = str(uuid4()) # random int for the user_name, but this can be anything, should be unique for each user
|
||||
user = honcho.create_user(user_name)
|
||||
```
|
||||
|
||||
Now let's create a session for that application. Honcho is a user context management system, so you can create sessions for users. Thus, a `user_id` is required.
|
||||
```python
|
||||
session = user.create_session()
|
||||
```
|
||||
|
||||
Let's add a user message and an AI message to that session:
|
||||
```python
|
||||
user_input = "Here's a message!"
|
||||
ai_response = "I'm a helpful assistant!"
|
||||
|
||||
session.create_message(is_user=True, content=user_input)
|
||||
session.create_message(is_user=False, content=ai_response)
|
||||
```
|
||||
|
||||
You can also easily query Honcho to get the session objects for that user with the following:
|
||||
```python
|
||||
sessions = list(user.get_sessions_generator())
|
||||
session = sessions[0] # gets the most recent session for that user
|
||||
```
|
||||
|
||||
And finally you can get the messages within a session with the following:
|
||||
```python
|
||||
messages = list(session.get_messages_generator())
|
||||
```
|
||||
|
||||
This is a super simple overview of how to get up and running with the Honcho SDK. We covered the basic methods for reading and writing from the hosted storage service. Next, we'll cover alternative forms of hosting Honcho.
|
||||
|
||||
For a more detailed look at the SDK check out the SDK reference [here](https://api.python.honcho.dev/).
|
||||
|
|
@ -0,0 +1,64 @@
|
|||
---
|
||||
title: 'Self-Hosting Honcho'
|
||||
sidebarTitle: 'Self-Hosting'
|
||||
description: 'Running a local version of the Honcho API Server'
|
||||
icon: 'cloud'
|
||||
---
|
||||
|
||||
|
||||
|
||||
Honcho is a monorepo that contains the server and API to manage database interactions. It stores data about an application's state along with the python sdk for interacting with the API.
|
||||
You can host it locally quite easily! This can be beneficial for iterative development, testing, and debugging. This guide will go through the different ways to host locally.
|
||||
|
||||
### Setup
|
||||
|
||||
1. Clone the repository:
|
||||
```bash
|
||||
git clone git@github.com:plastic-labs/honcho.git
|
||||
```
|
||||
|
||||
2. Copy the `.env.template` file to `.env` and specify the type of database and `CONNECTION_URI`. For testing sqlite is fine. The below example uses a sqlite database with a local file:
|
||||
|
||||
> Honcho has been tested with Postgresql and SQLite
|
||||
|
||||
```env
|
||||
DATABASE_TYPE=sqlite
|
||||
CONNECTION_URI=sqlite:///api.db
|
||||
```
|
||||
|
||||
Now the tutorial will diverge based on how you'd like to run the API.
|
||||
|
||||
### Poetry
|
||||
|
||||
This project utilizes [Poetry](https://python-poetry.org/) for dependency management, so you can run the API through a poetry virtual environment.
|
||||
|
||||
3. Create a virtualenv and install the API's dependencies:
|
||||
```bash
|
||||
cd honcho/api/ # change to the api directory
|
||||
poetry shell # Activate virutal environment
|
||||
poetry install # install dependencies
|
||||
```
|
||||
|
||||
4. Run the API via uvicorn:
|
||||
```bash
|
||||
cd honcho/api # change to the api directory
|
||||
poetry shell # Activate virtual environment if not already enabled
|
||||
python -m uvicorn src.main:app --reload
|
||||
```
|
||||
|
||||
### Docker
|
||||
|
||||
Alternatively there is also a `Dockerfile` included to run the API server from a docker container.
|
||||
|
||||
The `.env` file is not loaded into the docker container and should still be configured from outside.
|
||||
|
||||
3. Build the docker image:
|
||||
```bash
|
||||
cd honcho/api
|
||||
docker build -t honcho-api .
|
||||
```
|
||||
|
||||
4. Run the docker image:
|
||||
```bash
|
||||
docker run --env-file .env -p 8000:8000 honcho-api:latest
|
||||
```
|
||||
|
|
@ -0,0 +1,54 @@
|
|||
---
|
||||
title: "Dialectic Endpoint"
|
||||
description: "An endpoint for easily 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
|
||||
|
||||
## 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.
|
||||
|
||||
## 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.
|
||||
|
||||
This chat interface is exposed via the `Sessions` object.
|
||||
|
||||
Belows is some example code on how this works.
|
||||
|
||||
```python
|
||||
from honcho import Honcho
|
||||
|
||||
honcho = Honcho(app_name="demo")
|
||||
honcho.initialize()
|
||||
|
||||
# create or get user
|
||||
user = honcho.create_or_get_user("demo-user")
|
||||
|
||||
# create or get session
|
||||
session = honcho.create_or_get_session(user, "demo-session")
|
||||
|
||||
# Talk to the dialectic agent to reason about their needs
|
||||
answer = session.chat("What is the user's favorite way of completing the task")
|
||||
```
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,113 @@
|
|||
---
|
||||
title: "Discord Bots with Honcho"
|
||||
icon: 'discord'
|
||||
description: "Discord is a powerful chat application that handles many UI complications"
|
||||
sidebarTitle: 'Discord'
|
||||
---
|
||||
|
||||
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 **Discord** as an interface. If you're not familiar with Discord bot application logic, the [py-cord](https://pycord.dev/) docs would be a good place to start.
|
||||
|
||||
## Events
|
||||
|
||||
Most Discord bots have async functions that listen for specific events, the most common one being messages. We can use Honcho to store messages by user and session based on an interface's event logic. Take the following function definition for example:
|
||||
```python
|
||||
@bot.event
|
||||
async def on_message(message):
|
||||
if message.author == bot.user:
|
||||
return
|
||||
|
||||
user_id = f"discord_{str(message.author.id)}"
|
||||
user = honcho.get_or_create_user(user_id)
|
||||
location_id=str(message.channel.id)
|
||||
|
||||
sessions = list(user.get_sessions_generator(location_id))
|
||||
|
||||
if len(sessions) > 0:
|
||||
session = sessions[0]
|
||||
else:
|
||||
session = user.create_session(location_id)
|
||||
|
||||
history = list(session.get_messages_generator())
|
||||
chat_history = langchain_message_converter(history)
|
||||
|
||||
inp = message.content
|
||||
session.create_message(is_user=True, content=inp)
|
||||
|
||||
async with message.channel.typing():
|
||||
response = await chain.ainvoke({"chat_history": chat_history, "input": inp})
|
||||
await message.channel.send(response)
|
||||
|
||||
session.create_message(is_user=False, content=response)
|
||||
```
|
||||
|
||||
Let's break down what each chunk of code is doing...
|
||||
```python
|
||||
@bot.event
|
||||
async def on_message(message):
|
||||
if message.author == bot.user:
|
||||
return
|
||||
```
|
||||
|
||||
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
|
||||
user_id = f"discord_{str(message.author.id)}"
|
||||
location_id = str(message.channel.id)
|
||||
```
|
||||
|
||||
Honcho accepts a `location_id` argument to help separate out locations messages were sent (which is convenient for Discord channels).
|
||||
|
||||
```python
|
||||
sessions = list(user.get_sessions_generator(location_id))
|
||||
if len(sessions) > 0:
|
||||
session = sessions[0]
|
||||
else:
|
||||
session = user.create_session(user_id, location_id)
|
||||
```
|
||||
|
||||
Here we're querying the `session` object for the user 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 = list(session.get_messages_generator())
|
||||
chat_history = langchain_message_converter(history)
|
||||
|
||||
inp = message.content
|
||||
session.create_message(is_user=True, content=inp)
|
||||
|
||||
async with message.channel.typing():
|
||||
response = await chain.ainvoke({"chat_history": chat_history, "input": inp})
|
||||
await message.channel.send(response)
|
||||
|
||||
session.create_message(is_user=False, content=response)
|
||||
```
|
||||
|
||||
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](../llm-frameworks/langchain) guide). Then, we access the user message via `message.content` and use `session.create_message` to 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`.
|
||||
|
||||
## Slash Commands
|
||||
|
||||
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")
|
||||
async def restart(ctx):
|
||||
user_id=f"discord_{str(ctx.author.id)}"
|
||||
user = honcho.get_or_create_user(user_id)
|
||||
location_id=str(ctx.channel_id)
|
||||
sessions = list(user.get_sessions_generator(location_id))
|
||||
sessions[0].close() if len(sessions) > 0 else None
|
||||
|
||||
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.get_or_create_user(user_id)
|
||||
location_id=str(ctx.channel_id)
|
||||
```
|
||||
Then we can retrieve and delete the messages associated with that metadata:
|
||||
```python
|
||||
sessions = list(user.get_sessions_generator(user_id, location_id))
|
||||
sessions[0].close() if len(sessions) > 0 else None
|
||||
```
|
||||
|
|
@ -0,0 +1,75 @@
|
|||
---
|
||||
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 uuid import uuid4 # for generating random app and user names
|
||||
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
|
||||
app_name = str(uuid4())
|
||||
|
||||
honcho = Honcho(app_name=app_name)
|
||||
honcho.initialize()
|
||||
user_name = str(uuid4())
|
||||
user = honcho.create_or_get_user(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 langchain_message_converter(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
|
||||
```
|
||||
|
||||
Now we can structure Honcho calls around our LLM inference:
|
||||
```python
|
||||
sessions = list(user.get_sessions_generator(location_id)) # args come from application logic
|
||||
session = sessions[0] # most recent session for user
|
||||
history = list(session.get_messages_generator())
|
||||
chat_history = langchain_message_converter(history) # convert messages for LangChain
|
||||
inp = "Here's a user message!"
|
||||
session.create_message(is_user=True, content=inp)
|
||||
|
||||
response = await chain.ainvoke({"chat_history": chat_history, "input": inp})
|
||||
|
||||
session.create_message(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!
|
||||
|
|
@ -0,0 +1,6 @@
|
|||
---
|
||||
title: "Spellbooks and Tutorials"
|
||||
sidebarTitle: 'Overview'
|
||||
description: 'Helpful guides and design patterns for building with Honcho'
|
||||
icon: 'hat-wizard'
|
||||
---
|
||||
|
|
@ -0,0 +1,184 @@
|
|||
---
|
||||
title: "Simple Memory"
|
||||
icon: "brain"
|
||||
description: "A simple example of how to store and derive facts about individual users"
|
||||
---
|
||||
|
||||
This guide shows how to implement a simple user memory system that derives and stores facts about users that
|
||||
are then referenced later on.
|
||||
|
||||
A fully working example can be found on [GitHub](https://github.com/plastic-labs/honcho/tree/main/example/discord/honcho-fact-memory).
|
||||
It's setup as a discord bot so view our [Discord guide](../interfaces/discord)
|
||||
for more details on how to set that up.
|
||||
|
||||
## Initial Setup
|
||||
|
||||
First we'll have some setup code to initialize our LLM, Honcho client, and prompts.
|
||||
|
||||
```python
|
||||
from langchain import OpenAI
|
||||
from langchain.chat_models import ChatOpenAI
|
||||
from langchain.prompts.chat import (
|
||||
ChatPromptTemplate,
|
||||
SystemMessagePromptTemplate,
|
||||
HumanMessagePromptTemplate,
|
||||
)
|
||||
from langchain.schema import (
|
||||
AIMessage,
|
||||
HumanMessage,
|
||||
SystemMessage
|
||||
)
|
||||
from langchain_core.output_parsers import NumberedListOutputParser
|
||||
|
||||
llm: ChatOpenAI = ChatOpenAI(model_name="gpt-4")
|
||||
honcho = Honcho(app_id="Simple User Memory")
|
||||
```
|
||||
|
||||
The 3 steps to this project are:
|
||||
|
||||
1. Derive facts about the user.
|
||||
2. Store those facts in a per-user vector db (`Collection`).
|
||||
3. Retrieve those facts later on to improve our response.
|
||||
|
||||
|
||||
## Step 1 - Deriving Facts
|
||||
|
||||
For this part we will be leveraging LangChain and GPT-4 to derivce facts on the user based on their recent input.
|
||||
|
||||
```python
|
||||
def derive_facts(user_input):
|
||||
# Derive facts about the user
|
||||
|
||||
fact_derivation = ChatPromptTemplate.from_messages([
|
||||
SystemMessagePromptTemplate(prompt=prompt)
|
||||
])
|
||||
|
||||
chain = fact_derivation | llm
|
||||
|
||||
response = await chain.ainvoke({
|
||||
"user_input": input
|
||||
})
|
||||
|
||||
output_parser = NumberedListOutputParser()
|
||||
facts = output_parser.parse(response.content)
|
||||
|
||||
# Return a list of facts
|
||||
return facts
|
||||
```
|
||||
|
||||
Breaking down this function we start by using LCEL to make a chain that will take the `user_input` as a variable. The
|
||||
prompt used here is below:
|
||||
|
||||
```yaml
|
||||
_type: prompt
|
||||
input_variables:
|
||||
["user_input"]
|
||||
template: >
|
||||
You are tasked with deriving discrete facts about the user based on their input. The goal is to only extract absolute facts from the message, do not make inferences beyond the text provided.
|
||||
|
||||
```{user_input}```
|
||||
|
||||
Output the facts as a numbered list.
|
||||
```
|
||||
|
||||
We then invoke the chain and parse the output to get our list of facts. We take advantage of one of LangChain's built in output parsers for this.
|
||||
|
||||
## Step 2 - Storing Facts
|
||||
|
||||
This is where Honcho comes into play. With Honcho we can initialize `Collections` for each user and can store facts as vector embeddings. You can use multiple collections if you want to segment different types of facts or data, but for now we just need one.
|
||||
|
||||
```python
|
||||
def store_facts(user_name, facts):
|
||||
user = honcho.get_or_create_user(user_name)
|
||||
collection: Collection
|
||||
try: # Check if collection exists if not create it
|
||||
collection = user.get_collection("simple-memory")
|
||||
except Exception
|
||||
collection = user.create_collection("simple-memory")
|
||||
|
||||
for fact in facts: # store each fact in the collection
|
||||
collection.create_document(content=fact)
|
||||
|
||||
```
|
||||
|
||||
That's it. We just make the collection if it doesn't already exist for the user and add the facts.
|
||||
|
||||
## Step 3 - Retrieving Facts
|
||||
|
||||
This is where we actually make user of the facts. To do this we need to first determine a query to the collection. This query is natural language that is compared to other facts in the collection using cosine similarity.
|
||||
|
||||
The trick we use below is to have the LLM determine the query and then use it in a later step.
|
||||
|
||||
```python
|
||||
def introspect(chat_history, input):
|
||||
|
||||
introspection_prompt = ChatPromptTemplate.from_messages([
|
||||
system_introspection
|
||||
])
|
||||
|
||||
# LCEL
|
||||
chain = introspection_prompt | llm
|
||||
|
||||
# inference
|
||||
response = await chain.ainvoke({
|
||||
"chat_history": chat_history,
|
||||
"input": input
|
||||
})
|
||||
|
||||
# parse output
|
||||
questions = output_parser.parse(response.content)
|
||||
|
||||
return questions
|
||||
|
||||
def respond(chat_history, input):
|
||||
response_prompt = ChatPromptTemplate.from_messages([
|
||||
system_response,
|
||||
chat_history
|
||||
])
|
||||
|
||||
retrieved_facts = collection.query(query=input, top_k=10)
|
||||
|
||||
# LCEL
|
||||
chain = response_prompt | llm
|
||||
|
||||
# inference
|
||||
response = await chain.ainvoke({
|
||||
"facts": retrieved_facts,
|
||||
})
|
||||
|
||||
return response.content
|
||||
|
||||
```
|
||||
|
||||
In the the `introspect` method we are using the user's response as input to derive the query. The prompt used is below:
|
||||
|
||||
```yaml
|
||||
_type: prompt
|
||||
input_variables:
|
||||
["chat_history", "user_input"]
|
||||
template: >
|
||||
Given the conversation history and user input, use your theory of mind skills to list out questions you'd like to know about the user in order to best respond to them.
|
||||
|
||||
Chat history: ```{chat_history}```
|
||||
User input: ```{user_input}```
|
||||
|
||||
Output the questions as a numbered list.
|
||||
```
|
||||
|
||||
Then we use the question that it generated as the query in our `collection.query()` method. the `top_k` parameter allows you to control
|
||||
how many retrieved facts to return with a max of 50.
|
||||
|
||||
The prompt use there is below as well:
|
||||
|
||||
```yaml
|
||||
_type: prompt
|
||||
input_variables:
|
||||
["facts"]
|
||||
template: >
|
||||
You are a helpful assistant. Craft a useful response based on the context provided in the conversation history and the facts we know about the user:
|
||||
```{facts}```
|
||||
```
|
||||
---
|
||||
|
||||
This is a very simple method of using Honcho to hold user context. For further reading on the limits read about
|
||||
[violation of expectation](https://arxiv.org/abs/2310.06983).
|
||||
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<linearGradient id="paint2_linear_115_86" x1="7.94816" y1="8.01562" x2="1.7612" y2="18.746" gradientUnits="userSpaceOnUse">
|
||||
<stop/>
|
||||
<stop offset="1" stop-opacity="0"/>
|
||||
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|
||||
<radialGradient id="paint3_radial_115_86" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="translate(8.11404 20.8822) rotate(-75.7542) scale(21.6246 23.7772)">
|
||||
<stop stop-color="#00BBBB"/>
|
||||
<stop offset="0.712616" stop-color="#00DB65"/>
|
||||
</radialGradient>
|
||||
<linearGradient id="paint4_linear_115_86" x1="7.60205" y1="5.8709" x2="15.5561" y2="16.3719" gradientUnits="userSpaceOnUse">
|
||||
<stop/>
|
||||
<stop offset="1" stop-opacity="0"/>
|
||||
</linearGradient>
|
||||
<radialGradient id="paint5_radial_115_86" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="translate(7.84537 21.5181) rotate(-20.3525) scale(18.5603 17.32)">
|
||||
<stop stop-color="#00B0BB"/>
|
||||
<stop offset="1" stop-color="#00DB65"/>
|
||||
</radialGradient>
|
||||
<linearGradient id="paint6_linear_115_86" x1="16.8078" y1="13.0071" x2="10.0409" y2="22.9937" gradientUnits="userSpaceOnUse">
|
||||
<stop stop-color="#00B1BC"/>
|
||||
<stop offset="1"/>
|
||||
</linearGradient>
|
||||
<linearGradient id="paint7_linear_115_86" x1="16.8078" y1="13.0071" x2="14.1687" y2="23.841" gradientUnits="userSpaceOnUse">
|
||||
<stop/>
|
||||
<stop offset="1" stop-opacity="0"/>
|
||||
</linearGradient>
|
||||
</defs>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 9.0 KiB |
|
|
@ -0,0 +1,177 @@
|
|||
{
|
||||
"$schema": "https://mintlify.com/schema.json",
|
||||
"name": "Honcho",
|
||||
"logo": {
|
||||
"dark": "/logo/honcho-light.svg",
|
||||
"light": "/logo/honcho-dark.svg"
|
||||
},
|
||||
"favicon": "/favicon.svg",
|
||||
"colors": {
|
||||
"primary": "#FF5A7E",
|
||||
"light": "#FF5A7E",
|
||||
"dark": "#FF5A7E",
|
||||
"anchors": {
|
||||
"from": "#FF5A7E",
|
||||
"to": "#FF5A7E"
|
||||
}
|
||||
},
|
||||
"topbarCtaButton": {
|
||||
"type": "github",
|
||||
"url": "https://github.com/plastic-labs/honcho"
|
||||
},
|
||||
"tabs": [
|
||||
{
|
||||
"name": "Guides",
|
||||
"url": "guides"
|
||||
},
|
||||
{
|
||||
"name": "API Reference",
|
||||
"url": "api-reference"
|
||||
}
|
||||
],
|
||||
"anchors": [
|
||||
{
|
||||
"name": "SDK Reference",
|
||||
"icon": "book-open-cover",
|
||||
"url": "https://api.python.honcho.dev"
|
||||
},
|
||||
{
|
||||
"name": "Community",
|
||||
"icon": "discord",
|
||||
"url": "https://discord.gg/plasticlabs"
|
||||
},
|
||||
{
|
||||
"name": "Blog",
|
||||
"icon": "newspaper",
|
||||
"url": "https://blog.plasticlabs.ai"
|
||||
}
|
||||
],
|
||||
"navigation": [
|
||||
{
|
||||
"group": "Get Started",
|
||||
"pages": [
|
||||
"getting-started/introduction",
|
||||
"getting-started/quickstart",
|
||||
"getting-started/architecture",
|
||||
"getting-started/self-hosting",
|
||||
"getting-started/deploying"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "About",
|
||||
"pages": [
|
||||
"about/contributing",
|
||||
"about/license"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Getting Started",
|
||||
"pages": [
|
||||
"guides/overview"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Application Interfaces",
|
||||
"pages": [
|
||||
"guides/discord"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Integrations",
|
||||
"pages": [
|
||||
"guides/langchain"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Personal Memory",
|
||||
"pages": [
|
||||
"guides/simple-memory",
|
||||
"guides/dialectic-endpoint"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "API Documentation",
|
||||
"pages": [
|
||||
"api-reference/introduction"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "apps",
|
||||
"pages": [
|
||||
"api-reference/endpoint/apps/get-app",
|
||||
"api-reference/endpoint/apps/update-app",
|
||||
"api-reference/endpoint/apps/get-app-by-name",
|
||||
"api-reference/endpoint/apps/create-app",
|
||||
"api-reference/endpoint/apps/get-or-create-app"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "users",
|
||||
"pages": [
|
||||
"api-reference/endpoint/users/get-users",
|
||||
"api-reference/endpoint/users/create-user",
|
||||
"api-reference/endpoint/users/get-user-by-name",
|
||||
"api-reference/endpoint/users/get-or-create-user",
|
||||
"api-reference/endpoint/users/update-user"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "sessions",
|
||||
"pages": [
|
||||
"api-reference/endpoint/sessions/get-sessions",
|
||||
"api-reference/endpoint/sessions/create-session",
|
||||
"api-reference/endpoint/sessions/get-session",
|
||||
"api-reference/endpoint/sessions/update-session",
|
||||
"api-reference/endpoint/sessions/delete-session",
|
||||
"api-reference/endpoint/sessions/get-chat"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "messages",
|
||||
"pages": [
|
||||
"api-reference/endpoint/messages/get-messages",
|
||||
"api-reference/endpoint/messages/create-message-for-session",
|
||||
"api-reference/endpoint/messages/get-message",
|
||||
"api-reference/endpoint/messages/update-message",
|
||||
"api-reference/endpoint/messages/get-metamessages",
|
||||
"api-reference/endpoint/messages/create-metamessage",
|
||||
"api-reference/endpoint/messages/get-metamessage",
|
||||
"api-reference/endpoint/messages/update-metamessage"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "collections",
|
||||
"pages": [
|
||||
"api-reference/endpoint/collections/get-collections",
|
||||
"api-reference/endpoint/collections/create-collection",
|
||||
"api-reference/endpoint/collections/get-collection-by-name",
|
||||
"api-reference/endpoint/collections/update-collection",
|
||||
"api-reference/endpoint/collections/delete-collection"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "documents",
|
||||
"pages": [
|
||||
"api-reference/endpoint/documents/get-documents",
|
||||
"api-reference/endpoint/documents/create-document",
|
||||
"api-reference/endpoint/documents/get-document",
|
||||
"api-reference/endpoint/documents/update-document",
|
||||
"api-reference/endpoint/documents/delete-document",
|
||||
"api-reference/endpoint/documents/query-documents"
|
||||
]
|
||||
}
|
||||
],
|
||||
"footerSocials": {
|
||||
"twitter": "https://twitter.com/plastic_labs",
|
||||
"github": "https://github.com/plastic-labs",
|
||||
"linkedin": "https://www.linkedin.com/company/plasticlabs"
|
||||
},
|
||||
"openapi": [
|
||||
"https://demo.honcho.dev/openapi.json"
|
||||
],
|
||||
"analytics": {
|
||||
"posthog": {
|
||||
"apiKey": "phc_1yrzzcgywqXGcerkkI4g7C0YfyPMcAKNOOvGcjTCiUk"
|
||||
}
|
||||
}
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,16 @@
|
|||
{
|
||||
"name": "honcho-docs",
|
||||
"version": "1.0.0",
|
||||
"description": "## Setting Up `honcho-docs` Locally",
|
||||
"main": ".pnp.js",
|
||||
"scripts": {
|
||||
"dev": "mintlify dev",
|
||||
"test": "echo \"Error: no test specified\" && exit 1"
|
||||
},
|
||||
"author": "",
|
||||
"license": "ISC",
|
||||
"dependencies": {
|
||||
"@mintlify/scraping": "^3.0.92",
|
||||
"mintlify": "^4.0.132"
|
||||
}
|
||||
}
|
||||
|
|
@ -7,7 +7,7 @@ from langchain.schema import AIMessage, HumanMessage, SystemMessage
|
|||
from langchain_community.chat_models.fake import FakeListChatModel
|
||||
|
||||
from honcho import Honcho
|
||||
from honcho.ext.langchain import _messages_to_langchain
|
||||
from honcho.ext.langchain import messages_to_langchain
|
||||
|
||||
app_name = str(uuid4())
|
||||
|
||||
|
|
@ -36,7 +36,7 @@ def chat():
|
|||
break
|
||||
user_message = HumanMessage(content=user_input)
|
||||
history = list(session.get_messages_generator())
|
||||
langchain_history = _messages_to_langchain(history)
|
||||
langchain_history = messages_to_langchain(history)
|
||||
prompt = ChatPromptTemplate.from_messages(
|
||||
[system, *langchain_history, user_message]
|
||||
)
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@ import os
|
|||
from uuid import uuid1
|
||||
import discord
|
||||
from honcho import Honcho
|
||||
from honcho.ext.langchain import _messages_to_langchain
|
||||
from honcho.ext.langchain import messages_to_langchain
|
||||
from graph import chat
|
||||
from dspy import Example
|
||||
|
||||
|
|
@ -61,7 +61,7 @@ async def on_message(message):
|
|||
session = user.create_session(location_id)
|
||||
|
||||
history = list(session.get_messages_generator())[:5]
|
||||
chat_history = _messages_to_langchain(history)
|
||||
chat_history = messages_to_langchain(history)
|
||||
|
||||
inp = message.content
|
||||
user_message = session.create_message(is_user=True, content=inp)
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@ import os
|
|||
from uuid import uuid1
|
||||
import discord
|
||||
from honcho import Honcho
|
||||
from honcho.ext.langchain import _messages_to_langchain
|
||||
from honcho.ext.langchain import messages_to_langchain
|
||||
from chain import LMChain
|
||||
|
||||
|
||||
|
|
@ -59,7 +59,7 @@ async def on_message(message):
|
|||
session = user.create_session(location_id)
|
||||
|
||||
history = list(session.get_messages_generator())
|
||||
chat_history = _messages_to_langchain(history)
|
||||
chat_history = messages_to_langchain(history)
|
||||
|
||||
inp = message.content
|
||||
user_message = session.create_message(is_user=True, content=inp)
|
||||
|
|
|
|||
|
|
@ -11,8 +11,7 @@ from langchain_core.output_parsers import StrOutputParser
|
|||
from langchain_core.messages import AIMessage, HumanMessage
|
||||
|
||||
from honcho import Honcho
|
||||
from honcho.ext.langchain import _messages_to_langchain
|
||||
>>>>>>> main
|
||||
from honcho.ext.langchain import messages_to_langchain
|
||||
|
||||
load_dotenv()
|
||||
|
||||
|
|
@ -68,7 +67,7 @@ async def on_message(message):
|
|||
session = user.create_session(location_id)
|
||||
|
||||
history = list(session.get_messages_generator())
|
||||
chat_history = _messages_to_langchain(history)
|
||||
chat_history = messages_to_langchain(history)
|
||||
|
||||
inp = message.content
|
||||
session.create_message(is_user=True, content=inp)
|
||||
|
|
|
|||
|
|
@ -5,6 +5,12 @@ 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/).
|
||||
|
||||
## [0.0.7] — 2024-04-01
|
||||
|
||||
### Changed
|
||||
|
||||
* Langchain conversion utility names
|
||||
|
||||
## [0.0.6] — 2024-03-21
|
||||
|
||||
### Added
|
||||
|
|
|
|||
|
|
@ -6,10 +6,12 @@ from __future__ import annotations
|
|||
|
||||
import datetime
|
||||
import json
|
||||
import os
|
||||
import uuid
|
||||
from typing import Optional
|
||||
|
||||
import httpx
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from .schemas import Document, Message, Metamessage
|
||||
|
||||
|
|
@ -345,7 +347,12 @@ class AsyncGetCollectionPage(AsyncGetPage):
|
|||
class AsyncHoncho:
|
||||
"""Honcho API Client Object"""
|
||||
|
||||
def __init__(self, app_name: str, base_url: str = "https://demo.honcho.dev"):
|
||||
def __init__(
|
||||
self,
|
||||
app_name: str,
|
||||
base_url: str = "https://demo.honcho.dev",
|
||||
api_key: str = "default",
|
||||
):
|
||||
"""Constructor for Client
|
||||
|
||||
Args:
|
||||
|
|
@ -353,21 +360,34 @@ class AsyncHoncho:
|
|||
base_url (str): Base URL for the instance of the Honcho API defaults to
|
||||
https://demo.honcho.dev
|
||||
"""
|
||||
load_dotenv()
|
||||
token = os.getenv("HONCHO_API_KEY", api_key)
|
||||
self.server_url: str = base_url # Base URL for the instance of the Honcho API
|
||||
self.client: httpx.AsyncClient = httpx.AsyncClient()
|
||||
self.client: httpx.AsyncClient = httpx.AsyncClient(
|
||||
headers={"Authorization": f"Bearer {token}"}
|
||||
)
|
||||
self.app_name: str = app_name # Representing name of the client application
|
||||
self.app_id: uuid.UUID
|
||||
self.metadata: dict
|
||||
|
||||
async def initialize(self):
|
||||
"""Run initialization tasks for the Honcho client"""
|
||||
res = await self.client.get(
|
||||
f"{self.server_url}/apps/get_or_create/{self.app_name}"
|
||||
)
|
||||
res.raise_for_status()
|
||||
data = res.json()
|
||||
self.app_id: uuid.UUID = data["id"]
|
||||
self.metadata: dict = data["metadata"]
|
||||
try:
|
||||
res = await self.client.get(
|
||||
f"{self.server_url}/apps/get_or_create/{self.app_name}"
|
||||
)
|
||||
res.raise_for_status()
|
||||
data = res.json()
|
||||
self.app_id: uuid.UUID = data["id"]
|
||||
self.metadata: dict = data["metadata"]
|
||||
except httpx.HTTPStatusError as e:
|
||||
error_content = e.response.content
|
||||
print(error_content)
|
||||
raise Exception(error_content) from None
|
||||
|
||||
async def init(self):
|
||||
"""Synonym for initialize"""
|
||||
await self.initialize()
|
||||
|
||||
async def init(self):
|
||||
"""Synonym for initialize"""
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ from honcho import AsyncSession, Session
|
|||
from honcho.schemas import Message
|
||||
|
||||
|
||||
def requires_langchain(func):
|
||||
def _requires_langchain(func):
|
||||
"""A utility to check if langchain is installed before running a function"""
|
||||
|
||||
@functools.wraps(func)
|
||||
|
|
@ -25,8 +25,8 @@ def requires_langchain(func):
|
|||
return wrapper
|
||||
|
||||
|
||||
@requires_langchain
|
||||
def _messages_to_langchain(messages: List[Message]):
|
||||
@_requires_langchain
|
||||
def messages_to_langchain(messages: List[Message]):
|
||||
"""Converts Honcho messages to Langchain messages
|
||||
|
||||
Args:
|
||||
|
|
@ -47,8 +47,8 @@ def _messages_to_langchain(messages: List[Message]):
|
|||
return new_messages
|
||||
|
||||
|
||||
@requires_langchain
|
||||
def _langchain_to_messages(
|
||||
@_requires_langchain
|
||||
def langchain_to_messages(
|
||||
messages, session: Union[Session, AsyncSession]
|
||||
) -> List[Message]:
|
||||
"""Converts Langchain messages to Honcho messages and adds to appropriate session
|
||||
|
|
|
|||
|
|
@ -6,10 +6,12 @@ from __future__ import annotations
|
|||
|
||||
import datetime
|
||||
import json
|
||||
import os
|
||||
import uuid
|
||||
from typing import Optional
|
||||
|
||||
import httpx
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from .schemas import Document, Message, Metamessage
|
||||
|
||||
|
|
@ -345,7 +347,12 @@ class GetCollectionPage(GetPage):
|
|||
class Honcho:
|
||||
"""Honcho API Client Object"""
|
||||
|
||||
def __init__(self, app_name: str, base_url: str = "https://demo.honcho.dev"):
|
||||
def __init__(
|
||||
self,
|
||||
app_name: str,
|
||||
base_url: str = "https://demo.honcho.dev",
|
||||
api_key: str = "default",
|
||||
):
|
||||
"""Constructor for Client
|
||||
|
||||
Args:
|
||||
|
|
@ -353,21 +360,34 @@ class Honcho:
|
|||
base_url (str): Base URL for the instance of the Honcho API defaults to
|
||||
https://demo.honcho.dev
|
||||
"""
|
||||
load_dotenv()
|
||||
token = os.getenv("HONCHO_API_KEY", api_key)
|
||||
self.server_url: str = base_url # Base URL for the instance of the Honcho API
|
||||
self.client: httpx.Client = httpx.Client()
|
||||
self.client: httpx.Client = httpx.Client(
|
||||
headers={"Authorization": f"Bearer {token}"}
|
||||
)
|
||||
self.app_name: str = app_name # Representing name of the client application
|
||||
self.app_id: uuid.UUID
|
||||
self.metadata: dict
|
||||
|
||||
def initialize(self):
|
||||
"""Run initialization tasks for the Honcho client"""
|
||||
res = self.client.get(
|
||||
f"{self.server_url}/apps/get_or_create/{self.app_name}"
|
||||
)
|
||||
res.raise_for_status()
|
||||
data = res.json()
|
||||
self.app_id: uuid.UUID = data["id"]
|
||||
self.metadata: dict = data["metadata"]
|
||||
try:
|
||||
res = self.client.get(
|
||||
f"{self.server_url}/apps/get_or_create/{self.app_name}"
|
||||
)
|
||||
res.raise_for_status()
|
||||
data = res.json()
|
||||
self.app_id: uuid.UUID = data["id"]
|
||||
self.metadata: dict = data["metadata"]
|
||||
except httpx.HTTPStatusError as e:
|
||||
error_content = e.response.content
|
||||
print(error_content)
|
||||
raise Exception(error_content) from None
|
||||
|
||||
def init(self):
|
||||
"""Synonym for initialize"""
|
||||
self.initialize()
|
||||
|
||||
def init(self):
|
||||
"""Synonym for initialize"""
|
||||
|
|
|
|||
|
|
@ -668,6 +668,21 @@ pytest = ">=7.0.0,<9"
|
|||
docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
|
||||
testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
|
||||
|
||||
[[package]]
|
||||
name = "python-dotenv"
|
||||
version = "1.0.1"
|
||||
description = "Read key-value pairs from a .env file and set them as environment variables"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "python-dotenv-1.0.1.tar.gz", hash = "sha256:e324ee90a023d808f1959c46bcbc04446a10ced277783dc6ee09987c37ec10ca"},
|
||||
{file = "python_dotenv-1.0.1-py3-none-any.whl", hash = "sha256:f7b63ef50f1b690dddf550d03497b66d609393b40b564ed0d674909a68ebf16a"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
cli = ["click (>=5.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.31.0"
|
||||
|
|
@ -968,4 +983,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.9"
|
||||
content-hash = "3265d992168555f7d9d60f6f03c18dc515b32de3b975290158b086d82247fefc"
|
||||
content-hash = "181a418ea413f687cc31004dc10c50b606aba04cd4073391270d11ab99430e56"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "honcho-ai"
|
||||
version = "0.0.6"
|
||||
version = "0.0.7"
|
||||
description = "Python Client SDK for Honcho"
|
||||
authors = ["Plastic Labs <hello@plasticlabs.ai>"]
|
||||
license = "AGPL-3.0"
|
||||
|
|
@ -10,6 +10,7 @@ packages = [{include = "honcho"}]
|
|||
[tool.poetry.dependencies]
|
||||
python = "^3.9"
|
||||
httpx = "^0.26.0"
|
||||
python-dotenv = "^1.0.1"
|
||||
|
||||
[tool.poetry.group.test.dependencies]
|
||||
pytest = "^7.4.4"
|
||||
|
|
|
|||
Loading…
Reference in New Issue