* Peer- and session-scoped JWTs were effectively workspace-scoped: auth() walked the route's declared scope and fell through to a workspace match, so a {w: ws-a, p: alice} token could act on any peer in ws-a.
* feat: peer keys can read sessions they belong to; require workspace on scoped keys
* fix: authorize JWTs by narrowest scope and gate member reads
Follow-up hardening on the narrowest-claim auth fix:
- Scope get_peer_config member-read to the caller's own peer; a session
member could previously read a co-member's per-session config.
- Enforce session membership on POST /peers/{id}/chat: the session_id
arrives in the body (invisible to require_auth), so a peer key could
read any session's injected message history. Check is_peer_in_session
in the handler before the dialectic runs.
- Consolidate the workspace-match check in auth() to a single hoisted
guard so no branch can silently re-open cross-workspace access.
- Normalize empty-string scope claims to None in verify_jwt so a blank
workspace can't satisfy the peer/session token-shape invariant.
- Extract scope_requires_workspace(), shared by verify_jwt and the keys
API so the creation-time guard and verification invariant can't drift.
route requires auth) and CLAUDE.md auth-scoping guidance.
- docs: describe narrow-scope key semantics in the platform reference.
---------
Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com>
* fix: Add JSON repair for truncated LLM responses across all providers and Gemini thinking budget support
LengthFinishReasonError from OpenAI-compatible providers (custom, openai, groq) was crashing the deriver
with 14k+ occurrences in production. The vLLM path already had repair logic but it was gated on
provider=="vllm", unreachable when routing through litellm as a custom provider.
- Extract shared _repair_response_model_json() helper for all providers
- Catch LengthFinishReasonError in OpenAI/custom parse() path and repair truncated JSON
- Add repair fallback to Anthropic and Gemini response_model paths
- Add repair fallback to Groq response_model path
- Pass thinking_budget_tokens to Gemini 2.5 models via thinking_config
- Add 14 tests covering repair paths for all providers and Gemini thinking budget
Fixes HONCHO-YC
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat: live llm integration tests
* feat: Consistent Model Config Protocol
* fix: migrate the remaining app callers off the legacy llm_settings path
* fix: Docs and regression tests
* fix: refactor llm runtime path to model-config-only API
* fix: refactor config to nested model-config source of truth
* fix: refactor llm streaming and tool dispatch through backends
* fix: cut over llm config to nested model_config only
* fix: collapse vllm and custom into openai_compatible transport
* feat: refactor llm config to explicit transports and bare model ids
* feat: (embed) Add configurability for embedding model
* fix: tests for embedding provider
* fix: Address Review Comments
* fix: (llm) remove Groq backend and per-vendor base URLs
* chore: move llm tests
* fix: (llm) address review findings — config regressions, backend bugs, dead code
* fix: address backend end silly errors
* chore: (docs) update configuration and self-hosting guides
* chore: fix tests
* fix: address code rabbit comments
* fix: add validation to the dream settings
* fix: further address code rabbit comments
* fix: Address Code Rabbit Comments
* fix: Another round of code rabbit
* fix: Address Code Rabbit Nits
* fix: tests
* refactor: rename thinking validator to reflect transport scope
_validate_anthropic_thinking_minimum only enforces the >=1024 rule for
Anthropic and no-ops for other transports, so the name was misleading
now that it's shared across ConfiguredModelSettings, FallbackModelSettings,
and ModelConfig. Renamed to _validate_thinking_constraints with a docstring
clarifying per-transport behavior. No logic change.
* fix(config): drop transport-specific thinking params when env override changes transport
_fill_defaults_for_nested_field previously preserved the default MODEL_CONFIG's
thinking_budget_tokens/thinking_effort across a transport override. This leaked
Gemini-family defaults (e.g. thinking_budget_tokens=1024) into OpenAI-transport
overrides, and the OpenAI backend then correctly rejected the unsupported param
at call time (OpenAI uses reasoning.effort, not a token budget).
The helper now strips thinking_budget_tokens and thinking_effort from the
default dict when the env override supplies a transport different from the
default's. Explicit thinking params in the override are preserved.
* fix(config): apply thinking-param strip to dialectic level merge too
DialecticSettings._merge_level_defaults does its own inline MODEL_CONFIG
merge (parallel to _fill_defaults_for_nested_field), so the previous fix
missed dialectic-level overrides. E.g. flipping
DIALECTIC_LEVELS__minimal__MODEL_CONFIG__TRANSPORT from gemini (default)
to openai still leaked the default thinking_budget_tokens=0 into the
openai config, which the OpenAI backend then rejected at call time.
The level-merge path now applies the same 'strip transport-specific
thinking params when transport changes' rule as the generic helper.
Added a regression test exercising the merge validator directly.
* refactor(llm): wire ModelConfig knobs through, prune clients.py migration leftovers
Three connected fixes to finish carving the LLM stack out of src/utils/clients.py
and into src/llm/:
1. Propagate ModelConfig tuning knobs into backend calls.
honcho_llm_call_inner built extra_params from only {json_mode, verbosity},
silently dropping top_p, top_k, frequency_penalty, presence_penalty, seed,
and operator-supplied provider_params from any ModelConfig. Thread the
selected config through ProviderSelection and merge
build_config_extra_params(selected_config) into extra_params; per-call
kwargs still win over provider_params defaults. Makes
_build_config_extra_params public as build_config_extra_params so
clients.py and request_builder.py share one translation. Adds
TestModelConfigExtraParamsPropagation covering OpenAI/Anthropic knob
propagation, provider_params passthrough, and per-call override
precedence.
2. Drop dead extract_openai_* duplicates in clients.py.
extract_openai_reasoning_content, extract_openai_reasoning_details, and
extract_openai_cache_tokens had no callers outside their own definitions
— the live implementations live in src/llm/backends/openai.py. -103
lines from clients.py.
3. Unify on ModelTransport, delete SupportedProviders.
The "google" vs "gemini" split forced a _provider_for_model_config
translation shim in two places. Replace all SupportedProviders usages
with ModelTransport, rename CLIENTS["google"] → CLIENTS["gemini"],
update provider branches + LLMError labels + reasoning-trace entries
accordingly. Trace JSONL now writes "provider": "gemini" instead of
"google" — consistent with the broader env-var rename cutover.
Also tidies up pre-existing basedpyright findings in tests/llm/test_model_config.py
(pydantic before-validator dict inputs + descriptor-proxy call).
ruff: clean. basedpyright: 0 errors, 0 warnings. Tests: 153/153 pass across
tests/utils/test_clients.py, tests/utils/test_length_finish_reason.py,
tests/llm/, tests/dialectic/, tests/deriver/.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* refactor(llm): finish the src/utils/clients.py → src/llm/ migration
honcho_llm_call_inner now delegates to request_builder.execute_completion
and execute_stream instead of re-implementing backend call scaffolding
inline. The new _effective_config_for_call helper carries per-call kwargs
(temperature, stop_seqs, thinking_budget_tokens, reasoning_effort) onto
the selected ModelConfig — or synthesizes a minimal config for the
test-only callers that pass provider+model directly. max_output_tokens
is zeroed on the effective config to preserve the current
"per-call max_tokens wins" semantic; honoring ModelConfig.max_output_tokens
is a separable correctness concern.
Side effect of routing through the new path: ConfiguredModelSettings'
thinking_budget_tokens validator now fires on synthesized configs.
test_anthropic_thinking_budget was asserting that a sub-1024 budget
propagated to Anthropic — bumped to 1024 to match what Anthropic actually
accepts.
Unified client construction. Promoted the cached client factories in
src/llm/__init__.py (get_anthropic_client, get_openai_client,
get_gemini_client, get_{anthropic,openai,gemini}_override_client) to
public API and added them to __all__. Promoted
credentials._default_transport_api_key → default_transport_api_key.
Deleted the duplicate _build_client and _default_credentials_for_provider
from clients.py; _client_for_model_config now falls through to the
public factories. CLIENTS dict and _get_backend_for_provider stay as the
mockable seam for the ~50 patch.dict(CLIENTS, {...}) test call sites.
Wired operator-configurable Gemini cached-content reuse end-to-end.
PromptCachePolicy moved from src/llm/caching.py into src/config.py so
ModelConfig can reference it as a field without a circular import;
caching.py re-exports the name for existing imports. Added
cache_policy: PromptCachePolicy | None on ConfiguredModelSettings,
FallbackModelSettings, ResolvedFallbackConfig, and ModelConfig.
resolve_model_config, _resolve_fallback_config, and
_select_model_config_for_attempt copy the field through.
honcho_llm_call_inner passes effective_config.cache_policy into
execute_completion / execute_stream, so operators opt in via
e.g. DERIVER_MODEL_CONFIG__CACHE_POLICY__MODE=gemini_cached_content
and the selection actually fires instead of sitting on a dead path.
New regression test test_cache_policy_reaches_gemini_backend asserts the
PromptCachePolicy object reaches the Gemini backend's extra_params.
ruff + basedpyright: clean. Tests: 154/154 pass across
tests/utils/test_clients.py, tests/utils/test_length_finish_reason.py,
tests/llm/, tests/dialectic/, tests/deriver/.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* refactor(llm): move all LLM orchestration into src/llm/ and delete clients.py
The 1624-line src/utils/clients.py has been carved up into focused modules
under src/llm/ and deleted. There is now one golden path for LLM
orchestration and no dual entrypoint.
New module layout:
src/llm/
__init__.py thin stable re-export surface
api.py public honcho_llm_call with retry + fallback + tool
loop delegation
executor.py honcho_llm_call_inner (single-call executor); bridges
to request_builder.execute_completion / execute_stream
tool_loop.py execute_tool_loop + stream_final_response, plus
assistant-tool-message and tool-result formatting
runtime.py AttemptPlan dataclass (replaces the loose
ProviderSelection NamedTuple), effective_config_for_call,
plan_attempt, per-retry temperature bump, attempt
ContextVar
registry.py single owner of CLIENTS dict + cached default and
override SDK-client factories + backend/history-adapter
selection + high-level get_backend(config)
conversation.py count_message_tokens, tool-aware message grouping,
truncate_messages_to_fit
types.py HonchoLLMCallResponse, HonchoLLMCallStreamChunk,
StreamingResponseWithMetadata, IterationData,
IterationCallback, ReasoningEffortType, VerbosityType,
ProviderClient
request_builder.py low-level request assembly (ModelConfig → backend
complete/stream); no longer owns credential resolution
credentials.py default_transport_api_key, resolve_credentials
caching.py gemini_cache_store; re-exports PromptCachePolicy
from src.config
backend.py Protocol + normalized result types
history_adapters.py provider-specific assistant/tool message shapes
structured_output.py
backends/ AnthropicBackend, OpenAIBackend, GeminiBackend
handle_streaming_response had no production callers; it is deleted. The
three tests that used it now drive honcho_llm_call_inner(stream=True,
client_override=...) directly, which exercises the same code path the
public API uses.
Dead credential passthrough removed. The ProviderBackend Protocol and
all three concrete backends no longer accept api_key / api_base — those
are baked into the underlying SDK client at registry construction time
and were being del'd everywhere they appeared. request_builder also
stops resolving and forwarding them.
Client construction is unified. The cached default-client factories
(get_anthropic_client, get_openai_client, get_gemini_client) and override
factories (get_*_override_client) are promoted to public API; the
module-level CLIENTS dict populates from them and remains the
patch.dict(CLIENTS, {...}) mocking seam tests rely on. Old duplicate
helpers (_build_client, _default_credentials_for_provider) are gone.
default_transport_api_key is promoted to public.
Application imports now come from src.llm (dreamer, dialectic, deriver,
summarizer, telemetry-adjacent tests). No code imports from
src.utils.clients anywhere in the repo.
ruff: clean. basedpyright: 0 errors, 0 warnings. Tests: 1013/1013 pass
across the entire non-infra test suite (excluding tests/unified,
tests/bench, tests/live_llm, tests/alembic).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(llm): sanitize tool schemas for Gemini's function_declarations validator
Gemini's native-transport function-declarations validator accepts a narrow
subset of JSON-Schema / OpenAPI: type, format, description, nullable, enum,
properties, required, items, minItems, maxItems, minimum, maximum, title.
Anything else — additionalProperties, allOf, if/then/else, $ref, anyOf,
oneOf, $defs, patternProperties — triggers an INVALID_ARGUMENT 400 at call
time.
Our agent tool schemas in src/utils/agent_tools.py use several of those
(additionalProperties: false, allOf + if/then conditionals) because they
were authored for OpenAI strict-mode + Anthropic, which need the richer
vocabulary. GeminiBackend._convert_tools was passing them straight through.
Add _sanitize_schema(): walks the parameters tree and drops unsupported
keywords while preserving semantics for the keywords that hold user data
(properties maps field-name → sub-schema; required / enum are lists of
literals; items is a single sub-schema). Other backends are untouched and
continue to receive the full strict schemas.
Regression tests:
- test_gemini_sanitize_schema_strips_unsupported_keywords: confirms
additionalProperties, allOf + if/then, and $defs are stripped at nested
levels while legitimate fields survive.
- test_gemini_convert_tools_sanitizes_parameters_schema: end-to-end
_convert_tools output has no forbidden keys.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix: fix tool calling syntax for gemini
* refactor(llm): normalize defaults, widen OpenAI reasoning-model routing
* chore: fix test
* fix(llm): address post-migration review feedback
* fix(llm): gemini robustness + dreamer specialist ergonomics
* chore: addres review comments
* chore: (docs) unrelease changelog addition
* chore: (docs) merge commit changes
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Erosika <eri@plasticlabs.ai>
* chore: 3.0 honcho and 2.0 sdks changelog
fix: use PeerContextResponse in peer.ts
* chore: move docs to /v3/, build SDKs
* chore: code review
* feat: [WIP] migrate away from stainless in typescript sdk
* chore: move api from /v2/ to /v3/
* feat: no-stainless typescript with real tests
* feat: migrate python sdk off of stainless
* feat: clean typescript sdk
* chore: add tests for ts http client
* fix: rewrite entire python sdk in new format, update typescript sdk to use `configuration` not `config` for consistency with API
* fix: clean up SDKs, synchronize
* chore: update sdk examples
* chore: update OpenAPI documentation and SDK examples to reflect changes
* fix: better test
* fix: install deps in test runner, improve robustness of streaming in sdk, coderabbit nits
* fix: standardize around camelCase in TS SDK
* refactor: update configuration handling in SDKs to use typed models for workspace, session, and peer configurations
* docs: clarify queue status usage and remove polling methods from SDKs
add claude skills for migrations
* chore: fix links in docs
* feat: add deriver flush mode to bypass batch token threshold
- Introduced `is_deriver_flush_enabled` function to check if flush mode is active.
- Updated `QueueManager` to conditionally apply batch token thresholds based on flush mode.
- Enhanced `UnifiedTestExecutor` to enable flush mode via Redis.
- Added `flush` parameter to test cases to facilitate testing of flush mode behavior.
- Updated various test cases to utilize the new flush functionality.
* feat: implement schedule_dream functionality in SDKs, use in unified test runner
- Added `schedule_dream` method to both Python and TypeScript SDKs for scheduling dream tasks.
- Updated HTTP routes to include endpoint for scheduling dreams.
- Enhanced test runner to utilize the new `schedule_dream` method for scheduling actions.
- Updated TypeScript client to support the new scheduling functionality with appropriate parameters.
* feat: update single deriver task to support multiple observers
- Changed the `observer` parameter to `observers` as a list in multiple functions across the deriver module.
- Updated the processing logic to handle multiple observers for representation tasks.
- Adjusted related payload and queue management functions to accommodate the new observers structure.
- Modified tests to reflect changes in the representation task handling and ensure proper functionality.
* refactor: update enqueue tests to support deduplication of queue items with multiple observers
- Modified tests in `test_enqueue.py` to reflect changes in the queue item structure, where each message now results in a single queue item containing a list of observers.
- Updated assertions to validate that the `observers` field correctly includes all relevant peers, ensuring proper functionality of the deduplication logic.
- Removed redundant payload matching logic to streamline test cases and improve clarity.
* fix: add backwards compatibility for representation work unit keys and payload observers
* feat: update dialectic configuration and introduce cost calculator
- Adjusted LLM and dialectic settings in `.env.template`, `config.toml.example`, and `src/config.py` to reduce maximum tool output characters and session history tokens for cost efficiency.
- Implemented a new `dialectic_cost_calculator.py` script to estimate costs based on reasoning levels and model pricing.
- Enhanced `DialecticAgent` to utilize minimal tools and adjusted output token settings based on reasoning level to optimize performance and reduce costs.
* feat: add reasoning level to chat input in unified test runner
- Enhanced the `UnifiedTestExecutor` to include a `reasoning_level` parameter in the chat method call.
- Updated the `QueryAction` model to support the new `reasoning_level` attribute, allowing for more nuanced chat interactions.
* feat: run deriver once for multiple observers (#335)
* feat: update single deriver task to support multiple observers
- Changed the `observer` parameter to `observers` as a list in multiple functions across the deriver module.
- Updated the processing logic to handle multiple observers for representation tasks.
- Adjusted related payload and queue management functions to accommodate the new observers structure.
- Modified tests to reflect changes in the representation task handling and ensure proper functionality.
* refactor: update enqueue tests to support deduplication of queue items with multiple observers
- Modified tests in `test_enqueue.py` to reflect changes in the queue item structure, where each message now results in a single queue item containing a list of observers.
- Updated assertions to validate that the `observers` field correctly includes all relevant peers, ensuring proper functionality of the deduplication logic.
- Removed redundant payload matching logic to streamline test cases and improve clarity.
* fix: add backwards compatibility for representation work unit keys and payload observers
* feat: refactor benchmark runners to share common functionality
- Introduced a new `runner_common.py` module containing shared utilities for benchmark test runners, including common argument parsing, client creation, and queue management.
- Updated `BEAMRunner`, `LoCoMoRunner`, and `LongMemEvalRunner` to inherit from `RunnerMixin`, leveraging shared functionality for metrics collection and logging.
- Added `reasoning_level` and `redis_url` parameters to runner constructors for enhanced configuration.
- Streamlined argument parsing by utilizing `add_common_arguments` for shared command-line options across all runners.
* fix: update last_user_message handling to use message content instead of ID
* fix: standardize config vs configuration
---------
Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com>
* feat: add complex arbitrary filtering on all objects
* fix: safe numeric casting and application of comparators
* fix: add way more tests, fix bugs with filter parsing
* chore: pass model_class as arugment to apply_filter
* fix: default to not caring about is_active in get_sessions_for_peer
* fix: address coderabbit complaints (valid)
* fix: throw filter errors when necessary, validate inputs and handle edge cases with more tests
* fix: remove all type errors and most type warnings
* fix: don't use db in tests that don't need it
cheat: sprinkle in some pyright: ignore in filter.py
* fix: allowlist for filtering -- no filtering by content, message id, or anything internal
* fix: handle mixed types in metadata, add tests
* chore: refine types
* chore: rename fiter param everywhere
* type stuff
* add action
* bump python
* Refactor type annotations and update tracking decorators in agent and dependencies modules. Replace ai_track with track from src.utils.types, and enhance type hints for better clarity. Update pyproject.toml to allow untyped libraries.
* type everything basically
* fix migration typing
* type like crazy
* remove usless tests
* Update mocks in tests to use AsyncMock for dialectic_call and dialectic_stream, ensuring proper async behavior in test cases. Adjust mock return values for consistency and clarity.
* Update src/deriver/tom/single_prompt.py
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
* Update src/deriver/tom/long_term.py
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
* Enhance CLAUDE.md documentation with additional details on core concepts, API structure, and development commands. Update command syntax for running server and tests to use 'uv run' for consistency. Improve clarity in configuration and architectural decisions sections.
* Refactor type annotations in CRUD functions to accept more flexible filter types, changing from dict[str, str] to dict[str, Any]. Clean up logging in agent.py by removing unnecessary timing logs for user representation generation and query execution.
* Remove unused import of ai_track from long_term.py and single_prompt.py to clean up the codebase.
* pass tests
* update some stuff
* fix unused
* ruff
* make stuff work again
* Add LLM_GROQ_API_KEY to GitHub Actions and format tom_inference parameters
* test
* test
* Refactor LLM settings to use 'gemini' provider and update related model parameters; remove unused API keys from GitHub Actions workflow.
* Update LLM settings to use 'anthropic' provider and change model to 'claude-3-5-haiku-20241022'; maintain existing summarization provider.
* test
* llm provider stuff
* update
* revert
* Integrate client management for LLM providers across various modules; remove deprecated environment variable setup for API keys.
* only if key avaialble
* Refactor type hints and improve schema definitions for queue processing; remove unused imports and enhance function signatures for clarity.
* fix test
* model
* test
* Update LLM provider type annotations and enhance client management; replace Provider with Providers for better type handling in config and clients modules.
* Refactor LLM provider handling to default to "openai" for custom providers across multiple modules; update type annotations and improve client management for consistency.
---------
Co-authored-by: Dani Balcells <18307962+danibalcells@users.noreply.github.com>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
* chore: Update versioning for release
* fix: remove db creation at start and sync migrations and models
* fix: Checkpoint changing metamessage schema
* chore: linter fixes
* fix: session cloning working
* Hybrid long-term memory (#92)
* Add TOM method switching
* Add system prompt and note on format
* Add persistence tweaks
* Specify format for each section of user representation
* Parse XML tags before saving representation metamessage
* Clean up
* Use Claude 3.5 Haiku and refine prompt
* Simplify message processing
* chore: update token limit on dialectic and model for deriver
* Add embedding-based long-term fact retrieval
* Fix bug preventing new documents from being created
* Use multiple queries + tweak prompt
* Fix collection name bug + add duplicate removal
* First implementation of on-demand user rep generation
* WIP debug on-demand user rep changes
* Fixed representations not being stored & deriver issue
* Some speed improvements
* Play with number of facts / queries
* WIP prompt caching for Claude
* WIP fix anthropic caching
* Anthropic prompt caching working but messages too short
* Use Cerebras for small inferences
* Make dialectic responses 1000 tokens max
* Make user representation generation model a constant
* Use llama 3.1 8b for query generation
* Update env template
* Add crud.get_or_create_protected_collection
* rabbit comments
* Fix linter issues
* Add Cerebras to stream router method
* Better handling of default-empty string args
* Change prints to debug logs
* Add error handling to TOM inference
* Handle missing/empty client in model responses
* Handle no messages case in get_chat_history
* Fix indent
* Add error handling to single_prompt methods
* Fix get_or_create_user_protected_collection
* Simplify openAI-compatible model client instantiation
* Remove health endpoint
* Remove LocalEmbeddingStore
* Change prints to debug logs
* Change sentry track
* Code review changes
* Add README to ToM module
* Switch to Groq
* Fix inconsistent openai compatible provider list in stream()
* Update env template to include Groq variables
* Add model_client tests
* fix: Fix unit tests
---------
Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com>
* add scoped API keys (#91)
* add AUTH_JWT_SECRET and ADMIN_KEY, use in security middleware (TODO granular keys)
* WIP: convert all API paths to use scoped keys
* add basic unit tests for API keys, ruff formatting
* MVP of route using JWT for payload
* add get_user_from_token
* add key table to postgres, use it to enable key revocation
* add key revocation pt 2 -- fix order of param checks
* finish convenience routes that assume params from JWT
* add tests for key API
* get_keys
* add secrets utility script, add key rotation, fill out tests
* add tiny cache as PoC
* nits, validations, etc
* only create keys table migration if necessary
* fix keys tests to always use auth
* tiny fix to make custom DATABASE_SCHEMA work
* review: add better docs, fix security issue with cache, clear db on rotation, and more
* remove rotation
* remove key database entirely
* Add `/all` path to get all apps (#94)
* add `/all` path for apps
* assert vector extension installed (need this for groudon)
* review
---------
Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com>
* add scoped API keys (#91)
* add AUTH_JWT_SECRET and ADMIN_KEY, use in security middleware (TODO granular keys)
* WIP: convert all API paths to use scoped keys
* add basic unit tests for API keys, ruff formatting
* MVP of route using JWT for payload
* add get_user_from_token
* add key table to postgres, use it to enable key revocation
* add key revocation pt 2 -- fix order of param checks
* finish convenience routes that assume params from JWT
* add tests for key API
* get_keys
* add secrets utility script, add key rotation, fill out tests
* add tiny cache as PoC
* nits, validations, etc
* only create keys table migration if necessary
* fix keys tests to always use auth
* tiny fix to make custom DATABASE_SCHEMA work
* review: add better docs, fix security issue with cache, clear db on rotation, and more
* remove rotation
* remove key database entirely
* Add `/all` path to get all apps (#94)
* add `/all` path for apps
* assert vector extension installed (need this for groudon)
* review
---------
Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com>
* chore: README and CHANGELOG updates
* add JWT expiry
* fix: Consolidate get methods with JWT token resolution
* chore: Add Annotation to Path, Query, and Body params
* chore: run ruff formatter
* chore: nits & add one exhaustive test of a query route
* fix: undo change to fly.toml
* fix: Langfuse tracing
* Consolidate Get Methods (#96)
* fix: Consolidate get methods with JWT token resolution
* chore: Add Annotation to Path, Query, and Body params
* chore: run ruff formatter
* chore: nits & add one exhaustive test of a query route
* fix: undo change to fly.toml
---------
Co-authored-by: dr-frmr <docterformer@protonmail.com>
* fix: dev-667 fix streaming endpoint
* fix: Anthropic Langfuse Tracing
* fix: add scripts folder to dockerfile
* fix: Remove redundant fields from pydantic schemas
* fix: Add deeper protection on reserved collection
* fix: Consolidate chat and stream methods
* docs: Update Mintlify API Reference and Changelog
* remove langchain guide, update architecture diagram
* honcho mcp server
* chore: Update .env template
* update discord, temporarily remove other guides
* Limit dialectic & deriver context usage with two-scale progressive summarization (#97)
* WIP two tiered summaries
* Move to process_item
* Save user rep metamessage even if no message_id
* Change number of messages per short summary
* Fix broken mock
* Remove prints
* chore: fix test
---------
Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com>
* feat: Add Gemini Support, link facts to message, use 8b for dialectic fact queries
* chore: Styling
* chore: coderabbit nitpicks
* keep dialectic guide
* Add streaming guide
* Remove TODO from dialectic guide
* Fix JS snippets that referred to honcho singleton as client
* Add App explanation to architecture page
---------
Co-authored-by: Dani Balcells <18307962+danibalcells@users.noreply.github.com>
Co-authored-by: doria <93405247+dr-frmr@users.noreply.github.com>
Co-authored-by: dr-frmr <docterformer@protonmail.com>
Co-authored-by: vintro <vince@plasticlabs.ai>
Co-authored-by: Daniel Balcells <dbalcells@gmail.com>
Rajat Ahuja
Vineeth Voruganti
doria
Benjamin McCormick
Ayush Paul