* 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>
* fix: Inconsistencies in Docs, health endpoint, troubleshooting guide
* fix: (docs) maintain consistency on postgres db name
* chore: (docs) update v2 contributing docs with updates db paths
* docs: overhaul self-hosting docs for provider-agnostic setup
- .env.template: lead with provider options (custom, vllm, google,
anthropic, openai, groq) instead of baking in vendor-specific keys.
All provider/model settings commented out so server fails fast until
configured. Separate endpoint config from per-feature provider+model
from tuning knobs.
- docker-compose.yml.example: fix healthcheck -d honcho -> -d postgres
to match POSTGRES_DB=postgres.
- config.toml.example: reorder and document LLM key section with
OpenRouter and vLLM examples.
- self-hosting.mdx: replace multi-vendor key table with provider options
table. Add examples for OpenRouter, vLLM/Ollama, and direct vendor
keys. Remove duplicated key lists from Docker/manual setup sections.
- configuration.mdx: replace scattered provider docs with provider types
table. Fix Docker Compose snippet to match actual compose file. Note
code defaults as fallback, not recommended path.
- troubleshooting.mdx: add alternative provider issues section (custom
provider config, model name format, Docker localhost, structured
output failures).
* docs: add Docker build troubleshooting for permission errors
- Document BuildKit requirement (RUN --mount syntax)
- AppArmor/SELinux blocking Docker builds on Linux
- Volume mount UID mismatch between host and container app user
- Note in self-hosting docs that Docker path builds from source
* docs: reframe self-hosting as contributor/dev path, point to cloud service
* Revert "docs: reframe self-hosting as contributor/dev path, point to cloud service"
This reverts commit 3e766eb1a9.
* docs: add production compose, model guidance, thinking budget docs
- Add docker-compose.prod.yml for VM/server deployment: no source
mounts, restart policies, 127.0.0.1-bound ports, cache enabled
- Add model tier guidance and community quick-start link to self-hosting
- Document THINKING_BUDGET_TOKENS gotcha for non-Anthropic providers
- Add reverse proxy examples (Caddy + nginx) to production section
- Add backup/restore commands to production considerations
* docs: simplify self-hosting to single provider, restructure config guide
Self-hosting page now defaults to one OpenAI-compatible endpoint
with one model for all features. Moved model tiers, alternative
providers, and per-feature tuning into the configuration guide.
Eliminated duplicate config priority sections, dev/prod split,
and redundant TOML examples.
* docs: merge compose files, restore provider/model to feature sections in .env.template
Single docker-compose.yml.example with dev sections commented out.
Moved PROVIDER and MODEL back alongside each feature in .env.template
so settings stay colocated with their module. Updated self-hosting
docs to reference single compose file.
* fix: broken anchor links, redundant migration step, minor inconsistencies
Fix 4 broken internal links (#llm-provider-setup, #llm-api-keys,
#which-api-keys-do-i-need, #alternative-providers) to point to
correct headings. Remove redundant Docker migration step (entrypoint
already runs alembic). Fix cache URL missing ?suppress=true in
reference config. Fix uv install command to use official method.
* docs: env template ready to use, simplify self-hosting flow
.env.template now has provider/model lines uncommented with
placeholder values — user just sets endpoint, key, and model name.
Thinking budgets default to 0 for non-Anthropic providers.
Self-hosting page: removed 30-line env var wall, LLM setup now
points to the template. Merged duplicate verify sections.
Removed api_key from SDK examples (auth off by default).
* docs: reorder next steps, configuration guide first
* fix: default embedding provider to openrouter for single-endpoint setup
Without this, embeddings default to openai which requires a separate
LLM_OPENAI_API_KEY. Setting to openrouter routes embeddings through
the same OpenAI-compatible endpoint as everything else.
* fix: review issues — hermes page, thinking budget, production wording
Hermes integration page: replaced inline Docker/manual setup with
link to self-hosting guide, added elkimek community link. Removed
old env var names (OPENAI_API_KEY without LLM_ prefix).
Troubleshooting: removed "or 1" from thinking budget guidance.
Self-hosting: softened "production-ready" to "production-oriented"
since auth is disabled by default.
* docs: model examples in template, expanded LLM setup, better verify flow
.env.template: added "e.g. google/gemini-2.5-flash" hints next to
model placeholders so users know the expected format.
Self-hosting: expanded LLM Setup to show the 3 things users need to
set (endpoint, key, model name) with find-replace tip. Added build
time note, deriver log check, and real smoke test (create workspace)
to verify section. Health check now notes it doesn't verify DB/LLM.
* fix: smoke test uses v3 API path, not v1
* docs: clarify deriver metrics port vs Prometheus host port
* fix: remove deprecated memoryMode from hermes config example
* docs: update hermes page to match current memory provider config
Updated config to match hermes-agent docs: removed apiKey (not needed
for self-hosted), added hermes memory setup CLI command, added config
fields table (recallMode, writeFrequency, sessionStrategy, etc.).
Better verification tests: store-and-recall across sessions, direct
tool calling test. Links to upstream hermes docs for full field list.
* fix: invalid THINKING_BUDGET_TOKENS=0 and missing docker/ in image
Comment out THINKING_BUDGET_TOKENS=0 in .env.template — deriver,
summary, and dream validators require gt=0. Dialectic levels also
commented out since non-thinking models don't need the override.
Add COPY for docker/ directory in Dockerfile so entrypoint.sh is
available when docker-compose.yml.example references it.
* chore: Additional troubleshooting step
---------
Co-authored-by: Vineeth Voruganti <13438633+VVoruganti@users.noreply.github.com>
* 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>
fix wording around deriving from multiple turns and remove bars
feat: add DEDUPLICATE config flag, when true, uses cosine+token similarly in tandem to dedup
* feat: add optional JWT and webhook secrets to honcho instance creation
* chore: ignore spurious warnings
* feat: add response format if using gpt-5 model family
* feat: add response models to all apis except anthropic
* fix: raise NotImplementedError for response models in AsyncAnthropic client
* chore: address review
* [WIP] representation structure + deriver cleanup
* chore: add tests, cleanup
* feat: [WIP: semi-working] representation object
* fix: alignment
* fix: make observations hashable for dedup
* fix: datetime formatting, observation counting
* fix: switch to int for message id, clean up representation
* feat: remove need for metadata working rep
* chore: cleanup
* fix: use tenacity instead of custom fns
* feat: add representation and card to context if desired
* feat: add semantically relevant observations
* fix: pass all params to streaming, nonblocking streaming
* feat: consolidate document saving, make working representation fetching much smarter
* chore: add 100% test coverage of representation util
* feat: basic dream infra
* feat: dream queue item first pass
* chore: fixes & cleanup from coderabbit
* fix: dreams scheduled when new document count reaches a certain threshold
* feat: wip: timed dreams (not working)
* fix: test
* fix: remove useless pyright ignore
* fix: executing dreams
* feat: dreaming
* feat: [WIP] longmemeval bench
* feat: add USE_PEER_CARD setting, fix longmem test driver
* feat: get full working rep for dialectic in one swoop -- fix representation_from_documents to use the proper timestamp!
* fix: timestamps for real, handle assistant qs in longmem
* fix: remove old client, add batching to longmem
* perf: remove duplicate detection, will move to background task
* feat: track perf metrics on evals
* feat: adjust deriver prompt to use peer_id, add question date to question, clean up deriver
* fix: label metrics by task for better perf trace
* chore: code review
* feat: add efficiency score to longmem bench
* chore: tuning and cleaning up eval
* chore: bring in the big prompts
* feat: add support for vllm client
* feat: perf: bundle db calls in deriver and dialectic, increase max conns in docker db
* feat: add merge-sessions flag to longmemeval, add SUMMARY_ENABLED flag
* fix: COLLECT_METRICS default false
* chore: display start/end message ids, don't include in metrics
* fix: break large messages apart for eval
* fix: only get/create collection when needed
* feat: properly attribute documents with message id ranges and add session name column to documents
* fix: revert move of get_or_create_collection (need for fkey)
* fix: always get collection with peer name even if it's none
* chore: coderabbit
* fix: give peer card its own config, expand document schema, refactor get_context to be parallel, various cleanup chores and bugfixes
* chore: refactor: reify observer/observed system across entire codebase, including db migration
* refactor: cleanup code organization, make singletons where desired
* refactor: replace embeddings store with representation manager
* chore: coderabbit cleanup
* chore: update migration to non-null session param in documents, general review and cleanup
* chore: merge branch 'main' into ben/deriver-tidy
* chore: review fixes
* fix: sum input tokens and set session context cutoff to MAX_INPUT_TOKENS - sum
* fix: CR comments + remove context var
* fix: CR comments 2
* fix: use cache decorator; rm logger
* refactor: re-fetch formatted history after getting global working rep
* chore: fill out missing metadata inputs in python sdk
* feat: add get_peer_config to python sdk, thoroughly document ts sdk and remove bad client usage
* feat: zod
chore: update tests
chore: bump version, changelog
* chore: python sdk version bump and changelog
* [WIP] feat: combine search methods and rework endpoint to include limit param
* chore: test new stainless config with library
* nits: coderabbit
* Merge branch 'ben/sdk-improvements' into ben/search-rrf
* chore: pre-commit hooks cleanup
* feat: thoroughly document observation config
* Update sdks/python/src/honcho/peer.py
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
* chore: v1.3.0
* feat: update version to 2.2.0 and enhance search functionality with arbitrary filters
- Remove unused config variables
- Added arbitrary filters to all search endpoints.
- Pluralize `filters` everywhere in SDKs for consistency
- Updated documentation and changelog to reflect these changes.
* expose core client in TS and Python SDKs (#150)
* expose core client from sdks
* align text
* fix: resolve get_effective_observe me race condition, default peer config (#176)
* fix: resolve get_effective_observe me race condition, default peer config
* fix: preserve custom config even after leaving
* chore: test cases, enqueue types
* Update sdks/typescript/package.json
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* chore: formatting
* chore: revert undesired changes to v1 spec, clean up docs, coderabbit
* feat: better search docs, fix worker.ts
* fix: correctly make ts params optional in cases, update docs
* chore: coderabbit
* chore: remove spurious package-lock
* feat: [WIP] introduce peer cards
* chore: remove search.mdx
* chore: clean up deriver
* feat: peer cards working in deriver
* feat: add basic peer_card_bench
* feat: refine peer card prompt, add mini-benchmark, switch to gpt-5-nano
* refactor: update peer card handling in dialectic functions and improve error handling
- Enhanced `get_peer_card` function to handle `ResourceNotFoundException`.
- Updated `dialectic_call` and `dialectic_stream` to accept `peer_card` and `target_peer_card` parameters.
- Modified prompt generation to include peer card information.
- Cleaned up whitespace in several files for consistency.
* chore: update mirascope dependency version in configuration files
- Bumped mirascope version from 1.25.1 to 1.25.5 in pyproject.toml and uv.lock.
- Added a note in config.py regarding peer card output token handling.
- Removed unnecessary comments in clients.py for clarity.
* fix: [coderabbit] improve error handling in set_peer_card and enhance logging
- Added a check in `set_peer_card` to raise `ResourceNotFoundException` if the peer does not exist.
- Updated logging in `CertaintyReasoner` to capture exceptions with Sentry when enabled.
- Refined logging messages for clarity and consistency across various functions.
- Cleaned up whitespace and formatting in several files for improved readability.
* refactor: update working representation handling and improve metadata key usage
- Introduced constants for representation collection names to enhance clarity and maintainability.
- Updated function signatures in `get_working_representation` and `set_working_representation` to require `session_name`.
- Simplified metadata key determination logic by using constants instead of hardcoded strings.
- Removed legacy fallback logic for working representation data retrieval.
- Refactored `save_working_representation_to_peer` to utilize the new `set_working_representation` function for improved code reuse.
* chore: update configuration files and enhance working representation settings
- Added new peer card settings and context token limits to `.env.template`, `config.toml.example`, and documentation.
- Introduced `WORKING_REPRESENTATION_MAX_OBSERVATIONS` to `DeriverSettings` for better control over observation storage.
- Updated `set_working_representation` to merge new observations while respecting the maximum limit.
- Improved docstrings for clarity and consistency across functions.
* feat: introduce LLMError exception and enhance error handling in deriver
- Added LLMError exception to handle failures in LLM calls, normalizing inputs into a JSON-serializable format.
- Updated CertaintyReasoner to raise LLMError on exceptions during LLM function calls.
- Enhanced QueueManager to log LLMError occurrences and re-queue messages appropriately.
- Modified test runner to support asynchronous operations and improved output formatting for test results.
- Updated test cases to include session information for better context.
* feat: add __repr__ method to QueueItem for improved string representation
- Implemented a __repr__ method in the QueueItem class to provide a clear and informative string representation of its attributes.
- Updated timeout handling in TestRunner to default to 10000.0 seconds when timeout_seconds is not set, enhancing robustness in polling operations.
* refactor: update peer card data structure and improve handling in related functions
- Changed return type of `get_peer_card` and `set_peer_card` to use `list[str]` instead of `str | None`.
- Updated `peer_card_call` and related functions to accommodate the new list structure for peer cards.
- Introduced `PeerCardQuery` model to standardize responses from peer card queries.
- Adjusted prompt generation in `peer_card_prompt` to reflect the new data structure.
- Modified benchmark tests to align with the updated peer card handling.
* refactor: adjust peer card output token settings and update related functions
- Increased `PEER_CARD_MAX_OUTPUT_TOKENS` from 2000 to 4000 in `DeriverSettings`.
- Updated `critical_analysis_call` to use `json_mode` and removed unused parameters.
- Modified benchmark tests to utilize the new `PEER_CARD_MAX_OUTPUT_TOKENS` setting.
- Removed obsolete `add_dislike.json` test file.
* refactor: update peer card handling in critical analysis and dialectic prompts
- Changed `peer_card` parameter type from `str | None` to `list[str] | None` in `critical_analysis_call` and related functions.
- Simplified error handling in `process_representation_task` by removing redundant try-except block.
- Updated prompt generation in `critical_analysis_prompt` and `dialectic_prompt` to format `peer_card` as a string with newlines.
- Adjusted benchmark tests to reflect changes in peer card structure and output formatting.
* refactor: update peer card test cases to use list structure
- Modified test cases in `test_representation_crud.py` to reflect the change in `peer_card` parameter type from `str` to `list[str]`.
- Updated assertions to accommodate the new list format for setting and retrieving peer cards.
- Ensured that tests for missing peers correctly handle the list input format.
* fix: improve formatting of peer card output in prompts
- Updated `peer_card_prompt` to join `old_peer_card` list elements with newlines for better readability.
- Removed outdated comment in `dialectic_prompt` regarding handling of non-existent cards.
* chore: [coderabbit] enhance docstring and logging in prompts and queue manager
- Updated the docstring in `critical_analysis_prompt` to provide detailed type annotations for parameters.
- Improved logging in `chat` to differentiate between single and multiple retrieved peer cards.
- Adjusted logging format in `QueueManager` to use a more structured approach for shutdown messages.
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Co-authored-by: Rajat Ahuja <rahuja445@gmail.com>
* 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
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* Update src/deriver/tom/long_term.py
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* 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.
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Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
adavyas
banteg
Vineeth Voruganti
Eri Barrett
Rajat Ahuja
doria
Benjamin McCormick
Ayush Paul