RomanNum3ral
/
honcho
mirror of https://github.com/plastic-labs/honcho.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

chore(docs): Update changelogs and increment version (#713)

This commit is contained in:
Vineeth Voruganti 2026-05-21 14:32:41 -04:00 committed by GitHub
parent 0cf63c10da
commit 7470866d12
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
13 changed files with 643 additions and 1928 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

77
CHANGELOG.md
View File

@ -5,39 +5,74 @@ 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/).
## [Unreleased]
## [3.0.7] - 2026-05-21
### Added
- New `src/llm/` package as the single owner of provider runtime: clients, backends, history adapters, tool loop, request builder, credentials, and caching policy
- `AttemptPlan` dataclass captures per-retry provider selection (client, model, reasoning_effort, thinking_budget_tokens, selected_config) and pins it across stream-final retries so streaming doesn't bounce back to primary after the tool loop has settled on fallback
- Gemini JSON-schema sanitizer for `function_declarations` — strips keywords Gemini's validator rejects (`additionalProperties`, `allOf`, etc.) while preserving semantics for all other backends
- Dreamer specialists derive `effective_max_tokens` from `model_config.max_output_tokens` with a per-specialist default fallback
- Regression tests covering fallback-config thinking-param reach, provider_params → extra_params boundary, OpenAI reasoning-model parameter routing, Gemini blocked finish_reason handling, and fail-fast `max_tool_iterations` validation
- New `src/llm/` module as the single owner of provider runtime: clients, backends, history adapters, tool loop, request builder, credentials, and caching policy (#459)
- `AttemptPlan` dataclass captures per-retry provider selection (client, model, reasoning_effort, thinking_budget_tokens, selected_config) and pins it across stream-final retries so streaming doesn't bounce back to primary after the tool loop has settled on fallback (#459)
- Gemini JSON-schema sanitizer for `function_declarations` — strips keywords Gemini's validator rejects (`additionalProperties`, `allOf`, etc.) while preserving semantics for all other backends (#459)
- Dreamer specialists derive `effective_max_tokens` from `model_config.max_output_tokens` with a per-specialist default fallback (#459)
- New cloudevent `LLMCallCompletedEvent` (`llm.call.completed`) fires once per provider hit with full cost-attribution context: transport/provider_label, model, token counts with cache breakdown, finish_reason, outcome, `is_final_attempt`, retry/fallback state, duration, tool-call shape, streaming flag, and agent correlation (`run_id` + iteration). Includes a `CallPurpose` closed enum (`deriver.representation`, `dialectic.answer`, `dream.deduction|induction`, `summary.short|long`) (#637)
- `RepresentationCompletedEvent` now carries `total_input_tokens` for full-trace cost attribution (#637)
- Per-emitter `honcho_version` injection on all CloudEvents plus emitter health metrics (#637)
- `TelemetrySettings.HIGH_VOLUME_SAMPLE_RATE` (default 1.0) — deterministic per-`run_id` sampler so an entire agent trace is kept or dropped together; aggregate envelopes bypass the sampler (#637)
- Deriver custom instructions: per-workspace/peer guidance threaded into the deriver prompt with a `MAX_CUSTOM_INSTRUCTIONS_TOKENS` budget (default 2000); deriver `MAX_INPUT_TOKENS` raised 23000 → 25000 to make room (#609)
- Configurable embedding dimensions: `EMBEDDING_MODEL_CONFIG__DIMENSIONS_MODE` (`auto`/`always`/`never`) controls whether the OpenAI `dimensions=` parameter is forwarded; `auto` (default) sends it when the operator explicitly set `EMBEDDING_VECTOR_DIMENSIONS` and the model is not on the known-rejecting allowlist (#678)
- New `honcho-cli` package — Python CLI for inspecting and managing peers, sessions, and configuration against a Honcho deployment (#424)
- `HONCHO_API_URL` env var support in the MCP Worker, enabling self-hosted Honcho deployments to point the Worker at their own instance instead of `https://api.honcho.dev` (#575)
- API ID `max_length` increased from 100 to 512 across `WorkspaceCreate`, `PeerCreate`, and `SessionCreate` to align the API contract with the underlying DB schema (#684)
- Regression tests covering fallback-config thinking-param reach, provider_params → extra_params boundary, OpenAI reasoning-model parameter routing, Gemini blocked finish_reason handling, and fail-fast `max_tool_iterations` validation (#459)
### Changed
- All LLM orchestration moved out of `src/utils/clients.py` into `src/llm/` with modules split by responsibility (api, executor, tool_loop, runtime, registry, conversation, request_builder, credentials, caching, backends, history_adapters)
- Default `ModelConfig` factories (deriver, summary, dreamer specialists, dialectic levels) normalized to `openai/gpt-5.4-mini` with no extra parameters set by default; operators add transport/thinking overrides explicitly
- OpenAI reasoning-model routing widened via `_uses_max_completion_tokens` heuristic covering `gpt-5.x` and `o1/o3/o4` — these models receive `max_completion_tokens` instead of `max_tokens`
- Override client factories switched from unbounded `@cache` to `@lru_cache(maxsize=128)` for predictable memory growth on long-running processes
- `get_backend` now delegates to `client_for_model_config`, so the live-test path and production path share one missing-API-key validation
- Blocked Gemini responses (`SAFETY`, `RECITATION`, `PROHIBITED_CONTENT`, `BLOCKLIST`) raise `LLMError` in the streaming path too (previously only the non-streaming path), ensuring retry/fallback logic fires uniformly
- Transport-change env overrides now strip transport-specific thinking params (thinking_budget_tokens vs. reasoning_effort) during config merge, including at the dialectic-level merge, so switching from Anthropic → OpenAI doesn't leave orphaned Anthropic-only params that the OpenAI backend would reject
- `max_tool_iterations` out-of-range inputs now raise `ValidationException` instead of being silently clamped
- Troubleshooting docs updated to reflect nested-env-var form for per-component thinking-budget overrides
- All LLM orchestration moved out of `src/utils/clients.py` into `src/llm/` with modules split by responsibility (api, executor, tool_loop, runtime, registry, conversation, request_builder, credentials, caching, backends, history_adapters) (#459)
- Default `ModelConfig` factories (deriver, summary, dreamer specialists, dialectic levels) normalized to `openai/gpt-5.4-mini` with no extra parameters set by default; operators add transport/thinking overrides explicitly (#459)
- OpenAI reasoning-model routing widened via `_uses_max_completion_tokens` heuristic covering `gpt-5.x` and `o1/o3/o4` — these models receive `max_completion_tokens` instead of `max_tokens` (#459)
- Override client factories switched from unbounded `@cache` to `@lru_cache(maxsize=128)` for predictable memory growth on long-running processes (#459)
- `get_backend` now delegates to `client_for_model_config`, so the live-test path and production path share one missing-API-key validation (#459)
- Blocked Gemini responses (`SAFETY`, `RECITATION`, `PROHIBITED_CONTENT`, `BLOCKLIST`) raise `LLMError` in the streaming path too (previously only the non-streaming path), ensuring retry/fallback logic fires uniformly (#459)
- Transport-change env overrides now strip transport-specific thinking params (thinking_budget_tokens vs. reasoning_effort) during config merge, including at the dialectic-level merge, so switching from Anthropic → OpenAI doesn't leave orphaned Anthropic-only params that the OpenAI backend would reject (#459)
- `max_tool_iterations` out-of-range inputs now raise `ValidationException` instead of being silently clamped (#459)
- Public API schemas (`WorkspaceCreate`, `PeerCreate`, `SessionCreate`) and SDK validation (`api_types.py`, `validation.ts`) accept IDs up to 512 chars (was 100) (#684)
- Peer card prompts reframed as stable identity markers (replaces the prior "biographical/profile facts" language). Induction specialist is now opted out of peer card writes (`can_update_peer_card = False`) so only deduction touches the card (#686)
- Vector store queries no longer fetch embedding vectors — only document metadata is returned, reducing payload size and DB load (pgvector, lancedb, turbopuffer) (#682)
- Langfuse trace metadata now includes `namespace`, `model`, and `provider` so traces can be filtered by deployment slice (#565)
- Deriver: model-aware tokenizer (replaces the previously hardcoded encoding) and explicit guard on empty message content (#647)
- Dialectic level defaults now merge correctly with per-level overrides in `src/config` (DEV-1733) (#656)
- Default dialectic tool choice switched from forced/required to `auto` (#630)
- Vector sync given a substantial retry budget to tolerate transient embedding provider outages (#604)
- `AgentToolConclusionsDeletedEvent` payload now carries `levels` for parity with the rest of the conclusion event surface (#612)
- Turbopuffer vector store: `InternalServerError` caught and surfaced as a warning rather than a hard failure; unused `upsert_with_retry` and `VectorUpsertResult` removed; explicit silent and explicit-error paths for vector DB server errors (#561)
- Troubleshooting docs updated to reflect nested-env-var form for per-component thinking-budget overrides (#459)
- README refresh (#681)
- CLAUDE.md refreshed against the current `src/` layout (#680)
### Fixed
- Fallback `ModelConfig` temperature and `thinking_budget_tokens` reach the backend on the final retry — previously the primary's values were pre-populated into caller kwargs early and clobbered fallback values via `effective_config_for_call(update=...)`
- Stream-final retries pin to the `AttemptPlan` that succeeded rather than re-running provider selection through the outer `current_attempt` ContextVar (which could roll streaming back to primary after the tool loop had already switched to fallback)
- OpenAI structured-output calls continue to use `chat.completions.parse()` with strict schema enforcement, while tool-calling paths use `chat.completions.create()` without `strict:True` for broader proxy compatibility (OpenRouter, vLLM, Ollama)
- Gemini `cached_content` reuse keys now include `system_instruction` and `tool_config` so cache hits don't cross configurations that differ only in those fields
- `reverse` query parameter is now honored on the v3 workspace list (`POST /v3/workspaces/list`), peer list (`POST /v3/workspaces/{workspace_id}/peers/list`), workspace-scoped session list (`POST /v3/workspaces/{workspace_id}/sessions/list`), and peer-scoped session list (`POST /v3/workspaces/{workspace_id}/peers/{peer_id}/sessions`). Honcho SDKs at 2.1.0+ were already sending `reverse=true` for these routes but the server silently ignored it. Ties on `created_at` now fall back to the internal nanoid `id` so ordering remains stable across pages.
- Fallback `ModelConfig` temperature and `thinking_budget_tokens` reach the backend on the final retry — previously the primary's values were pre-populated into caller kwargs early and clobbered fallback values via `effective_config_for_call(update=...)` (#459)
- Stream-final retries pin to the `AttemptPlan` that succeeded rather than re-running provider selection through the outer `current_attempt` ContextVar (which could roll streaming back to primary after the tool loop had already switched to fallback) (#459)
- OpenAI structured-output calls continue to use `chat.completions.parse()` with strict schema enforcement, while tool-calling paths use `chat.completions.create()` without `strict:True` for broader proxy compatibility (OpenRouter, vLLM, Ollama) (#459)
- Gemini `cached_content` reuse keys now include `system_instruction` and `tool_config` so cache hits don't cross configurations that differ only in those fields (#459)
- Removed strict parameter validation for thinking params on Anthropic and OpenAI transports — was rejecting valid per-transport configs (#686)
- `reverse` query parameter is now honored on the v3 workspace list (`POST /v3/workspaces/list`), peer list (`POST /v3/workspaces/{workspace_id}/peers/list`), workspace-scoped session list (`POST /v3/workspaces/{workspace_id}/sessions/list`), and peer-scoped session list (`POST /v3/workspaces/{workspace_id}/peers/{peer_id}/sessions`). Honcho SDKs at 2.1.0+ were already sending `reverse=true` for these routes but the server silently ignored it. Ties on `created_at` now fall back to the internal nanoid `id` so ordering remains stable across pages (#685)
- LLM client factories now receive `base_url` from `LLMSettings` for default providers — previously the override path honored `base_url` but the default path didn't, so operators pointing at OpenAI-compatible proxies via `LLM__OPENAI_BASE_URL` were ignored (#643, fixes #641)
- Internal N+1 query in dialectic agent tool execution (DEV-1721) — collapsed per-iteration DB lookups into a single fetch (#652)
- Dreamer threshold and time-guard semantics: `check_and_schedule_dream` count filter now includes only `documents.level == 'explicit'` (dreamer-created levels are output, not input, and were inflating the threshold and creating a feedback loop); `last_dream_at` write relocated from `enqueue_dream` into `process_dream` so duplicate enqueues or failed runs no longer reset the 8-hour time guard (#573)
- Deriver: blank observations are filtered out before embedding (previously triggered noisy embedding calls and persisted empty rows); blank-observation filtering unified across tool paths (#615)
- Surprisal module: filter for level observations changed from `{"level": levels}` to `{"level": {"in": levels}}` — `apply_filter()` requires operator syntax, so the prior call silently returned 0 results and made the entire Surprisal phase of the Dream cycle a no-op (#581, fixes #559)
- Removed hardcoded `stop_sequences` override from Deriver `ModelConfig` (was clobbering operator-configured stop sequences) (#587)
- Removed stale `stop_sequences` from tests (#607)
- Embedding client: `embed()` now wraps single-string input in an array, restoring compatibility with OpenAI-compatible third-party providers that reject scalar input (#586)
- Docker Compose: deriver service startup gated on the API service healthcheck (prevents races where the deriver starts before the API has run migrations) (#689)
- Docker image: `HEALTHCHECK` directive removed from the shared base image — it probed an HTTP endpoint only the API serves, permanently marking deriver containers as unhealthy. Service-level health checks now belong in each service's own configuration (k8s readiness/liveness probes on the API Deployment only) (#530)
- `tests/unified`: `--test-dir`/`--test-file` arguments now use an argparse mutually-exclusive group instead of manual validation (#650)
- CrewAI example updated for the latest CrewAI protocol (#631)
### Removed
- `src/utils/clients.py` deleted; its responsibilities are split across `src/llm/registry.py`, `src/llm/credentials.py`, and the backend-specific modules
- `src/utils/clients.py` deleted; its responsibilities are split across `src/llm/registry.py`, `src/llm/credentials.py`, and the backend-specific modules (#459)
- `HEALTHCHECK` directive removed from the shared Docker image (#530)
## [3.0.6] - 2026-04-10

7
CLAUDE.md
View File

@ -140,6 +140,7 @@ The Deriver processes batches of incoming messages and extracts conclusions abou
- **Output**: Explicit conclusions (direct facts) and deductive conclusions (inferences) saved to `(observer, observed)` collections.
- **Entry point**: `src/deriver/__main__.py` → `queue_manager.main()`.
- **Prompts**: `src/deriver/prompts.py` (`minimal_deriver_prompt`).
- **Custom instructions**: per-workspace/peer guidance can be threaded into the prompt via reasoning configuration; `DERIVER__MAX_CUSTOM_INSTRUCTIONS_TOKENS` caps the addition (default 2000) and `DERIVER__MAX_INPUT_TOKENS` defaults to 25000 to make room.
#### 2. Dialectic (`src/dialectic/`)
@ -177,8 +178,9 @@ The Dreamer is an orchestrated multi-specialist system that runs during schedule
#### Shared Agent Infrastructure
- **Tool definitions** (`src/utils/agent_tools.py`): unified `TOOLS` dict; per-agent lists (`DIALECTIC_TOOLS`, `DIALECTIC_TOOLS_MINIMAL`, `DREAMER_TOOLS`, `DEDUCTION_SPECIALIST_TOOLS`, `INDUCTION_SPECIALIST_TOOLS`).
- **LLM subsystem** (`src/llm/`): provider-agnostic `honcho_llm_call()`. Backends in `src/llm/backends/` (`anthropic.py`, `gemini.py`, `openai.py`). Includes prompt caching (`caching.py`), structured output (`structured_output.py`), tool loop (`tool_loop.py`), history adapters for cross-provider message formats, and a model registry.
- **LLM subsystem** (`src/llm/`): provider-agnostic `honcho_llm_call()`. Backends in `src/llm/backends/` (`anthropic.py`, `gemini.py`, `openai.py`). Includes prompt caching (`caching.py`), structured output (`structured_output.py`), tool loop (`tool_loop.py`), history adapters for cross-provider message formats, and a model registry. Per-retry provider selection is pinned via an `AttemptPlan` so stream-final retries don't bounce back to primary after the tool loop has settled on fallback.
- **Per-agent model config**: each agent has its own `MODEL_CONFIG` in `src/config.py` with fallback chains (see `ConfiguredModelSettings`, `FallbackModelSettings`).
- **Telemetry**: cloudevents in `src/telemetry/events/` cover API routes, dialectic, dream, deletion, reconciliation, representation, and per-call LLM accounting (`llm.py` — `LLMCallCompletedEvent` fires once per provider hit with full cost-attribution context). High-volume events are sampled deterministically per `run_id` via `TelemetrySettings.HIGH_VOLUME_SAMPLE_RATE`.
### Project Structure
@ -192,7 +194,8 @@ src/
├── dependencies.py # FastAPI DI (tracked_db, etc.)
├── exceptions.py # Custom exception types (HonchoException + subclasses)
├── security.py # JWT authentication
├── embedding_client.py # Embedding provider client
├── embedding_client.py # Embedding provider client (configurable dimensions
│ # via EMBEDDING_MODEL_CONFIG__DIMENSIONS_MODE)
├── schemas/ # Pydantic schemas
│ ├── api.py # Public API request/response schemas
│ ├── configuration.py # Per-resource configuration schemas

46
README.md
View File

@ -8,7 +8,7 @@
---
![Static Badge](https://img.shields.io/badge/Server-3.0.6-blue)
![Static Badge](https://img.shields.io/badge/Server-3.0.7-blue)
[![PyPI version](https://img.shields.io/pypi/v/honcho-ai.svg)](https://pypi.org/project/honcho-ai/)
[![NPM version](https://img.shields.io/npm/v/@honcho-ai/sdk.svg)](https://npmjs.org/package/@honcho-ai/sdk)
[![Discord](https://img.shields.io/discord/1016845111637839922?style=flat&logo=discord&logoColor=23ffffff&label=Plastic%20Labs&labelColor=235865F2)](https://discord.gg/honcho)
@ -43,21 +43,21 @@ The Honcho project is split between several repositories, with this one hosting
## Start Here
| I want to... | Path | Get started |
|---|---|---|
| I want to... | Path | Get started |
| -------------------------------------- | ---------------------------------------------------------- | ----------------------------- |
| Give my coding agent persistent memory | Claude Code, OpenCode, OpenClaw, Hermes, or any MCP client | [Integrations](#integrations) |
| Add memory to my product | Python or TypeScript SDK | [Quickstart](#quickstart) |
| Self-host Honcho | Docker / local development | [Self-hosting](#self-hosting) |
| Add memory to my product | Python or TypeScript SDK | [Quickstart](#quickstart) |
| Self-host Honcho | Docker / local development | [Self-hosting](#self-hosting) |
## Why Honcho
| Capability | What it means |
|---|---|
| Reasoning-first memory | Extracts conclusions from conversations and events, not just matching chunks. |
| Peer-centric model | Tracks users, agents, groups, projects, and ideas as entities that change over time. |
| Multi-peer perspective | Models what one peer knows about another when configured. |
| Managed or self-hosted | Use `api.honcho.dev` or run the FastAPI server yourself. |
| Agent-tool integrations | MCP, Claude Code, OpenCode, OpenClaw, Hermes, Cursor-compatible clients. |
| Capability | What it means |
| ----------------------- | ------------------------------------------------------------------------------------ |
| Reasoning-first memory | Extracts conclusions from conversations and events, not just matching chunks. |
| Peer-centric model | Tracks users, agents, groups, projects, and ideas as entities that change over time. |
| Multi-peer perspective | Models what one peer knows about another when configured. |
| Managed or self-hosted | Use `api.honcho.dev` or run the FastAPI server yourself. |
| Agent-tool integrations | MCP, Claude Code, OpenCode, OpenClaw, Hermes, Cursor-compatible clients. |
## The Honcho Loop
@ -139,7 +139,9 @@ await session.addMessages([
tutor.message("Absolutely. Send me your first problem!"),
]);
const answer = await alice.chat("What learning styles does the user respond to best?");
const answer = await alice.chat(
"What learning styles does the user respond to best?",
);
const context = await session.context({ summary: true, tokens: 10_000 });
const openai = new OpenAI();
@ -153,15 +155,15 @@ const completion = await openai.chat.completions.create({
## What Honcho Gives You
| Need | API |
|---|---|
| Save interaction history | `session.add_messages(...)` |
| Ask what Honcho knows about a peer | `peer.chat(...)` |
| Get prompt-ready context | `session.context(...).to_openai(...)` / `.to_anthropic(...)` |
| Hybrid search (BM25 + vector) | `peer.search(...)`, `session.search(...)`, `honcho.search(...)` |
| Low-latency static representations | `peer.representation(...)`, `session.representation(...)` |
| Import documents | `session.upload_file(...)` |
| Inspect background processing | `honcho.queue_status(...)` |
| Need | API |
| ---------------------------------- | --------------------------------------------------------------- |
| Save interaction history | `session.add_messages(...)` |
| Ask what Honcho knows about a peer | `peer.chat(...)` |
| Get prompt-ready context | `session.context(...).to_openai(...)` / `.to_anthropic(...)` |
| Hybrid search (BM25 + vector) | `peer.search(...)`, `session.search(...)`, `honcho.search(...)` |
| Low-latency static representations | `peer.representation(...)`, `session.representation(...)` |
| Import documents | `session.upload_file(...)` |
| Inspect background processing | `honcho.queue_status(...)` |
See the full [SDK Reference](https://honcho.dev/docs/v3/documentation/reference/sdk) and [API Reference](https://honcho.dev/docs/v3/api-reference/introduction).

7
docs/changelog/compatibility-guide.mdx
View File

@ -10,14 +10,14 @@ This guide helps you match the right SDK version to your Honcho API version. New
<CardGroup cols={2}>
<Card title="TypeScript SDK" icon="js">
**Latest:** v2.1.1
**Latest:** v2.1.2
```bash
npm install @honcho-ai/sdk
```
</Card>
<Card title="Python SDK" icon="python">
**Latest:** v2.1.1
**Latest:** v2.1.2
```bash
pip install honcho-ai
@ -30,7 +30,8 @@ This guide helps you match the right SDK version to your Honcho API version. New
| Honcho API Version | TypeScript SDK | Python SDK |
|-------------------|---------------|------------|
| v3.0.6 (Current) | v2.1.1 | v2.1.1 |
| v3.0.7 (Current) | v2.1.2 | v2.1.2 |
| v3.0.6 | v2.1.1 | v2.1.1 |
| v3.0.5 | v2.1.0 | v2.1.0 |
| v3.0.4 | v2.1.0 | v2.1.0 |
| v3.0.3 | v2.1.0 | v2.1.0 |

81
docs/changelog/introduction.mdx
View File

@ -27,7 +27,59 @@ Welcome to the Honcho changelog! This section documents all notable changes to t
### Honcho API and SDK Changelogs
<Tabs>
<Tab title="Honcho API">
<Update label="v3.0.6 (Current)">
<Update label="v3.0.7 (Current)">
### Added
- New `src/llm/` package as the single owner of provider runtime: clients, backends, history adapters, tool loop, request builder, credentials, and caching policy (#459)
- New cloudevent `LLMCallCompletedEvent` (`llm.call.completed`) fires once per provider hit with full cost-attribution context: transport/provider_label, model, token counts with cache breakdown, finish_reason, outcome, retry/fallback state, duration, tool-call shape, streaming flag, and agent correlation (`run_id` + iteration) (#637)
- `RepresentationCompletedEvent` now carries `total_input_tokens` for full-trace cost attribution; per-emitter `honcho_version` injection; deterministic per-`run_id` high-volume sampler via `TelemetrySettings.HIGH_VOLUME_SAMPLE_RATE` (#637)
- Deriver custom instructions: per-workspace/peer guidance threaded into the deriver prompt with a `MAX_CUSTOM_INSTRUCTIONS_TOKENS` budget (default 2000); deriver `MAX_INPUT_TOKENS` raised 23000 → 25000 (#609)
- Configurable embedding dimensions: `EMBEDDING_MODEL_CONFIG__DIMENSIONS_MODE` (`auto`/`always`/`never`) controls whether OpenAI `dimensions=` is forwarded (#678)
- New `honcho-cli` package — Python CLI for inspecting and managing peers, sessions, and configuration against a Honcho deployment (#424)
- `HONCHO_API_URL` env var support in the MCP Worker for self-hosted deployments (#575)
- API ID `max_length` increased from 100 to 512 across `WorkspaceCreate`, `PeerCreate`, and `SessionCreate` to align with the DB schema (#684)
- `AttemptPlan` dataclass pins per-retry provider selection across stream-final retries so streaming doesn't bounce back to primary after the tool loop has settled on fallback (#459)
- Gemini JSON-schema sanitizer for `function_declarations` — strips keywords Gemini's validator rejects while preserving semantics for other backends (#459)
### Changed
- All LLM orchestration moved out of `src/utils/clients.py` into `src/llm/` with modules split by responsibility (#459)
- Default `ModelConfig` factories (deriver, summary, dreamer specialists, dialectic levels) normalized with no extra parameters set by default; operators add transport/thinking overrides explicitly (#459)
- OpenAI reasoning-model routing widened to cover `gpt-5.x` and `o1/o3/o4` — these models receive `max_completion_tokens` instead of `max_tokens` (#459)
- Peer card prompts reframed as stable identity markers; induction specialist now opts out of peer card writes so only deduction touches the card (#686)
- Vector store queries no longer fetch embedding vectors — only document metadata is returned, reducing payload size and DB load (pgvector, lancedb, turbopuffer) (#682)
- Langfuse trace metadata now includes `namespace`, `model`, and `provider` so traces can be filtered by deployment slice (#565)
- Deriver: model-aware tokenizer (replaces the previously hardcoded encoding) and explicit guard on empty message content (#647)
- Dialectic level defaults now merge correctly with per-level overrides (#656)
- Default dialectic tool choice switched to `auto` (#630)
- Vector sync given a substantial retry budget to tolerate transient embedding provider outages (#604)
- `AgentToolConclusionsDeletedEvent` payload now carries `levels` (#612)
- Turbopuffer: `InternalServerError` caught and surfaced as a warning rather than a hard failure; vector store sync errors downgraded to warnings (#561)
### Fixed
- `reverse` query parameter is now honored on the v3 workspace list, peer list, workspace-scoped session list, and peer-scoped session list. Honcho SDKs at 2.1.0+ were already sending `reverse=true` for these routes but the server silently ignored it. Ties on `created_at` now fall back to the internal nanoid `id` for stable ordering across pages (#685)
- LLM client factories now receive `base_url` from `LLMSettings` for default providers — operators pointing at OpenAI-compatible proxies via `LLM__OPENAI_BASE_URL` were previously ignored on the default path (#643, fixes #641)
- Internal N+1 query in dialectic agent tool execution — collapsed per-iteration DB lookups into a single fetch (#652)
- Dreamer threshold and time-guard semantics: count filter now includes only `documents.level == 'explicit'` (was inflating threshold via dreamer-created levels and creating a feedback loop); `last_dream_at` write relocated from enqueue to process so duplicate enqueues or failed runs no longer reset the 8-hour time guard (#573)
- Deriver: blank observations are filtered out before embedding (previously triggered noisy embedding calls and persisted empty rows) (#615)
- Surprisal module: filter format corrected from `{"level": levels}` to `{"level": {"in": levels}}` — the prior call silently returned 0 results and made the entire Surprisal phase of the Dream cycle a no-op (#581, fixes #559)
- Removed hardcoded `stop_sequences` override from Deriver `ModelConfig` (was clobbering operator-configured stop sequences) (#587)
- Embedding client: `embed()` now wraps single-string input in an array, restoring compatibility with OpenAI-compatible third-party providers that reject scalar input (#586)
- Docker Compose: deriver service startup gated on the API service healthcheck — prevents races where the deriver starts before the API has run migrations (#689)
- Docker image: `HEALTHCHECK` directive removed from the shared base image; service-level health checks now belong in each service's own configuration (#530)
- Removed strict parameter validation for thinking params on Anthropic and OpenAI transports — was rejecting valid per-transport configs (#686)
- Stream-final retries pin to the `AttemptPlan` that succeeded rather than re-running provider selection through the outer `current_attempt` ContextVar (#459)
- Gemini `cached_content` reuse keys now include `system_instruction` and `tool_config` so cache hits don't cross configurations (#459)
- CrewAI example updated for the latest CrewAI protocol (#631)
### Removed
- `src/utils/clients.py` deleted; its responsibilities are split across `src/llm/registry.py`, `src/llm/credentials.py`, and the backend-specific modules (#459)
- `HEALTHCHECK` directive from the shared Docker image (#530)
</Update>
<Update label="v3.0.6">
### Changed
- Tightened transaction scopes across search, agent tools, queue manager, and webhook delivery to minimize DB connection hold time during external operations (#525)
@ -558,7 +610,17 @@ Welcome to the Honcho changelog! This section documents all notable changes to t
<Tab title="Python SDK">
[Python SDK](https://pypi.org/project/honcho-ai/)
<Update label="v2.1.1 (Current)">
<Update label="v2.1.2 (Current)">
### Added
- `page`, `size`, and `reverse` pagination parameters on `Honcho.workspaces()` and `HonchoAio.workspaces()`, closing the gap from 2.1.0 which added these to other list methods but not to `workspaces()`. Honoring `reverse` on the workspace/peer/session list routes also requires a Honcho server with the matching API fix; older servers silently ignore the parameter.
- `peers` parameter on `Honcho.session()` and `HonchoAio.session()` — attach peers to a session at creation time instead of needing a follow-up `session.add_peers()` call. Accepts the same shapes as `Session.add_peers` (peer ID string, `Peer` object, list of either, or tuples with `SessionPeerConfig`).
### Changed
- `WorkspaceCreateParams`, `PeerCreateParams`, and `SessionCreateParams` now accept IDs up to 512 characters (was 100), matching the server-side schema change in Honcho v3.0.7.
</Update>
<Update label="v2.1.1">
### Fixed
- Broadened HTTP retry logic to cover `httpx.NetworkError` and `httpx.RemoteProtocolError` in addition to `httpx.TimeoutException` and `httpx.ConnectError`, improving resilience against transient network failures
@ -700,7 +762,20 @@ Welcome to the Honcho changelog! This section documents all notable changes to t
<Tab title="TypeScript SDK">
[TypeScript SDK](https://www.npmjs.com/package/@honcho-ai/sdk)
<Update label="v2.1.1 (Current)">
<Update label="v2.1.2 (Current)">
### Added
- `peers` option on `Honcho.session()` — attach peers to a session at creation time instead of needing a follow-up `session.addPeers()` call. Accepts the same `PeerAddition` shape as `session.addPeers()` (peer ID strings, `Peer` objects, arrays of either, or a record with per-peer `observe_me`/`observe_others` config).
### Changed
- ID validation in `validation.ts` now accepts workspace, peer, and session IDs up to 512 characters (was 100), matching the server-side schema change in Honcho v3.0.7.
### Fixed
- `Honcho.workspaces()` now actually forwards the `reverse` option to the server. The 2.1.0 changelog listed `workspaces()` among the list methods that gained `reverse`, but `client.ts` was missing the field on the params type and request builder, so the option was silently dropped. Honoring `reverse` on the workspace/peer/session list routes also requires a Honcho server with the matching API fix; older servers silently ignore the parameter.
</Update>
<Update label="v2.1.1">
### Fixed
- Broadened fetch error retry logic to catch all `TypeError` network failures (connection resets, DNS errors, etc.) instead of only those with `'fetch'` in the message, improving resilience across runtimes (Node, Bun, browsers)

2
docs/docs.json
View File

@ -24,7 +24,7 @@
"navigation": {
"versions": [
{
"version": "v3.0.6",
"version": "v3.0.7",
"api": {
"openapi": ["v3/openapi.json"]
},

2322
docs/v3/openapi.json
View File

File diff suppressed because it is too large Load Diff

2
pyproject.toml
View File

@ -1,6 +1,6 @@
[project]
name = "honcho"
version = "3.0.6"
version = "3.0.7"
description = "Honcho Server"
authors = [
{name = "Plastic Labs", email = "hello@plasticlabs.ai"},

7
sdks/python/CHANGELOG.md
View File

@ -5,11 +5,16 @@ 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/).
## [Unreleased]
## [2.1.2] - 2026-05-21
### Added
- `page`, `size`, and `reverse` pagination parameters on `Honcho.workspaces()` and `HonchoAio.workspaces()`, closing the gap from 2.1.0 which added these to `peers()`, `sessions()`, `messages()`, and `conclusions.list()` but not to `workspaces()`. Honoring `reverse` on the workspace/peer/session list routes also requires a Honcho server with the matching API fix; older servers silently ignore the parameter.
- `peers` parameter on `Honcho.session()` and `HonchoAio.session()` — attach peers to a session at creation time instead of needing a follow-up `session.add_peers()` call. Accepts the same shapes as `Session.add_peers` (peer ID string, `Peer` object, list of either, or tuples with `SessionPeerConfig`).
### Changed
- `WorkspaceCreateParams`, `PeerCreateParams`, and `SessionCreateParams` now accept IDs up to 512 characters (was 100), matching the server-side schema change in Honcho v3.0.7.
## [2.1.1] - 2026-04-01

2
sdks/python/pyproject.toml
View File

@ -1,6 +1,6 @@
[project]
name = "honcho-ai"
version = "2.1.1"
version = "2.1.2"
description = "Official DX Optimized Python SDK for Honcho"
dynamic = ["readme"]
license = "Apache-2.0"

10
sdks/typescript/CHANGELOG.md
View File

@ -5,7 +5,15 @@ 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/).
## [Unreleased]
## [2.1.2] - 2026-05-21
### Added
- `peers` option on `Honcho.session()` — attach peers to a session at creation time instead of needing a follow-up `session.addPeers()` call. Accepts the same `PeerAddition` shape as `session.addPeers()` (peer ID strings, `Peer` objects, arrays of either, or a record with per-peer `observe_me`/`observe_others` config).
### Changed
- ID validation in `validation.ts` now accepts workspace, peer, and session IDs up to 512 characters (was 100), matching the server-side schema change in Honcho v3.0.7.
### Fixed

2
sdks/typescript/package.json
View File

@ -1,6 +1,6 @@
{
"name": "@honcho-ai/sdk",
"version": "2.1.1",
"version": "2.1.2",
"description": "Official DX Optimized TypeScript SDK for Honcho",
"author": "Plastic Labs <hello@plasticlabs.ai>",
"license": "Apache-2.0",

6
uv.lock
View File

@ -8,7 +8,7 @@ resolution-markers = [
]
[options]
exclude-newer = "2026-05-09T19:09:35.818254Z"
exclude-newer = "2026-05-16T17:58:57.678125Z"
exclude-newer-span = "P5D"
[manifest]
@ -1159,7 +1159,7 @@ wheels = [
[[package]]
name = "honcho"
version = "3.0.6"
version = "3.0.7"
source = { virtual = "." }
dependencies = [
{ name = "alembic" },
@ -1270,7 +1270,7 @@ dev = [
[[package]]
name = "honcho-ai"
version = "2.1.1"
version = "2.1.2"
source = { editable = "sdks/python" }
dependencies = [
{ name = "httpx" },