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chore: release v2.4.3
Ships the Steward capability-extraction fix (a905363), which has been on
main since earlier today while production continued to route on prose:
the running v2.4.2 still matches capability domains as substrings across
the Steward's whole response, so "description" selects housekeeper and
"acknowledge" selects librarian and biographer.

Patch rather than minor: no new capability, and the JSON on the wire is
unchanged. What changes is which agents get invoked, and only in the
cases that were already wrong.

Also carries the routing benchmark, its fixtures, the shared GPU
residency guard and the findings document, none of which are
user-visible.

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-08 18:30:28 +02:00

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# Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [Unreleased]
## [2.4.3] - 2026-08-08
### Fixed
- Steward routing no longer triggers on words inside its own explanation. Capability
extraction reads the declared `DELEGATE:` line instead of substring-matching
capability domains across the whole response, where ordinary English routed
requests — "description" contains the housekeeper domain "script", "acknowledge"
contains "knowledge" and "know". A spurious capability meant a real agent call,
including web searches, on queries that needed none.
## [2.4.2] - 2026-07-19
### Fixed
- Container crash-loop on fresh builds: cap `opentelemetry-api` below 1.44,
which removed the private `_events` module that pydantic-ai 1.27 imports
## [2.4.1] - 2026-07-19
### Changed
- **Container-name network defaults** - `SEARXNG_HOST`, `LIBRARY_DESK_HOST`, and `CORE_API_HOST` now default to docker container names on the docker-dataplane network (`http://searxng:8080`, `http://library-desk:8089`, `http://core-api:8083`) instead of host `localhost` ports, ahead of the loopback port rebinding; this also fixes `CORE_API_HOST` pointing at port 8090 (the Scheduler's host port) rather than Core-API's 8083. `scripts/test_housekeeper.sh` now reaches Core-API via `localhost:8083` instead of the LAN IP. Local development against host-published ports still works via `.env` overrides
## [2.4.0] - 2026-07-14
### Removed
- **Dead delegation stack** - deleted the duplicate, never-wired coordination layer so exactly ONE delegation implementation remains (`src/agents/delegation.py`): `src/agents/coordination.py` (`CoordinationEngine`, its own `delegate_to_librarian`, `AGENT_EXECUTORS`/`AGENT_STREAM_EXECUTORS`), the broken-by-design `run_librarian_stream` path it used (Ollama streaming + tool call bug), the `stream_delegate_to_*` wrappers with their never-parsed `__DELEGATION_RESULT__` marker, and `HouseholdRegistry.get_streaming_delegation_tools()` (no callers)
- **Orphaned agent protocol models** - `src/agents/protocol.py` now contains only the live `AgentError`; the coordination wire protocol it carried (`AgentRequest`, `AgentResponse`, `DelegationIntent`, `CoordinationResult`, `DelegationReason`, `TaskComplexity`, `ToolCallRecord`, `AgentTimeoutError`, `AgentUnavailableError`, `DelegationError`) had no importer left outside its own tests after the coordination stack removal
### Added
- **Test-suite tenant guard** - `tests/conftest.py` hard-fails the whole pytest session (exit code 1, zero tests run) if the effective tenant resolves to the production tenant `jpmschweitzer`, mirroring the guard library-desk applies on its side. Suite-level assertions pin that the session runs under `llm_tester` namespaces (Qdrant `memories_llm_tester`, Redis `session:llm_tester:*`), and the e2e isolation constants now derive from the shared `TEST_TENANT`/`PRODUCTION_TENANT` config constants instead of string literals
- **Explicit tenant on every library-desk request** - the librarian client now resolves and sends the `user` parameter explicitly on every request (library-desk is removing its server-side default; a missing user would 422). The content extraction endpoints now carry the tenant too, `search_web` no longer falls back to a phantom `tatlock-librarian` user, and a client-level assertion rejects an empty/whitespace tenant before any bytes hit the wire. A parametrized sweep pins the wire contract for all 15 tenant-scoped client methods
- **Tenant isolation guard** - non-production environments (development/testing) now FORCE the effective tenant to the reserved test tenant `llm_tester` (only `llm_tester` itself or a `test_`-prefixed override is accepted), regardless of `DEFAULT_USER` misconfiguration, at both config resolution and request-context resolution (`get_user()`). Startup refuses (clear error) when a non-production environment is explicitly configured with the production tenant `jpmschweitzer`, and one loud startup log line states the effective/forced tenant
- **Conversation context for experts + real-time think messages** - direct delegation (streaming and non-streaming) now passes a trimmed conversation history (last 6 turns) as expert context, so follow-up questions keep their referent; `_stream_direct_delegation` is now an async generator, so butler think messages ("Allow me to consult the archives, sir.") stream BEFORE the research runs instead of after it completes
- **Bounded retries and connection reuse for library-desk** - GETs and the read-only `POST /query/*` and `POST /rag/search` endpoints retry once (2 attempts, short backoff) on transport errors and retryable 5xx; wiki writes are never retried. The client now honors `LIBRARY_DESK_TIMEOUT` instead of hardcoded 60s/30s, a librarian run holds one shared HTTP connection instead of constructing a client per tool call, and read tools raise `ModelRetry` on transient HTTP errors so the agent's retry budget engages
- **One librarian timeout budget** - new `LIBRARIAN_TIMEOUT` (default 180s) enforced with `asyncio.wait_for` inside `delegate_to_librarian`, capping the previously uncapped live paths (steward direct delegation and streaming). The Ollama provider's AsyncOpenAI client now carries an explicit `OLLAMA_TIMEOUT` instead of the SDK's ~600s default, and the contradictory unused 60s default in `AgentRequest.timeout_seconds` was removed (None defers to the configured budget)
- **Search degradation signaling** - The librarian client parses `source_counts` (plus the additive `source_status`/`degraded` fields when a newer library-desk sends them; absence is tolerated), and `hybrid_search` appends a one-line coverage note when a search is degraded or an enabled source leg contributed nothing, so outages are visible to the model and the user. When `source_status` is present it is used exclusively; without it, count-absence is only inferred for the optional legs the request explicitly enabled (web/documents/volatile) - never the always-on vector/graph legs, whose absence from the top-N counts is normal ranking behavior, so healthy searches no longer emit warnings
### Fixed
- **Clearing all wiki-page tags is possible again** - the Ollama-safe empty-list sentinel in `update_wiki_page` means "leave unchanged", which made it impossible to remove all tags; passing exactly `["__CLEAR__"]` now sends an empty tag list to library-desk (documented in the tool docstring for the local model)
- **Text-delegation fallback pairs results strictly** - the parallel branch now verifies `asyncio.gather` returned one result per parsed delegation (`zip(..., strict=True)`); a count mismatch fails loudly with a curated apology instead of silently attributing outputs to the wrong agent
- **Ollama-safe librarian tool schemas** - `update_wiki_page` and `smart_create_wiki_page` no longer use `X | None` parameters (Ollama's OpenAI-compatible API mishandles `anyOf[X, null]`); empty-string/empty-list sentinels are translated to `None` inside the tools, matching the biographer pattern. A snapshot test pins every librarian tool schema to contain no nullable `anyOf`
- **Honest expert failures** - `run_librarian` now raises a structured `AgentError` instead of returning error text as if it were research output, so delegation correctly reports `success=False` and the streaming error branch is reachable. Failures surface to the user as curated butler-toned sentences; exception detail (including internal URLs) stays in the logs only. Librarian tool errors no longer leak `str(e)` into synthesis
- **HybridRAG response mapping** - The librarian client now parses the field names library-desk actually returns (`source_type`/`sources`, `rrf_score`, `context`, per-item `related_dossiers`, synonyms nested in the `keywords` dict); previously every result rendered as "unknown (score: 0.00)". Source icons now key off the per-item `sources` list. Requests no longer send zero limits (the service rejects them with 422); legs are disabled via `enable_*` flags. Pinned by a contract test against a recorded live response (`tests/agents/librarian/fixtures/`)
## [2.3.0] - 2026-07-13
### Changed
- **Local-first backend (claudification rollback)** - Ollama/gemma4 is now the primary backend; Claude remains as fallback. `PREFER_CLOUD_BACKEND` defaults to `false`, Claude is used automatically when the Ollama startup health check fails, and the Steward retries mid-request failures on the other backend in both directions
- **Default Claude model `claude-sonnet-5`** - `claude-sonnet-4-20250514` was retired by Anthropic on 2026-06-15 and would 404, leaving the fallback dead
- **Dedicated orchestration prompt** - `orchestrate_tool_calls()` now uses a terse tool-execution prompt (`TATLOCK_ORCHESTRATION_PROMPT`); the butler persona prompt suppressed gemma4 tool calling (the model reasoned about the calculator, then answered from memory with wrong arithmetic). Synthesis keeps the persona prompt, so user-visible voice is unchanged
### Fixed
- **Startup crash with broken anthropic package** - Anthropic SDK imports in the model selector are now lazy, so an incompatible `anthropic` install degrades to Ollama-only operation instead of crashing the app at import time (root cause of the production outage since April)
- **Claude Sonnet 5 rejects sampling parameters** - removed `temperature` from the Steward's direct Claude call and made the Housekeeper's temperature setting backend-conditional via `get_sampling_settings()`
- **Pin `anthropic>=0.77,<1.0`** - the April image resolved an anthropic version incompatible with pydantic-ai 1.27
- **Steward timeout configurable** - new `STEWARD_TIMEOUT` (default 60s) replaces the hardcoded 30s, which gemma4 chronically exceeded (~35s warm analysis), causing every request to fail or fall back
### Added
- **Ollama startup health check** - verifies the server is reachable and `OLLAMA_DEFAULT_MODEL` is pulled; feeds backend resolution and `get_model_info()`
- **Contract tests** (`tests/contracts/`, `make test-contracts`) - wire-level tests that send the raw requests the code sends to Ollama (native + OpenAI-compat tool calling), Anthropic (including the pinned temperature-rejection contract), Qdrant, SearXNG, library-desk, and Redis; unreachable services skip, wrong response shapes fail
- **Backend resolution unit tests** (`tests/anthropic/`)
## [2.2.0] - 2026-04-04
### Changed
- **Switch default Ollama model to gemma4:e2b** - Replaces mistral-nemo as the local LLM backend; gemma4:e2b has native function calling support, faster tool calling (2-4s vs 15-20s), better parameter accuracy on word problems, and uses less VRAM (8GB vs 9.2GB)
### Added
- **Tool calling benchmark script** (`scripts/benchmark_tool_calling.py`) - Compares tool calling accuracy and latency across Ollama models via the Tatlock API
## [2.1.0] - 2026-02-05
### Fixed
- **Streaming SSE compatibility with Open WebUI** - Switch from `exclude_none=True` to `exclude_unset=True` for SSE chunk serialization; `exclude_none` was too aggressive — it stripped `finish_reason: null` from intermediate chunks (which OpenAI includes), while `exclude_unset` correctly omits only fields never passed to the constructor (like `reasoning_content` on content-only chunks) while preserving explicitly-set `finish_reason: null`
### Changed
- **Project structure consolidation** - Moved documentation to `docs/`, consolidated all config into `pyproject.toml`, replaced `wakeup.sh`/`pytest.ini`/`requirements*.txt` with `Makefile` + `pyproject.toml`
- **CI test gate** - Unit tests now gate release and build jobs in Gitea Actions workflow
- **Build output organization** - Tool caches in `.cache/`, generated output (coverage, logs) in `build/`
## [2.0.5] - 2026-02-05
### Fixed
- **Streaming JSON compatibility** - Exclude null fields from streaming chunks using `exclude_none=True`; OpenAI's API omits null fields entirely, and including them (e.g., `content: null`, `reasoning_content: null`) caused parsing issues in Open WebUI
## [2.0.4] - 2026-02-05
### Fixed
- **Open WebUI streaming compatibility** - Replaced `sse_starlette` `EventSourceResponse` with plain `StreamingResponse` for chat completions; `sse_starlette` added `\r\n` line endings and extra SSE fields that Open WebUI couldn't parse
## [2.0.3] - 2026-02-05
### Fixed
- **Steward analysis leaking into responses** - Removed internal routing analysis (`DELEGATE: tatlock_core...`) from user-visible reasoning in both streaming and non-streaming paths
## [2.0.2] - 2026-02-05
### Fixed
- **tool_choice format incompatibility** - Removed `extra_body` tool_choice hack for Claude backend; PydanticAI handles tool_choice natively for Anthropic, preventing infinite tool call loops
- **CI trigger** - Changed workflow trigger from `release:published` to `push:tags:v[0-9]*`
## [2.0.1] - 2026-02-05
### Fixed
- **Expert agent registration failure** - `AnthropicModel` does not accept `api_key` directly; now passes it via `AnthropicProvider`
## [2.0.0] - 2026-02-05
### Added
- **Claude backend support (Claudification Phase 1)** - All agents now prefer Claude over Ollama
- New `src/anthropic/` module with model selector and health check
- `get_model()` factory returns Claude if available, Ollama as fallback
- Startup health check caches Claude API availability
- Configuration: `ANTHROPIC_API_KEY`, `ANTHROPIC_MODEL`, `PREFER_CLOUD_BACKEND`
- 200k token context when using Claude backend
- **Steward dual-backend support** - Direct API calls to Claude or Ollama
- `_call_claude()`: Anthropic Messages API path
- `_call_ollama()`: Existing Ollama generate API path (preserved)
- Automatic fallback: if Claude call fails mid-request, retries with Ollama
- **Claudification project tracking** - `PROJECT_CLAUDIFICATION.md` with Phase 1/2 roadmap
### Changed
- **All PydanticAI agents refactored to use `get_model()`**:
- Tatlock (6 instantiation locations)
- Librarian
- Biographer
- Housekeeper
- **`initialize_application()` is now async** - Supports async Claude health check at startup
- **Dependencies**: `pydantic-ai-slim[openai,anthropic]` replaces `pydantic-ai-slim[openai]`
- **Startup logging** now includes backend selection info (claude/ollama)
- **Agent creation logging** now includes backend and model info
### Removed
- Stale `tests/core/test_benchmarks.py` (benchmark system was removed in v1.10.0)
## [1.11.0] - 2025-12-30
### Added
- **Paperless document integration** - HybridRAG now includes indexed PDFs and scanned documents from Paperless-ngx
- New `include_documents` parameter in `hybrid_search` tool
- 📑 icon for document sources in search results
- Librarian prompt updated with document awareness
- **Volatile cache integration** - HybridRAG now includes pre-fetched real-time data
- New `include_volatile` parameter in `hybrid_search` tool
- ⚡ icon for volatile sources in search results
- Supports weather, forecast, news, stock, crypto, sun, air_quality namespaces
- Librarian prompt updated with volatile cache awareness (user-configured items only)
- **Biographer routing in Steward** - Personal memory queries now correctly route to The Biographer
- Added explicit routing rules for "where do I live", "what car do I drive", etc.
- Added biographer delegation examples to Steward prompt
- Location keywords ("live", "where", "home") now trigger profile pre-fetch
### Changed
- **LibraryDeskClient.hybrid_search** - Now passes full config including `document_limit`, `volatile_limit`, and enable flags
- **Steward guidelines** - Clarified that research queries about TOPICS go to Librarian, queries about USER go to Biographer
## [1.10.1] - 2025-12-23
### Fixed
- **Tatlock's excessive apologizing** - Strengthened personality prompt to prevent unnecessary apologies after successful Librarian delegations. Added explicit "do NOT apologize" instructions to both system prompt and synthesis prompt.
## [1.10.0] - 2025-12-22
### Added
#### Lightweight Request Tracing
- **JSON-based tracing system** for local development debugging
- Captures full request flow through multi-agent architecture
- `Trace` and `Span` dataclasses with automatic timing and nesting
- ContextVar-based propagation for async-safe tracing
- `trace_span` async context manager for clean instrumentation
- Traces written to `logs/traces/{trace_id}.json`
- Enabled via `DEBUG=true` environment variable
- **Trace Viewer UI** (`logs/traces/viewer.html`)
- Standalone HTML viewer with timeline visualization
- Filter by status, search by request text
- Expandable span details with prompts and responses
- **Tracing REST API** (`/traces`)
- `GET /traces` - Serve trace viewer UI
- `GET /traces/list` - List available traces with filtering
- `GET /traces/{trace_id}` - Retrieve specific trace JSON
- Only available when `DEBUG=true`
- **Full pipeline instrumentation**
- Router-level trace start/end with context management
- Steward analysis spans in preprocessing
- Tatlock orchestrate/synthesize spans
- Expert delegation spans (librarian/biographer/housekeeper)
- Tool-level spans extracted from PydanticAI messages
### Changed
- **Replaced Redis benchmarks with file-based tracing** - Simpler, more useful for debugging
- **Context management moved to service layer** - Router simplified, context set in response service
- **Server binds to all interfaces** - `wakeup.sh` now uses `0.0.0.0` for network access
### Removed
- **Redis benchmark system** (`src/core/benchmarks.py`)
- `ENABLE_BENCHMARKS` config setting
- `REDIS_BENCHMARK_DB` config setting
- `redis_url` property (kept `redis_memory_url`)
- Benchmark recording in Steward service and tool tracking
### Fixed
- **Librarian fabrication prevention** - Added explicit instructions to never invent data when tools fail or sources are unavailable
## [1.9.0] - 2025-12-18
### Changed
- **Housekeeper prompt optimization** - Rewrote system prompt for Mistral-Nemo function calling with negative constraints, step-by-step process, and explicit entity ID format guidance
- **Housekeeper temperature setting** - Set temperature to 0.1 for deterministic tool calling behavior
- **Device list room group priority** - Room groups now appear first in `list_devices` output with `[ROOM GROUP]` marker to address positional bias
- **Tool docstring improvements** - Updated turn_on/turn_off/toggle with explicit `entity_id=` parameter examples
### Added
- **Housekeeper optimization findings** - Added `docs/housekeeper-optimization-findings.md` documenting the experiment journey from 0% to 100% success rate
- **Housekeeper test script** - Added `scripts/test_housekeeper.sh` for room group detection regression testing
## [1.8.6] - 2025-12-17
### Fixed
- **Housekeeper API paths** - Updated all client endpoints to use `/housekeeping/` prefix to match core-api routes
- **Housekeeper entity hallucination** - Improved system prompt with critical rule requiring `list_devices()` before any control action to prevent guessing entity IDs
### Added
- **Housekeeping API spec** - Added `docs/housekeeping-api-spec.md` documenting the core-api home automation interface
## [1.8.5] - 2025-12-16
### Fixed
- **Redis benchmark boolean storage** - Convert booleans to strings for Redis `hset` (Redis doesn't accept bool type directly)
- **Tool tracking capability matching** - `delegate_to_librarian` now correctly recognized as using "librarian" capability when checking Steward recommendations
- **E2E test fixture scope** - Fixed pytest-asyncio ScopeMismatch error by using `loop_scope="module"` for module-scoped async fixtures
## [1.8.4] - 2025-12-16
### Fixed
- **Remove `<think>` wrappers from think messages** - Messages in `reasoning_content` should be plain text
- Removed `<think>` wrappers from delegation.py household think messages
- Removed `<think>` wrappers from orchestration.py status messages
- Think messages now appear cleanly in Open WebUI's reasoning block
## [1.8.3] - 2025-12-16
### Fixed
- **Open WebUI streaming rendering** - Use `reasoning_content` field for thinking (DeepSeek R1 format) instead of `<think>` tags in `content`
- Open WebUI now renders thinking as proper collapsible blocks instead of broken HTML
## [1.8.2] - 2025-12-16
### Fixed
- **HybridRAG keywords schema mismatch** - library-desk now returns `keywords` as dict with `core_keywords`, client now handles both formats
## [1.8.1] - 2025-12-16
### Fixed
#### Ollama Message Sanitization
- **Fixed `invalid message content type: <nil>` error** from Ollama
- Created custom `TatlockOllamaProvider` that sanitizes messages before sending to Ollama
- Ollama rejects assistant messages with `content: null` (tool-only messages from PydanticAI)
- Provider converts `null` content to empty string `""` for compatibility
- Updated all agents (Librarian, Biographer, Housekeeper, Tatlock) to use sanitized provider
- Added `src/ollama/provider.py` with reusable provider pattern
#### Streaming Think Message Accumulation
- **Fixed repeating think messages in frontend** (e.g., 10x "The Librarian has compiled...")
- Frontend was accumulating `ReasoningSummaryDelta` events expecting concatenation
- Added `ReasoningSummaryDone()` signal after each think message to indicate completion
- Each think slug is now treated as a complete message, not a continuation
## [1.8.0] - 2025-12-15
### Fixed
#### Steward Routing for Web Search
- Updated Steward guidelines to route web searches, weather, news → Librarian with `search_web`
- Added URL/article reading → Librarian with `read_url` to routing guidelines
- Added examples showing `search_web` and `read_url` tool usage
#### Librarian Agent Tool Registration
- Registered `search_web`, `read_url`, `read_urls_batch` tools with the Librarian PydanticAI agent
- Updated Librarian system prompt with Web Search & Content Extraction section
- Fixed tool count in agent logger (11 → 14 tools)
#### Query Enrichment Integration
- Fixed enriched query (with location/timezone context) not being passed to delegations
- Response service now uses `enriched_query` from Steward recommendation for all delegations
- Weather queries now automatically include user's stored location
#### Action Type Detection
- Added "read", "fetch", "url", "http" keywords to RESEARCH action type for Librarian
- Ensures proper think messages for URL reading tasks
## [1.7.0] - 2025-12-15
### Added
#### Web Search Migration to Librarian
- **`search_web()`** tool in Librarian for web search via library-desk `/rag/search` endpoint
- **`read_url()`** tool for single URL content extraction via Trafilatura
- **`read_urls_batch()`** tool for parallel batch URL extraction (max 20 URLs)
- `WebSearchResult`, `WebSearchResponse` models in LibraryDeskClient
- `ContentExtractionResult`, `BatchExtractionResponse` models for content extraction
- `search_web()`, `extract_content()`, `extract_content_batch()` methods in LibraryDeskClient
- Comprehensive unit tests for new Librarian tools (`tests/agents/librarian/test_tools.py`)
### Changed
- Librarian capability updated with web search domains: "web", "url", "internet"
- Tatlock system prompt now delegates web search to Librarian
- `tatlock_core` capability reduced to computation/datetime only (no longer requires network)
### Removed
- `search_web` function from `src/agents/tatlock_core/tools.py`
- `web_search_tool` from `tatlock_core_tools` list
- `search_web` from legacy `src/agents/tools.py`
- Search tests from `tests/agents/test_tools.py` (moved to Librarian tests)
## [1.6.0] - 2025-12-15
### Added
#### Two-Phase Tatlock Execution
- **Phase 1: Orchestration** - Executes tool calls and expert delegations, returns structured results
- **Phase 2: Synthesis** - Synthesizes butler-toned response from gathered results
- `orchestrate_tool_calls()` method in TatlockAgent for coordination phase
- `synthesize_from_results()` method in TatlockAgent for synthesis phase
- Guarantees butler personality in all responses by separating coordination from response generation
#### Automatic Think Slugs
- **Deterministic butler-perspective messages** during expert delegation (no LLM involved)
- `ActionType` enum: RETRIEVE, RESEARCH, CREATE, CONTROL, RECORD
- `HOUSEHOLD_THINK_MESSAGES` mapping with butler-perspective messages for all experts:
- Librarian: "Allow me to consult the archives, sir." / "I'm having the Librarian prepare a new entry."
- Biographer: "Let me consult the household records." / "I've asked the Biographer to take note, sir."
- Housekeeper: "I'm instructing the household staff now, sir." / "Allow me to inquire with the household staff."
- `_detect_action_type()` function for keyword-based action detection
- `get_think_message()` helper for retrieving appropriate messages
- Streaming delegation wrappers: `stream_delegate_to_librarian()`, `stream_delegate_to_biographer()`, `stream_delegate_to_housekeeper()`
- `STREAMING_DELEGATION_WRAPPERS` mapping in delegation.py
- `get_streaming_delegation_tools()` method in HouseholdRegistry
#### Steward Query Enrichment
- **Auto-fill user context** (location, timezone) when not specified in query
- `_build_enriched_query()` function in steward service
- Regex word boundary matching for accurate location detection (avoids false positives)
- `enriched_query` field added to `StewardRecommendation` schema
- Automatic enrichment for weather queries (location), time queries (timezone), temperature preferences
#### Documentation
- **ORCHESTRATION_SCENARIOS.md** completely rewritten with:
- Mermaid flow diagrams for two-phase execution
- 4 new Housekeeper scenarios (light control, device status, parallel delegation)
- Biographer memory recording scenario
- Complete think slug reference tables
- Action type detection tables
- Updated architecture mindmap
- **TESTING_IMPROVEMENTS.md** - LLM testing best practices for future implementation
### Changed
- `create_response_with_steward()` now uses two-phase execution
- `_direct_delegation()` routes through synthesis phase for consistent butler tone
- `_execute_single_delegation()` now supports housekeeper
- Streaming response handler integrated with think slug system
- All 326 unit tests passing
## [1.5.0] - 2025-12-15
### Added
#### The Housekeeper Agent
- **New home automation expert agent** following the Librarian pattern
- `CoreAPIClient` for communicating with core-api service (Home Assistant wrapper)
- 13 tools for home automation:
- Discovery: `list_areas`, `list_devices`, `get_device_state`
- Control: `turn_on`, `turn_off`, `toggle`
- Scenes: `list_scenes`, `activate_scene`
- Scripts: `list_scripts`, `run_script`
- Automations: `list_automations`, `toggle_automation`
- History: `get_history`
- PydanticAI agent with system prompt for home automation tasks
- `HouseholdCapability` registration with domains: lights, switches, automation, home, smart home, scene, script, device, climate, fan, cover, blinds
- `delegate_to_housekeeper()` delegation wrapper
- Config settings: `CORE_API_HOST`, `CORE_API_KEY`, `CORE_API_TIMEOUT`
#### Development Port Change
- **Dev server port changed from 8123 to 8777** to avoid conflict with Home Assistant default port
- Updated `wakeup.sh`, E2E tests, and documentation
### Changed
- All unit tests pass (421 passed, 5 xfailed)
- Housekeeper registered on startup alongside Librarian and Biographer
## [1.4.0] - 2025-12-14
### Added
#### Environment-Aware Configuration
- **Auto-selected logging level**: DEBUG for development, WARNING for production
- **Auto-selected default user**: `llm_tester` for development (isolated test scope), `jpmschweitzer` for production
- Properties `effective_log_level` and `effective_default_user` in config
- User context logging at request entry with INFO level
#### Direct Delegation Bypass
- **Pure memory/librarian requests bypass Tatlock**: When Steward recommends only biographer/librarian, skip Tatlock LLM call
- `_direct_delegation()` function for immediate expert agent execution
- Reduces latency for memory-only requests
#### Text-Based Delegation Fallback
- **Parse text delegation patterns**: Handle LLM outputs like `[DELEGATE:biographer] task="..."`
- Multiple pattern support for delegation parsing
- Sequential and parallel execution with `[PARALLEL]` prefix
#### Comprehensive E2E Test Suite
- **22 new orchestration tests** in `tests/e2e/test_orchestration_e2e.py`
- `QdrantVerifier` helper class for data verification
- `assert_llm_behavior()` for flexible LLM output pattern matching
- Test classes covering:
- Memory storage and recall
- Steward delegation
- Direct delegation bypass
- User context isolation (llm_tester vs production)
- Data verification in Qdrant
- Integration health checks
- Orchestration scenarios (weather, calculator, wiki, multi-expert)
- Error handling
- Evaluation reports
- Updated `tests/e2e/README.md` with comprehensive documentation
### Fixed
- **Unit test mocks**: Updated Steward streaming tests to mock `run_with_scoped_tools_stream` (async generator)
- **Temporal context in tests**: Tests now account for `_inject_temporal_context()` appending timestamps
- **LLM non-determinism**: Integration tests use `pytest.xfail()` for LLM-dependent assertions
- **Streaming test timeouts**: Increased timeouts (60-90s) for LLM processing time
### Changed
- All unit tests now pass (380 passed, 5 xfailed for LLM non-determinism)
- E2E tests use `llm_tester` user for isolation from production data
## [1.3.3] - 2025-12-14
### Fixed
- **Memory**: Fix Qdrant point IDs - use UUID5 instead of arbitrary strings
## [1.3.2] - 2025-12-14
### Fixed
- **Memory**: Fix biographer tool type hints for Ollama compatibility (remove `| None` union types)
## [1.3.1] - 2025-12-14
### Fixed
- **Memory**: Add biographer to delegation wrappers (was returning raw tools causing Ollama error)
- **Config**: Add Qdrant host/port to .env.example
## [1.3.0] - 2025-12-14
### Fixed
- **Memory**: Update Qdrant client to use `query_points` API (qdrant-client >= 1.10)
### Changed
- **Config**: Rename `REDIS_DB` to `REDIS_BENCHMARK_DB` for clarity
- **Config**: Update Redis defaults to match stack allocation (benchmark=6, memory=1)
## [1.2.5] - 2025-12-14
### Fixed
- **Dependencies**: Add missing `pydantic-settings` (not included in pydantic-ai-slim)
## [1.2.4] - 2025-12-14
### Added
- **CI**: Trigger Watchtower update after successful image push
## [1.2.3] - 2025-12-14
### Fixed
- **CI**: Upgrade to build-push-action@v6, disable provenance and sbom for Gitea registry
## [1.2.2] - 2025-12-13
### Fixed
- **CI**: Add `provenance: false` to docker/build-push-action to fix Gitea registry push
## [1.2.1] - 2025-12-13
### Changed
- **Dependency slimming**: Switched from `pydantic-ai` to `pydantic-ai-slim[openai]`
- Removes unused LLM provider SDKs (anthropic, boto3, cohere, google-genai, groq, huggingface)
- Production packages: 53 (down from ~158)
- Production footprint: 178MB
- Tatlock uses Ollama via OpenAI-compatible API, so only `openai` extra is needed
- See `DEPENDENCY_SLIM.md` for rollback instructions
## [1.2.0] - 2025-12-13
### Added
#### Phase F: Memory System (The Biographer)
- **Memory Infrastructure** (Phase F.1):
- `src/core/context.py`: ContextVar-based request context for async-safe user/conversation tracking
- `get_user()`, `get_conversation_id()` helpers
- `RequestContext` manager for clean setup/teardown
- `src/core/multi_tenancy.py`: User ID sanitization and collection naming
- Per-user collection pattern: `memories_{user}`
- Redis key patterns: `session:{user}:{conv}`, `entities:{user}:{conv}`
- `src/core/embeddings.py`: Ollama embedding client
- nomic-embed-text model (768 dimensions)
- `embed()`, `embed_batch()`, `health_check()` methods
- `src/core/qdrant.py`: Qdrant vector database client
- `ensure_collection()`, `upsert_memory()`, `search_memories()`, `delete_memory()`
- Type-based filtering for memory queries
- `src/core/memory_cache.py`: Redis session memory cache
- Session context with 24h TTL (db=2, separate from benchmarks)
- Recent entities tracking per conversation
- **Memory Service** (Phase F.2a):
- `src/core/memory_service.py`: Direct access layer for fast, LLM-free memory lookups
- Profile methods: `get_profile()`, `set_profile()`
- Preference methods: `get_preference()`, `set_preference()`, `get_all_preferences()`
- Fact methods: `store_fact()`, `get_fact()`
- Session context: `get_session_context()`, `set_session_context()`, `update_session_context()`
- Steward integration: `prefetch_context()` for request preprocessing
- **The Biographer Agent** (Phase F.2b):
- `src/agents/biographer/`: Household memory keeper agent
- PydanticAI agent with discreet chronicler personality
- System prompt emphasizes privacy and accurate recall
- **Biographer Tools** (`src/agents/biographer/tools.py`):
- `recall_semantic`: Semantic search for memories by meaning
- `list_memories`: Browse stored memories by type
- `store_insight`: Record new facts from conversation
- `update_profile`: Update core profile fields (name, location, timezone)
- `update_preference`: Update user preferences (units, theme)
- `forget_memory`: Remove specific memories
- **Capability Registration**:
- `BIOGRAPHER_CAPABILITY` with context domain
- Automatic registration on startup
- Low cost (vector search, minimal LLM)
- **Delegation Wrapper**:
- `delegate_to_biographer()` in `src/agents/delegation.py`
- Async delegation with error handling
- **Steward Memory Integration**:
- Memory context pre-fetch during request analysis
- Profile and preferences included in Steward's note to Butler
- Keyword-based context determination (weather → location, time → timezone)
- **Configuration**:
- `QDRANT_HOST`, `QDRANT_PORT`, `QDRANT_EMBEDDING_DIM` (768)
- `OLLAMA_EMBEDDING_MODEL` (nomic-embed-text)
- `REDIS_MEMORY_DB` (2), `REDIS_MEMORY_TTL_HOURS` (24)
- **Test Suite**:
- 34 new tests for memory system
- Biographer capability tests (15 tests)
- Memory service tests (19 tests)
- **OpenAI Standard `user` Field**:
- Added `user` field to `ResponseRequest` schema
- Request context set at API entry point
- Propagates through async calls via ContextVar
### Changed
- Application startup now registers The Biographer with Household Registry
- Steward analysis includes memory context pre-fetch
- Librarian client methods now use `get_user()` from context (12 methods updated)
- Request router sets user/conversation context at entry
## [1.1.0] - 2025-12-11
### Added
#### Phase 3: Butler Orchestration (Multi-Agent Coordination)
- **The Librarian Agent**: Expert agent for research and knowledge management
- PydanticAI agent with specialized research assistant personality
- Connects to library-desk API for HybridRAG capabilities
- System prompt emphasizes fetching wiki pages before summarizing
- Streaming support via `run_librarian_stream()`
- **Library-Desk API Client** (`src/agents/librarian/client.py`):
- Async HTTP client with httpx for library-desk API integration
- HybridRAG search (vector + graph + web search)
- Wiki operations (search, get, list, create, update pages)
- Smart page creation with HybridRAG research (`POST /wiki/pages/smart-create`)
- Semantic vector search
- Knowledge graph queries (Cypher execution)
- Dossier (tag collection) browsing
- Health check endpoint
- **Librarian Tools** (`src/agents/librarian/tools.py`):
- Research tools:
- `hybrid_search`: Combined vector, graph, and web search
- `search_wiki`: Full-text wiki page search
- `get_wiki_page`: Fetch full wiki page content by ID
- `semantic_search`: Vector similarity search
- `list_dossiers`: Browse knowledge collections
- `get_dossier_pages`: Get pages in a dossier
- `explore_knowledge_graph`: Entity and relationship discovery
- `find_related_entities`: Find connected concepts
- Write tools:
- `smart_create_wiki_page`: Create page with automatic HybridRAG research (PREFERRED for topic-based creation)
- `create_wiki_page`: Create page with user-provided content
- `update_wiki_page`: Update existing page (partial updates supported)
- **Agent Communication Protocol** (`src/agents/protocol.py`):
- `AgentRequest`: Standardized task request with context and constraints
- `AgentResponse`: Response with result, reasoning, tool calls, confidence
- `DelegationIntent`: Routing intent with target agent and reason
- `CoordinationResult`: Aggregated multi-agent results
- `DelegationReason` enum: domain expertise, tool access, resource efficiency, user preference
- Error types: `AgentError`, `AgentTimeoutError`, `AgentUnavailableError`
- **Coordination Engine** (`src/agents/coordination.py`):
- `CoordinationEngine`: Multi-agent task orchestration
- Routing tasks to appropriate expert agents
- Sequential and parallel execution support
- Result aggregation from multiple agents
- Graceful error handling and degradation
- Streaming delegation support
- Convenience functions: `delegate_to_librarian()`, `delegate_to_librarian_stream()`
- **Librarian Capability Registration**:
- `LIBRARIAN_CAPABILITY` definition with research domains
- Automatic registration on application startup
- Integration with Household Registry
- **Configuration**:
- `LIBRARY_DESK_HOST`: Library-desk API URL (default: `http://localhost:8089`)
- `LIBRARY_DESK_API_KEY`: Optional API key for authentication
- `LIBRARY_DESK_TIMEOUT`: Request timeout in seconds (default: 60)
- **Test Suite**:
- 78 new tests for Phase 3 components
- Protocol model tests (requests, responses, intents, errors)
- Coordination engine tests (delegation, streaming, multi-agent)
- Library-desk client tests (all endpoints with mocked HTTP)
- Wiki write operation tests (update, smart-create)
- Capability registration tests
### Changed
- Application startup now registers The Librarian with Household Registry
- Configuration expanded to support library-desk API integration
- **Version loading**: APP_VERSION now dynamically loaded from pyproject.toml
## [1.0.0a] - 2025-12-11
### Added
- **CI/CD Pipeline**: Release-triggered automated builds
- Dockerfile for containerized deployment (Python 3.12-slim, port 8000)
- Gitea Actions workflow triggered on release publish
- Builds and pushes to git.schweitz.net registry with latest and version tags
- Watchtower integration for automatic container updates
- **Portainer Stack**: Production deployment configuration
- Connects to docker-dataplane network for service discovery
- Integration with ollama, searxng, and redis-shared services
- Health check endpoint monitoring
- Resource limits (1 CPU, 1GB memory)
### Changed
- Version bump to 1.0.0 marking production-ready release
## [0.2.5] - 2025-12-07
### Added
#### Phase 2: The Steward (Two-Tier Architecture)
- **The Steward Agent**: First-tier LLM agent for request analysis and capability recommendation
- Analyzes requests with full conversation context awareness
- Recommends relevant household capabilities for each request
- Detects missing capabilities and provides guidance
- Estimates request complexity (simple/moderate/complex)
- Uses same Ollama model as Tatlock for VRAM efficiency
- **Household Registry**: Centralized capability management system
- `HouseholdRegistry` for registering capabilities and toolsets
- `HouseholdCapability` executive summaries for coordination
- `HouseholdMember` specifications with PydanticAI toolsets
- Domain-based tool organization (e.g., `src/agents/tatlock_core/`)
- Dynamic tool scoping per request
- **Request Preprocessing Pipeline**: Steward → Tatlock flow integration
- `preprocess_request()` orchestrates Steward analysis
- Creates scoped toolsets based on recommendations
- Formats Steward notes for Butler (conversation context included)
- Integrated with Responses API via `create_response_with_steward()`
- **Tool Usage Tracking**: Benchmarking and accuracy analysis
- `ToolCallTracker` for monitoring recommended vs. actual tool usage
- Tracks recommendation accuracy metrics
- Records benchmarks to Redis for cross-session analysis
- Supports precision/recall/F1 score calculation
- **Streaming Transparency**: Real-time Steward analysis visibility
- Streams Steward's reasoning as reasoning summary deltas
- Streams Tatlock's response as output text deltas
- Full SSE support for Steward + Tatlock flow
- Conversation context and missing capabilities visible in stream
- **Structured Logging**: Operation timing and metadata tracking
- `structlog`-based JSON logging for machine parsing
- Context managers for automatic operation timing
- Metadata enrichment for debugging and analysis
- Integrated with benchmark recording
- **Redis Benchmark Storage**: Performance metrics persistence
- Cross-session benchmark storage with 30-day expiry
- Time-series metrics for Steward analysis and tool calls
- Queryable by operation, time range, and metadata
- Support for recommendation accuracy tracking
- **Benchmark Analysis Tools**: Performance analysis CLI
- `scripts/benchmark_analysis.py` for metric analysis
- Steward performance statistics (latency, success rate, recommendations)
- Tool recommendation accuracy analysis (precision, recall, F1)
- Per-tool accuracy breakdown and duration statistics
- **End-to-End Test Suite**: Comprehensive API integration tests
- 17 E2E tests making real HTTP requests to running server
- Tests for Chat Completions, Responses API, and streaming endpoints
- OpenAI API spec compliance verification (format validation)
- Steward preprocessing integration verification
- Error handling tests (404, 422 status codes)
- Flexible assertions for LLM output variance
- Tool usage indicators: 🧮 (calculator), 🔍 (search), 🕐 (datetime)
- Full documentation in `tests/e2e/README.md`
#### Phase 1 Enhancements
- **Conversation history support**: Tatlock now remembers previous turns in multi-turn conversations
- OpenAI-format messages converted to PydanticAI `ModelRequest`/`ModelResponse` objects
- Full conversation context passed to agent via `message_history` parameter
- Empty messages filtered to prevent Ollama errors
- **Tool call logging to reasoning output**: Users can see what tools are doing in real-time
- `ToolCallTracker` dependency system for per-request tool usage logging
- Web search queries appear with 🔍 emoji (e.g., "🔍 Searching for: 'Python 3.13'")
- Calculator expressions appear with 🧮 emoji (e.g., "🧮 Calculating: sqrt(144) + 25")
- Date/time operations appear with 🕐 emoji (e.g., "🕐 Calculating date offset: 2 weeks ago")
- Tool usage visible in `<think>` tags in Open WebUI
### Changed
- **Architecture**: Two-tier request flow (Steward analysis → Tatlock execution)
- **Tool Organization**: Tatlock core tools reorganized into domain directory
- **Tool Scoping**: Tatlock runs with dynamically scoped toolsets per request
- **Responses API**: Integrated Steward preprocessing for all Tatlock requests
- **Streaming**: Enhanced to include Steward reasoning transparency
- Enhanced Tatlock agent with conversation memory capabilities
- All tools now log their usage via `RunContext` dependencies
- Improved debug logging for message history construction
### Fixed
- **Streaming text repetition**: Fixed text accumulation bug causing repetitive output in Open WebUI
- Changed from accumulated text to delta mode (`stream_text(delta=True)`)
- Implemented proper `run_with_scoped_tools_stream()` using PydanticAI's `run_stream()`
- Replaced artificial word-by-word chunking with real LLM deltas
- **Broken tool execution in streaming**: Tools now execute properly in streaming mode
- Previously showed raw JSON function calls instead of executed results
- Now properly streams tool execution results
- **Invalid schema parameter**: Removed invalid `thinking` parameter from `ReasoningOutputItem`
- **Case sensitivity in model routing**: Model comparison now case-insensitive (`.lower()`)
- Conversation context now properly maintained across multiple turns
- Tool usage transparency - users can see exactly what queries/calculations are being performed
- Schema object handling in usage calculation (_calculate_usage reordered isinstance checks)
## [0.2.0] - 2025-12-06
### Added
#### PydanticAI Integration (Phase 1)
- Real Tatlock agent using PydanticAI with Ollama backend (mistral-nemo:latest)
- British butler personality with research-oriented mindset
- Lazy agent initialization to avoid connection issues in tests
- Streaming response integration with reasoning output
- Error handling for PydanticAI-specific exceptions
#### Permanent Tools (Phase 1)
- **Calculator tool** (`src/agents/tools.py`):
- Safe mathematical expression evaluation using restricted namespace
- Support for arithmetic, algebra, trigonometry, logarithms
- Math functions: sqrt, sin, cos, tan, log, exp, etc.
- Constants: pi, e
- Integer result formatting (removes unnecessary decimals)
- **Date/Time toolkit**:
- `get_current_datetime`: Current date/time in multiple formats
- `calculate_time_offset`: Relative date calculations ("1 week ago", "2 months from now")
- `time_difference`: Human-readable time differences between dates
- **Web Search tool**:
- SearXNG integration for privacy-preserving web search
- Automatic fallback from production to localhost in development
- Formatted search results with titles, URLs, and snippets
- Configurable result limits (max 10)
#### Tool Framework
- PydanticAI tool registration with `@agent.tool` decorator
- Tool descriptions visible to LLM for intelligent usage
- Async tool support for I/O operations
- Error handling with string-based error messages
- Tool usage guidelines in system prompt
#### Configuration
- SearXNG configuration in `src/core/config.py`:
- `SEARXNG_HOST` with development fallback
- `SEARXNG_TIMEOUT` setting
- Updated `.env.example` with SearXNG configuration
- Ollama configuration documentation
#### Testing
- 26 new tool tests (`tests/agents/test_tools.py`):
- 7 calculator tests (arithmetic, functions, error handling)
- 14 date/time tests (current time, offsets, differences)
- 5 web search tests (mocked HTTP client)
- Updated registry tests for tools capability
- Total: 131 tests, 81.78% coverage (up from 95 tests, 78.95%)
#### Documentation
- Comprehensive README.md updates:
- Tatlock agent capabilities and tool descriptions
- Requirements section with Ollama and SearXNG setup
- Configuration examples for external services
- Tool usage examples and philosophy
- Troubleshooting for Ollama and SearXNG
- Updated test statistics
- AGENTS.md refactored for LLM development:
- PydanticAI tool registration pattern
- Tool implementation guidelines
- Removed project status, focused on development instructions
- IMPLEMENTATION_ROADMAP.md updates:
- Phase 1 marked as "MOSTLY COMPLETE"
- Detailed completion status for each deliverable
- Updated current state summary
### Changed
- Tatlock agent converted from mock to real PydanticAI implementation
- Tatlock capabilities updated: `tools: True`
- Streaming coordination now handles chunk-based delivery (50 chars) to preserve markdown
- Chat service streaming updated to preserve formatting
- System prompt enhanced with tool usage guidelines and research mindset
- Agent initialization changed to lazy pattern for better testability
### Fixed
- Text duplication bug in streaming responses (proper delta calculation)
- Markdown formatting preservation in streamed responses
- GeneratorExit errors from async context managers in generators
- PydanticAI API usage (`result.output` instead of `result.data`)
## [0.1.1] - 2025-12-06
### Added
#### Agent Interface (Phase 1)
- Abstract `AgentInterface` base class for model abstraction
- `LoremTesterAgent`: Full-featured mock agent with realistic behavior
- Configurable reasoning effort levels (none, minimal, low, medium, high, xhigh)
- Random tool/function call generation for testing
- Error triggers: rate_limit, context_overflow, invalid_tool
- Temperature-based response variation
- `TatlockAgent`: Placeholder for future PydanticAI integration
- `ModelRegistry`: Centralized model management and discovery
- 18 agent tests with comprehensive coverage
#### Responses API (Phases 2, 3, 6)
- OpenAI Responses API format with structured output (`/v1/responses`)
- Reasoning items (thinking summaries with configurable effort)
- Function call items (tool execution simulation)
- Message items (assistant responses with output_text)
- Streaming and non-streaming modes
- Real-time streaming with SSE-Starlette
- Conversation history management (Phase 3):
- Hybrid client/server approach (client maintains state, server tracks)
- Auto-generated deterministic conversation IDs from message hash
- Configurable max turns with automatic trimming (default: 20)
- Context window management with approximate token counting
- Token usage statistics
- Placeholder for future vector memory (Qdrant)
- Advanced features (Phase 6):
- Parameter validation with Pydantic field validators
- Temperature: 0.0-2.0 range enforcement
- Reasoning effort: 6 levels validation
- Max output tokens: positive integer enforcement
- Stop sequences: up to 4, non-empty strings
- Real-time stop sequence detection during streaming
- Real-time max tokens enforcement with token counting
- 45 Responses API tests (router, error handling, history, advanced features)
#### Chat Completions Wrapper (Phase 5)
- OpenAI Chat Completions compatibility layer (`/v1/chat/completions`)
- Single source of truth architecture (wraps Responses API)
- Automatic reasoning generation
- Converts reasoning items to `<think>` tags for Open WebUI
- Pipeline prefix preservation
- System message support
- Enhanced error types (RateLimitError, ContextLengthError)
- 12 Chat Completions tests (router + streaming wrapper)
#### Application Infrastructure
- FastAPI application factory pattern
- CORS middleware with configurable origins
- Global exception handlers:
- AppException handler for custom errors
- RequestValidationError handler for Pydantic validation
- General exception handler for unexpected errors
- Lifespan management for startup/shutdown
- OpenAPI schema with interactive documentation
- 16 main application tests
#### Testing Infrastructure
- Comprehensive test suite: 95 tests, 78.95% coverage (up from 62%)
- Async test support with pytest-asyncio
- Test fixtures for sync and async clients
- Integration tests for all API endpoints
- Streaming functionality tests
- Parameter validation tests
- Error handling tests
- Conversation history tests
#### Documentation
- Complete README.md rewrite with hybrid architecture
- Architecture diagrams and decision documentation
- AGENTS.md with technical implementation details
- API usage examples for all endpoints
- Conversation history guide
- Open WebUI integration instructions
- Troubleshooting section
- Implementation planning documents
### Changed
- Hybrid architecture with Responses API as primary endpoint
- Chat Completions now wraps Responses API (no duplicate logic)
- Enhanced error handling with OpenAI-compatible format
- Improved streaming with word-by-word delivery
- Better test organization with domain-based structure
### Security
- Minor version locking for all dependencies
- All packages CVE-checked (as of 2025-12-06)
- Environment variable protection via .gitignore
- No known vulnerabilities in dependency tree
- Input validation on all API endpoints
## [0.1.0] - 2025-12-06
### Added
- Project initialization
- Python 3.12.11 environment
- FastAPI 0.123.9 web framework
- PydanticAI 1.27.0 dependency (ready for future integration)
- Mock chat completions (lorem ipsum responses)
- Mock model listing (mistral-nemo:latest)
- Testing infrastructure (pytest, coverage, ruff, mypy)
- Configuration management with pydantic-settings
- CORS middleware
- Exception handlers (OpenAI-compatible error format)
[Unreleased]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v2.1.0...main
[2.1.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v2.0.5...v2.1.0
[2.0.5]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v2.0.0...v2.0.5
[2.0.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.11.0...v2.0.0
[1.11.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.10.0...v1.11.0
[1.10.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.9.0...v1.10.0
[1.9.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.8.6...v1.9.0
[1.8.6]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.8.5...v1.8.6
[1.8.5]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.8.4...v1.8.5
[1.8.4]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.8.3...v1.8.4
[1.8.3]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.8.2...v1.8.3
[1.8.2]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.8.1...v1.8.2
[1.8.1]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.8.0...v1.8.1
[1.8.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.7.0...v1.8.0
[1.7.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.6.0...v1.7.0
[1.6.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.5.0...v1.6.0
[1.5.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.4.0...v1.5.0
[1.4.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.3.3...v1.4.0
[1.3.3]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.3.2...v1.3.3
[1.3.2]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.3.1...v1.3.2
[1.3.1]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.3.0...v1.3.1
[1.3.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.2.5...v1.3.0
[1.2.5]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.2.4...v1.2.5
[1.2.4]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.2.3...v1.2.4
[1.2.3]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.2.2...v1.2.3
[1.2.2]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.2.1...v1.2.2
[1.2.1]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.2.0...v1.2.1
[1.2.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.1.0...v1.2.0
[1.1.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v1.0.0a...v1.1.0
[1.0.0a]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v0.2.5...v1.0.0a
[0.2.5]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v0.2.0...v0.2.5
[0.2.0]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v0.1.1...v0.2.0
[0.1.1]: https://git.schweitz.net/jpmschweitzer/tatlock/compare/v0.1.0...v0.1.1
[0.1.0]: https://git.schweitz.net/jpmschweitzer/tatlock/releases/tag/v0.1.0