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Author SHA1 Message Date
jpmschweitzerandClaude Opus 4.5 64cad4500a feat: environment-aware config, direct delegation, E2E test suite (v1.4.0)
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Details 
### Added
- Environment-aware configuration:
  - Auto-selected logging (DEBUG for dev, WARNING for prod)
  - Auto-selected default user (llm_tester for dev isolation)
  - User context logging at request entry
- Direct delegation bypass:
  - Pure memory/librarian requests skip Tatlock LLM
  - Reduces latency for memory-only requests
- Text-based delegation fallback:
  - Parse [DELEGATE:agent] patterns from LLM output
  - Sequential and parallel execution support
- Comprehensive E2E test suite:
  - 22 orchestration tests with QdrantVerifier
  - assert_llm_behavior() for flexible pattern matching
  - Tests for memory, delegation, isolation, scenarios

### Fixed
- Unit test mocks for streaming (async generator)
- Temporal context handling in tests
- LLM non-determinism with pytest.xfail()
- Streaming test timeouts increased

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2025-12-14 21:19:47 +01:00
jpmschweitzerandClaude Opus 4.5 4c6ac89808 feat: add Phase F.1 memory infrastructure 
Add multi-tenancy support and memory storage infrastructure:

- Add ContextVar-based request context (src/core/context.py)
  - Async-safe user/conversation tracking via contextvars
  - RequestContext manager for clean setup/teardown
  - get_user(), get_conversation_id() helpers

- Add multi-tenancy utilities (src/core/multi_tenancy.py)
  - User ID sanitization for collection/key names
  - get_memory_collection_name(), get_session_key() helpers

- Add Ollama embedding client (src/core/embeddings.py)
  - nomic-embed-text model (768 dimensions)
  - embed(), embed_batch(), health_check() methods

- Add Qdrant client wrapper (src/core/qdrant.py)
  - Per-user collection pattern: memories_{user}
  - upsert_memory(), search_memories(), delete_memory()
  - Type-based filtering support

- Add Redis memory cache (src/core/memory_cache.py)
  - Session context with 24h TTL
  - Recent entities tracking
  - Separate from benchmarks (db=2)

- Update config with memory settings
  - QDRANT_HOST, QDRANT_PORT, QDRANT_EMBEDDING_DIM
  - OLLAMA_EMBEDDING_MODEL
  - REDIS_MEMORY_DB, REDIS_MEMORY_TTL_HOURS

- Add user field to ResponseRequest (OpenAI standard)
- Set context in router, reset in finally block
- Update librarian client to use get_user() (12 methods)

All 333 unit tests pass.

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
 2025-12-13 17:27:51 +01:00
jpmschweitzerandClaude Sonnet 4.5 6eed5f4d13 feat: implement Phase 2 two-tier architecture with Steward 
Add comprehensive two-tier architecture where Steward analyzes requests
and Tatlock executes with scoped tools. Includes full infrastructure for
request preprocessing, tool tracking, benchmarking, and streaming.

**Added:**
- Steward agent for request analysis and capability recommendation
- Household Registry for centralized capability management
- Request preprocessing pipeline (Steward → Tatlock flow)
- Tool usage tracking and benchmarking system
- Streaming transparency (Steward reasoning visible in streams)
- Structured logging with operation timing
- Redis benchmark storage with 30-day expiry
- Benchmark analysis CLI tools

**Infrastructure:**
- src/agents/steward/ - Steward agent implementation
- src/agents/tatlock_core/ - Tatlock capability domain
- src/core/preprocessing.py - Request preprocessing pipeline
- src/core/tool_tracking.py - Tool call tracking
- src/core/benchmarks.py - Benchmark recording system
- src/core/household_registry.py - Capability registry
- src/core/startup.py - Application startup coordination
- src/core/logging_config.py - Structured logging setup

**Integration:**
- Responses API uses Steward for Tatlock requests
- Chat Completions wraps Responses API for OpenAI compatibility
- Streaming coordinator supports Steward + Tatlock flow
- Tool scoping per request based on Steward recommendations

**Testing:**
- Integration tests for Steward-Tatlock flow
- Benchmark and registry unit tests
- Steward streaming tests

See PHASE2_PLAN.md and PHASE2_COMPLETE.md for detailed documentation.

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Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
 2025-12-07 15:39:20 +01:00
jpmschweitzerandClaude ff6c3cf1b5 Add Responses API with streaming, history, and advanced features 
Implements Phases 2, 3, and 6: Complete Responses API implementation

Core API (Phase 2):
- OpenAI Responses API format with structured output items
- Streaming and non-streaming support via SSE-Starlette
- Reasoning items (thinking summaries)
- Function call items (tool execution)
- Message items (assistant responses)
- Router, schemas, service, and streaming coordinator

Conversation History (Phase 3):
- Hybrid client/server approach
- Auto-generated deterministic conversation IDs
- Configurable max turns with automatic trimming
- Context window management with token counting
- Token usage statistics
- Placeholder for future vector memory integration

Advanced Features (Phase 6):
- Parameter validation with Pydantic field validators:
  - Temperature: 0.0-2.0 range enforcement
  - Reasoning effort: 6 levels (none to xhigh)
  - 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
- Graceful error handling and OpenAI-compatible error format

Testing:
- 9 unit tests for API endpoints and streaming
- 11 unit tests for error handling
- 13 unit tests for conversation history and context
- 12 unit tests for advanced features and validation
- Total: 45 tests with comprehensive coverage

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-06 19:38:00 +01:00