Commit Graph
7 Commits
Author SHA1 Message Date
jpmschweitzerandClaude Opus 4.5 49f0da8068 feat: two-phase execution, think slugs, query enrichment (v1.6.0)
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Two-Phase Tatlock Execution:
- orchestrate_tool_calls() for Phase 1 coordination
- synthesize_from_results() for Phase 2 butler-toned synthesis
- Guarantees butler personality in all responses

Automatic Think Slugs:
- Deterministic butler-perspective messages during expert delegation
- ActionType enum: RETRIEVE, RESEARCH, CREATE, CONTROL, RECORD
- HOUSEHOLD_THINK_MESSAGES mapping for all experts
- Streaming delegation wrappers with automatic think messages

Steward Query Enrichment:
- Auto-fill user context (location, timezone) when not specified
- _build_enriched_query() with regex word boundary matching
- enriched_query field in StewardRecommendation schema

Documentation:
- ORCHESTRATION_SCENARIOS.md rewritten with Mermaid diagrams
- New Housekeeper and Biographer scenarios
- TESTING_IMPROVEMENTS.md for future LLM testing patterns

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-15 14:00:32 +01:00
jpmschweitzerandClaude Opus 4.5 64cad4500a feat: environment-aware config, direct delegation, E2E test suite (v1.4.0)
Build and Push / build (release) Successful in 52s
### 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 4d109100fe fix: implement proper streaming with PydanticAI delta mode
Fix streaming issues that caused text repetition and broken tool execution
in Open WebUI. Implements real LLM streaming using PydanticAI's run_stream()
with delta=True instead of artificial word-by-word chunking.

**Fixed:**
- Text repetition in streaming output (was accumulating instead of deltas)
- Broken tool execution (tools now execute properly in streaming mode)
- Invalid 'thinking' parameter in ReasoningOutputItem schema

**Changes:**
- Add run_with_scoped_tools_stream() method to TatlockAgent
  - Uses PydanticAI's run_stream() with delta=True for real deltas
  - Properly streams LLM output with tool execution
- Update StreamingCoordinator.stream_response_with_steward()
  - Uses new streaming method instead of fake word-by-word streaming
  - Removes invalid thinking parameter from ReasoningOutputItem
- All streaming now uses actual LLM deltas, not accumulated text

Resolves streaming issues reported in Open WebUI where responses showed
repetitive text and tool calls appeared as raw JSON instead of executed results.

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Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2025-12-07 15:39:52 +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
jpmschweitzer 4216d89f12 fix: resolve streaming duplication and markdown formatting issues
- Fix text duplication bug with proper delta calculation
- Preserve markdown formatting with chunk-based delivery (50 chars)
- Handle GeneratorExit errors from async context managers
- Update Chat service streaming to preserve formatting
- Ensure proper word-by-word streaming without duplicates
2025-12-07 00:12:52 +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