Add comprehensive test suite covering:
Conversation History Tests:
- test_tatlock_conversation_history_memory: Verify Tatlock remembers user's
name and preferences across turns
- test_tatlock_multi_turn_context: Ensure context maintained over multiple
turns with topic references
- test_tatlock_conversation_history_with_tools: Test memory works correctly
when tools are used
Tool Call Logging Tests:
- test_tatlock_tool_call_logging_search: Verify search queries appear in
reasoning output with 🔍 emoji
- test_tatlock_tool_call_logging_calculator: Check calculator expressions
logged with 🧮 emoji
- test_tatlock_tool_call_logging_datetime: Ensure date/time operations shown
with 🕐 emoji
- test_tatlock_no_tool_calls_no_logging: Confirm tool logging only appears
when tools are actually used
All tests verify tool usage appears in <think> tags visible in Open WebUI.
Tests use non-streaming responses for deterministic assertions.
14/15 tests passing consistently (93% pass rate).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Convert Tatlock from mock to real PydanticAI agent:
- Connect to Ollama backend (mistral-nemo:latest)
- British butler personality with research-oriented mindset
- Lazy initialization pattern for better testability
- Register permanent tools (calculator, date/time, search)
- Streaming response support with reasoning output
- Error handling for PydanticAI exceptions
- Update registry tests for tools capability
- Add integration test for streaming functionality
Application Configuration:
- FastAPI application factory pattern
- CORS middleware for cross-origin support
- Global exception handlers for consistent error responses
- AppException handler for custom errors
- RequestValidationError handler for Pydantic validation
- General exception handler for unexpected errors
- Lifespan management for startup/shutdown events
- Router registration for all API endpoints
- OpenAPI schema with interactive documentation
Models Service:
- Integration with ModelRegistry
- List available models endpoint
- Model capability discovery
Test Infrastructure:
- Pytest configuration with async support
- Test client fixtures for sync and async testing
- Comprehensive main application tests (14 tests):
- App creation and metadata
- Router registration verification
- CORS middleware and functionality
- Exception handler registration and behavior
- Lifespan event handling
- OpenAPI schema generation
- Documentation accessibility
- Validation error handling
- Models API tests (2 tests)
- Total: 95 tests, 78.95% coverage
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implements Phase 5: OpenAI Chat Completions compatibility layer
Features:
- Wraps Responses API for single source of truth
- Automatically enables reasoning generation
- Converts reasoning items to <think> tags for Open WebUI
- Maintains OpenAI-compatible chat completion format
- Supports both streaming and non-streaming modes
- Pipeline prefix preservation for model names
- System message handling
Architecture:
- Service layer calls Responses API internally
- Streams word-by-word for smooth UX
- Reasoning displayed in thought bubbles (Open WebUI)
- Main response shown separately from thinking
Error Handling:
- Enhanced exception types (RateLimitError, ContextLengthError)
- OpenAI-compatible error format
- Graceful error propagation from Responses API
Testing:
- 6 unit tests for chat router functionality
- 6 unit tests for streaming wrapper behavior
- Total: 12 tests with comprehensive coverage
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implements Phase 1: Agent abstraction layer with multiple model support
Features:
- Abstract AgentInterface base class with standard contract
- LoremTesterAgent: Full-featured mock agent with realistic behavior
- Configurable reasoning effort levels (none to xhigh)
- Random tool/function call generation
- Error triggers for testing (rate_limit, context_overflow)
- Temperature-based response variation
- TatlockAgent: Placeholder for future PydanticAI integration
- ModelRegistry: Centralized model management and discovery
Testing:
- 9 unit tests for lorem-tester agent behavior
- 9 unit tests for registry operations
- Coverage: Agent abstraction fully tested
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
jpmschweitzerandClaude Sonnet 4.5