Commit Graph
16 Commits
Author SHA1 Message Date
jpmschweitzerandClaude Opus 4.5 1e4bba2422 feat: add sequential multi-expert execution to orchestration
Adds multi-expert coordination infrastructure:
- ExecutionMode enum (SEQUENTIAL, PARALLEL)
- MultiExpertResult dataclass for aggregating results
- execute_sequential(): Tasks run one after another
- execute_parallel(): Tasks run concurrently via asyncio.gather
- orchestrate_multi_expert(): Streaming think updates during multi-expert work

Supports:
- Stop-on-failure mode for sequential execution
- Partial failure handling (some succeed, some fail)
- Result aggregation with combined output formatting
- Exception handling in parallel execution

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-13 13:22:11 +01:00
jpmschweitzerandClaude Opus 4.5 1970751b2f feat: add orchestration loop with think update streaming
Creates orchestration module for multi-expert coordination:
- parse_delegation_from_steward_note(): Extracts delegation task
- execute_delegation(): Routes to appropriate expert agent
- orchestrate_with_think_updates(): Streams <think> updates around
  delegation calls while using run() internally

This enables real-time user feedback while avoiding Ollama's
streaming+tool call bugs.

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-13 12:59:20 +01:00
jpmschweitzerandClaude Opus 4.5 6cc0bd78b2 feat: update Steward prompt for clearer delegation instructions
Updates Steward's output format to structured delegation format:
- DELEGATE: [capability] to [action] [task]
- REASON: [explanation]
- COMPLEXITY: [simple/moderate/complex]
- CONTEXT: [relevant history or "none"]

Also adds guidance for conversation memory queries (handled by
Tatlock directly, not delegated to Librarian).

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-13 12:46:51 +01:00
jpmschweitzerandClaude Opus 4.5 54b6fcd7cc feat: add DelegationTask dataclass and delegate_to_librarian wrapper
Introduces agent-as-tool pattern infrastructure:
- DelegationTask: Structured representation of expert work
- DelegationResult: Typed result from expert delegation
- delegate_to_librarian(): Wrapper for Librarian agent calls

This implements PydanticAI's recommended delegation pattern where
parent agents call child agents via tool wrappers.

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-13 11:19:35 +01:00
jpmschweitzerandClaude Opus 4.5 b5ee1f3e44 fix: use run() instead of run_stream() for scoped tools to avoid Ollama 400 bug
PydanticAI + Ollama streaming with tool calls has known issues:
- Issue #1292: Streaming stops after tool call due to empty TextPart
- Issue #2256: Empty text part causes run to end prematurely

This change uses run() for the actual tool execution while still
yielding the response in chunks to maintain the streaming UX.
The orchestration loop can emit <think> updates between await calls.

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-12 10:59:58 +01:00
jpmschweitzerandClaude Opus 4.5 4efa717796 fix: improve Steward delegation instructions for Librarian
Build and Push / build (release) Successful in 10s
- Update Librarian capability description to highlight CREATE/UPDATE/SEARCH
- Add specific Steward guidelines for wiki creation, updates, and research
- Add dynamic time injection to user prompts for temporal awareness
- Expand domains to include 'create', 'write', 'update'
- Update test to match new capability description

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-11 21:55:17 +01:00
jpmschweitzerandClaude Opus 4.5 7ec6e03c65 feat(phase3): add multi-agent coordination engine
- CoordinationEngine for task orchestration between agents
- 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()

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-11 21:29:03 +01:00
jpmschweitzerandClaude Opus 4.5 f6f37b341b feat(phase3): add The Librarian agent with library-desk integration
Library-Desk API Client:
- Async HTTP client with httpx for library-desk API
- HybridRAG search (vector + graph + web)
- Wiki operations (search, get, list, create, update)
- Smart page creation with HybridRAG research
- Semantic vector search and knowledge graph queries
- Dossier browsing and health checks

Librarian Tools (11 total):
- Research: hybrid_search, search_wiki, get_wiki_page, semantic_search
- Browse: list_dossiers, get_dossier_pages, explore_knowledge_graph
- Graph: find_related_entities
- Write: create_wiki_page, update_wiki_page, smart_create_wiki_page

Agent:
- PydanticAI agent with research assistant personality
- System prompt with research and writing workflows
- Streaming support via run_librarian_stream()

Capability:
- LIBRARIAN_CAPABILITY definition for Household Registry
- Automatic registration on startup

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-11 21:27:09 +01:00
jpmschweitzerandClaude Opus 4.5 92c0d5d770 feat(phase3): add agent communication protocol
- AgentRequest/AgentResponse for standardized inter-agent communication
- DelegationIntent for routing tasks to expert agents
- CoordinationResult for aggregated multi-agent results
- DelegationReason enum (domain expertise, tool access, etc.)
- Error types: AgentError, AgentTimeoutError, AgentUnavailableError

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-11 21:26:52 +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
jpmschweitzerandClaude Sonnet 4.5 38120696bf feat: add conversation history and tool call logging
Add two major features to enhance Tatlock's capabilities:

1. Conversation History Support:
   - Convert OpenAI-format messages to PydanticAI ModelRequest/ModelResponse
   - Pass full conversation context via message_history parameter
   - Filter empty messages to prevent Ollama errors
   - Add debug logging for message history construction
   - Tatlock now remembers previous turns in multi-turn conversations

2. Tool Call Logging:
   - Implement ToolCallTracker dependency for per-request tracking
   - Tools log usage via RunContext deps parameter
   - Web search: "🔍 Searching for: 'query'"
   - Calculator: "🧮 Calculating: expression"
   - Date/time: "🕐 Calculating date offset: description"
   - Tool logs appear in reasoning output as <think> tags in Open WebUI

Both features improve user experience by maintaining conversation context
and providing transparency into tool usage.

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Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2025-12-07 01:13:19 +01:00
jpmschweitzer 67481515cc feat: integrate Tatlock agent with PydanticAI and Ollama
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
2025-12-07 00:12:39 +01:00
jpmschweitzer f3e2681a6c feat: implement permanent tools (calculator, date/time, search)
Add three permanent tools for Tatlock agent:
- Calculator: Safe math expression evaluation (arithmetic, algebra, trig, log)
- Date/Time toolkit: Current time, relative dates, time differences
- Web Search: SearXNG integration for privacy-preserving search

Tools use PydanticAI @agent.tool decorator pattern with:
- Clear docstrings visible to LLM
- Error handling with string-based messages
- Async support for I/O operations (web search)
- 26 comprehensive tool tests
2025-12-07 00:10:49 +01:00
jpmschweitzer da9b4954be rename to Tatlock 2025-12-06 20:59:15 +01:00
jpmschweitzerandClaude 4e6ca4466b Add agent interface and model implementations
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

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-06 19:36:53 +01:00