Compare commits
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9d7ce399c8 | ||
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8e38a568ef |
@@ -25,6 +25,10 @@ REDIS_MEMORY_DB=1
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REDIS_BENCHMARK_DB=6
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REDIS_TIMEOUT=5
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# Qdrant Configuraton
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QDRANT_HOST=qdrant
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QDRANT_PORT=6333
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# Logging
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LOG_LEVEL=INFO
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ENABLE_BENCHMARKS=true
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@@ -7,6 +7,19 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## [Unreleased]
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## [1.3.2] - 2025-12-14
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### Fixed
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- **Memory**: Fix biographer tool type hints for Ollama compatibility (remove `| None` union types)
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## [1.3.1] - 2025-12-14
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### Fixed
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- **Memory**: Add biographer to delegation wrappers (was returning raw tools causing Ollama error)
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- **Config**: Add Qdrant host/port to .env.example
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## [1.3.0] - 2025-12-14
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### Fixed
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@@ -432,7 +432,7 @@ For LLM agent development guidelines and architectural decisions, see [AGENTS.md
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## Version
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Current version: **1.3.0** - Memory system fixes and Redis config cleanup
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Current version: **1.3.2** - Biographer tool type hints fix
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---
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+1
-1
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
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[project]
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name = "tatlock"
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version = "1.3.0"
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version = "1.3.2"
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description = "OpenAI-compatible API with Ollama backend"
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requires-python = ">=3.12"
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dependencies = []
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@@ -25,7 +25,7 @@ logger = get_logger(__name__)
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async def recall_semantic(
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query: str,
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memory_type: str | None = None,
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memory_type: str = "",
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limit: int = 5,
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) -> str:
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"""
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@@ -64,7 +64,7 @@ async def recall_semantic(
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user=user,
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query_vector=query_vector,
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limit=limit,
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memory_type=memory_type,
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memory_type=memory_type if memory_type else None,
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)
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if not results:
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@@ -111,7 +111,6 @@ async def recall_semantic(
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async def store_insight(
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key: str,
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value: str,
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keywords: list[str] | None = None,
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importance: float = 0.5,
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) -> str:
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"""
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@@ -128,7 +127,6 @@ async def store_insight(
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Args:
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key: Short identifier for the memory (e.g., "car", "employer", "pet")
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value: The actual information to remember
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keywords: Optional keywords for better search (auto-extracted if not provided)
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importance: How important is this? 0.0 (trivial) to 1.0 (critical)
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Returns:
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@@ -137,15 +135,12 @@ async def store_insight(
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Examples:
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store_insight("car", "User drives a Tesla Model 3")
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store_insight("employer", "Works at Acme Corp as software engineer", importance=0.8)
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store_insight("coffee", "Prefers oat milk lattes", keywords=["coffee", "drink", "preference"])
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"""
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try:
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# Auto-generate keywords if not provided
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if not keywords:
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keywords = [key]
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# Extract simple keywords from value
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words = value.lower().split()
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keywords.extend([w for w in words if len(w) > 4][:5])
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# Auto-generate keywords from key and value
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keywords = [key]
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words = value.lower().split()
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keywords.extend([w for w in words if len(w) > 4][:5])
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success = await memory_service.store_fact(
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key=key,
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@@ -223,12 +223,12 @@ class HouseholdRegistry:
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>>> # Returns: [delegate_to_librarian, calculate, datetime, ...]
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>>> # Instead of: [hybrid_search, search_wiki, create_wiki_page, ... (16 tools)]
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"""
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from src.agents.delegation import delegate_to_librarian
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from src.agents.delegation import delegate_to_librarian, delegate_to_biographer
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# Map of expert names to their delegation wrappers
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delegation_wrappers = {
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"librarian": delegate_to_librarian,
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# Future: "memory": delegate_to_memory,
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"biographer": delegate_to_biographer,
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# Future: "home_automation": delegate_to_home_automation,
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}
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