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## Summary This PR introduces comprehensive Supermemory integration for the Microsoft Agent Framework, providing three complementary approaches to add persistent memory capabilities to agents: middleware for automatic memory injection, context providers for session-based memory management, and tools for explicit memory operations. ## Key Changes - **SupermemoryChatMiddleware**: Automatic memory injection middleware that fetches relevant memories from Supermemory before LLM calls and optionally saves conversations. Supports three modes: - `"profile"`: Injects all static and dynamic profile memories - `"query"`: Searches for memories relevant to the current user message - `"full"`: Combines both profile and query modes - **SupermemoryContextProvider**: Idiomatic context provider following the Agent Framework pattern (similar to built-in Mem0 integration). Integrates with the session pipeline via `before_run()` and `after_run()` hooks for automatic memory retrieval and storage. - **SupermemoryTools**: FunctionTool-compatible tools that agents can use for explicit memory operations: - `search_memories()`: Search for specific memories - `add_memory()`: Add new memories - `get_profile()`: Retrieve user profile - **Utility Functions**: Helper functions for: - Memory deduplication across static, dynamic, and search result sources - Profile-to-markdown conversion for LLM consumption - Message extraction and conversation formatting - Logging with configurable verbosity - **Exception Hierarchy**: Custom exceptions for better error handling: - `SupermemoryConfigurationError`: Missing/invalid configuration - `SupermemoryAPIError`: API request failures - `SupermemoryNetworkError`: Network connectivity issues - `SupermemoryMemoryOperationError`: Memory operation failures - **Comprehensive Documentation**: README with quick start examples, configuration options, and API reference for all three integration approaches. - **Test Suite**: Unit tests covering middleware, context provider, tools, and utility functions with proper mocking and error scenarios. ## Implementation Details - Supports both async (aiohttp) and sync (requests) HTTP clients with automatic fallback - Handles multiple message formats (dict, objects with attributes, content arrays) - Configurable memory storage with optional conversation grouping via `conversation_id` - Environment variable fallback for API key configuration (`SUPERMEMORY_API_KEY`) - Background task management for non-blocking memory operations in middleware - Proper async/sync compatibility for the Supermemory SDK https://claude.ai/code/session_012idB5y6UGK3zmeFULgTc4z
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
"""Tests for Supermemory tools."""
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import pytest
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from supermemory_agent_framework import AgentSupermemory, SupermemoryTools
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def _make_conn(**kwargs):
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kwargs.setdefault("api_key", "test-key")
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kwargs.setdefault("container_tag", "msft_agent_chat")
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return AgentSupermemory(**kwargs)
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class TestSupermemoryTools:
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def test_create_tools_instance(self) -> None:
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conn = _make_conn()
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tools = SupermemoryTools(conn)
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assert tools._connection.container_tag == "msft_agent_chat"
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def test_create_tools_with_custom_tag(self) -> None:
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conn = _make_conn(container_tag="custom-tag")
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tools = SupermemoryTools(conn)
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assert tools._connection.container_tag == "custom-tag"
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def test_get_tools_returns_list(self) -> None:
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conn = _make_conn()
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tools = SupermemoryTools(conn)
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result = tools.get_tools()
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assert isinstance(result, list)
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assert len(result) == 3
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def test_get_tools_names(self) -> None:
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conn = _make_conn()
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tools = SupermemoryTools(conn)
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result = tools.get_tools()
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names = [t.name for t in result]
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assert "search_memories" in names
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assert "add_memory" in names
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assert "get_profile" in names
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def test_uses_connection_client(self) -> None:
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conn = _make_conn()
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tools = SupermemoryTools(conn)
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assert tools._client is conn.client
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def test_shares_custom_id_with_connection(self) -> None:
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conn = _make_conn(conversation_id="conv-123")
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tools = SupermemoryTools(conn)
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assert tools._connection.custom_id == "conversation_conv-123"
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