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984297b62d
## 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
125 lines
4 KiB
Python
125 lines
4 KiB
Python
"""Tests for Supermemory context provider."""
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import pytest
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from supermemory_agent_framework import AgentSupermemory, SupermemoryContextProvider
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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", "user-123")
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return AgentSupermemory(**kwargs)
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class TestContextProviderConfiguration:
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def test_accepts_connection(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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assert provider._container_tag == "user-123"
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assert provider.source_id == "supermemory"
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def test_uses_connection_client(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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assert provider._client is conn.client
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def test_custom_source_id(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(
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conn, source_id="custom-source"
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)
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assert provider.source_id == "custom-source"
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def test_default_mode(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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assert provider._mode == "full"
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def test_custom_mode(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn, mode="profile")
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assert provider._mode == "profile"
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def test_store_conversations_default(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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assert provider._store_conversations is False
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def test_conversation_id_from_connection(self) -> None:
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conn = _make_conn(conversation_id="conv-xyz")
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provider = SupermemoryContextProvider(conn)
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assert provider._connection.conversation_id == "conv-xyz"
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assert provider._connection.custom_id == "conversation_conv-xyz"
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def test_entity_context_from_connection(self) -> None:
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conn = _make_conn(entity_context="User prefers TypeScript")
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provider = SupermemoryContextProvider(conn)
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assert provider._connection.entity_context == "User prefers TypeScript"
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class TestExtractQuery:
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def test_dict_messages(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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class MockContext:
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input_messages = [
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{"role": "user", "content": "Hello!"},
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{"role": "assistant", "content": "Hi!"},
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{"role": "user", "content": "How are you?"},
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]
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result = provider._extract_query_from_context(MockContext())
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assert result == "How are you?"
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def test_empty_messages(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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class MockContext:
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input_messages = []
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result = provider._extract_query_from_context(MockContext())
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assert result == ""
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def test_no_messages_attr(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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class MockContext:
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pass
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result = provider._extract_query_from_context(MockContext())
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assert result == ""
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class TestExtractConversation:
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def test_basic_conversation(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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class MockContext:
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input_messages = [
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{"role": "user", "content": "Hello!"},
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]
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response = None
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result = provider._extract_conversation_from_context(MockContext())
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assert "User: Hello!" in result
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def test_with_response(self) -> None:
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conn = _make_conn()
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provider = SupermemoryContextProvider(conn)
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class MockResponse:
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text = "Hi there!"
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class MockContext:
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input_messages = [
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{"role": "user", "content": "Hello!"},
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]
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response = MockResponse()
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result = provider._extract_conversation_from_context(MockContext())
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assert "User: Hello!" in result
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assert "Assistant: Hi there!" in result
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