mirror of
https://github.com/basicmachines-co/basic-memory
synced 2026-06-21 13:47:35 +00:00
Paul Hernandez
093dab5f03
## Summary - Add comprehensive documentation to all MCP prompt modules - Enhance search prompt with detailed contextual output formatting - Implement consistent logging and docstring patterns across prompt utilities - Fix type checking in prompt modules ## Prompts Added/Enhanced - `search.py`: New formatted output with relevance scores, excerpts, and next steps - `recent_activity.py`: Enhanced with better metadata handling and documentation - `continue_conversation.py`: Improved context management ## Resources Added/Enhanced - `ai_assistant_guide`: Resource with description to give to LLM to understand how to use the tools ## Technical improvements - Added detailed docstrings to all prompt modules explaining their purpose and usage - Enhanced the search prompt with rich contextual output that helps LLMs understand results - Created a consistent pattern for formatting output across prompts - Improved error handling in metadata extraction - Standardized import organization and naming conventions - Fixed various type checking issues across the codebase This PR is part of our ongoing effort to improve the MCP's interaction quality with LLMs, making the system more helpful and intuitive for AI assistants to navigate knowledge bases. 🤖 Generated with [Claude Code](https://claude.ai/code) --------- Co-authored-by: phernandez <phernandez@basicmachines.co>
62 lines
2.5 KiB
Python
62 lines
2.5 KiB
Python
"""Tests for MCP prompts."""
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import pytest
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from basic_memory.mcp.prompts.continue_conversation import continue_conversation
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@pytest.mark.asyncio
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async def test_continue_conversation_with_topic(client, test_graph):
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"""Test continue_conversation with a topic."""
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# We can use the test_graph fixture which already has relevant content
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# Call the function with a topic that should match existing content
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result = await continue_conversation(topic="Root", timeframe="1w")
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# Check that the result contains expected content
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assert "Continuing conversation on: Root" in result
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assert "This is a memory retrieval session" in result
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assert "Start by executing one of the suggested commands" in result
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assert "read_note" in result
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@pytest.mark.asyncio
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async def test_continue_conversation_with_recent_activity(client, test_graph):
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"""Test continue_conversation with no topic, using recent activity."""
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# Call the function without a topic
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result = await continue_conversation(timeframe="1w")
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# Check that the result contains expected content for recent activity
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assert "Continuing conversation on: Recent Activity" in result
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assert "This is a memory retrieval session" in result
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assert "Please use the available basic-memory tools" in result
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assert "Next Steps" in result
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@pytest.mark.asyncio
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async def test_continue_conversation_no_results(client):
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"""Test continue_conversation when no results are found."""
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# Call with a non-existent topic
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result = await continue_conversation(topic="NonExistentTopic", timeframe="1w")
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# Check the response indicates no results found
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assert "Continuing conversation on: NonExistentTopic" in result
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assert "I couldn't find any recent work specifically on this topic" in result
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assert "Try a different search term" in result
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@pytest.mark.asyncio
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async def test_continue_conversation_creates_structured_suggestions(client, test_graph):
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"""Test that continue_conversation generates structured tool usage suggestions."""
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# Call the function with a topic that should match existing content
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result = await continue_conversation(topic="Root", timeframe="1w")
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# Verify the response includes clear tool usage instructions
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assert "start by executing one of the suggested commands" in result.lower()
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# Check that the response contains tool call examples
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assert "read_note" in result
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assert "search" in result
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assert "recent_activity" in result
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assert "build_context" in result
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