Introduction
You will complete your agent by adding a Text2Cypher query tool as the third tool.
The agent automatically chooses the best tool for each question type:
Schema Tool:
Document Retrieval Tool:
Database Query Tool:
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Precise queries and counts
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"How many risk factors does Apple face?"
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"What stock has Microsoft issued?"
Open the notebook: 02_03_text2cypher_agent.ipynb
Your complete agent will now have:
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Tool 1: Schema Tool (database structure exploration)
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Tool 2: Document Retrieval Tool (vector search + graph context)
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Tool 3: Database Query Tool (text-to-Cypher for precise queries) ← NEW!
This creates a comprehensive GraphRAG agent that can handle any type of question intelligently.
Try These Questions
Try these questions to see all three tools in action:
Semantic Search (Vector Tool):
Contextual Search (Vector + Cypher Tool):
Precise Queries (Text2Cypher Tool):
Complex Questions (Multiple Tools):
Notice: The agent intelligently selects the right tool(s) for each question type!
Summary
In this lesson, you completed your GraphRAG agent by adding the Text2Cypher Retriever as the third tool:
Key Concepts:
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Complete tool suite: All three retrievers now available as conversational tools
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Intelligent routing: Agent automatically selects best tool(s) for each question
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Progressive capability: From simple search to complex multi-tool reasoning
What You Built:
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Complete GraphRAG agent with three retriever tools
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Conversational interface to all retriever capabilities from previous modules
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Intelligent tool selection for optimal answers
Your Journey:
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✅ Knowledge Graph Creation: PDF to Knowledge Graph pipeline
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✅ Retriever Development: Built three different retrievers
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✅ Agent Tools: Converted retrievers to conversational agent tools
Final Result: A complete GraphRAG agent that can answer any question using the most appropriate retrieval strategy automatically!