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GraphRAG: tg:Question → tg:Exploration → tg:Focus → tg:Synthesis Agent: tg:Question → tg:Analysis(s) → tg:Conclusion All entities also have their PROV-O type (prov:Activity or prov:Entity). Updated commit message: Add provenance recording to React agent loop Enables agent sessions to be traced and debugged using the same explainability infrastructure as GraphRAG. Entity types follow human reasoning patterns: - tg:Question - the user's query (shared with GraphRAG) - tg:Analysis - each think/act/observe cycle - tg:Conclusion - the final answer Also adds explicit TG types to GraphRAG entities: - tg:Question, tg:Exploration, tg:Focus, tg:Synthesis All types retain their PROV-O base types (prov:Activity, prov:Entity). Changes: - Add session_id and collection fields to AgentRequest schema - Add explainability entity types to namespaces.py - Create agent provenance triple generators - Register explainability producer in agent service - Emit provenance triples during agent execution - Update CLI tools to detect and render both trace types |
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TrustGraph Documentation
Welcome to TrustGraph! For comprehensive documentation, please visit:
📖 https://docs.trustgraph.ai
The main documentation site includes:
- Overview - Introduction to TrustGraph concepts and architecture
- Guides - Step-by-step tutorials and how-to guides
- Deployment - Deployment options and configuration
- Reference - API specifications and CLI documentation
Getting Started
New to TrustGraph? Start with the Overview to understand the system.
Ready to deploy? Check out the Deployment Guide.
Integrating with code? See the API Reference for REST, WebSocket, and SDK documentation.