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🔒 Add real AI knowledge graph integration (API keys redacted)
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🎯 Add Automatic Sample Data System for New Users
✅ Features implemented: • Automatic sample data insertion for empty databases • 3 curated examples showing increasing complexity levels • Pre-generated knowledge graphs for each sample trace • Non-destructive insertion (skips if data exists) 📊 Sample data includes: • Basic Q&A: Simple arithmetic calculation (6 entities, 5 relations) • Research Task: Location/hours research (6 entities, 6 relations) • Multi-Agent: Algorithm analysis (10 entities, 16 relations) 🔧 Technical implementation: • backend/database/sample_data.py - Core data and insertion logic • backend/database/init_db.py - Modified to trigger insertion • Full transaction support with error handling • Comprehensive logging and status reporting 🎯 User experience: • New users see working examples immediately • Examples serve as templates and learning materials • Demonstrates different trace types and complexity levels • No more empty system on first launch 📚 Documentation: • Complete READM…9e60d50 -
🎯 Add Smart Sample Data Preloading System
✨ New Features: • Intelligent sample data preloader for better UX • Auto-preloads 6 diverse examples on first startup • Smart selection algorithm ensures variety in agent types, complexity, domains • Non-blocking background preload doesn't delay startup 🔧 Implementation: • backend/scripts/preload_sample_data.py - Core preloading logic • Modified backend/app.py with startup preload check • Enhanced trace metadata with rich categorization tags • Handles database deduplication and error recovery 📊 Benefits: • New users get immediate examples to explore • No more empty 'My Traces' on first visit • Diverse samples showcase different agent interaction patterns • Knowledge graphs can be generated on-demand from preloaded traces 🐛 Bug Fixes: • Fixed 'str expected, not NoneType' errors in multiple modules • Added null checks for OPENAI_API_KEY environment variable • Resolved circular import issues in knowledge graph components 🚀 User Experience: • Immedia…95b5fc0 -
🧹 Code Cleanup and Optimization
✅ Improvements: • Removed debug print statements from backend/app.py • Cleaned up unnecessary imports in backend/database/__init__.py • Optimized knowledge graph processing modules • Removed temporary debugging code across multiple files 🎯 Focus areas: • Backend startup process optimization • Database initialization cleanup • Knowledge graph processing efficiency • Multi-agent extractor refinements 🚀 Impact: • Cleaner console output in production • Improved code maintainability • Better performance with fewer debug calls • Professional deployment-ready codebasefa515bb -
🎉 Complete Fix for HF Spaces Sample Data Loading
✅ Fixed All Critical Issues: 1. OPENAI_API_KEY None TypeError (4 files): - multi_agent_knowledge_extractor.py - knowledge_graph_merger.py - knowledge_graph_tester.py - knowledge_graph_processor.py → Added null checks: if OPENAI_API_KEY: os.environ[...] = OPENAI_API_KEY 2. SQLAlchemy ObjectNotExecutableError: - Added text() import and wrapped all SQL strings → All execute() calls now use text("SQL") format 3. SQLAlchemy ArgumentError - Parameter Format: - Converted positional parameters to named parameters - Changed ?, ?, ? → :param1, :param2, :param3 - Changed tuple params → dict params → All queries now use {"param1": value1, "param2": value2} format 🎯 Local Test Results: ✅ Application starts successfully ✅ Sample data loads completely: • 1 trace inserted • 1 knowledge graph inserted • 5 entities inserted • 4 relations inserted ✅ All database operations successful ✅ Transaction committed successfully ✅ Final counts match expected values…de48716
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🔧 Fix 'str expected, not NoneType' startup error
✅ Problem solved: • Fixed LANGFUSE environment variable assignment in knowledge_graph_tester.py • Added null checks before setting os.environ values • Only set env vars when values are not None 🎯 Root cause: • Lines 40-41 unconditionally set LANGFUSE_PUBLIC_KEY/SECRET_KEY to environ • These could be None, causing TypeError in os.environ assignment • Added proper null validation ⚡ Result: • Backend server now starts successfully • No more TypeError: str expected, not NoneType • Ready for HF Spaces deployment26d8ef2 -
🚀 Deploy AgentGraph: Complete agent monitoring and knowledge graph system
Features: - 📊 Real-time agent monitoring dashboard - 🕸️ Knowledge graph extraction from traces - 📈 Interactive visualizations and analytics - 🔄 Multi-agent system with CrewAI - 🎨 Modern React + FastAPI architecture Ready for Docker deployment on HF Spaces (port 7860)c2ea5ed