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fix: resolve service validation and timeout issues in agent workflow
- Fix LLM router prompts to use correct service name 'station_data' instead of 'table_scraper' - Increase agent timeout from 30s to 60s for web scraping operations - Optimize table scraper wait times (reduce by ~9 seconds total) - Remove redundant tool_planning_node from workflow architecture - Add comprehensive logging with colored output for development - Update LLM configurations to latest model versions (Gemini 1.5, GPT-4o, Claude 3.5) - Add input validation and improved error handling with specific error types - Remove deprecated parsed_intent state field in favor of routing_result - Fix Streamlit CORS configuration and update documentation - Add test scripts for agent validation and debugging Resolves service validation rejection errors and timeout issues when running locally. Agent now successfully processes OMIRL weather queries with proper routing validation. Tested: ✅ Service validation passes ✅ Tool execution completes within timeout8e973ef
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Comprehensive update: LLM Router implementation and Docker fixes
Major Features: - Implemented LLM Router with support for multiple providers (Gemini, OpenAI, Anthropic) - Added LLM router configuration and validation system - New agent architecture with improved state management and nodes - Enhanced geographic services and text summarization capabilities Docker Improvements: - Fixed Playwright installation using 'python -m playwright install chromium' - Added PATH configuration for app user to resolve Streamlit executable issues - Cleaned up system dependencies and removed conflicting environment variables Security & Configuration: - Added pre-commit security hooks for API key protection - Implemented comprehensive secret checking system - Enhanced .gitignore for better security coverage - Added environment configuration management - Fixed API key pattern detection to avoid false positives in code/docs Documentation: - Added deployment guide and progress tracking documents - Documented LLM router progress and integration tasks - Added security s…e45fdd8
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Set up of the project structure: langgraph and tool based agent. Implemented first tool and task: omirl_snapshot_summary adapter can scrape data from sensorstable omirl. Next step: add tool to agentic framework and deploy to hugging face. Next step: scrape data based on sensor filter.
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