Gemini ve OpenRouter ile Open Deep Research çalıştırma

# Open Deep Research - AI-Powered Autonomous Research Workflow ## Overview Automated workflow: Open Deep Research - AI-Powered Autonomous Research Workflow. This workflow integrates 11 different services: stickyNote, httpRequest, code, agent, chainLlm. It contains 21 nodes and follows best practices for error handling and security. ## Workflow Details - Total Nodes: 21 - Node Types: 11 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - Chat Message Trigger: chatTrigger - Generate Search Queries using LLM: chainLlm - LLM Response Provider (OpenRouter): lmChatOpenRouter - Parse and Chunk JSON Data: code - Perform SerpAPI Search Request: httpRequest - Perform Jina AI Analysis Request: httpRequest - Format SerpAPI Organic Results: code - Extract Relevant Context via LLM: agent - Generate Comprehensive Research Report: agent - Split Data for SerpAPI Batching: splitInBatches - ... and 11 more nodes ## Usage Instructions 1. Configure Credentials: Set up all required API keys and credentials 2. Update Variables: Replace any placeholder values with actual data 3. Test Workflow: Run in test mode to verify functionality 4. Deploy: Activate the workflow for production use ## Security Notes - All sensitive data has been removed or replaced with placeholders - Error handling is implemented for reliability - Follow security best practices when configuring credentials ## Troubleshooting - Check error logs if workflow fails - Verify all credentials are properly configured - Ensure all required services are accessible