runtime error

Exit code: 1. Reason: tabase initialized ================================================================================ 🚀 BUILDING VECTOR DATABASE (RAG - Real Documents Only) ================================================================================ ⚠️ NOTE: Training Q&A pairs are for fine-tuning ONLY! ⚠️ Vector DB should contain ONLY actual web content with URLs ❌ Document file not found: /app/data/rackspace_knowledge.json ⚠️ Please run the data integration script first! ❌ No documents to index! ================================================================================ 🧪 TESTING DATABASE ================================================================================ 🔍 Testing search: 'What are Rackspace's cloud adoption and migration services?' 📋 Top 5 results: 🔍 Testing search: 'How do I deploy applications on AWS with Rackspace?' 📋 Top 5 results: ✅ Vector DB rebuilt successfully! 🔤 Loading embedding model: sentence-transformers/all-MiniLM-L6-v2 Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads. Loading weights: 0%| | 0/103 [00:00<?, ?it/s] Loading weights: 100%|██████████| 103/103 [00:00<00:00, 3590.95it/s] BertModel LOAD REPORT from: sentence-transformers/all-MiniLM-L6-v2 Key | Status | | ------------------------+------------+--+- embeddings.position_ids | UNEXPECTED | | Notes: - UNEXPECTED :can be ignored when loading from different task/architecture; not ok if you expect identical arch. ✅ Enhanced RAG Chatbot with Groq ready! Traceback (most recent call last): File "/app/app.py", line 4, in <module> chatbot = get_chatbot() File "/app/enhanced_rag_chatbot.py", line 890, in get_chatbot _chatbot_instance = EnhancedRAGChatbot() File "/app/enhanced_rag_chatbot.py", line 66, in __init__ query_embedding = self.embedding_model.encode([query])[0] NameError: name 'query' is not defined

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