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| import openai | |
| import time | |
| import os | |
| # Set your OpenAI API key | |
| openai.api_key = os.getenv("OPENAI_API_KEY") | |
| def generate_response_from_document(query, retrieved_docs): | |
| if not retrieved_docs: # Check if no documents were retrieved | |
| return "I cannot answer the question due to insufficient information in the documents." | |
| context = " ".join([doc.page_content for doc in retrieved_docs]) # Now iterates over Document objects | |
| prompt = ( | |
| "You are a highly intelligent assistant tasked with answering a question based strictly on the provided context. " | |
| f"Given Question: {query} \n\n" | |
| f"Context: {context} \n" | |
| "Answer the question directly and concisely using only the information available in the context." | |
| ) | |
| try: | |
| response = openai.chat.completions.create( # Use the new chat completions API | |
| model= "gpt-3.5-turbo", #"gpt-4", #"gpt-3.5-turbo" Or use another suitable model like gpt-4 | |
| messages=[{"role": "user", "content": prompt}], | |
| max_tokens=300, | |
| temperature=0.7, | |
| ) | |
| return response.choices[0].message.content.strip() # Extract content from message | |
| except Exception as e: | |
| return f"Error generating response: {str(e)}" |