generator.py

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
    context = " ".join([doc for doc in retrieved_docs])
    # prompt = """
    #     "You are an accurate and reliable AI assistant that can answer questions with the help of external documents.
    #      Please note that external documents may contain noisy or factually incorrect information. 
    #      If the information in the document contains the correct answer, you will give an accurate answer. 
    #      If the information in the document does not contain the answer, you will generate ’I can not answer the question because of the insufficient information in documents.‘. 
    #      If there are inconsistencies with the facts in some of the documents, please generate the response 'There are factual errors in the provided documents.' and provide the correct answer."

    #      Context or Document: {context}
    #      Query: {query}
    # """
    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"
            f"Answer the question directly and concisely using only the information available in the context."
             "Do not include any other information which is not there 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)}"