llm.py

import google.generativeai as genai
import os
import json
import time
from dotenv import load_dotenv
load_dotenv()

api_key = os.getenv("GOOGLE_API_KEY")
if not api_key:
    raise ValueError("GOOGLE_API_KEY environment variable is not set. Please add it to your .env file")

print(f"Google API Key loaded: {api_key[:10]}..." if api_key else "No API key found")
genai.configure(api_key=api_key)

def query_gemini(questions, contexts):
    start_time = time.time()
    print(f"Starting LLM processing for {len(questions)} questions with {len(contexts)} context chunks")
    
    try:
        # Time context preparation
        context_start = time.time()
        context = "\n\n".join(contexts)
        context_time = time.time() - context_start
        print(f"Context preparation took: {context_time:.2f} seconds")
        print(f"Total context length: {len(context)} characters")
        
        # Time prompt preparation
        prompt_start = time.time()
        # Create a numbered list of questions
        questions_text = "\n".join([f"{i+1}. {q}" for i, q in enumerate(questions)])
        
        prompt = f"""
You are a skilled insurance policy assistant. Based only on the provided context, answer each question clearly and briefly.

🎯 GOAL:
- Each answer should be precise, informative, and phrased naturally — around 1–2 full sentences.
- Avoid long clauses or repeating policy language verbatim.
- Focus on **clarity**, **brevity**, and **accuracy** — your answers will be judged for quality and relevance.

📘 INSTRUCTIONS:
1. Only use the context below. If the answer is not present, respond with exactly: "Not Found".
2. Answers must be helpful and compact — **complete, but not wordy**. Avoid long multi-clause sentences.
3. Do NOT include section references (like “as per section 3.1.6”) or legal codes.
4. Avoid copying large phrases from the document. Rephrase naturally using simpler language where appropriate.
5. Follow the tone and length of these examples:

   - "A grace period of thirty days is provided for premium payment after the due date."
   - "Yes, maternity expenses are covered after 24 months of continuous coverage, limited to two deliveries or terminations."
   - "Yes, the policy covers organ donor expenses for harvesting the organ if donated to the insured person."
   - "Not Found"

📤 RETURN FORMAT:
Respond in the exact JSON format below — no extra text or explanations.

{{
  "answers": [
    "Answer to question 1",
    "Answer to question 2",
    ...
  ]
}}

📚 CONTEXT:
{context}

❓ QUESTIONS:
{questions_text}

Your task: Answer each question concisely and professionally. Use plain phrasing, stay within 1–2 clear sentences, and avoid unnecessary detail or repetition.
"""





        prompt_time = time.time() - prompt_start
        print(f"Prompt preparation took: {prompt_time:.2f} seconds")
        print(f"Total prompt length: {len(prompt)} characters")
        
        # Time model initialization and API call
        api_start = time.time()
        model = genai.GenerativeModel('gemini-2.0-flash-exp')
        response = model.generate_content(prompt)
        api_time = time.time() - api_start
        print(f"Gemini API call took: {api_time:.2f} seconds")
        
        # Time response processing
        process_start = time.time()
        response_text = response.text.strip()
        print(f"Raw response length: {len(response_text)} characters")
        
        # Try to parse the response as JSON
        try:
            # Remove any markdown code blocks if present
            if response_text.startswith("```json"):
                response_text = response_text.replace("```json", "").replace("```", "").strip()
            elif response_text.startswith("```"):
                response_text = response_text.replace("```", "").strip()
            
            parsed_response = json.loads(response_text)
            process_time = time.time() - process_start
            print(f"Response processing took: {process_time:.2f} seconds")
            
            total_time = time.time() - start_time
            print(f"Total LLM processing took: {total_time:.2f} seconds")
            
            return parsed_response
        except json.JSONDecodeError:
            # If JSON parsing fails, return a structured response
            process_time = time.time() - process_start
            print(f"Response processing took: {process_time:.2f} seconds (JSON parsing failed)")
            print(f"Failed to parse JSON response: {response_text}")
            
            total_time = time.time() - start_time
            print(f"Total LLM processing took: {total_time:.2f} seconds")
            
            return {"answers": ["Error parsing response"] * len(questions)}
            
    except Exception as e:
        total_time = time.time() - start_time
        print(f"Error in query_gemini after {total_time:.2f} seconds: {str(e)}")
        return {"answers": [f"Error generating response: {str(e)}"] * len(questions)}