rag_sec/senamtic_response_generator.py

from transformers import pipeline

class SemanticResponseGenerator:
    def __init__(self):
        self.generator = pipeline("text-generation", model="gpt2")

    def generate_response(self, retrieved_docs):
        combined_docs = " ".join(retrieved_docs[:2])  # Use top 2 matches
        response = self.generator(f"Based on the following information: {combined_docs}", max_length=100)
        return response[0]["generated_text"]