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Main Execution Script for Retrieval-based Medical QA Chatbot
============================================================
This script handles:
1. Query preprocessing
2. Information retrieval
3. Answer generation
"""
import warnings
warnings.filterwarnings("ignore", category=UserWarning)
from dotenv import load_dotenv
load_dotenv()
from Query_processing import preprocess_query
from Retrieval import Retrieval_averagedQP
from Answer_Generation import answer_generation
from Retrieval import Embed_and_FAISS
# -------------------------------
# Optional: Embed and Store FAISS Index
# -------------------------------
# Uncomment the below line to generate embeddings and build the FAISS index if not already done.
# Embed_and_FAISS()
# -------------------------------
# Define User Question
# -------------------------------
Question = input("Enter your question: ")
# -------------------------------
# Step 1: Query Preprocessing
# -------------------------------
(intent, sub_intent), entities = preprocess_query(Question)
# -------------------------------
# Step 2: Retrieve Relevant Chunks
# -------------------------------
top_chunks = Retrieval_averagedQP(Question, intent, entities, top_k=10, alpha=0.8)
# -------------------------------
# Step 3: Answer Generation
# -------------------------------
Generated_answer = answer_generation(Question, top_chunks, top_k=3)
# -------------------------------
# Display Generated Answer
# -------------------------------
print("Generated Answer:", Generated_answer)
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