deepkansara-123 commited on
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db541a4
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1 Parent(s): fab240c

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Files changed (1) hide show
  1. app.py +9 -16
app.py CHANGED
@@ -13,7 +13,7 @@ from database1 import create_db
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  from first1 import pdf_query
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  from q_generator1 import QGenerator
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  from ans_generator1 import AnswerGenerator
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- from flask import request, jsonify
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  import sqlite3, json
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  from q_generator1 import QGenerator
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  from transformers import pipeline
@@ -56,12 +56,10 @@ qgen = QGenerator()
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  qa_model = pipeline("text2text-generation", model="google/flan-t5-base")
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- def generate_qa():
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  try:
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- filename = request.form.get("filename")
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-
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  if not filename:
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- return jsonify({"error": "⚠️ Filename not provided."}), 400
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  # Load chunk_data from DB
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  with sqlite3.connect("my_database.db") as conn:
@@ -70,7 +68,7 @@ def generate_qa():
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  row = cursor.fetchone()
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  if not row:
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- return jsonify({"error": "❌ No data found for this filename."}), 404
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  chunks = json.loads(row[0])
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  qa_pairs = []
@@ -85,24 +83,19 @@ def generate_qa():
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  try:
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  result = qa_model(prompt, max_length=256, do_sample=False)
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  answer = result[0]["generated_text"].strip()
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- qa_pairs.append({
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- "question": question,
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- "answer": answer
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- })
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  except Exception as e:
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  print(f"QA model failed: {e}")
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  continue
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  if not qa_pairs:
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- return jsonify({"message": "⚠️ No Q&A pairs generated."}), 200
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- return jsonify({
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- "filename": filename,
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- "qa_pairs": qa_pairs
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- }), 200
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  except Exception as e:
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- return jsonify({"error": f"❌ Error: {str(e)}"}), 500
 
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  # ✅ Ask question using token (semantic similarity)
 
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  from first1 import pdf_query
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  from q_generator1 import QGenerator
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  from ans_generator1 import AnswerGenerator
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+ from flask import Flask, request, jsonify
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  import sqlite3, json
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  from q_generator1 import QGenerator
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  from transformers import pipeline
 
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  qa_model = pipeline("text2text-generation", model="google/flan-t5-base")
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+ def generate_qa(filename):
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  try:
 
 
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  if not filename:
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+ return "⚠️ Filename not provided."
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  # Load chunk_data from DB
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  with sqlite3.connect("my_database.db") as conn:
 
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  row = cursor.fetchone()
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  if not row:
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+ return "❌ No data found for this filename."
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  chunks = json.loads(row[0])
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  qa_pairs = []
 
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  try:
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  result = qa_model(prompt, max_length=256, do_sample=False)
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  answer = result[0]["generated_text"].strip()
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+ qa_pairs.append(f"Q: {question}\nA: {answer}")
 
 
 
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  except Exception as e:
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  print(f"QA model failed: {e}")
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  continue
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  if not qa_pairs:
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+ return "⚠️ No Q&A pairs generated."
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+ return "\n\n".join(qa_pairs)
 
 
 
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  except Exception as e:
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+ return f"❌ Error: {str(e)}"
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+
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  # ✅ Ask question using token (semantic similarity)