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app.py
CHANGED
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@@ -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
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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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@@ -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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if not filename:
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return
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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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@@ -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
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chunks = json.loads(row[0])
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qa_pairs = []
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@@ -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
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return
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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
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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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# ✅ Ask question using token (semantic similarity)
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