Update app.py

app.py

@@ -18,7 +18,7 @@ embedding_model = SentenceTransformer("intfloat/e5-large")
 
 print("Loading text generation model...")
 # Use a lighter model for testing
-#qa_pipeline = pipeline("text-generation", model="gpt2")
+qa_pipeline = pipeline("text-generation", model="gpt2")
 
 # === Qdrant Setup ===
 print("Connecting to Qdrant...")
@@ -67,9 +67,9 @@ class MathRetrievalQA(dspy.Program):
             return dspy.Output(answer="", retrieved_context="")
         prompt = f"Question: {question}\nContext: {context}\nAnswer:"
         print("Generating answer...")
-       # answer = qa_pipeline(prompt, max_new_tokens=100)[0]["generated_text"]
-        print("Generated answer:", prompt)
-        return {"answer": prompt, "retrieved_context": context}
+        answer = qa_pipeline(prompt, max_new_tokens=100)[0]["generated_text"]
+        print("Generated answer:", answer)
+        return {"answer": answer, "retrieved_context": context}
 
        # return dspy.Output(answer=answer, retrieved_context=context)