Update app.py

app.py

@@ -57,55 +57,39 @@ class MathAnswer(dspy.Signature):
     answer = dspy.OutputField()
 
 # === DSPy Programs ===
-# === DSPy Programs with Output Guard ===
 class MathRetrievalQA(dspy.Program):
     def forward(self, question):
         print("Inside MathRetrievalQA...")
         context_items = retrieve_from_qdrant(question)
         context = "\n".join([item["solution"] for item in context_items if "solution" in item])
         print("Context for generation:", context)
-        
         if not context:
-            return {"answer": "", "retrieved_context": ""}
-
-        # === Replace below with real model call when ready ===
+            return dspy.Output(answer="", retrieved_context="")
         prompt = f"Question: {question}\nContext: {context}\nAnswer:"
-        print("Prompt for generation:", prompt)
-
-        # TEMP answer (replace with real generated output)
-        generated_answer = "This is a placeholder answer based on the context."  # Simulated generation
-        print("Generated answer:", generated_answer)
-
-        # === Output Guard ===
-        if not generated_answer or len(generated_answer.strip()) < 10 or "I don't know" in generated_answer:
-            return {"answer": "", "retrieved_context": context}
-
-        return {"answer": generated_answer.strip(), "retrieved_context": context}
+        print("Generating answer...")
+       # answer = qa_pipeline(prompt, max_new_tokens=100)[0]["generated_text"]
+        print("Generated answer:", prompt)
+        return {"answer": prompt, "retrieved_context": context}
 
+       # return dspy.Output(answer=answer, retrieved_context=context)
 
 class WebFallbackQA(dspy.Program):
     def forward(self, question):
         print("Fallback to Tavily...")
         answer = web_search_tavily(question)
-        if not answer or len(answer.strip()) < 10 or "No answer found" in answer:
-            answer = "❌ Sorry, I couldn't find a reliable answer."
-        return {"answer": answer.strip(), "retrieved_context": "Tavily"}
+       # return dspy.Output(answer=answer, retrieved_context="Tavily")
+        return {"answer": answer, "retrieved_context": "Tavily"}
 
 
 class MathRouter(dspy.Program):
     def forward(self, question):
         print("Routing question:", question)
         if not is_valid_math_question(question):
-            return {"answer": "❌ Only math questions are accepted. Please rephrase.", "retrieved_context": ""}
-        
+            return dspy.Output(answer="❌ Only math questions are accepted. Please rephrase.", retrieved_context="")
         result = MathRetrievalQA().forward(question)
-
-        if result["answer"]:
-            return result
-        else:
-            return WebFallbackQA().forward(question)
-
-
+        #return result if result.answer else WebFallbackQA().forward(question)
+        return result if result["answer"] else WebFallbackQA().forward(question)
+router = MathRouter()
 
 # === Feedback Storage ===
 def store_feedback(question, answer, feedback, correct_answer):
@@ -120,26 +104,14 @@ def store_feedback(question, answer, feedback, correct_answer):
     with open("feedback.json", "a") as f:
         f.write(json.dumps(entry) + "\n")
 
-def load_feedback_entries():
-    entries = []
-    try:
-        with open("feedback.json", "r") as f:
-            for line in f:
-                entry = json.loads(line)
-                entries.append(entry)
-    except FileNotFoundError:
-        pass
-    return entries
-
-
-# === Gradio Functions ===
 # === Gradio Functions ===
 def ask_question(question):
     print("ask_question() called with:", question)
     result = router.forward(question)
     print("Result:", result)
-    return result["answer"], question, result["answer"]
-
+    #return result.answer, question, result.answer
+    #return result["answer"], question, result["answer"]
+    return result["answer"]
 
 
 def submit_feedback(question, model_answer, feedback, correct_answer):
@@ -170,29 +142,8 @@ with gr.Blocks() as demo:
         fb_correct = gr.Textbox(label="Correct Answer (optional)")
         fb_submit_btn = gr.Button("Submit Feedback")
         fb_status = gr.Textbox(label="Status", interactive=False)
-    
-        feedback_display = gr.Dataframe(headers=["Question", "Answer", "Feedback", "Correct Answer", "Timestamp"], 
-                                         row_count=10, max_rows=50, wrap=True)
-    
-        def feedback_submission_and_display(question, answer, feedback, correct_answer):
-            store_feedback(question, answer, feedback, correct_answer)
-            entries = load_feedback_entries()
-            display_rows = [[
-                e["question"], 
-                e["model_answer"], 
-                e["feedback"], 
-                e["correct_answer"], 
-                e["timestamp"]
-            ] for e in entries]
-            return "✅ Feedback received. Thank you!", display_rows
-    
-        fb_submit_btn.click(
-            fn=feedback_submission_and_display,
-            inputs=[fb_question, fb_answer, fb_like, fb_correct],
-            outputs=[fb_status, feedback_display]
-        )
-
-
-   
+        fb_submit_btn.click(fn=submit_feedback,
+                            inputs=[fb_question, fb_answer, fb_like, fb_correct],
+                            outputs=[fb_status])
 
 demo.launch(share=True, debug=True)