Update app.py

app.py

@@ -1,3 +1,4 @@
+#R&D
 import gradio as gr
 import time
 
@@ -34,7 +35,7 @@ summarizer = pipeline("summarization", model="google/flan-t5-small", device_map=
 def intelligently_show_context_with_pages_resources(context, query, docs, top_n=3):
     """ Intelligently extract paragraphs with PAGE NUMBERS + RESOURCE names """
     display_context = []
-    display_context.append("📄 **FULL CONTEXT with Pages & Resources**\n")
+    display_context.append("📄 ****\n")
     display_context.append("=" * 120)
     
     paragraphs = [p.strip() for p in re.split(r'\n\s*\n', context) if p.strip()]
@@ -121,21 +122,67 @@ def show_history_compact(limit=3):
         output += "\n" + "─" * 60
     
     return output
-def summarize_with_flan_t5(query):
+#========================optimized the question
+def reframe_question_with_history(user_question, history_limit=3):
+    """
+    Generate a single, comprehensive question using conversation history context.
+    """
+    # Build history context
+    history_context = ""
+    recent_history = HISTORY[-history_limit:] if HISTORY else []
+    
+    if recent_history:
+        history_context = "Recent conversation context:\n"
+        for entry in recent_history:
+            history_context += f"- {entry['query'][:80]}... ({entry['timestamp']})\n"
+        history_context += "\n"
+    
+    # Reframing prompt
+    reframe_prompt = f"""Generate a single, comprehensive question that best captures the information needed to address the user's query or intent and includes the context from the conversation history.
+
+User's question: {user_question}
+
+{history_context}Only output the optimized question.
+
+OPTIMIZED QUESTION:"""
+    
+    # Use FLAN-T5 for reframing (lightweight)
+    reframer = pipeline("text2text-generation", model="google/flan-t5-small", device_map="cpu")
+    reframed = reframer(
+        reframe_prompt, 
+        max_new_tokens=100,
+        max_length=512,
+        temperature=0.1,
+        do_sample=False
+    )[0]['generated_text']
+    
+    # Extract just the question
+    optimized_question = reframed.split("OPTIMIZED QUESTION:")[-1].strip()
+    if not optimized_question or len(optimized_question) < 10:
+        optimized_question = user_question  # Fallback
+    
+    return optimized_question
+
+#========================main funcition
+def summarize_with_flan_t5(query,history):
     user_repo_id = "manabb/nrl"
     msg=""
     """Generate bullet summary + context + HISTORY TRACKING."""
     try:
-        
-        docs = retriever.invoke(query)
-        print(f"✅ Retrieved {len(docs)} docs")
+        # REFRARE QUESTION WITH HISTORY
+        #print("🔄 Reframing question with history...")
+        optimized_query = reframe_question_with_history(query)
+        #print(f"📝 Original: {query}")
+        #print(f"📝 Optimized: {optimized_query}")
+        docs = retriever.invoke(optimized_query)
+        #print(f"✅ Retrieved {len(docs)} docs")
         context = "\n".join([doc.page_content for doc in docs])   
         
         bullet_prompt = f"""Summarize as 4-6 bullet points:
 
 {context[:900]}
 
-BULLETS:"""
+Main Points:"""
         
         bullet_summary = summarizer(bullet_prompt, max_length=200, min_length=50, do_sample=False)[0]['summary_text']
         
@@ -147,9 +194,9 @@ BULLETS:"""
         # ✅ COMBINE HISTORY + CURRENT RESULT
         history_section = show_history_compact(limit=3)  # Last 3 queries
         combined_result = f"""
-        🤖 **YOUR ANSWER: "{query}"**
+        🤖 **YOUR Querry: "{query}"**
         
-        📋 **BULLET SUMMARY:**
+        📋 **SUMMARY:**
         {bullet_summary}
 
         📄 **INTELLIGENT CONTEXT:**
@@ -168,7 +215,8 @@ BULLETS:"""
     finally:
         if os.path.exists("temp_faiss"):
             shutil.rmtree("temp_faiss")
-    return msg
+    history.append(msg)
+    return history," "
 
 
 def login(user, pwd):
@@ -194,6 +242,9 @@ def load_resources():
         gr.update(visible=False)    # hide tabs
     )
 
+
+#==========================gradio
+
 with gr.Blocks() as demo:
     status = gr.Markdown("# 🚀 NRL AI Space for commercial department - Guwahati")
 
@@ -208,13 +259,15 @@ with gr.Blocks() as demo:
     # ---- Tabs Container (initially hidden) ----
     with gr.Column(visible=False) as tabs_panel:
         with gr.Tab("📄 ASK on manual of procurement of Goods"):
+            
+            
+            answer_output1 = gr.Textbox(label="✅ Answer", height=500)
             query_input1 = gr.Textbox(label="❓ Your Question pls", placeholder="e.g., What is Gem?")
             query_btn1 = gr.Button("🧠 Get Answer", variant="primary")
-            answer_output1 = gr.Textbox(label="✅ Answer", lines=15)
             query_btn1.click(
                 fn=summarize_with_flan_t5,
                 inputs=query_input1,
-                outputs=answer_output1  # answers with bullet, smart context and history
+                outputs=[answer_output1,query_input1]  # answers with bullet, smart context and history
                 )
 
         with gr.Tab("📊 Upcoming functionality-1"):
@@ -236,3 +289,4 @@ with gr.Blocks() as demo:
     )
 
 demo.launch()
+