Update app.py

app.py

@@ -187,7 +187,6 @@ def generate_response(db, query_text, previous_context):
     Using the context provided below, answer the following question. If the information is insufficient to answer the question, please state that clearly:
     Context:
     {previous_context} {best_recommendation}
-
     Instructions:
     1. Cross-Reference: Use all provided context to define variables and identify any unknown entities. 
     2. Mathematical Calculations: Perform any necessary calculations based on the context and available data. 
@@ -202,23 +201,15 @@ def generate_response(db, query_text, previous_context):
         filename="unsloth.BF16.gguf",
     )
     
-    output_stream = llm(
+    # Directly get the output without streaming
+    output = llm(
         prompt_template,
-        stream=True,
         temperature=0.1,
         top_p=0.9,
         top_k=20
     )
     
-    full_response = ""
-    
-    response_placeholder = st.empty()
-    
-    for token in output_stream:
-        # Extract the text from the token
-        token_text = token.get("choices", [{}])[0].get("text", "")
-        full_response += token_text
-        response_placeholder.text(full_response)  # Print token output in real-time
+    full_response = output["choices"][0]["text"]
 
     return full_response
 
@@ -271,24 +262,15 @@ def streamlit_app():
             st.session_state.messages = []
         return st.session_state.messages
 
-    st.session_state.messages = get_messages()
-
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    # Chat input section
-    if prompt := st.chat_input("Ask a question about the models:"):
-        st.chat_message("user").markdown(prompt)
-        st.session_state.messages.append({"role": "user", "content": prompt})
-
-        if st.session_state.db is None:
-            st.error("Database is not initialized. Please process the models first.")
+    # Query input and response generation
+    query = st.text_area("Ask a question about the models:")
+    
+    if st.button("Get Response"):
+        if st.session_state.db:
+            response = generate_response(st.session_state.db, query, "")
+            st.write("Response: ", response)
         else:
-            response = generate_response(st.session_state.db, prompt, st.session_state.messages)
-
-            st.chat_message("assistant").markdown(response)  # Directly display the final response
-            st.session_state.messages.append({"role": "assistant", "content": response})
+            st.warning("Database is not initialized. Please search and analyze models first.")
 
 if __name__ == "__main__":
     streamlit_app()