Update app.py

app.py

@@ -33,16 +33,19 @@ model_info = {
 def format_promt(message, conversation_history, custom_instructions=None):
     prompt = ""
     if custom_instructions:
-        prompt += f"\[INST\] {custom_instructions} \[/INST\]"
+        prompt += f"\[INST\] {custom_instructions} \[/INST\]\n"
     
     # Add conversation history to the prompt
     prompt += "\[CONV_HISTORY\]\n"
     for role, content in conversation_history:
         prompt += f"{role.upper()}: {content}\n"
-    prompt += "\[/CONV_HISTORY\]"
+    prompt += "\[/CONV_HISTORY\]\n"
     
     # Add the current message
-    prompt += f"\[INST\] {message} \[/INST\]"
+    prompt += f"\[INST\] {message} \[/INST\]\n"
+    
+    # Add the response format
+    prompt += "\[RESPONSE\]\n"
     
     return prompt
 
@@ -52,7 +55,7 @@ def reset_conversation():
     '''
     st.session_state.conversation = []
     st.session_state.messages = []
-    st.experimental_rerun()  # Add this line to rerun the app after reset
+    st.session_state.chat_state = "reset"
 
 def load_conversation_history():
     history_file = "conversation_history.pickle"
@@ -86,6 +89,9 @@ if st.session_state.prev_option != selected_model:
     st.session_state.messages = []
     st.session_state.prev_option = selected_model
 
+if "chat_state" not in st.session_state:
+    st.session_state.chat_state = "normal"
+
 # Load the conversation history from the file
 if "messages" not in st.session_state:
     st.session_state.messages = load_conversation_history()
@@ -93,37 +99,42 @@ if "messages" not in st.session_state:
 repo_id = model_links[selected_model]
 st.subheader(f'{selected_model}')
 
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
-
-if prompt := st.chat_input(f"Hi I'm {selected_model}, How can I help you today?"):
-    custom_instruction = "Act like a Human in conversation"
-    with st.chat_message("user"):
-        st.markdown(prompt)
-    
-    st.session_state.messages.append({"role": "user", "content": prompt})
-    conversation_history = [(message["role"], message["content"]) for message in st.session_state.messages]
-    
-    formated_text = format_promt(prompt, conversation_history, custom_instruction)
-    
-    with st.chat_message("assistant"):
-        client = InferenceClient(
-            model=model_links[selected_model], )
-        max_new_tokens = 2048  # Adjust this value as needed
-        try:
-            output = client.text_generation(
-                formated_text,
-                temperature=temp_values,
-                max_new_tokens=max_new_tokens,
-                stream=True
-            )
-            response = st.write_stream(output)
-        except ValueError as e:
-            if "Input validation error" in str(e):
-                st.error("Error: The input prompt is too long. Please try a shorter prompt.")
+if st.session_state.chat_state == "normal":
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+    if prompt := st.chat_input(f"Hi I'm {selected_model}, How can I help you today?"):
+        custom_instruction = "Act like a Human in conversation"
+        with st.chat_message("user"):
+            st.markdown(prompt)
+        
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        conversation_history = [(message["role"], message["content"]) for message in st.session_state.messages]
+        
+        formated_text = format_promt(prompt, conversation_history, custom_instruction)
+        
+        with st.chat_message("assistant"):
+            client = InferenceClient(
+                model=model_links[selected_model], )
+            max_new_tokens = 2048  # Adjust this value as needed
+            try:
+                output = client.text_generation(
+                    formated_text,
+                    temperature=temp_values,
+                    max_new_tokens=max_new_tokens,
+                    stream=True
+                )
+                response = st.write_stream(output)
+            except ValueError as e:
+                if "Input validation error" in str(e):
+                    st.error("Error: The input prompt is too long. Please try a shorter prompt.")
+                else:
+                    st.error(f"An error occurred: {e}")
             else:
-                st.error(f"An error occurred: {e}")
-        else:
-            st.session_state.messages.append({"role": "assistant", "content": response})
-            save_conversation_history(st.session_state.messages)
+                st.session_state.messages.append({"role": "assistant", "content": response})
+                save_conversation_history(st.session_state.messages)
+
+elif st.session_state.chat_state == "reset":
+    st.session_state.chat_state = "normal"
+    st.experimental_rerun()