Upload utils_chatbox.py

utils/utils_chatbox.py

@@ -0,0 +1,93 @@
+import time
+
+import streamlit as st
+
+def display_chat_history(model_name: str):
+    for message in st.session_state[model_name]:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+def chat_input(model_name: str):
+    if prompt := st.chat_input("Say something"):
+        # Display user message in chat message container
+        st.chat_message("user").markdown(prompt)
+
+        # Add user message to chat history
+        st.session_state[model_name].append({"role": "user", "content": prompt})
+
+        return prompt
+
+def display_bot_msg(model_name: str, bot_response: str):
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+        message_placeholder = st.empty()
+        full_response = ""
+
+        # simulate the chatbot "thinking" before responding
+        # (or stream its response)
+        for chunk in bot_response.split():
+            full_response += chunk + " "
+            time.sleep(0.05)
+
+            # add a blinking cursor to simulate typing
+            message_placeholder.markdown(full_response + "▌")
+
+        message_placeholder.markdown(full_response)
+        # st.markdown(response)
+
+    # Add assistant response to chat history
+    st.session_state[model_name].append(
+        {"model_name": model_name, "role": "assistant", "content": full_response}
+    )
+
+def chatbox(model_name: str, model: None):
+    # Display chat messages from history on app rerun
+    for message in st.session_state.messages:
+        if (message["model_name"] == model_name):
+            with st.chat_message(message["role"]):
+                st.markdown(message["content"])
+
+    if prompt := st.chat_input("Say something"):
+        # Display user message in chat message container
+        st.chat_message("user").markdown(prompt)
+
+        # Add user message to chat history
+        st.session_state.messages.append({"model_name": model_name, "role": "user", "content": prompt})
+
+        with st.spinner("Processing your query..."):
+            bot_response = model.get_response(prompt)
+
+        print("bot: ", bot_response)
+
+        # Display assistant response in chat message container
+        with st.chat_message("assistant"):
+            message_placeholder = st.empty()
+            full_response = ""
+
+            # simulate the chatbot "thinking" before responding
+            # (or stream its response)
+            for chunk in bot_response.split():
+                full_response += chunk + " "
+                time.sleep(0.05)
+
+                # add a blinking cursor to simulate typing
+                message_placeholder.markdown(full_response + "▌")
+
+            message_placeholder.markdown(full_response)
+            # st.markdown(response)
+
+        # Add assistant response to chat history
+        st.session_state.messages.append(
+            {"model_name": model_name, "role": "assistant", "content": full_response}
+        )
+
+        # Scroll to the bottom of the chat container
+        # st.markdown(
+        #     """
+        #     <script>
+        #     const chatContainer = document.getElementsByClassName("css-1n76uvr")[0];
+        #     chatContainer.scrollTop = chatContainer.scrollHeight;
+        #     </script>
+        #     """,
+        #     unsafe_allow_html=True,
+        # )