Update app.py

app.py

@@ -1,142 +1,142 @@
-import time
-import os
-import joblib
-import streamlit as st
-import google.generativeai as genai
-from dotenv import load_dotenv
-load_dotenv()
-GOOGLE_API_KEY=os.environ.get('GOOGLE_API_KEY')
-genai.configure(api_key=GOOGLE_API_KEY)
-
-new_chat_id = f'{time.time()}'
-MODEL_ROLE = 'ai'
-AI_AVATAR_ICON = '✨'
-
-# Create a data/ folder if it doesn't already exist
-try:
-    os.mkdir('data/')
-except:
-    # data/ folder already exists
-    pass
-
-# Load past chats (if available)
-try:
-    past_chats: dict = joblib.load('data/past_chats_list')
-except:
-    past_chats = {}
-
-# Sidebar allows a list of past chats
-with st.sidebar:
-    st.write('# Past Chats')
-    if st.session_state.get('chat_id') is None:
-        st.session_state.chat_id = st.selectbox(
-            label='Pick a past chat',
-            options=[new_chat_id] + list(past_chats.keys()),
-            format_func=lambda x: past_chats.get(x, 'New Chat'),
-            placeholder='_',
-        )
-    else:
-        # This will happen the first time AI response comes in
-        st.session_state.chat_id = st.selectbox(
-            label='Pick a past chat',
-            options=[new_chat_id, st.session_state.chat_id] + list(past_chats.keys()),
-            index=1,
-            format_func=lambda x: past_chats.get(x, 'New Chat' if x != st.session_state.chat_id else st.session_state.chat_title),
-            placeholder='_',
-        )
-    # Save new chats after a message has been sent to AI
-    # TODO: Give user a chance to name chat
-    st.session_state.chat_title = f'ChatSession-{st.session_state.chat_id}'
-
-st.write('# Chat with our Advanced Opensource LLM')
-
-# Chat history (allows to ask multiple questions)
-try:
-    st.session_state.messages = joblib.load(
-        f'data/{st.session_state.chat_id}-st_messages'
-    )
-    st.session_state.gemini_history = joblib.load(
-        f'data/{st.session_state.chat_id}-Alex_messages'
-    )
-    print('old cache')
-except:
-    st.session_state.messages = []
-    st.session_state.gemini_history = []
-    print('new_cache made')
-st.session_state.model = genai.GenerativeModel('gemini-pro')
-st.session_state.chat = st.session_state.model.start_chat(
-    history=st.session_state.gemini_history,
-)
-
-# Display chat messages from history on app rerun
-for message in st.session_state.messages:
-    with st.chat_message(
-        name=message['role'],
-        avatar=message.get('avatar'),
-    ):
-        st.markdown(message['content'])
-
-# React to user input
-if prompt := st.chat_input('Your message here...'):
-    # Save this as a chat for later
-    if st.session_state.chat_id not in past_chats.keys():
-        past_chats[st.session_state.chat_id] = st.session_state.chat_title
-        joblib.dump(past_chats, 'data/past_chats_list')
-    # Display user message in chat message container
-    with st.chat_message('user'):
-        st.markdown(prompt)
-    # Add user message to chat history
-    st.session_state.messages.append(
-        dict(
-            role='user',
-            content=prompt,
-        )
-    )
-    ## Send message to AI
-    response = st.session_state.chat.send_message(
-        prompt,
-        stream=True,
-    )
-    # Display assistant response in chat message container
-    with st.chat_message(
-        name=MODEL_ROLE,
-        avatar=AI_AVATAR_ICON,
-    ):
-        message_placeholder = st.empty()
-        full_response = ''
-        assistant_response = response
-        # Streams in a chunk at a time
-        for chunk in response:
-            # Simulate stream of chunk
-            # TODO: Chunk missing `text` if API stops mid-stream ("safety"?)
-            for ch in chunk.text.split(' '):
-                full_response += ch + ' '
-                time.sleep(0.05)
-                # Rewrites with a cursor at end
-                message_placeholder.write(full_response + '▌')
-        # Write full message with placeholder
-        message_placeholder.write(full_response)
-
-    # Add assistant response to chat history
-    st.session_state.messages.append(
-        dict(
-            role=MODEL_ROLE,
-            content=st.session_state.chat.history[-1].parts[0].text,
-            avatar=AI_AVATAR_ICON,
-        )
-    )
-    st.session_state.gemini_history = st.session_state.chat.history
-    # Save to file
-    joblib.dump(
-        st.session_state.messages,
-        f'data/{st.session_state.chat_id}-st_messages',
-    )
-    joblib.dump(
-        st.session_state.gemini_history,
-        f'data/{st.session_state.chat_id}-Alex_messages',
-    )
-
-footer_html = """<div style='text-align: center;'>
-<p>Developed  by Ramu Maloth</p>
-</div>"""
+import time
+import os
+import joblib
+import streamlit as st
+import google.generativeai as genai
+from dotenv import load_dotenv
+load_dotenv()
+GOOGLE_API_KEY=os.environ.get('GOOGLE_API_KEY')
+genai.configure(api_key=GOOGLE_API_KEY)
+
+new_chat_id = f'{time.time()}'
+MODEL_ROLE = 'ai'
+AI_AVATAR_ICON = '✨'
+
+# Create a data/ folder if it doesn't already exist
+try:
+    os.mkdir('data/')
+except:
+    # data/ folder already exists
+    pass
+
+# Load past chats (if available)
+try:
+    past_chats: dict = joblib.load('data/past_chats_list')
+except:
+    past_chats = {}
+
+# Sidebar allows a list of past chats
+with st.sidebar:
+    st.write('# Past Chats')
+    if st.session_state.get('chat_id') is None:
+        st.session_state.chat_id = st.selectbox(
+            label='Pick a past chat',
+            options=[new_chat_id] + list(past_chats.keys()),
+            format_func=lambda x: past_chats.get(x, 'New Chat'),
+            placeholder='_',
+        )
+    else:
+        # This will happen the first time AI response comes in
+        st.session_state.chat_id = st.selectbox(
+            label='Pick a past chat',
+            options=[new_chat_id, st.session_state.chat_id] + list(past_chats.keys()),
+            index=1,
+            format_func=lambda x: past_chats.get(x, 'New Chat' if x != st.session_state.chat_id else st.session_state.chat_title),
+            placeholder='_',
+        )
+    # Save new chats after a message has been sent to AI
+    # TODO: Give user a chance to name chat
+    st.session_state.chat_title = f'ChatSession-{st.session_state.chat_id}'
+
+st.write('# Chat with our Opensource LLM')
+
+# Chat history (allows to ask multiple questions)
+try:
+    st.session_state.messages = joblib.load(
+        f'data/{st.session_state.chat_id}-st_messages'
+    )
+    st.session_state.gemini_history = joblib.load(
+        f'data/{st.session_state.chat_id}-Alex_messages'
+    )
+    print('old cache')
+except:
+    st.session_state.messages = []
+    st.session_state.gemini_history = []
+    print('new_cache made')
+st.session_state.model = genai.GenerativeModel('gemini-pro')
+st.session_state.chat = st.session_state.model.start_chat(
+    history=st.session_state.gemini_history,
+)
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(
+        name=message['role'],
+        avatar=message.get('avatar'),
+    ):
+        st.markdown(message['content'])
+
+# React to user input
+if prompt := st.chat_input('Your message here...'):
+    # Save this as a chat for later
+    if st.session_state.chat_id not in past_chats.keys():
+        past_chats[st.session_state.chat_id] = st.session_state.chat_title
+        joblib.dump(past_chats, 'data/past_chats_list')
+    # Display user message in chat message container
+    with st.chat_message('user'):
+        st.markdown(prompt)
+    # Add user message to chat history
+    st.session_state.messages.append(
+        dict(
+            role='user',
+            content=prompt,
+        )
+    )
+    ## Send message to AI
+    response = st.session_state.chat.send_message(
+        prompt,
+        stream=True,
+    )
+    # Display assistant response in chat message container
+    with st.chat_message(
+        name=MODEL_ROLE,
+        avatar=AI_AVATAR_ICON,
+    ):
+        message_placeholder = st.empty()
+        full_response = ''
+        assistant_response = response
+        # Streams in a chunk at a time
+        for chunk in response:
+            # Simulate stream of chunk
+            # TODO: Chunk missing `text` if API stops mid-stream ("safety"?)
+            for ch in chunk.text.split(' '):
+                full_response += ch + ' '
+                time.sleep(0.05)
+                # Rewrites with a cursor at end
+                message_placeholder.write(full_response + '▌')
+        # Write full message with placeholder
+        message_placeholder.write(full_response)
+
+    # Add assistant response to chat history
+    st.session_state.messages.append(
+        dict(
+            role=MODEL_ROLE,
+            content=st.session_state.chat.history[-1].parts[0].text,
+            avatar=AI_AVATAR_ICON,
+        )
+    )
+    st.session_state.gemini_history = st.session_state.chat.history
+    # Save to file
+    joblib.dump(
+        st.session_state.messages,
+        f'data/{st.session_state.chat_id}-st_messages',
+    )
+    joblib.dump(
+        st.session_state.gemini_history,
+        f'data/{st.session_state.chat_id}-Alex_messages',
+    )
+
+footer_html = """<div style='text-align: center;'>
+<p>Developed  by Ramu Maloth</p>
+</div>"""
 st.markdown(footer_html, unsafe_allow_html=True)