Update streamlit_app.py

streamlit_app.py

@@ -1,40 +1,55 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+from hugchat import hugchat
+from hugchat.login import Login
+
+# App title
+st.set_page_config(page_title="🤗💬 HugChat")
+
+# Hugging Face Credentials
+with st.sidebar:
+    st.title('🤗💬 HugChat')
+    if ('EMAIL' in st.secrets) and ('PASS' in st.secrets):
+        st.success('HuggingFace Login credentials already provided!', icon='✅')
+        hf_email = st.secrets['EMAIL']
+        hf_pass = st.secrets['PASS']
+    else:
+        hf_email = st.text_input('Enter E-mail:', type='password')
+        hf_pass = st.text_input('Enter password:', type='password')
+        if not (hf_email and hf_pass):
+            st.warning('Please enter your credentials!', icon='⚠️')
+        else:
+            st.success('Proceed to entering your prompt message!', icon='👉')
+    st.markdown('📖 Learn how to build this app in this [blog](https://blog.streamlit.io/how-to-build-an-llm-powered-chatbot-with-streamlit/)!')
+
+# Store LLM generated responses
+if "messages" not in st.session_state.keys():
+    st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}]
+
+# Display chat messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.write(message["content"])
+
+# Function for generating LLM response
+def generate_response(prompt_input, email, passwd):
+    # Hugging Face Login
+    sign = Login(email, passwd)
+    cookies = sign.login()
+    # Create ChatBot                        
+    chatbot = hugchat.ChatBot(cookies=cookies.get_dict())
+    return chatbot.chat(prompt_input)
+
+# User-provided prompt
+if prompt := st.chat_input(disabled=not (hf_email and hf_pass)):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.write(prompt)
+
+# Generate a new response if last message is not from assistant
+if st.session_state.messages[-1]["role"] != "assistant":
+    with st.chat_message("assistant"):
+        with st.spinner("Thinking..."):
+            response = generate_response(prompt, hf_email, hf_pass) 
+            st.write(response) 
+    message = {"role": "assistant", "content": response}
+    st.session_state.messages.append(message)