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Create app_v3.py

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  1. app_v3.py +69 -0
app_v3.py ADDED
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+ import streamlit as st
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+ from hugchat import hugchat
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+ from hugchat.login import Login
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+ import os
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+
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+ # App title
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+ st.set_page_config(page_title="🤗💬 HugChat")
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+
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+ # Hugging Face Credentials
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+ with st.sidebar:
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+ st.title('🤗💬 HugChat')
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+ if ('EMAIL' in st.secrets) and ('PASS' in st.secrets):
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+ st.success('HuggingFace Login credentials already provided!', icon='✅')
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+ hf_email = st.secrets['EMAIL']
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+ hf_pass = st.secrets['PASS']
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+ else:
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+ hf_email = st.text_input('Enter E-mail:', type='password')
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+ hf_pass = st.text_input('Enter password:', type='password')
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+ if not (hf_email and hf_pass):
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+ st.warning('Please enter your credentials!', icon='⚠️')
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+ else:
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+ st.success('Proceed to entering your prompt message!', icon='👉')
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+ st.markdown('📖 Learn how to build this app in this [blog](https://blog.streamlit.io/how-to-build-an-llm-powered-chatbot-with-streamlit/)!')
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+
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+ # Store LLM generated responses
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+ if "messages" not in st.session_state:
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+ st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
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+
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+ # Display or clear chat messages
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+ for message in st.session_state.messages:
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+ with st.chat_message(message["role"]):
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+ st.write(message["content"])
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+
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+ def clear_chat_history():
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+ st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
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+ st.sidebar.button('Clear Chat History', on_click=clear_chat_history)
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+
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+ # Function for generating LLM response
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+ def generate_response(prompt_input, email, passwd):
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+ # Hugging Face Login
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+ sign = Login(email, passwd)
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+ cookies = sign.login()
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+ # Create ChatBot
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+ chatbot = hugchat.ChatBot(cookies=cookies.get_dict())
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+
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+ for dict_message in st.session_state.messages:
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+ string_dialogue = "You are a helpful assistant."
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+ if dict_message["role"] == "user":
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+ string_dialogue += "User: " + dict_message["content"] + "\n\n"
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+ else:
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+ string_dialogue += "Assistant: " + dict_message["content"] + "\n\n"
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+
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+ prompt = f"{string_dialogue} {prompt_input} Assistant: "
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+ return chatbot.chat(prompt)
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+
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+ # User-provided prompt
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+ if prompt := st.chat_input(disabled=not (hf_email and hf_pass)):
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+ st.session_state.messages.append({"role": "user", "content": prompt})
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+ with st.chat_message("user"):
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+ st.write(prompt)
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+
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+ # Generate a new response if last message is not from assistant
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+ if st.session_state.messages[-1]["role"] != "assistant":
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+ with st.chat_message("assistant"):
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+ with st.spinner("Thinking..."):
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+ response = generate_response(prompt, hf_email, hf_pass)
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+ st.write(response)
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+ message = {"role": "assistant", "content": response}
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+ st.session_state.messages.append(message)