74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
import streamlit as st
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from openai import OpenAI # OpenAI compatibility
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import json
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# reference:
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# - Use OpenAI to connect Ollama: https://ollama.com/blog/openai-compatibility
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# - Build Chatbot with streamlit: https://streamlit.io/generative-ai
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# - finetune: https://docs.loopin.network/tutorials/LLM/llama3-finetune
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# - Ollama docker: https://hub.docker.com/r/ollama/ollama
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# Set up the Streamlit app
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st.markdown("<h1 style='text-align: center; color: #451002;'>BuffBot🦬</h1>", unsafe_allow_html=True)
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# st.subheader()
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st.info("Powered by llama3.2:1b model via [Ollama](https://ollama.com/library/llama3.2:1b)!")
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with st.expander("See Source Code"):
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with open(__file__, "r") as f:
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st.code(f.read(), language="python")
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# Load API credentials from config.json
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with open('chatbot_config.json') as config_file:
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config = json.load(config_file)
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api_base_url = config["ollama_api_url"]
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api_key = config["ollama_api_key"]
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client = OpenAI(api_key=api_key, base_url=api_base_url)
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# Initialize session state to store chat history and message count
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if "messages" not in st.session_state:
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st.session_state.messages = []
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# print welcome message
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with st.chat_message("assistant", avatar="🦬"):
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st.markdown("Welcome to BuffBot! How can I help you today??")
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# Display chat history
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for message in st.session_state.messages:
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if message["role"] == "user":
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avatar="🤠"
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else:
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avatar="🦬"
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with st.chat_message(message["role"], avatar=avatar):
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st.markdown(message["content"])
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# Chat input
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if prompt := st.chat_input("Type your message..."):
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": prompt})
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with st.chat_message("user", avatar="🤠"):
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st.markdown(prompt)
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# Call DeepSeek for a response
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with st.chat_message("assistant", avatar="🦬"):
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with st.spinner('Thinking...'):
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stream = client.chat.completions.create(
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model="llama3.2:1b",
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messages=[
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{"role": m["role"], "content": m["content"]}
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for m in st.session_state.messages
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],
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stream=True,
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)
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response = st.write_stream(stream)
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st.session_state.messages.append({"role": "assistant", "content": response})
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if st.button("Clear Chat"):
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st.session_state.messages = []
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st.toast("Chat Cleaned", icon="🧹")
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