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| import streamlit as st | |
| from openai import OpenAI | |
| import os | |
| import sys | |
| from dotenv import load_dotenv, dotenv_values | |
| load_dotenv() | |
| # initialize the client | |
| client = OpenAI( | |
| base_url="https://api-inference.huggingface.co/v1", | |
| api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')#"hf_xxx" # Replace with your token | |
| ) | |
| #Create supported models | |
| model_links ={ | |
| "Meta-Llama-3.1-8B": "meta-llama/Meta-Llama-3.1-8B-Instruct", | |
| "Mistral-7B-Instruct-v0.3": "mistralai/Mistral-7B-Instruct-v0.3", | |
| "Gemma-7b-it": "google/gemma-7b-it", | |
| } | |
| #Pull info about the model to display | |
| model_info ={ | |
| "Meta-Llama-3.1-8B": | |
| {'description':"""The Llama (3.1) model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \ | |
| \nIt was created by the [**Meta's AI**](https://llama.meta.com/) team and has over **8 billion parameters.** \n""", | |
| 'logo':'llama_logo.gif'}, | |
| "Mistral-7B-Instruct-v0.3": | |
| {'description':"""The Mistral-7B-Instruct-v0.3 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.3.\n \ | |
| \nIt was created by the [**Mistral AI**](https://mistral.ai/news/announcing-mistral-7b/) team as has over **7 billion parameters.** \n""", | |
| 'logo':'https://mistral.ai/images/logo_hubc88c4ece131b91c7cb753f40e9e1cc5_2589_256x0_resize_q97_h2_lanczos_3.webp'}, | |
| "Gemma-7b-it": | |
| {'description':"""Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.\n \ | |
| \nThey are text-to-text, decoder-only large language models, available in English, with open weights, pre-trained variants, and instruction-tuned variants. \n"""}, | |
| } | |
| #Random dog images for error message | |
| random_dog = ["BlueLogoBox.jpg"] | |
| # Define the available models | |
| models =[key for key in model_links.keys()] | |
| # Create the sidebar with the dropdown for model selection | |
| selected_model = st.sidebar.selectbox("Select Model", models) | |
| #Create a temperature slider | |
| temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5)) | |
| # Create model description | |
| st.sidebar.write(f"You're now chatting with **{selected_model}**") | |
| st.sidebar.markdown(model_info[selected_model]['description']) | |
| st.sidebar.image(model_info[selected_model]['logo']) | |
| st.sidebar.markdown("*Generated content may be inaccurate or false.*") | |
| if "prev_option" not in st.session_state: | |
| st.session_state.prev_option = selected_model | |
| if st.session_state.prev_option != selected_model: | |
| st.session_state.messages = [] | |
| st.write(f"Changed to {selected_model}") | |
| st.session_state.prev_option = selected_model | |
| #Pull in the model we want to use | |
| repo_id = model_links[selected_model] | |
| st.header(f'Liahona.AI') | |
| st.markdown(f'_powered_ by ***:violet[{selected_model}]***') | |
| # st.title(f'ChatBot Using {selected_model}') | |
| # Set a default model | |
| if selected_model not in st.session_state: | |
| st.session_state[selected_model] = model_links[selected_model] | |
| # Initialize chat history | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| # Display chat messages from history on app rerun | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| # Accept user input | |
| if prompt := st.chat_input(f"Type message here..."): | |
| # 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({"role": "user", "content": prompt}) | |
| # Display assistant response in chat message container | |
| with st.chat_message("assistant"): | |
| try: | |
| stream = client.chat.completions.create( | |
| model=model_links[selected_model], | |
| messages=[ | |
| {"role": m["role"], "content": m["content"]} | |
| for m in st.session_state.messages | |
| ], | |
| temperature=temp_values,#0.5, | |
| stream=True, | |
| max_tokens=4000, | |
| ) | |
| response = st.write_stream(stream) | |
| except Exception as e: | |
| # st.empty() | |
| response = "😵💫 Looks like someone unplugged something!\ | |
| \n Either the model space is being updated or something is down.\ | |
| \n\ | |
| \n Try again later. \ | |
| \n\ | |
| \n Here's a random pic of a 🐶:" | |
| st.write(response) | |
| random_dog_pick = 'https://random.dog/'+ random_dog[np.random.randint(len(random_dog))] | |
| st.image(random_dog_pick) | |
| st.write("This was the error message:") | |
| st.write(e) | |
| st.session_state.messages.append({"role": "assistant", "content": response}) |