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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://wzmh05cfg7kqctcc.us-east-1.aws.endpoints.huggingface.cloud/v1/", | |
| api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')#"hf_xxx" # Replace with your token | |
| ) | |
| #Create model | |
| model_links ={ | |
| "Turkish-7b-mix":"burak/Trendyol-Turkcell-stock" | |
| } | |
| #Pull info about the model to display | |
| model_info ={ | |
| "Turkish-7b-mix": | |
| { 'description':"""Turkish-7b-Mix is a merge of pre-trained language models created using **mergekit**.\n \ | |
| ### Merge Method\n \ | |
| This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Trendyol/Trendyol-LLM-7b-chat-dpo-v1.0](https://huggingface.co/Trendyol/Trendyol-LLM-7b-chat-dpo-v1.0) as a base.\n \ | |
| ### Models Merged\n \ | |
| The following models were included in the merge:\n \ | |
| * [TURKCELL/Turkcell-LLM-7b-v1](https://huggingface.co/TURKCELL/Turkcell-LLM-7b-v1)\n \ | |
| * [Trendyol/Trendyol-LLM-7b-chat-v1.0](https://huggingface.co/Trendyol/Trendyol-LLM-7b-chat-v1.0)\n""", | |
| 'logo': 'https://huggingface.co/spaces/burak/TurkishChatbot/resolve/main/icon.jpg' | |
| }, | |
| } | |
| def reset_conversation(): | |
| ''' | |
| Resets Conversation | |
| ''' | |
| st.session_state.conversation = [] | |
| st.session_state.messages = [] | |
| return None | |
| st.sidebar.image(model_info["Turkish-7b-mix"]['logo']) | |
| # 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)) | |
| #Add reset button to clear conversation | |
| st.sidebar.button('Reset Chat', on_click=reset_conversation) #Reset button | |
| # Create model description | |
| st.sidebar.write(f"You're now chatting with **{selected_model}**") | |
| st.sidebar.markdown(model_info[selected_model]['description']) | |
| 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 | |
| reset_conversation() | |
| #Pull in the model we want to use | |
| repo_id = model_links[selected_model] | |
| st.subheader(f'AI - {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"Hi I'm {selected_model}, ask me a question"): | |
| # 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"): | |
| 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=500, | |
| ) | |
| response = st.write_stream(stream) | |
| st.session_state.messages.append({"role": "assistant", "content": response}) |