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| # Import necessary libraries | |
| import streamlit as st | |
| import os | |
| from openai import OpenAI | |
| import json | |
| working_dir = os.path.dirname(os.path.abspath(__file__)) | |
| endpoint_data = json.load(open(f"{working_dir}/model_info.json")) | |
| def clear_chat(): | |
| st.session_state.messages = [] | |
| st.title("Inference as a Service Playground") | |
| # Extract the keys (model names) from the JSON data | |
| model_names = list(endpoint_data.keys()) | |
| with st.sidebar: | |
| modelname = st.selectbox("Select a LLM model (Running on Intel® Gaudi®) ", model_names) | |
| st.write(f"You selected: {modelname}") | |
| st.button("Start New Chat", on_click=clear_chat) | |
| # Add a text input for the API key | |
| api_key = st.text_input("Enter your API Key", type="password") | |
| if api_key: | |
| st.session_state.api_key = api_key | |
| # Check if the API key is provided | |
| if "api_key" not in st.session_state or not st.session_state.api_key: | |
| st.error("Please enter your API Key in the sidebar.") | |
| else: | |
| try: | |
| endpoint = endpoint_data[modelname] | |
| api_key = st.session_state.api_key | |
| base_url = endpoint | |
| client = OpenAI(api_key=api_key, base_url=base_url) | |
| # Extract the model name | |
| models = client.models.list() | |
| modelname = models.data[0].id | |
| st.write(f"**Model Info:** `{modelname}`") | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| if prompt := st.chat_input("What is up?"): | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| with st.chat_message("user"): | |
| st.markdown(prompt) | |
| with st.chat_message("assistant"): | |
| try: | |
| stream = client.chat.completions.create( | |
| model=modelname, | |
| messages=[ | |
| {"role": m["role"], "content": m["content"]} | |
| for m in st.session_state.messages | |
| ], | |
| max_tokens=1024, | |
| stream=True, | |
| ) | |
| response = st.write_stream(stream) | |
| except Exception as e: | |
| st.error(f"An error occurred while generating the response: {e}") | |
| response = "An error occurred while generating the response." | |
| st.session_state.messages.append({"role": "assistant", "content": response}) | |
| except KeyError as e: | |
| st.error(f"Key error: {e}") | |
| except Exception as e: | |
| st.error(f"An unexpected error occurred: {e}") | |