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| """ | |
| @author: idoia lerchundi | |
| """ | |
| import os | |
| import streamlit as st | |
| from huggingface_hub import InferenceClient | |
| import random | |
| # Load the API token from an environment variable | |
| api_key = os.getenv("HF_TOKEN") | |
| # Instantiate the InferenceClient | |
| client = InferenceClient(api_key=api_key) | |
| # Streamlit app title | |
| st.title("Text-generation model using Streamlit from Inference API (serverless) feature.") | |
| # Ensure the full_text key is initialized in session state | |
| if "full_text" not in st.session_state: | |
| st.session_state["full_text"] = "" | |
| # Model selection dropdown | |
| model_options = [ "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "gpt2", "facebook/opt-1.3b", "EleutherAI/gpt-neo-2.7B","meta-llama/Llama-Llama-3-8B-Instruct", "meta-llama/Llama-Llama-3.1-1B-Instruct", "meta-llama/Llama-Llama-3.2-3B-Instruct", "meta-llama/Llama-Llama-3.2-8B-Instruct", "Qwen/Qwen2.5-1.5B-Instruct", "openai-community/gpt2", "google/gemma-1.1-7b-it", "google/gemma-1.27b-it", "google/gemma-1.2b-it", "google/gemma-1.9b-it", "google/gemma-2.2b-it", "HuggingFaceH4/starchat7b-beta", "distilbert/distilgpt2", "facebook/opt-1.3b", "distributed/optimized=gpt2-1b" ] | |
| selected_model = st.selectbox("Choose a model:"= st.selectbox("Choose a model:", model_options) | |
| # Create a text input area for user prompts | |
| with st.form("my_form"): | |
| text = st.text_area("JOKER (TinyLlama is not great at joke telling.) (using model TinyLlama/TinyLlama-1.1B-Chat-v1.0):", "Tell me a clever and funny joke in exactly 4 sentences. It should make me laugh really hard. Don't repeat the topic in your joke. Be creative and concise.") | |
| submitted = st.form_submit_button("Submit") | |
| # Initialize the full_text variable | |
| full_text = " " | |
| # Generate a random temperature between 0.5 and 1.0 | |
| temperature = random.uniform(0.5, 1.0) | |
| if submitted: | |
| messages = [ | |
| {"role": "user", "content": text} | |
| ] | |
| # Create a new stream for each submission | |
| stream = client.chat.completions.create( | |
| model=selected_model, | |
| messages=messages, | |
| # Generate a random temperature between 0.5 and 1.0 | |
| temperature = random.uniform(0.5, 1.0), | |
| max_tokens=300, | |
| top_p=random.uniform(0.7, 1.0), | |
| stream=True | |
| ) | |
| # Concatenate chunks to form the full response | |
| for chunk in stream: | |
| full_text += chunk.choices[0].delta.content | |
| # Update session state with the full response | |
| st.session_state["full_text"] = full_text | |
| # Display the full response | |
| if st.session_state["full_text"]: | |
| st.info(st.session_state["full_text"]) |