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Sleeping
| import streamlit as st | |
| from transformers import pipeline | |
| # Load the Hugging Face model for text generation | |
| model = pipeline("text-generation") | |
| # Streamlit app | |
| def main(): | |
| st.title("Cherry Bot") | |
| st.markdown("*Your Companion for Suicide Prevention*") | |
| # Add tabs for each chat in the sidebar | |
| chat_tabs = st.sidebar.radio("Chats", ["Chat 1", "Chat 2", "Chat 3"]) | |
| # Add a sidebar to the app | |
| with st.sidebar: | |
| st.markdown("# Text Generation Settings") | |
| # Slider for adjusting the maximum length of generated text | |
| max_length = st.slider("Max Length of Generated Text:", min_value=10, max_value=200, value=50, step=10) | |
| # Text input for user to input starting text for generation | |
| starting_text = st.text_area(f"Enter starting text for {chat_tabs}:", height=100) | |
| # Perform text generation when the user clicks the button | |
| if st.button("Generate Text"): | |
| if starting_text: | |
| # Generate text using the loaded model | |
| generated_text = model(starting_text, max_length=max_length)[0]['generated_text'] | |
| # Display the generated text | |
| st.write("Generated Text:") | |
| st.write(generated_text) | |
| if __name__ == "__main__": | |
| main() | |