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| import os | |
| import gradio as gr | |
| from openai import OpenAI | |
| # Load API key from Hugging Face Secrets | |
| # (set OPENAI_API_KEY in your Space settings) | |
| client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) | |
| # Function to ask the app | |
| def ask_app(question): | |
| try: | |
| response = client.responses.create( | |
| prompt={ | |
| "id": "pmpt_69f610df1d70819683a15d371bd47ca00b92de12291fced1", | |
| "version": "1" | |
| }, | |
| input=question, | |
| reasoning={"summary": "auto"} | |
| ) | |
| return response.output_text | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| # Gradio interface | |
| demo = gr.Interface( | |
| fn=ask_app, | |
| inputs=gr.Textbox( | |
| lines=3, | |
| placeholder="Type your question here...", | |
| label="Your Question" | |
| ), | |
| outputs=gr.Textbox( | |
| lines=10, | |
| label="Answer" | |
| ), | |
| title="DDS Cohort 10 2nd App Python Research Bot", | |
| description="Ask a question and get answers from your saved prompt + vector store." | |
| ) | |
| # Launch app | |
| demo.launch(share=True) | |