| import gradio as gr |
| from openai import OpenAI |
|
|
|
|
| def complete_text(prompt, max_tokens, temperature, top_p, openai_api_key): |
| """ |
| Get a plain text completion from OpenAI gpt-3.5-turbo-instruct. |
| """ |
| if not openai_api_key: |
| return "⚠️ Please enter a valid OpenAI API key." |
|
|
| client = OpenAI(api_key=openai_api_key) |
|
|
| response_text = "" |
| stream = client.completions.create( |
| model="gpt-3.5-turbo-instruct", |
| prompt=prompt, |
| max_tokens=max_tokens, |
| temperature=temperature, |
| top_p=top_p, |
| stream=True, |
| ) |
|
|
| for event in stream: |
| if hasattr(event, "choices") and event.choices: |
| token = event.choices[0].text or "" |
| response_text += token |
| yield response_text |
|
|
|
|
| with gr.Blocks() as demo: |
| gr.Markdown("## ✍️ Text Completion Demo (OpenAI gpt-3.5-turbo-instruct)") |
| gr.Markdown("Enter a prompt, adjust decoding parameters, and watch the model complete your text.") |
|
|
| with gr.Row(): |
| with gr.Column(scale=2): |
| prompt = gr.Textbox( |
| label="Prompt", |
| placeholder="Type the beginning of your text...", |
| lines=4, |
| ) |
| max_tokens = gr.Slider( |
| minimum=1, maximum=1024, value=100, step=1, label="Max tokens" |
| ) |
| temperature = gr.Slider( |
| minimum=0.0, maximum=2.0, value=0.7, step=0.1, label="Temperature" |
| ) |
| top_p = gr.Slider( |
| minimum=0.1, maximum=1.0, value=1.0, step=0.05, label="Top-p" |
| ) |
| api_key = gr.Textbox( |
| placeholder="sk-... Paste your OpenAI API key here", |
| label="🔑 OpenAI API Key", |
| type="password", |
| ) |
| submit = gr.Button("Generate Completion") |
| with gr.Column(scale=3): |
| output = gr.Textbox( |
| label="Generated Completion", |
| lines=15, |
| ) |
|
|
| submit.click( |
| fn=complete_text, |
| inputs=[prompt, max_tokens, temperature, top_p, api_key], |
| outputs=output, |
| ) |
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
|
|
|
|
