| import gradio as gr | |
| import sambanova_gradio | |
| gr.load("Qwen2.5-Coder-32B-Instruct", src=sambanova_gradio.registry).launch() | |
| # import os | |
| # import gradio as gr | |
| # import openai | |
| # # Set up the OpenAI client with the Sambanova API | |
| # client = openai.OpenAI( | |
| # api_key=os.environ.get("SAMBANOVA_API_KEY"), | |
| # base_url="https://api.sambanova.ai/v1", | |
| # ) | |
| # def generate_text(prompt): | |
| # response = client.chat.completions.create( | |
| # model='Qwen2.5-Coder-32B-Instruct', | |
| # messages=[ | |
| # {"role": "system", "content": "You are a helpful assistant"}, | |
| # {"role": "user", "content": prompt} | |
| # ], | |
| # temperature=0, | |
| # max_tokens=8192 | |
| # ) | |
| # return response.choices[0].message.content | |
| # # Create the Gradio interface | |
| # iface = gr.Interface( | |
| # fn=generate_text, | |
| # inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."), | |
| # outputs="text", | |
| # title="Qwen2.5-Coder-32B-Instruct Chatbot", | |
| # description="Enter a prompt and get a response from the Qwen2.5-Coder-32B-Instruct model." | |
| # ) | |
| # # Launch the interface | |
| # iface.launch() |