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| import gradio as gr | |
| import requests | |
| # Define the Hugging Face API endpoint and your API token | |
| API_URL = "https://z94ka3s1dsuof4va.us-east-1.aws.endpoints.huggingface.cloud" | |
| API_TOKEN = "hf\_XgrSWzAWKtqKXgSFLZMZsQeSSjCcMbqUIt" # Replace with your actual API token | |
| # Function to query the Hugging Face model | |
| def query_huggingface_model(input_text): | |
| headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
| payload = {"inputs": input_text} | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| if response.status_code == 200: | |
| return response.json() | |
| else: | |
| return {"error": f"Request failed with status code {response.status_code}"} | |
| # Define a function to process the input and return the model's output | |
| def generate_response(input_text): | |
| response = query_huggingface_model(input_text) | |
| if "error" in response: | |
| return response["error"] | |
| else: | |
| return response[0]['generated_text'] | |
| # Create a Gradio interface | |
| iface = gr.Interface( | |
| fn=generate_response, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter your text here..."), | |
| outputs="text", | |
| title="LLaMA-2-7B Guanaco Dolly Mini Model", | |
| description="Generate responses using the LLaMA-2-7B Guanaco Dolly Mini model from Hugging Face." | |
| ) | |
| # Launch the interface | |
| iface.launch() | |