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| import requests | |
| import os | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| # Define the endpoint and your API key | |
| api_url = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct" | |
| api_key = os.getenv('HFSecret') | |
| # Define the headers for authorization | |
| headers = { | |
| "Authorization": f"Bearer {api_key}" | |
| } | |
| # Function to call the HuggingFace API | |
| def call_huggingface_api(prompt): | |
| data = { | |
| "inputs": prompt, | |
| "parameters": {"max_length": 500, "temperature": 0.5} | |
| } | |
| response = requests.post(api_url, headers=headers, json=data) | |
| if response.status_code != 200: | |
| raise Exception(f"Error: {response.status_code}, {response.text}") | |
| return response.json() | |
| # Example: Sentiment analysis | |
| prompt = "Perform sentiment analysis on the following text: I love programming!" | |
| try: | |
| result = call_huggingface_api(prompt) | |
| print(result) | |
| except Exception as e: | |
| print(f"Error: {e}") | |