import requests import os from transformers import Tool # Import other necessary libraries if needed class TextGenerationTool(Tool): name = "text_generator" description = ( "This is a tool for text generation. It takes a prompt as input and returns the generated text." ) inputs = ["text"] outputs = ["text"] def __call__(self, prompt: str): API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-v0.1" headers = {"Authorization": + os.environ['hf']} def query(payload): response = requests.post(API_URL, headers=headers, json=payload) print(response) return response.json() output = query({ "inputs": prompt, }) # Define the payload for the request #payload = { # "inputs": prompt # Adjust this based on your model's input format #} # Make the request to the API #generated_text = requests.post(API_URL, headers=headers, json=payload).json() # Extract and return the generated text #return generated_text["generated_text"] # Uncomment and customize the following lines based on your text generation needs # text_generator = pipeline(model="gpt2") # generated_text = text_generator(prompt, max_length=500, num_return_sequences=1, temperature=0.7) # Print the generated text if needed # print(generated_text)