text_generator.py

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)