text_generator.py

import os
import requests

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/lukasdrg/clinical_longformer_same_tokens_220k"
        headers = {"Authorization": "Bearer " + os.environ['hf']}

        # 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)