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from flask import Flask, request, jsonify | |
from transformers import GPT2LMHeadModel, GPT2Tokenizer | |
import torch | |
app = Flask("Response API") | |
# Load the Hugging Face GPT-2 model and tokenizer | |
model = GPT2LMHeadModel.from_pretrained("microsoft/DialoGPT-medium") | |
tokenizer = GPT2Tokenizer.from_pretrained("microsoft/DialoGPT-medium") | |
def receive_data(): | |
data = request.get_json() | |
print("Prompt:", data['prompt']) | |
print("Length:", data['length']) | |
input_text = data['prompt'] | |
# Tokenize the input text | |
input_ids = tokenizer.encode(input_text, return_tensors="pt") | |
# Generate output using the model | |
output_ids = model.generate(input_ids, max_length=data['length'], num_beams=5, no_repeat_ngram_size=2) | |
generated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True) | |
answer_data = { "answer": generated_text } | |
print("Answered with:", answer_data) | |
return jsonify(answer_data) | |
app.run(debug=False, port=7860) | |