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main.py

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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")
+
+@app.route("/", methods=["POST"])
+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)

requirements.txt

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+transformers
+torch
+flask