File size: 1,098 Bytes
7023b3d d42ac1f 7023b3d d42ac1f ddc6288 d42ac1f 7023b3d d42ac1f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | from flask import Flask, request, jsonify
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
app = Flask(__name__)
# Load model and tokenizer once at startup
model_name = "gpt-oss-20b"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
@app.route("/generate", methods=["GET"])
def generate_text():
# Get 'message' parameter from query string
prompt = request.args.get("message", "")
if not prompt:
return jsonify({"error": "Please provide a 'message' parameter."}), 400
# Tokenize input
inputs = tokenizer(prompt, return_tensors="pt")
# Generate text
outputs = model.generate(
**inputs,
max_length=100,
num_return_sequences=1,
no_repeat_ngram_size=2,
temperature=0.7
)
# Decode generated text
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
# Return as JSON
return jsonify({"input": prompt, "output": generated_text})
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860) |