app.py

import os
import time
import logging
from flask import Flask, request, jsonify
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
from flores200_codes import flores_codes

app = Flask(__name__)

logging.basicConfig(level=logging.DEBUG)

def load_models():
    model_name_dict = {"nllb-distilled-600M": "facebook/nllb-200-distilled-600M"}
    model_dict = {}

    for call_name, real_name in model_name_dict.items():
        logging.info(f"\tLoading model: {call_name}")
        model = AutoModelForSeq2SeqLM.from_pretrained(real_name)
        tokenizer = AutoTokenizer.from_pretrained(real_name)
        model_dict[call_name + "_model"] = model
        model_dict[call_name + "_tokenizer"] = tokenizer

    return model_dict

global model_dict
model_dict = load_models()

@app.route("/api/translate", methods=["POST"])
def translate_text():
    data = request.json
    logging.debug(f"Received data: {data}")
    source_lang = data.get("source")
    target_lang = data.get("target")
    input_text = data.get("text")

    if not source_lang or not target_lang or not input_text:
        logging.error("Missing fields in the request")
        return jsonify({"error": "source, target, and text fields are required"}), 400

    model_name = "nllb-distilled-600M"
    start_time = time.time()
    source = flores_codes.get(source_lang)
    target = flores_codes.get(target_lang)

    if not source or not target:
        logging.error("Invalid source or target language code")
        return jsonify({"error": "Invalid source or target language code"}), 400

    model = model_dict[model_name + "_model"]
    tokenizer = model_dict[model_name + "_tokenizer"]

    translator = pipeline(
        "translation",
        model=model,
        tokenizer=tokenizer,
        src_lang=source,
        tgt_lang=target,
    )
    output = translator(input_text, max_length=400)

    end_time = time.time()
    output_text = output[0]["translation_text"]

    result = {
        "inference_time": end_time - start_time,
        "source": source_lang,
        "target": target_lang,
        "result": output_text,
    }
    logging.debug(f"Translation result: {result}")
    return jsonify(result)

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5000, debug=True)