loggin added

app.py

@@ -1,18 +1,20 @@
 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():
-        print(f"\tLoading model: {call_name}")
+        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
@@ -20,19 +22,19 @@ def load_models():
 
     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"
@@ -41,6 +43,7 @@ def translate_text():
     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"]
@@ -64,8 +67,8 @@ def translate_text():
         "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)