Update app.py

app.py

@@ -1,7 +1,8 @@
-import os
 from fastapi import FastAPI, HTTPException
-from transformers import pipeline
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+import langdetect
 import logging
+import os
 
 # Atur direktori cache untuk Hugging Face
 os.environ["HF_HOME"] = "/app/cache"
@@ -14,19 +15,65 @@ logger = logging.getLogger(__name__)
 
 try:
     logger.info("Loading translation model...")
-    translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-id")
+    # Load model dan tokenizer M2M100
+    model_name = "facebook/m2m100_418M"
+    model = M2M100ForConditionalGeneration.from_pretrained(model_name)
+    tokenizer = M2M100Tokenizer.from_pretrained(model_name)
     logger.info("Model loaded successfully")
 except Exception as e:
     logger.error(f"Failed to load model: {str(e)}")
     raise Exception(f"Model initialization failed: {str(e)}")
 
+def detect_language(text: str) -> str:
+    """Deteksi bahasa dari teks menggunakan langdetect."""
+    try:
+        lang = langdetect.detect(text)
+        # Konversi kode bahasa ke format M2M100
+        lang_map = {
+            "id": "id",  # Indonesia
+            "fr": "fr",  # Prancis
+            "es": "es",  # Spanyol
+            "de": "de",  # Jerman
+            "ja": "ja",  # Jepang
+            "zh": "zh",  # Mandarin
+            "ru": "ru",  # Rusia
+            "th": "th",  # Thailand
+        }
+        return lang_map.get(lang, "en")  # Default ke Inggris jika tidak dikenali
+    except Exception as e:
+        logger.warning(f"Language detection failed: {str(e)}, defaulting to English")
+        return "en"
+
+def translate_to_english(text: str, source_lang: str) -> str:
+    """Terjemahkan teks ke Inggris menggunakan M2M100."""
+    try:
+        # Set bahasa sumber
+        tokenizer.src_lang = source_lang
+        # Encode teks
+        encoded = tokenizer(text, return_tensors="pt")
+        # Generate terjemahan (ke Inggris)
+        generated_tokens = model.generate(**encoded, forced_bos_token_id=tokenizer.get_lang_id("en"))
+        # Decode hasil
+        translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+        return translated_text
+    except Exception as e:
+        logger.error(f"Translation failed: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Translation failed: {str(e)}")
+
 @app.post("/translate")
 async def translate(text: str):
     if not text:
         raise HTTPException(status_code=400, detail="Text input is required")
     try:
-        result = translator(text)
-        return {"translated_text": result[0]["translation_text"]}
+        # Deteksi bahasa
+        source_lang = detect_language(text)
+        logger.info(f"Detected source language: {source_lang}")
+        # Jika sudah Inggris, kembalikan teks asli
+        if source_lang == "en":
+            return {"translated_text": text}
+        # Terjemahkan ke Inggris
+        translated_text = translate_to_english(text, source_lang)
+        return {"translated_text": translated_text}
     except Exception as e:
-        logger.error(f"Translation failed: {str(e)}")
-        raise HTTPException(status_code=500, detail=f"Translation failed: {str(e)}")
+        logger.error(f"Processing failed: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Processing failed: {str(e)}")