Update app.py

app.py

@@ -1,6 +1,7 @@
 from fastapi import FastAPI, Request, Query
 import src.Paraphrase as Paraphrase
-import src.Translate as Translate
+import src.Translation as Translation
+import src.Translate as Cltranslate
 from typing import Optional
 from fastapi_mcp import FastApiMCP
 from huggingface_hub import hf_hub_download, list_repo_files
@@ -8,8 +9,9 @@ from sentence_transformers import SentenceTransformer
 
 app = FastAPI()
 # app = FastAPI(docs_url="/docs")
-MODELS = {'enro': 'BlackKakapo/opus-mt-en-ro',
-          'roen': 'BlackKakapo/opus-mt-ro-en',
+MODELS = {'benro': 'BlackKakapo/opus-mt-en-ro',
+          'broen': 'BlackKakapo/opus-mt-ro-en',
+          'mttcbig': 'Helsinki-NLP/opus-mt-tc-big-en-ro',
           'gemma': 'Gargaz/gemma-2b-romanian-better',
           'paraphrase': 'tuner007/pegasus_paraphrase'}
 EMBEDDING_MODELS = {"all-MiniLM-L6-v2":384,
@@ -54,10 +56,17 @@ def paraphrase(text: str, model: str  = MODELS['paraphrase']):
     resultValue, exception = Paraphrase.paraphraseParaphraseMethod(text, model)
     return {"input": text, "result": resultValue, "exception": exception}
 
+@app.get("/listmodels", operation_id="list_models", description="List models", tags=["listmodels"], summary="List models")
+def listmodels():
+    return {"MODELS": MODELS, "EMBEDDING_MODELS": EMBEDDING_MODELS}
+
+# text: str, model: Optional[str] = MODELS['benro']
 @app.get("/translate", operation_id="get_translate", description="Translate text", tags=["translate"], summary="Translate text")
-def translate(text: str, model: Optional[str] = MODELS['enro']):
-    if 'BlackKakapo' in model:
-        translation = Translate.paraphraseTranslateMethod(text, model)
+def translate(input_text: str, model_name: str = MODELS['mttcbig'], sl: str = 'en', tl: str = 'ro'):
+    if 'BlackKakapo' in model_name:
+        translation = Translation.paraphraseTranslateMethod(text, model_name)
+    elif 'Helsinki-NLP' in model_name:
+        translation = Cltranslate.HelsinkiNLP_mulroa(model_name, sl, tl, input_text)
     else:
         translation: str = Translate.gemma_direct(text, model)
     return {"input": text, "result": translation, "model": model}