Update app/config.py

app/config.py

@@ -6,22 +6,21 @@ from typing import Dict
 @dataclass
 class Config:
     HF_TOKEN: str = field(
-        default_factory=lambda: os.environ.get("HF_TOKEN", "HF_TOKEN").strip()
+        default_factory=lambda: os.environ.get("HF_TOKEN", "").strip()
     )
 
     # Language detection
     FASTTEXT_MODEL: str = "facebook/fasttext-language-identification"
 
-    # Translation 
-    TRANSLATION_MODEL_TO_ENG:   str = "facebook/nllb-200-3.3B"
-    TRANSLATION_MODEL_FROM_ENG: str = "facebook/nllb-200-3.3B"
-    BASE_TRANSLATION: str = 'drrobot9/nllb-ig-yo-ha-finetuned'
-  
+
+    TRANSLATION_MODEL: str = "facebook/nllb-200-3.3B"
+
+    # LLM
     LLM_MODEL:       str   = "Qwen/Qwen2.5-1.5B-Instruct"
     LLM_MAX_TOKENS:  int   = 512
     LLM_TEMPERATURE: float = 0.2
 
-    # ASR  one model per language, selected by user
+
     ASR_MODELS: Dict[str, str] = field(default_factory=lambda: {
         "yoruba":  "NCAIR1/Yoruba-ASR",
         "igbo":    "NCAIR1/Igbo-ASR",
@@ -34,12 +33,12 @@ class Config:
     # Memory
     MAX_HISTORY_TURNS: int = 10
 
-    #  language codes for  models
-    LANG_CODES: Dict[str, str] = field(default_factory=lambda: {
-        "yoruba":  "yo",
-        "igbo":    "ig",
-        "hausa":   "ha",
-        "english": "en",
+
+    NLLB_CODES: Dict[str, str] = field(default_factory=lambda: {
+        "yoruba":  "yor_Latn",
+        "igbo":    "ibo_Latn",
+        "hausa":   "hau_Latn",
+        "english": "eng_Latn",
     })