Update app.py

app.py

@@ -107,69 +107,89 @@
 
 # love
 
-import os
-from huggingface_hub import InferenceClient
-import gradio as gr
-from dotenv import load_dotenv
+# import os
+# from huggingface_hub import InferenceClient
+# import gradio as gr
+# from dotenv import load_dotenv
 
-# Load env
-load_dotenv()
-HF_TOKEN = os.getenv("HF_TOKEN")
-
-# Init client
-client = InferenceClient(token=HF_TOKEN)
-
-# Languages supported
-LANGUAGES = {
-    "English → Afrikaans": "afr",
-    "English → Xhosa": "xho",
-    "English → Zulu": "zul",
-    "English → Sesotho": "sot",
-    "English → Tswana": "tsn",
-    "English → Northern Sotho": "nso",
-    "English → Swati": "ssw",
-    "English → Tsonga": "tso",
-    "English → Venda": "ven",
-}
-
-MODEL_NAME = "facebook/nllb-200-distilled-600M"
-
-
-def translate(input_text: str, language_label: str) -> str:
-    if not input_text.strip():
-        return "Error: Please enter text to translate."
-
-    lang_code = LANGUAGES[language_label]
-    formatted_input = f">>{lang_code}<< {input_text}"
-
-    try:
-        response = client.text_generation(
-            prompt=formatted_input,
-            model=MODEL_NAME,
-            max_new_tokens=200,
-        )
-        return response.strip()
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-# Gradio UI
-translator = gr.Interface(
-    fn=translate,
-    inputs=[
-        gr.Textbox(label="Input Text", placeholder="Type English text here..."),
-        gr.Dropdown(list(LANGUAGES.keys()), label="Target Language"),
-    ],
-    outputs=gr.Textbox(label="Translation"),
-    title="NLLB-200 Translator",
-    description="Translate English to South African languages using Meta's NLLB model",
-)
-
-translator.launch()
+# # Load env
+# load_dotenv()
+# HF_TOKEN = os.getenv("HF_TOKEN")
+
+# # Init client
+# client = InferenceClient(token=HF_TOKEN)
+
+# # Languages supported
+# LANGUAGES = {
+#     "English → Afrikaans": "afr",
+#     "English → Xhosa": "xho",
+#     "English → Zulu": "zul",
+#     "English → Sesotho": "sot",
+#     "English → Tswana": "tsn",
+#     "English → Northern Sotho": "nso",
+#     "English → Swati": "ssw",
+#     "English → Tsonga": "tso",
+#     "English → Venda": "ven",
+# }
+
+# MODEL_NAME = "facebook/nllb-200-distilled-600M"
+
+
+# def translate(input_text: str, language_label: str) -> str:
+#     if not input_text.strip():
+#         return "Error: Please enter text to translate."
+
+#     lang_code = LANGUAGES[language_label]
+#     formatted_input = f">>{lang_code}<< {input_text}"
+
+#     try:
+#         response = client.text_generation(
+#             prompt=formatted_input,
+#             model=MODEL_NAME,
+#             max_new_tokens=200,
+#         )
+#         return response.strip()
+#     except Exception as e:
+#         return f"Error: {str(e)}"
+
+
+# # Gradio UI
+# translator = gr.Interface(
+#     fn=translate,
+#     inputs=[
+#         gr.Textbox(label="Input Text", placeholder="Type English text here..."),
+#         gr.Dropdown(list(LANGUAGES.keys()), label="Target Language"),
+#     ],
+#     outputs=gr.Textbox(label="Translation"),
+#     title="NLLB-200 Translator",
+#     description="Translate English to South African languages using Meta's NLLB model",
+# )
+
+# translator.launch()
 
 
 # hate
 
+import os
+from dotenv import load_dotenv
+from huggingface_hub import InferenceClient
+
+load_dotenv()
+token = os.getenv("HF_TOKEN")
+client = InferenceClient(token=token)
+
+try:
+    prompt = ">>zul<< Hello, how are you?"
+    response = client.text_generation(
+        prompt=prompt, model="facebook/nllb-200-distilled-600M", max_new_tokens=100
+    )
+    print("Result:", response.strip())
+except Exception as e:
+    import traceback
+
+    print("Error occurred:", str(e))
+    print(traceback.format_exc())
+
 
 # import requests
 # import gradio as gr