Update app.py

app.py

@@ -105,6 +105,83 @@
 # translator.launch()
 
 
+# import requests
+# import gradio as gr
+# from dotenv import load_dotenv
+# import os
+
+# # Load Hugging Face token from .env
+# load_dotenv()
+# HF_TOKEN = os.getenv("HF_TOKEN")
+# headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+
+# # NLLB model name
+# MODEL_NAME = "facebook/nllb-200-3.3B"
+# API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
+
+# # Define supported language pairs and NLLB codes
+# LANGUAGE_PAIRS = {
+#     "English → Afrikaans": ("eng_Latn", "afr_Latn"),
+#     "English → Xhosa": ("eng_Latn", "xho_Latn"),
+#     "English → Zulu": ("eng_Latn", "zul_Latn"),
+#     "English → Sesotho": ("eng_Latn", "sot_Latn"),
+#     "English → Tswana": ("eng_Latn", "tsn_Latn"),
+#     "English → Northern Sotho": ("eng_Latn", "nso_Latn"),
+#     "English → Swati": ("eng_Latn", "ssw_Latn"),
+#     "English → Tsonga": ("eng_Latn", "tso_Latn"),
+#     "Afrikaans → English": ("afr_Latn", "eng_Latn"),
+#     "Xhosa → English": ("xho_Latn", "eng_Latn"),
+#     "Zulu → English": ("zul_Latn", "eng_Latn"),
+#     "Sesotho → English": ("sot_Latn", "eng_Latn"),
+#     "Tswana → English": ("tsn_Latn", "eng_Latn"),
+#     "Northern Sotho → English": ("nso_Latn", "eng_Latn"),
+#     "Swati → English": ("ssw_Latn", "eng_Latn"),
+#     "Tsonga → English": ("tso_Latn", "eng_Latn"),
+# }
+
+
+# def translate(input_text, language_pair):
+#     src_lang, tgt_lang = LANGUAGE_PAIRS[language_pair]
+
+#     payload = {
+#         "inputs": input_text,
+#         "parameters": {
+#             "src_lang": src_lang,
+#             "tgt_lang": tgt_lang,
+#         },
+#         "options": {"wait_for_model": True},
+#     }
+
+#     response = requests.post(API_URL, headers=headers, json=payload)
+
+#     if response.status_code != 200:
+#         return f"[ERROR] {response.status_code}: {response.text}"
+
+#     try:
+#         output = response.json()
+#         return output[0]["translation_text"]
+#     except Exception as e:
+#         return f"[ERROR] Failed to parse response: {e}"
+
+
+# # Gradio UI
+# translator = gr.Interface(
+#     fn=translate,
+#     inputs=[
+#         gr.Textbox(label="Input Text", placeholder="Type text here..."),
+#         gr.Dropdown(choices=list(LANGUAGE_PAIRS.keys()), label="Select Language Pair"),
+#     ],
+#     outputs=gr.Textbox(label="Translation"),
+#     title="Translademia (NLLB Edition)",
+#     description="Translate between English and official South African languages using Meta's NLLB-200 model.",
+# )
+
+# translator.launch(share=True)
+
+
+# ///////////////////////////////////////////////////////////////////////////////////////////////////////////////
+# Using Unesco API
+
 import requests
 import gradio as gr
 from dotenv import load_dotenv
@@ -115,7 +192,7 @@ load_dotenv()
 HF_TOKEN = os.getenv("HF_TOKEN")
 headers = {"Authorization": f"Bearer {HF_TOKEN}"}
 
-# NLLB model name
+# NLLB model endpoint
 MODEL_NAME = "facebook/nllb-200-3.3B"
 API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
 
@@ -141,14 +218,18 @@ LANGUAGE_PAIRS = {
 
 
 def translate(input_text, language_pair):
+    if not input_text.strip():
+        return "[ERROR] Please enter some text to translate."
+
+    # Get source and target language codes
     src_lang, tgt_lang = LANGUAGE_PAIRS[language_pair]
 
+    # Prepend target language token to the input
+    formatted_input = f">>{tgt_lang}<< {input_text.strip()}"
+
+    # Send request to Hugging Face Inference API
     payload = {
-        "inputs": input_text,
-        "parameters": {
-            "src_lang": src_lang,
-            "tgt_lang": tgt_lang,
-        },
+        "inputs": formatted_input,
         "options": {"wait_for_model": True},
     }
 
@@ -173,7 +254,7 @@ translator = gr.Interface(
     ],
     outputs=gr.Textbox(label="Translation"),
     title="Translademia (NLLB Edition)",
-    description="Translate between English and official South African languages using Meta's NLLB-200 model.",
+    description="Translate between English and South African languages using Meta's NLLB-200 multilingual model.",
 )
 
 translator.launch(share=True)