Update app.py

app.py

@@ -1,85 +1,136 @@
+# Using Public space/
 import requests
 import gradio as gr
-from dotenv import load_dotenv
-from transformers import MBart50TokenizerFast
-import os
 
-# Load environment variables
-load_dotenv()
-HF_TOKEN = os.getenv("HF_TOKEN")
-headers = {"Authorization": f"Bearer {HF_TOKEN}"}
-
-# Correct mBART-50 language codes
+# Supported target languages and their ISO 639-1 codes
 LANGUAGES = {
-    "English → Afrikaans": "af_ZA",
-    "English → Xhosa": "xh_ZA",
-    "English → Zulu": "zu_ZA",
-    "English → Sesotho": "st_ZA",  # Southern Sotho
-    "English → Tswana": "tn_ZA",
-    # The following are *not officially* supported by mBART-50 and may raise errors
-    # You can remove them if not working
-    # "English → Northern Sotho": "nso_ZA",
-    # "English → Swati": "ss_ZA",
-    # "English → Tsonga": "ts_ZA",
-    # "English → Venda": "ve_ZA",
+    "English → Afrikaans": ("en", "af"),
+    "English → Xhosa": ("en", "xh"),
+    "English → Zulu": ("en", "zu"),
+    "English → Sesotho": ("en", "st"),
+    "English → Tswana": ("en", "tn"),
+    "English → Northern Sotho": ("en", "nso"),
+    "English → Swati": ("en", "ss"),
+    "English → Tsonga": ("en", "ts"),
+    "English → Venda": ("en", "ve"),
 }
 
-MODEL_NAME = "facebook/mbart-large-50-many-to-many-mmt"
-API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
-
-# Load tokenizer to get language token IDs
-tokenizer = MBart50TokenizerFast.from_pretrained(MODEL_NAME)
+API_URL = "https://sepioo-facebook-translation.hf.space/translate"
 
 
-def get_token_id(lang_code):
-    """Return the forced_bos_token_id for the target language."""
-    return tokenizer.lang_code_to_id[lang_code]
+def translate(input_text, language_label):
+    source_lang, target_lang = LANGUAGES[language_label]
 
+    payload = {"source": source_lang, "target": target_lang, "text": input_text}
 
-def query(payload):
-    """Send the translation request to the Hugging Face API."""
-    response = requests.post(API_URL, headers=headers, json=payload)
+    response = requests.post(API_URL, json=payload)
 
     if response.status_code != 200:
-        print(f"[ERROR] API failed: {response.status_code} - {response.text}")
-        return {"error": f"Request failed with {response.status_code}"}
+        return f"Error: {response.status_code} - {response.text}"
 
     try:
-        return response.json()
-    except requests.exceptions.JSONDecodeError:
-        print(f"[ERROR] Failed to parse JSON: {response.text}")
-        return {"error": "Invalid JSON from API"}
-
-
-def translate(input_text, language_label):
-    """Main translation function."""
-    target_lang_code = LANGUAGES[language_label]
-    token_id = get_token_id(target_lang_code)
-
-    payload = {
-        "inputs": input_text,
-        "parameters": {"forced_bos_token_id": token_id},
-        "options": {"wait_for_model": True},
-    }
-
-    response = query(payload)
-
-    if "error" in response:
-        return f"Error: {response['error']}"
-
-    return response[0]["translation_text"]
+        return response.json()["translation"]
+    except Exception as e:
+        return f"Error parsing response: {e}"
 
 
 # Gradio UI
 translator = gr.Interface(
     fn=translate,
     inputs=[
-        gr.Textbox(label="Input Text", placeholder="Type text here..."),
+        gr.Textbox(label="Input Text", placeholder="Type English text here..."),
         gr.Dropdown(list(LANGUAGES.keys()), label="Select Language Target"),
     ],
     outputs=gr.Textbox(label="Translation"),
-    title="Translademia",
-    description="Translate English text to South African languages using Meta's mBART-50 model.",
+    title="Translademia (Community-Powered)",
+    description="Translate English to South African languages using a public Hugging Face Space backend (no token needed).",
 )
 
 translator.launch()
+
+
+# import requests
+# import gradio as gr
+# from dotenv import load_dotenv
+# from transformers import MBart50TokenizerFast
+# import os
+
+# # Load environment variables
+# load_dotenv()
+# HF_TOKEN = os.getenv("HF_TOKEN")
+# headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+
+# # Correct mBART-50 language codes
+# LANGUAGES = {
+#     "English → Afrikaans": "af_ZA",
+#     "English → Xhosa": "xh_ZA",
+#     "English → Zulu": "zu_ZA",
+#     "English → Sesotho": "st_ZA",  # Southern Sotho
+#     "English → Tswana": "tn_ZA",
+#     # The following are *not officially* supported by mBART-50 and may raise errors
+#     # You can remove them if not working
+#     # "English → Northern Sotho": "nso_ZA",
+#     # "English → Swati": "ss_ZA",
+#     # "English → Tsonga": "ts_ZA",
+#     # "English → Venda": "ve_ZA",
+# }
+
+# MODEL_NAME = "facebook/mbart-large-50-many-to-many-mmt"
+# API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
+
+# # Load tokenizer to get language token IDs
+# tokenizer = MBart50TokenizerFast.from_pretrained(MODEL_NAME)
+
+
+# def get_token_id(lang_code):
+#     """Return the forced_bos_token_id for the target language."""
+#     return tokenizer.lang_code_to_id[lang_code]
+
+
+# def query(payload):
+#     """Send the translation request to the Hugging Face API."""
+#     response = requests.post(API_URL, headers=headers, json=payload)
+
+#     if response.status_code != 200:
+#         print(f"[ERROR] API failed: {response.status_code} - {response.text}")
+#         return {"error": f"Request failed with {response.status_code}"}
+
+#     try:
+#         return response.json()
+#     except requests.exceptions.JSONDecodeError:
+#         print(f"[ERROR] Failed to parse JSON: {response.text}")
+#         return {"error": "Invalid JSON from API"}
+
+
+# def translate(input_text, language_label):
+#     """Main translation function."""
+#     target_lang_code = LANGUAGES[language_label]
+#     token_id = get_token_id(target_lang_code)
+
+#     payload = {
+#         "inputs": input_text,
+#         "parameters": {"forced_bos_token_id": token_id},
+#         "options": {"wait_for_model": True},
+#     }
+
+#     response = query(payload)
+
+#     if "error" in response:
+#         return f"Error: {response['error']}"
+
+#     return response[0]["translation_text"]
+
+
+# # Gradio UI
+# translator = gr.Interface(
+#     fn=translate,
+#     inputs=[
+#         gr.Textbox(label="Input Text", placeholder="Type text here..."),
+#         gr.Dropdown(list(LANGUAGES.keys()), label="Select Language Target"),
+#     ],
+#     outputs=gr.Textbox(label="Translation"),
+#     title="Translademia",
+#     description="Translate English text to South African languages using Meta's mBART-50 model.",
+# )
+
+# translator.launch()