dhhhd

.gradio/flagged/dataset3.csv

@@ -1,2 +1,3 @@
 Input Text,Translation,timestamp
 Thobela,,2025-07-27 21:39:41.511509
+Hello,,2025-07-28 00:30:59.744082

app.py

@@ -53,30 +53,46 @@ import gradio as gr
 from dotenv import load_dotenv
 import os
 
-# Load environment variables from .env file
+# Load env
 load_dotenv()
 HF_TOKEN = os.getenv("HF_TOKEN")
 
 model_name = "Helsinki-NLP/opus-mt-en-nso"
 API_URL = f"https://api-inference.huggingface.co/models/{model_name}"
-headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+headers = {"Authorization": f"Bearer {HF_TOKEN}", "Accept": "application/json"}
 
 
 def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
-    print(f"Status Code: {response.status_code}")
-    print(f"Response content: {response.text[:500]}")  # Print first 500 chars
-    response.raise_for_status()  # Raise exception if bad HTTP status
-    return response.json()
+
+    if response.status_code == 200:
+        try:
+            return response.json()
+        except Exception as e:
+            return {"error": f"JSON decode error: {str(e)}"}
+    else:
+        # Show error message from HF API or HTTP code
+        try:
+            err = response.json()
+        except:
+            err = response.text
+        return {"error": f"HTTP {response.status_code}: {err}"}
 
 
 def translate(input_text):
-    # API Request:
+    if not input_text.strip():
+        return "Please enter text to translate."
+
     response = query({"inputs": input_text, "options": {"wait_for_model": True}})
 
-    translation = response[0]["translation_text"]
+    if "error" in response:
+        return f"Error: {response['error']}"
 
-    return translation
+    try:
+        translation = response[0]["translation_text"]
+        return translation
+    except (KeyError, IndexError):
+        return f"Unexpected response format: {response}"
 
 
 translator = gr.Interface(