Update app.py

app.py

@@ -1,20 +1,3 @@
-import streamlit as st
-from transformers import pipeline
-import requests
-
-# Translation Pipelines
-translator_ur_en = pipeline("translation", model="Helsinki-NLP/opus-mt-ur-en")
-translator_en_ur = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ur")
-
-# Hugging Face API Setup
-HF_API_TOKEN = "YOUR_HF_API_KEY"  # Replace with your token from https://huggingface.co/settings/tokens
-DEEPSEEK_MODEL = "deepseek-ai/deepseek-llm-7b-chat"
-
-headers = {
-    "Authorization": f"Bearer {HF_API_TOKEN}",
-    "Content-Type": "application/json"
-}
-
 def query_deepseek(prompt):
     payload = {
         "inputs": f"<|system|>You are a helpful assistant.<|user|>{prompt}<|assistant|>",
@@ -25,23 +8,12 @@ def query_deepseek(prompt):
         headers=headers,
         json=payload
     )
-    result = response.json()
-    return result[0]["generated_text"].split("<|assistant|>")[-1].strip()
-
-# Streamlit UI
-st.title("🤖 Urdu AI Assistant (Powered by DeepSeek)")
-
-urdu_input = st.text_area("اپنا سوال اردو میں لکھیں:", height=100)
-
-if st.button("جواب حاصل کریں"):
-    with st.spinner("ترجمہ ہو رہا ہے..."):
-        english_prompt = translator_ur_en(urdu_input)[0]['translation_text']
     
-    with st.spinner("DeepSeek سے جواب حاصل کیا جا رہا ہے..."):
-        english_response = query_deepseek(english_prompt)
-    
-    with st.spinner("جواب اردو میں ترجمہ ہو رہا ہے..."):
-        urdu_response = translator_en_ur(english_response)[0]['translation_text']
-    
-    st.markdown("### 📝 جواب:")
-    st.write(urdu_response)
+    try:
+        result = response.json()
+        # Debug output if response is not a list
+        if isinstance(result, dict) and "error" in result:
+            return f"⚠️ DeepSeek API error: {result['error']}"
+        return result[0]["generated_text"].split("<|assistant|>")[-1].strip()
+    except Exception as e:
+        return f"⚠️ Failed to parse DeepSeek response: {e}"