Create app.py

app.py

@@ -0,0 +1,47 @@
+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|>",
+        "parameters": {"max_new_tokens": 200}
+    }
+    response = requests.post(
+        f"https://api-inference.huggingface.co/models/{DEEPSEEK_MODEL}",
+        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)