Update app.py

app.py

@@ -15,15 +15,15 @@ embed_model = SentenceTransformer("all-MiniLM-L6-v2")
 
 # ✅ Use your OpenRouter API key from environment
 API_KEY = os.environ.get("OPENROUTER_API_KEY")
-MODEL = "deepseek/deepseek-chat-v3-0324:free"
+MODEL = "deepseek/deepseek-r1-0528:free"
 
-# ✅ Function to search relevant context
+# ✅ Function to get relevant context
 def get_context(query, top_k=5):
     query_vec = embed_model.encode([query])
     D, I = index.search(np.array(query_vec), top_k)
     return "\n".join([texts[i] for i in I[0]])
 
-# ✅ Function to handle chat
+# ✅ Chat function
 def chat_fn(message, history):
     headers = {
         "Authorization": f"Bearer {API_KEY}",
@@ -56,78 +56,8 @@ def chat_fn(message, history):
 
     return reply
 
-def upload_fn(file):
-    if file is None:
-        return "No file uploaded."
-    try:
-        # Read uploaded file
-        with open(file.name, 'r', encoding='utf-8') as f:
-            new_texts = [line.strip() for line in f if line.strip()]
-        if not new_texts:
-            return "Uploaded file is empty."
-
-        # Load current texts
-        with open("texts.json", "r", encoding="utf-8") as f:
-            texts = json.load(f)
-
-        # Add new texts
-        texts.extend(new_texts)
-        with open("texts.json", "w", encoding="utf-8") as f:
-            json.dump(texts, f, ensure_ascii=False, indent=2)
-
-        # Embed new texts and add to FAISS index
-        new_vecs = embed_model.encode(new_texts)
-        index.add(np.array(new_vecs))
-        faiss.write_index(index, "faiss_index.bin")
-
-        return f"Successfully added {len(new_texts)} new texts."
-    except Exception as e:
-        return f"❌ Error during upload: {e}"
-
-def save_chat_history(user, assistant):
-    try:
-        history_file = "chat_history.json"
-        if os.path.exists(history_file):
-            with open(history_file, "r", encoding="utf-8") as f:
-                chat_history = json.load(f)
-        else:
-            chat_history = []
-        chat_history.append({"user": user, "assistant": assistant})
-        with open(history_file, "w", encoding="utf-8") as f:
-            json.dump(chat_history, f, ensure_ascii=False, indent=2)
-    except Exception as e:
-        pass  # Optionally log error
-
-# ✅ Modified chat function for Gradio API compatibility
-def chat_and_save_fn(message, history):
-    reply = chat_fn(message, history)
-    save_chat_history(message, reply)
-    return [reply]  # ✅ Fix: return a list for API response
-
-# ✅ Optional: file upload handler if used in UI (not exposed via API)
-def upload_and_respond_fn(file, history):
-    status = upload_fn(file)
-    return [status]  # ✅ Fix: ensure return is list for compatibility
-
-# ✅ Gradio UI (for local test / HF Space frontend)
-with gr.Blocks(theme="soft") as app:
-    gr.Markdown("# CODEX MIRXA KAMRAN\nChat with AI MODEL trained By Mirxa Kamran")
-    chatbot = gr.Chatbot()
-    with gr.Row():
-        msg = gr.Textbox(placeholder="Type your message here...")
-        upload = gr.File(label="Upload .txt", file_types=[".txt"])
-        send_btn = gr.Button("Send")
-
-    def user_send(user_message, chat_history, file):
-        if file is not None:
-            return upload_and_respond_fn(file, chat_history), "", None
-        if user_message.strip() == "":
-            return chat_history, "", None
-        reply = chat_and_save_fn(user_message, chat_history)[0]  # unpack from list
-        chat_history = chat_history + [[user_message, reply]]
-        return chat_history, "", None
-
-    send_btn.click(user_send, [msg, chatbot, upload], [chatbot, msg, upload])
-    msg.submit(user_send, [msg, chatbot, upload], [chatbot, msg, upload])
-
-app.launch()
+# ✅ Launch Gradio chat without titles or descriptions (clean look)
+gr.ChatInterface(
+    fn=chat_fn,
+    theme="soft"
+).launch(inbrowser=True, share=True)