Update app.py

app.py

@@ -1,83 +1,83 @@
 import gradio as gr
-from transformers import pipeline
 import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import traceback
 
-# ===============================
-# 🤖 Load Model LOCALLY
-# ===============================
-MODEL_NAME = "kawkabelaloom/astramind"
+MODEL_NAME = "Qwen/Qwen2.5-7B-Instruct"
 
-generator = pipeline(
-    "text-generation",
-    model=MODEL_NAME,
-    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-    device=0 if torch.cuda.is_available() else -1
+SYSTEM_PROMPT = "أنت مساعد عربي ذكي، تجيب بوضوح وبأسلوب بسيط ومفيد."
+
+# ---------- تحميل الموديل ----------
+print("🔄 Loading tokenizer...")
+tokenizer = AutoTokenizer.from_pretrained(
+    MODEL_NAME,
+    trust_remote_code=True
+)
+
+print("🔄 Loading model (CPU)...")
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=torch.float32,
+    device_map="cpu",
+    trust_remote_code=True
 )
 
-# ===============================
-# 🧠 Chat Logic
-# ===============================
-history = []
+print("✅ Model loaded")
 
-SYSTEM_PROMPT = (
-    "أنت مساعد عربي ذكي اسمك أسترا. "
-    "أجب بلغة عربية واضحة ومفيدة.\n\n"
+generator = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer
 )
 
-def build_prompt(user_message):
-    prompt = SYSTEM_PROMPT
-    for h in history[-6:]:
-        if h["role"] == "user":
-            prompt += f"المستخدم: {h['content']}\n"
-        else:
-            prompt += f"المساعد: {h['content']}\n"
+# ---------- تنسيق البرومبت ----------
+def build_prompt(history, user_message):
+    prompt = SYSTEM_PROMPT + "\n\n"
+    for user, bot in history:
+        prompt += f"المستخدم: {user}\n"
+        prompt += f"المساعد: {bot}\n"
     prompt += f"المستخدم: {user_message}\nالمساعد:"
     return prompt
 
-def chat(user_message, chat_history, max_tokens, temperature):
-    if not user_message.strip():
-        return chat_history, ""
 
-    prompt = build_prompt(user_message)
-
-    output = generator(
-        prompt,
-        max_new_tokens=max_tokens,
-        temperature=temperature,
-        do_sample=True,
-        return_full_text=False
-    )[0]["generated_text"]
+# ---------- دالة الرد ----------
+def chat(user_message, history):
+    if not user_message.strip():
+        return history, "⚠️ اكتب رسالة"
 
-    history.append({"role": "user", "content": user_message})
-    history.append({"role": "assistant", "content": output})
+    try:
+        prompt = build_prompt(history, user_message)
 
-    chat_history.append((user_message, output))
-    return chat_history, ""
+        output = generator(
+            prompt,
+            max_new_tokens=256,
+            temperature=0.7,
+            top_p=0.9,
+            do_sample=True
+        )
 
-def clear_chat():
-    history.clear()
-    return []
+        full_text = output[0]["generated_text"]
+        response = full_text.split("المساعد:")[-1].strip()
 
-# ===============================
-# 🖥️ Gradio UI
-# ===============================
-with gr.Blocks(title="Astramind") as demo:
-    gr.Markdown("# 🤖 Astramind Chatbot")
-    gr.Markdown("تشغيل محلي داخل HuggingFace Space")
+        history.append((user_message, response))
+        return history, ""
 
-    chatbot = gr.Chatbot(height=400)
+    except Exception as e:
+        error_msg = f"❌ Error:\n{str(e)}\n\n{traceback.format_exc()}"
+        history.append((user_message, error_msg))
+        return history, ""
 
-    with gr.Row():
-        msg = gr.Textbox(placeholder="اكتب رسالتك...", lines=2)
-        send = gr.Button("إرسال")
 
-    with gr.Accordion("⚙️ الإعدادات"):
-        tokens = gr.Slider(50, 500, 200, step=10, label="طول الرد")
-        temp = gr.Slider(0.1, 1.0, 0.7, step=0.1, label="الإبداع")
+# ---------- واجهة Gradio ----------
+with gr.Blocks(title="Qwen2.5 Arabic Chatbot") as demo:
+    gr.Markdown("# 🤖 Qwen2.5 Arabic Chatbot")
+    gr.Markdown("نموذج Qwen2.5 يعمل بدون messages وبدون API")
 
-    send.click(chat, [msg, chatbot, tokens, temp], [chatbot, msg])
-    msg.submit(chat, [msg, chatbot, tokens, temp], [chatbot, msg])
+    chatbot = gr.Chatbot(height=450)
+    msg = gr.Textbox(label="رسالتك", placeholder="اكتب سؤالك هنا...")
+    clear = gr.Button("🗑️ مسح المحادثة")
 
-    gr.Button("مسح المحادثة").click(clear_chat, outputs=chatbot)
+    msg.submit(chat, [msg, chatbot], [chatbot, msg])
+    clear.click(lambda: [], None, chatbot)
 
 demo.launch()