Update app.py

app.py

@@ -9,8 +9,7 @@ from typing import Tuple
 
 os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
 
-
-
+# الحصول على التوكن من البيئة
 token = os.getenv("HF_TOKEN")
 Najeb_pipeline = pipeline("text-generation", model="sohiebwedyan/NAJEB_BOT", token=token, device=0 if torch.cuda.is_available() else -1)
 gpt2_pipeline = pipeline("text-generation", model="Qwen/Qwen-1_8B-Chat", device=0 if torch.cuda.is_available() else -1, trust_remote_code=True)
@@ -19,6 +18,7 @@ summarization_pipeline = pipeline("summarization", model="Falconsai/text_summari
 
 previous_questions = []
 
+# توليد الردود باستخدام GPT-2
 async def generate_gpt2(question, max_length, num_beams, temperature):
     return gpt2_pipeline(
         question,
@@ -31,6 +31,7 @@ async def generate_gpt2(question, max_length, num_beams, temperature):
         temperature=temperature
     )[0]['generated_text']
 
+# توليد الردود باستخدام Najeb
 async def generate_Najeb(question, max_length, num_beams, temperature):
     return Najeb_pipeline(
         question,
@@ -43,6 +44,7 @@ async def generate_Najeb(question, max_length, num_beams, temperature):
         temperature=temperature
     )[0]['generated_text']
 
+# توليد الردود باستخدام LLaMA 2
 async def generate_llama2(question, max_length, num_beams, temperature):
     return llama2_pipeline(
         question,
@@ -50,22 +52,21 @@ async def generate_llama2(question, max_length, num_beams, temperature):
         num_return_sequences=1,
         num_beams=num_beams,
         do_sample=True,
-        top_k=30,
-        top_p=0.9,
+        top_k=50,
+        top_p=0.95,
         temperature=temperature
     )[0]['generated_text']
 
+# التعامل مع الردود بشكل غير متزامن
 async def generate_responses_async(question, max_length=128, num_beams=2, temperature=0.5):
     previous_questions.append(question)
 
-
     gpt2_task = asyncio.create_task(generate_gpt2(question, max_length, num_beams, temperature))
     Najeb_task = asyncio.create_task(generate_Najeb(question, max_length, num_beams, temperature))
     llama2_task = asyncio.create_task(generate_llama2(question, max_length, num_beams, temperature))
 
     gpt2_response, Najeb_response, llama2_response = await asyncio.gather(gpt2_task, Najeb_task, llama2_task)
 
-
     combined_responses = f"GPT-2: {gpt2_response}\nNajeb: {Najeb_response}\nLLaMA 2: {llama2_response}"
     summarized_response = summarization_pipeline(combined_responses, max_length=150, min_length=50, do_sample=False)[0]['summary_text']
 
@@ -77,6 +78,7 @@ async def generate_responses_async(question, max_length=128, num_beams=2, temper
         "Previous Questions": "\n".join(previous_questions[-5:])
     }
 
+# تحديد طريقة الحساب بناءً على المدخل
 def handle_mode_selection(mode, input_text, max_length, num_beams, temperature):
     if mode == "AI Question Answering":
         result = asyncio.run(generate_responses_async(input_text, max_length, num_beams, temperature))
@@ -90,6 +92,8 @@ def handle_mode_selection(mode, input_text, max_length, num_beams, temperature):
     else:
         subnet_result = calculate_subnet(input_text)
         return subnet_result, "", "", "", ""
+
+# الحصول على الشبكة وعنوان الـ IP
 def get_network(ip_input: str) -> Tuple[ipaddress.IPv4Network, str]:
     try:
         if ip_input.count("/") == 0:
@@ -100,19 +104,18 @@ def get_network(ip_input: str) -> Tuple[ipaddress.IPv4Network, str]:
     except ValueError:
         return None, None
 
+# حساب الشبكة الفرعية
 def calculate_subnet(ip_input: str) -> str:
     network, ip = get_network(ip_input)
     if network is None or ip is None:
         return "Invalid IP Address or Subnet!"
 
-
     network_address = network.network_address
     broadcast_address = network.broadcast_address
     usable_hosts = list(network.hosts())
     num_usable_hosts = len(usable_hosts)
     usable_hosts_range = f"{usable_hosts[0]} - {usable_hosts[-1]}" if usable_hosts else "NA"
 
-
     octets = str(ip).split('.')
     binary_octets = [bin(int(octet))[2:].zfill(8) for octet in octets]
     bin_ip = '.'.join(binary_octets)
@@ -123,7 +126,6 @@ def calculate_subnet(ip_input: str) -> str:
     bin_mask = str(bin(int(network.netmask))[2:].zfill(32))
     bin_mask = '.'.join([bin_mask[i:i+8] for i in range(0, len(bin_mask), 8)])
 
- 
     result = f"""
 IP Address:             {ip}
 Address (bin):          {bin_ip}
@@ -141,8 +143,7 @@ Private IP:             {network.is_private}
 """
     return result.strip()
 
-
-
+# تحديد التصميم المخصص
 custom_css = """
 body {
     background-color: #f0f8ff;
@@ -202,7 +203,6 @@ p {
     box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
 }
 
-
 #image-container {
     text-align: center;
     position: relative;
@@ -240,58 +240,36 @@ p {
     padding: 10px;
     margin-top: 10px;
 }
-#GPT2_title, #Najeb_title, #LLaMA_title, #summary_title, #previous_title {
-    color: black;
-    font-weight: bold;
+#GPT2_output, #Najeb_output, #Llama2_output {
+    width: 400px;
+    height: 120px;
+}
+#summary_box {
+    background-color: rgba(255, 255, 255, 0.9);
 }
 """
 
-scroll_js = """
-<script>
-    function scrollToTop() {
-        document.getElementById('target-section').scrollIntoView({behavior: 'smooth'});
-    }
-</script>
-"""
-
-
-
-iface = gr.Blocks(css=custom_css)
-
-with iface:
-    gr.Markdown(f"<h1>Welcome to Najeb</h1><p>AI Question & Subnet Calculator, Enter your question or IP address to generate answers or calculate subnets.</p>")
-
-    gr.HTML(f"""
-    <div id="image-container">
-        <img src="https://news.cornell.edu/sites/default/files/styles/story_thumbnail_xlarge/public/2024-07/robot-1280x720_0.jpg?itok=AF6MakCq" alt="AI Image">
-        <button onclick="scrollToTop()">Go to Najeb</button>
-    </div>
-    {scroll_js}  <!-- Adding the JS to handle scrolling -->
-    """)
-    
-
-    with gr.Row():
-        mode_selector = gr.Radio(["AI Question Answering", "Subnet Calculation"], label="Select Mode", value="AI Question Answering")
-
+# إنشاء واجهة Gradio
+with gr.Blocks(css=custom_css) as iface:
     with gr.Row():
         with gr.Column():
-            input_text = gr.Textbox(label="Enter your question or IP", placeholder="Type here...", lines=2)
-            max_length_slider = gr.Slider(50, 1024, 128, label="Max Length")
-            num_beams_slider = gr.Slider(1, 10, 2, label="Number of Beams", step=1)
-            temperature_slider = gr.Slider(0.1, 1.0, 0.5, label="Temperature", step=0.1)
-            submit_button = gr.Button("Submit")
+            question_input = gr.Textbox(label="Enter Your Question", placeholder="Ask a question here...", lines=3)
+            mode_selector = gr.Dropdown(
+                label="Select Mode", choices=["AI Question Answering", "IP Subnet Calculation"], value="AI Question Answering"
+            )
+            max_length_slider = gr.Slider(50, 500, step=10, label="Max Length", value=150)
+            num_beams_slider = gr.Slider(1, 5, step=1, label="Number of Beams", value=2)
+            temperature_slider = gr.Slider(0.0, 1.0, step=0.05, label="Temperature", value=0.5)
 
         with gr.Column():
-            gpt2_output_box = gr.Markdown(label="GPT-2 Model Response")
-            najeb_output_box = gr.Markdown(label="Najeb Model Response")
-            llama2_output_box = gr.Markdown(label="LLaMA 2 Model Response")
-            summary_output_box = gr.Markdown(label="Summarized Response")
-            previous_questions_box = gr.Markdown(label="Previous Questions")
-
-    submit_button.click(
-        handle_mode_selection,
-        inputs=[mode_selector, input_text, max_length_slider, num_beams_slider, temperature_slider],
-        outputs=[gpt2_output_box, najeb_output_box, llama2_output_box, summary_output_box, previous_questions_box]
-    )
+            gpt2_output = gr.Textbox(label="GPT-2 Output", interactive=False)
+            Najeb_output = gr.Textbox(label="Najeb Output", interactive=False)
+            Llama2_output = gr.Textbox(label="Llama2 Output", interactive=False)
+            summarized_output = gr.Textbox(label="Summarized Answer", interactive=False)
+            previous_questions_output = gr.Textbox(label="Previous Questions", interactive=False)
+
+    mode_selector.change(handle_mode_selection, inputs=[mode_selector, question_input, max_length_slider, num_beams_slider, temperature_slider],
+                         outputs=[gpt2_output, Najeb_output, Llama2_output, summarized_output, previous_questions_output])
 
+# إطلاق الواجهة
 iface.launch(share=True)