|
|
import gradio as gr |
|
|
from transformers import pipeline |
|
|
|
|
|
|
|
|
|
|
|
pipe = pipeline("text2text-generation", model="google/flan-t5-small") |
|
|
|
|
|
def analyze_response(prompt): |
|
|
if not prompt: |
|
|
return "Please enter text.", "⚪" |
|
|
|
|
|
try: |
|
|
|
|
|
output = pipe(prompt, max_length=100) |
|
|
response_text = output[0]['generated_text'] |
|
|
|
|
|
|
|
|
evaluation = "" |
|
|
if len(response_text) > 2: |
|
|
evaluation = "✅ النموذج فهم وأجاب (Success)" |
|
|
else: |
|
|
evaluation = "⚠️ إجابة قصيرة (Short)" |
|
|
|
|
|
return response_text, evaluation |
|
|
|
|
|
except Exception as e: |
|
|
return f"Error: {str(e)}", "❌ Failed" |
|
|
|
|
|
|
|
|
with gr.Blocks(theme=gr.themes.Soft()) as demo: |
|
|
gr.Markdown("# 🤖 اختبار فهم النماذج (Local Model Test)") |
|
|
gr.Markdown("يتم الآن تشغيل النموذج داخلياً (Local Execution) لضمان الاستقرار.") |
|
|
|
|
|
with gr.Row(): |
|
|
input_text = gr.Textbox(label="أدخل الـ Prompt (English preferred)", placeholder="Example: What is the capital of Egypt?") |
|
|
|
|
|
btn = gr.Button("تشغيل التحليل", variant="primary") |
|
|
|
|
|
with gr.Row(): |
|
|
output_text = gr.Textbox(label="الرد (Response)") |
|
|
eval_text = gr.Label(label="التقييم (Evaluation)") |
|
|
|
|
|
btn.click(analyze_response, inputs=input_text, outputs=[output_text, eval_text]) |
|
|
|
|
|
demo.launch() |
