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Update app.py
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app.py
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import os
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import
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from datetime import date
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from gradio_client import Client, handle_file
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#
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HF_TOKEN = "
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DAILY_QUOTA = 3 # จำกัดวันละ 3 ภาพ
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QUOTA_FILE = "usage_quota.json"
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today = str(date.today())
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if not os.path.exists(QUOTA_FILE):
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usage_data = {"date": today, "count": 0}
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else:
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with open(QUOTA_FILE, "r") as f:
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usage_data = json.load(f)
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if usage_data["date"] != today:
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usage_data = {"date": today, "count": 0}
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if usage_data["count"] >= DAILY_QUOTA:
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return False, usage_data["count"]
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return True, usage_data["count"]
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def update_quota(current_count):
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with open(QUOTA_FILE, "w") as f:
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json.dump({"date": str(date.today()), "count": current_count + 1}, f)
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# 2. ฟังก์ชันเรียก API
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def run_editor_api(image_path, prompt):
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can_run, current_count = check_quota()
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if not can_run:
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print(f"❌ ขออภัย: คุณใช้โควต้าครบ {DAILY_QUOTA} ภาพสำหรับวันนี้แล้ว")
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return None
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print(f"🔄 กำลังประมวลผล (ภาพที่ {current_count + 1}/{DAILY_QUOTA})...")
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try:
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result = client.predict(
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image=handle_file(image_path),
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prompt=prompt,
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api_name="/predict"
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)
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update_quota(current_count)
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print("✅ ประมวลผลสำเร็จ!")
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return result
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except Exception as e:
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return None
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# --- ส่วนการใช้งาน ---
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# ใส่พาธรูปภาพ และ Prompt ที่ต้องการแก้ไข
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my_image = "input.jpg"
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my_prompt = "change the background to a beach"
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import os
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import gradio as gr
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from gradio_client import Client, handle_file
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# Fetch Token from Space Secrets (Name it HF_TOKEN in Settings)
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HF_TOKEN = os.getenv("HF_TOKEN")
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TARGET_SPACE = "selfit-camera/omni-image-editor"
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def bridge_api(image_path, prompt):
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if not image_path:
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return None
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try:
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# Direct connection to the target API
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client = Client(TARGET_SPACE, hf_token=HF_TOKEN)
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# API prediction call
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# Note: Ensure parameter names match target space's client.view_api()
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result = client.predict(
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image=handle_file(image_path),
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prompt=prompt,
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api_name="/predict"
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)
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return result
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except Exception as e:
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return f"API Bridge Error: {str(e)}"
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# UI Layout
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with gr.Blocks(title="Omni Editor Proxy") as demo:
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gr.Markdown("## 🚀 Omni Image Editor (Proxy Mode)")
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gr.Markdown("Processing is handled by the backend API and returned here.")
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with gr.Row():
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with gr.Column():
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input_img = gr.Image(type="filepath", label="Input Image")
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input_prompt = gr.Textbox(label="Edit Prompt", placeholder="e.g., 'change background to sunset'")
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submit_btn = gr.Button("Process", variant="primary")
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with gr.Column():
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output_img = gr.Image(label="Output")
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submit_btn.click(
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fn=bridge_api,
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inputs=[input_img, input_prompt],
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outputs=output_img
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)
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demo.launch()
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