Create app.py

app.py

@@ -0,0 +1,78 @@
+import requests
+import json
+import gradio as gr
+
+def calculate1(course_input, course_profile, course_hour):
+    url = "https://ai-knowledge-navigator.onrender.com/process"
+
+    headers = {
+        "Content-Type": "application/json"
+    }
+
+    data = {
+        "title": course_input,
+        "content": course_profile,
+        "hour": course_hour
+    }
+
+    try:
+        response = requests.post(url, json=data, headers=headers, timeout=50)
+
+        if response.status_code == 200:
+            try:
+                response_json = response.json()
+                # 解析回傳結果
+                success = response_json.get("success", False)
+                title = response_json.get("title", "未知課程")
+                competencies = response_json.get("competencies", ["未能成功匹配"])
+
+                if success:
+                    return f"課程 '{title}' 職能匹配成功！", ", ".join(competencies)
+                else:
+                    return "匹配失敗，請稍後再試", "無職能項目"
+
+            except json.JSONDecodeError:
+                return "錯誤: 伺服器回應非 JSON 格式", "無職能項目"
+
+        else:
+            return f"錯誤: 伺服器返回 HTTP {response.status_code}", "無職能項目"
+
+    except requests.exceptions.Timeout:
+        return "錯誤: 伺服器回應超時", "無職能項目"
+    except requests.exceptions.RequestException as e:
+        return f"請求失敗: {str(e)}", "無職能項目"
+
+def setup_gradio_interface():
+    with gr.Blocks() as demo:
+        with gr.Row():
+            course_input = gr.Textbox(label="課程名稱", placeholder="請輸入課程名稱")
+            course_hour = gr.Textbox(label="課程時數", placeholder="請輸入課程時數")
+        with gr.Row():
+            course_profile = gr.Textbox(label="課程簡介", placeholder="請輸入課程簡介")
+        with gr.Row():
+            submit_button = gr.Button("計算職能項目")
+        with gr.Row():
+            txt_response = gr.Textbox(label="計算狀態", placeholder="計算結果")
+            course_competencies = gr.Textbox(label="職能項目", placeholder="職能項目")
+
+        # 修正 inputs 和 outputs
+        submit_button.click(
+            calculate1,
+            inputs=[course_input, course_profile, course_hour],
+            outputs=[txt_response, course_competencies]
+        )
+
+    return demo
+
+try:
+    import gradio as gr
+except ImportError:
+    import sys
+    import gradio as gr
+
+# Run the interface
+if __name__ == "__main__":
+    demo = setup_gradio_interface()
+    #port = int(os.environ.get("PORT", 7860))
+    demo.launch()
+    #demo.launch(server_name="0.0.0.0", server_port=port)