Create app.py

app.py

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+from pptx import Presentation
+import openai
+
+def translate_text(text, apikey):
+    openai.api_key = apikey
+    completion = openai.chat.completions.create(
+        model="gpt-4o",
+        messages=[{"role": "user", "content": "請把字串「"+text+"」翻譯成為英文，不需要有其他多餘的說明"}]
+        )
+    return completion.choices[0].message.content
+
+def translate_pptx(file, key):
+    prs = Presentation(file.name)
+    for slide in prs.slides:
+        for shape in slide.shapes:
+            if shape.has_text_frame:
+                for paragraph in shape.text_frame.paragraphs:
+                    original_text = ''.join(run.text for run in paragraph.runs)
+                    translated_text = translate_text(original_text, key)
+                    for run in paragraph.runs:
+                        run.text = translated_text
+
+    # Save the modified presentation to a new file
+    output_file_path = "translated_presentation.pptx"
+    prs.save(output_file_path)
+    return output_file_path
+
+def setup_gradio_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("## PowerPoint Translator")
+        gr.Markdown("Upload your PowerPoint presentation in Chinese, and download it translated into English.")
+        with gr.Row():
+            file_input = gr.File(label="Upload PPTX file")
+            api_key_input = gr.Textbox(label="Enter OpenAI API Key", placeholder="OpenAI API Key")
+            submit_button = gr.Button("Translate")
+        file_output = gr.File(label="Download Translated Presentation")
+
+        def translate_and_download(file):
+            if file is not None:
+                output_path = translate_pptx(file, key)
+                return output_path
+
+        submit_button.click(
+            translate_and_download,
+            inputs=[file_input, api_key_input],
+            outputs=file_output
+        )
+
+    return demo
+
+# First, try importing gradio. If it fails, attempt to install it.
+try:
+    import gradio as gr
+except ImportError:
+    import sys
+    import gradio as gr
+
+# Run the interface
+if __name__ == "__main__":
+    demo = setup_gradio_interface()
+    demo.launch()