Delete app.py

app.py

@@ -1,117 +0,0 @@
-import warnings
-
-# 過濾 SyntaxWarning 警告
-warnings.filterwarnings("ignore", category=SyntaxWarning)
-
-import gradio as gr
-from moviepy.editor import VideoFileClip
-import cv2
-import base64
-from openai import OpenAI
-import os
-
-def extract_frames(video_path, seconds_per_frame):
-    base64Frames = []
-    video = cv2.VideoCapture(video_path)
-    total_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
-    fps = video.get(cv2.CAP_PROP_FPS)
-    frames_to_skip = int(fps * seconds_per_frame)
-    curr_frame = 0
-
-    while curr_frame < total_frames - 1:
-        video.set(cv2.CAP_PROP_POS_FRAMES, curr_frame)
-        success, frame = video.read()
-        if not success:
-            break
-        _, buffer = cv2.imencode(".jpg", frame)
-        base64Frames.append(base64.b64encode(buffer).decode("utf-8"))
-        curr_frame += frames_to_skip
-    video.release()
-    return base64Frames
-
-def extract_audio(video_path):
-    base_video_path, _ = os.path.splitext(video_path)
-    audio_path = f"{base_video_path}.mp3"
-    clip = VideoFileClip(video_path)
-    clip.audio.write_audiofile(filename=audio_path, codec="mp3", bitrate="32k")
-    # Remove the line that closes the audio
-    clip.close()
-    return audio_path
-
-def process_video(video_path, seconds_per_frame=2):
-    base64Frames = extract_frames(video_path, seconds_per_frame)
-    audio_path = extract_audio(video_path)
-    return base64Frames, audio_path
-
-def get_summary_prompt(summary_detail):
-    if summary_detail == "簡短":
-        return "生成一個簡短的摘要，不超過50字。"
-    elif summary_detail == "中等":
-        return "生成一個中等長度的摘要，概述影片的主要內容。"
-    else:  # 詳細
-        return "生成一個詳細的摘要，包括影片的主要內容和關鍵細節。"
-
-def summarize_video(file_path, summary_detail):
-    api_key = "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"
-    # api_key = os.getenv("OPENAI_API_KEY")
-    client = OpenAI(api_key=api_key)
-
-    # 抽取幀和音頻（每0.5秒一幀）
-    base64Frames, audio_path = process_video(file_path, seconds_per_frame=int(0.5))
-
-    # 使用Whisper進行音頻轉錄
-    transcription = client.audio.transcriptions.create(
-        model="whisper-1", file=open(audio_path, "rb")
-    )
-
-    # 根據用戶選擇的詳細程度設置提示
-    summary_prompt = get_summary_prompt(summary_detail)
-
-    # 使用GPT-4o生成摘要
-    response = client.chat.completions.create(
-        model="gpt-4o",
-        messages=[
-            {
-                "role": "system",
-                "content": f"""您是一名優秀的摘要專家，請根據提供的影片和其轉錄內容生成Markdown格式的摘要。{summary_prompt}""",
-            },
-            {
-                "role": "user",
-                "content": [
-                    "以下是從影片中提取的幀畫面",
-                    *map(
-                        lambda x: {
-                            "type": "image_url",
-                            "image_url": {
-                                "url": f"data:image/jpg;base64,{x}",
-                                "detail": "low",
-                            },
-                        },
-                        base64Frames,
-                    ),
-                    {
-                        "type": "text",
-                        "text": f"這是影片的轉錄內容: {transcription.text}",
-                    },
-                ],
-            },
-        ],
-        temperature=0,
-    )
-
-    return response.choices[0].message.content
-
-demo = gr.Interface(
-    fn=summarize_video,
-    inputs=[
-        gr.File(label="上傳影片 (mp4)"),
-        gr.Radio(["簡短", "中等", "詳細"], label="摘要詳細程度", value="中等")
-    ],
-    outputs="markdown",
-    title="影片摘要生成器",
-    description="上傳影片，將生成影片的摘要。",
-    flagging_dir=""  # 這會移除 Flag 功能
-)
-
-if __name__ == "__main__":
-    demo.launch()