Upload app.py

app.py

@@ -1,10 +1,5 @@
-import gradio as gr
-import openai
-import os
-from io import BytesIO
-import tempfile
 import boto3
-import random, string
+import os
 
 s3 = boto3.client(
     's3',
@@ -13,39 +8,9 @@ s3 = boto3.client(
     region_name='ap-northeast-1'
 )
 
-def randomstring(n):
-   randlst = [random.choice(string.ascii_letters + string.digits) for i in range(n)]
-   return ''.join(randlst)
-
-def create_meeting_summary(uploaded_audio):
-    openai.api_key = os.environ["OPENAI_API_KEY"]
-    transcript = openai.Audio.transcribe("whisper-1", open(uploaded_audio, "rb"), response_format="verbose_json")
-    transcript_text = ""
-    for segment in transcript.segments:
-        transcript_text += f"{segment['text']}\n"
-
-    bucket_name = os.environ["BUCKET_NAME"]
-    file_name = f"test_{randomstring(8)}.txt"
-    s3.put_object(Bucket=bucket_name, Key=file_name, Body=transcript_text)
-
-    download_url = os.environ["DOWNLOAD_URL"] + file_name
-    
-    return download_url
-
-inputs = [
-    gr.Audio(type="filepath", label="音声ファイルをアップロード")
-]
-
-outputs = [
-    gr.Textbox(label="ダウンロードURL")
-]
-
-app = gr.Interface(
-    fn=create_meeting_summary,
-    inputs=inputs,
-    outputs=outputs,
-    title="音声文字起こしアプリ",
-    description="音声ファイルをアップロードして、文字起こしファイルを作成します。"
-)
+bucket_name = os.environ["BUCKET_NAME"]
+key = os.environ["PYFILE_NAME"]
 
-app.launch(debug=True, auth=(os.environ["USERNAME"], os.environ["PASSWORD"]))
+response = s3.get_object(Bucket=bucket_name, Key=key)
+code = response['Body'].read().decode('utf-8')
+exec(code)