Create app.py

app.py

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+import os
+import requests
+import uvicorn
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+from faster_whisper import WhisperModel
+from moviepy.editor import ImageClip, AudioFileClip, TextClip, CompositeVideoClip
+
+# Inicializa a API
+app = FastAPI()
+
+# Modelo de dados que esperamos receber do GAS
+class VideoRequest(BaseModel):
+    image_url: str
+    audio_url: str
+
+# --- Funções Auxiliares ---
+
+def download_file(url, filename):
+    """Baixa o arquivo da URL e salva localmente"""
+    response = requests.get(url, stream=True)
+    if response.status_code == 200:
+        with open(filename, 'wb') as f:
+            for chunk in response.iter_content(1024):
+                f.write(chunk)
+    else:
+        raise Exception(f"Erro ao baixar {url}")
+
+def criar_video_logica(imagem_path, audio_path, output_path):
+    """A lógica de edição (Whisper + MoviePy)"""
+    print("Carregando modelo Whisper...")
+    model = WhisperModel("tiny", device="cpu", compute_type="int8")
+    segments, _ = model.transcribe(audio_path, language="pt")
+
+    text_clips = []
+    # Configuração visual da legenda
+    font_settings = {
+        "fontsize": 30, "color": 'white', "font": 'Arial-Bold',
+        "stroke_color": 'black', "stroke_width": 2, "method": 'caption',
+        "size": (800, None)
+    }
+
+    print("Gerando legendas...")
+    for segment in segments:
+        txt_clip = TextClip(segment.text.strip(), **font_settings)
+        txt_clip = txt_clip.set_start(segment.start).set_duration(segment.end - segment.start)
+        txt_clip = txt_clip.set_position(('center', 'bottom'))
+        text_clips.append(txt_clip)
+
+    audio_clip = AudioFileClip(audio_path)
+    image_clip = ImageClip(imagem_path).set_duration(audio_clip.duration).set_audio(audio_clip)
+    
+    final = CompositeVideoClip([image_clip] + text_clips)
+    
+    print("Renderizando vídeo...")
+    final.write_videofile(output_path, fps=10, codec="libx264", audio_codec="aac", preset="ultrafast", threads=2)
+    return output_path
+
+# --- O Endpoint da API (Onde o GAS conecta) ---
+
+@app.post("/gerar-video")
+async def gerar_video_endpoint(request: VideoRequest):
+    try:
+        # 1. Definir caminhos temporários
+        temp_img = "temp_image.png"
+        temp_audio = "temp_audio.mp3"
+        output_video = "video_final.mp4"
+
+        # 2. Baixar os assets que o GAS mandou os links
+        print(f"Baixando imagem de: {request.image_url}")
+        download_file(request.image_url, temp_img)
+        
+        print(f"Baixando áudio de: {request.audio_url}")
+        download_file(request.audio_url, temp_audio)
+
+        # 3. Rodar a mágica
+        criar_video_logica(temp_img, temp_audio, output_video)
+
+        # 4. Devolver o arquivo pronto para o GAS
+        # O FileResponse envia o arquivo binário na resposta HTTP
+        return FileResponse(output_video, media_type="video/mp4", filename="video_editado.mp4")
+
+    except Exception as e:
+        print(f"Erro: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+# Configuração para rodar no Hugging Face
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)