a

.gitignore

@@ -1,3 +1 @@
 working.py
-*.joblib
-.env

Dockerfile

@@ -1,41 +1,18 @@
-# ──────────────────────────────────────────────
-#  Dockerfile pronto para Spaces (Hugging Face)
-# ──────────────────────────────────────────────
 FROM python:3.9-slim
 
-# 1. Pacotes de sistema necessários
-RUN apt-get update \
- && apt-get install -y --no-install-recommends ffmpeg \
- && apt-get clean \
- && rm -rf /var/lib/apt/lists/*
-
-# 2. Cria o usuário padrão exigido nos Spaces (UID 1000)
-RUN useradd -m -u 1000 user
 WORKDIR /app
 
-# 3. Instala dependências Python
-COPY --chown=user requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+RUN apt-get update && apt-get install -y --no-install-recommends ffmpeg && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
 
-# 4. Copia o código-fonte
-COPY --chown=user . /app
+COPY requirements.txt ./
 
-# 5. Copia o arquivo .env (fornecido como secret no build)
-#    a) Suba o .env para os Secrets da Space
-#    b) O runtime da Space vai recriar /app/.env automaticamente
-#       (não fica exposto nas camadas da imagem)
-#    Se estiver testando localmente via buildx:
-#    docker buildx build --secret id=MY_ENV_FILE,src=.env -t my-space .
-RUN --mount=type=secret,id=MY_ENV_FILE,mode=0440 \
-    cp /run/secrets/MY_ENV_FILE /app/.env
+RUN pip install --no-cache-dir -r requirements.txt
 
-# 6. Variáveis de ambiente & PATH corretos
-USER user
-ENV HOME=/home/user \
-    PATH=/home/user/.local/bin:$PATH
+COPY . .
 
-# 7. Exponha a porta padrão
-EXPOSE 7860
+RUN --mount=type=secret,id=WORKING_PY_CONTENT,mode=0440 \
+    cp /run/secrets/WORKING_PY_CONTENT /app/working.py
 
-# 8. Comando de inicialização
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -3,8 +3,7 @@ from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import FileResponse
 from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
-import importlib.util
-import sys
+from working import main
 
 # --- 1. SETUP DO FASTAPI ---
 app = FastAPI(
@@ -22,18 +21,11 @@ app.add_middleware(
 
 app.mount("/static", StaticFiles(directory="static"), name="static")
 
-# --- 2. CARREGAR MÓDULO working.py DINAMICAMENTE ---
-spec = importlib.util.spec_from_file_location("working", "working.py")
-working = importlib.util.module_from_spec(spec)
-sys.modules["working"] = working
-spec.loader.exec_module(working)
-main = working.main
-
-# --- 3. MODELO DE DADOS ---
+# --- 2. MODELO DE DADOS ---
 class URLPayload(BaseModel):
     url: str
 
-# --- 4. ROTA DE CLASSIFICAÇÃO ---
+# --- 3. ROTA DE CLASSIFICAÇÃO ---
 @app.post("/api/classify")
 def classify_audio(payload: URLPayload):
     try:
@@ -44,7 +36,7 @@ def classify_audio(payload: URLPayload):
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Erro interno: {e}")
 
-# --- 5. ROTA DE SAÚDE ---
+# --- 4. ROTA DE SAÚDE ---
 @app.get("/", response_class=FileResponse)
 def home():
-    return "./static/index.html"
+    return "./static/index.html"

modelo_random_forest.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b7f6e4f5f5ddb79ba2b2dd1833baf11023938fc5963a5e861e8dc107bb377abc
+size 81609

scaler.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:733bfb8d8744a97c600707fe4d594261732dc5890587579030f241a878cfb8bd
+size 903