Update app.py

app.py

@@ -1,73 +1,80 @@
 import os
-import requests
-from flask import Flask, request, jsonify
-from flask_cors import CORS
+import json
 import firebase_admin
 from firebase_admin import credentials, firestore
+from flask import Flask, request, jsonify
 from dotenv import load_dotenv
+from huggingface_hub import InferenceClient
 
-# Carregar variáveis de ambiente
+# Carregar variáveis do .env
 load_dotenv()
 
 app = Flask(__name__)
-CORS(app)
 
-# -----------------------------
-# Firebase Setup
-# -----------------------------
+# === Inicialização segura do Firebase ===
 if not firebase_admin._apps:
-    cred = credentials.Certificate("firebase_key.json")  # coloque a chave no container
-    firebase_admin.initialize_app(cred)
+    firebase_key = os.getenv("FIREBASE_KEY")
+
+    if not firebase_key:
+        raise RuntimeError("❌ Variável FIREBASE_KEY não encontrada no ambiente.")
 
-db = firestore.client()
+    try:
+        cred_dict = json.loads(firebase_key)
+        cred = credentials.Certificate(cred_dict)
+        firebase_admin.initialize_app(cred)
+        db = firestore.client()
+        print("✅ Firebase conectado com sucesso.")
+    except Exception as e:
+        print(f"❌ Erro ao inicializar Firebase: {e}")
+        db = None
 
-# -----------------------------
-# HuggingFace API
-# -----------------------------
-HF_API_URL = os.getenv("HF_API_URL", "https://api-inference.huggingface.co/models/YOUR_MODEL")
-HF_API_KEY = os.getenv("HF_API_KEY")
+# === Configuração do modelo da Hugging Face ===
+HF_TOKEN = os.getenv("HF_TOKEN")
+if not HF_TOKEN:
+    raise RuntimeError("❌ Variável HF_TOKEN não encontrada no ambiente.")
 
-headers = {"Authorization": f"Bearer {HF_API_KEY}"}
+client = InferenceClient(token=HF_TOKEN)
 
+# === Rota de teste ===
 @app.route("/")
-def home():
-    return jsonify({"status": "ok", "message": "MindVoice API online!"})
+def index():
+    return jsonify({"status": "online", "message": "API Flask funcionando!"})
 
+# === Rota principal de análise de emoção ===
 @app.route("/analyze", methods=["POST"])
 def analyze():
-    """
-    Recebe um áudio ou texto e envia para HuggingFace.
-    Exemplo de payload:
-    {
-        "text": "Estou feliz hoje"
-    }
-    """
     try:
         data = request.get_json()
-        if not data:
-            return jsonify({"error": "Payload vazio"}), 400
+        if not data or "text" not in data:
+            return jsonify({"error": "Campo 'text' é obrigatório"}), 400
 
-        # Caso seja texto
-        if "text" in data:
-            payload = {"inputs": data["text"]}
-        else:
-            return jsonify({"error": "Faltando campo 'text'"}), 400
+        text = data["text"]
 
-        response = requests.post(HF_API_URL, headers=headers, json=payload, timeout=60)
-        result = response.json()
+        # Envia texto para Hugging Face
+        response = client.text_classification(
+            model="SamLowe/roberta-base-go_emotions",
+            inputs=text,
+        )
 
-        # Salvar no Firestore
-        db.collection("insights").add({
-            "text": data["text"],
-            "result": result,
-        })
+        emotion = response[0]["label"]
+        score = round(response[0]["score"], 4)
+
+        result = {"emotion": emotion, "score": score}
+
+        # Armazena no Firestore
+        if db:
+            db.collection("emotions").add(result)
+
+        return jsonify(result)
 
-        return jsonify({"analysis": result})
     except Exception as e:
+        print(f"❌ Erro na rota /analyze: {e}")
         return jsonify({"error": str(e)}), 500
 
 
 if __name__ == "__main__":
-    port = int(os.getenv("PORT", 8080))
-    app.run(host="0.0.0.0", port=port, debug=True)
+    port = int(os.environ.get("PORT", 8080))
+    # Importante: host='0.0.0.0' para acessível no container
+    app.run(host="0.0.0.0", port=port, debug=False)
+