Update app.py

app.py

@@ -1,10 +1,12 @@
 import os
 import json
 import firebase_admin
+import requests
 from firebase_admin import credentials, firestore
 from flask import Flask, request, jsonify
 from huggingface_hub import InferenceClient
 
+
 app = Flask(__name__)
 
 # =============================
@@ -91,24 +93,40 @@ def analyze():
             return jsonify({"error": "Campo 'text' é obrigatório"}), 400
 
         text = data["text"]
-
         print(f"\n🧠 Recebido texto para análise: {text}\n")
 
-        # Chamada segura via API genérica
-        response = client.post(
-            json={"inputs": text},
-            model="pysentimiento/robertuito-emotion-analysis",
-            task="text-classification"
-        )
+        # =============================
+        # Chamada direta à API do Hugging Face
+        # =============================
+        HF_MODEL = "pysentimiento/robertuito-emotion-analysis"
+        HF_URL = f"https://api-inference.huggingface.co/models/{HF_MODEL}"
+
+        headers = {
+            "Authorization": f"Bearer {HF_TOKEN}",
+            "Content-Type": "application/json"
+        }
+
+        payload = {"inputs": text}
+
+        response = requests.post(HF_URL, headers=headers, json=payload)
+        response.raise_for_status()
+
+        result_json = response.json()
+        print(f"📩 Resposta bruta do modelo:\n{json.dumps(result_json, indent=2, ensure_ascii=False)}\n")
 
-        print(f"📩 Resposta bruta do modelo:\n{json.dumps(response, indent=2, ensure_ascii=False)}\n")
+        # Alguns modelos retornam [ [ {label, score}, ... ] ]
+        # Outros apenas [ {label, score}, ... ]
+        if isinstance(result_json, list) and isinstance(result_json[0], list):
+            result_json = result_json[0]
 
-        if not isinstance(response, list) or len(response) == 0:
-            raise ValueError("Resposta inesperada da API do Hugging Face")
+        if not isinstance(result_json, list) or len(result_json) == 0:
+            raise ValueError("Resposta inesperada da API Hugging Face.")
 
-        # Processa probabilidades
+        # =============================
+        # Processamento das emoções
+        # =============================
         probabilities = {}
-        for item in response:
+        for item in result_json:
             label = item.get("label", "").lower()
             score = round(float(item.get("score", 0.0)), 4)
             emotion_pt = map_emotion(label, score)