Update app.py

app.py

@@ -10,7 +10,7 @@ from mistralai import Mistral
 import google.generativeai as genai
 from huggingface_hub import snapshot_download
 
-# --- 1. SEGURANÇA (RATE LIMIT) ---
+# --- 1. SEGURANÇA (ANTI-SPAM) ---
 MAX_REQUESTS_PER_MINUTE = 15
 BLOCK_TIME_SECONDS = 60
 ip_tracker = {}
@@ -40,19 +40,18 @@ mistral_client = Mistral(api_key=os.environ.get("MISTRAL_API_KEY")) if os.enviro
 if os.environ.get("GEMINI_API_KEY"):
     genai.configure(api_key=os.environ.get("GEMINI_API_KEY"))
 
-# --- 3. HELPER (IMAGEM) ---
+# --- 3. HELPER IMAGEM ---
 def encode_image(image_path):
     try:
         with open(image_path, "rb") as image_file:
             return base64.b64encode(image_file.read()).decode('utf-8')
     except: return None
 
-# --- 4. FUNÇÕES DE EXECUÇÃO ---
+# --- 4. EXECUTORES ---
 
 @spaces.GPU(duration=120)
 def run_local_h200(messages):
     global local_model, local_tokenizer
-    
     for m in messages:
         if isinstance(m['content'], list): return "⚠️ Modelo Local não suporta imagens. Use Gemini/Pixtral."
 
@@ -72,7 +71,6 @@ def run_groq(messages, model_id):
     for m in messages:
         if isinstance(m['content'], list): return "⚠️ Groq não suporta imagens. Use Gemini/Pixtral."
     if not groq_client: return "❌ Erro: GROQ_API_KEY ausente."
-    
     clean_msgs = [{"role": m['role'], "content": m['content']} for m in messages]
     try:
         completion = groq_client.chat.completions.create(
@@ -83,7 +81,6 @@ def run_groq(messages, model_id):
 
 def run_mistral(messages, model_id):
     if not mistral_client: return "❌ Erro: MISTRAL_API_KEY ausente."
-    
     formatted_msgs = []
     for m in messages:
         content = m['content']
@@ -99,7 +96,6 @@ def run_mistral(messages, model_id):
                         new_content.append({"type": "image_url", "image_url": f"data:image/jpeg;base64,{b64}"})
                     else: new_content.append(item)
         formatted_msgs.append({"role": m['role'], "content": new_content})
-
     try:
         res = mistral_client.chat.complete(model=model_id, messages=formatted_msgs)
         return res.choices[0].message.content
@@ -110,7 +106,6 @@ def run_gemini(messages, model_id):
     try:
         model = genai.GenerativeModel(model_id)
         chat_history = []
-        
         for m in messages[:-1]:
             role = "user" if m['role'] == "user" else "model"
             parts = []
@@ -144,6 +139,7 @@ def router(message, history, model_selector, request: gr.Request):
     if not check_spam(request):
         return "⛔ BLOQUEADO: Limite de mensagens excedido. Aguarde."
 
+    # Normaliza histórico
     messages = []
     if history:
         for turn in history:
@@ -156,6 +152,7 @@ def router(message, history, model_selector, request: gr.Request):
             elif isinstance(turn, dict):
                 messages.append(turn)
 
+    # Processa mensagem atual
     current_content = []
     if isinstance(message, dict): 
         text = message.get("text", "")
@@ -168,8 +165,7 @@ def router(message, history, model_selector, request: gr.Request):
     else:
         messages.append({"role": "user", "content": str(message)})
 
-    print(f"🔀 Roteando para: {model_selector}")
-
+    # Seleção
     if "Gemini" in model_selector:
         tid = "gemini-1.5-flash"
         if "3.0" in model_selector: tid = "gemini-3.0-pro-preview"
@@ -197,39 +193,50 @@ def router(message, history, model_selector, request: gr.Request):
         
     return "⚠️ Modelo não reconhecido."
 
-# --- 6. INTERFACE (SEM TEMA - CORREÇÃO) ---
-# Berta: Removi theme=gr.themes.Soft() pois sua versão do Gradio não suporta.
+# --- 6. INTERFACE ---
 with gr.Blocks() as demo:
-    gr.Markdown("# 🔀 APIDOST v8: The Arsenal")
+    gr.Markdown("# 🔀 APIDOST v9 (API Bridge Fixed)")
     
+    models_list = [
+        "✨ Google: Gemini 3.0 Pro (Experimental)",
+        "✨ Google: Gemini 2.5 Pro",
+        "✨ Google: Gemini 2.5 Flash",
+        "✨ Google: Gemini 2.0 Flash",
+        "☁️ Groq: GPT OSS 120B (OpenAI) 🆕",
+        "☁️ Groq: GPT OSS 20B (OpenAI) 🆕",
+        "☁️ Groq: Llama 3.3 70B",
+        "🇫🇷 Mistral: Magistral Medium 2509 🆕",
+        "🇫🇷 Mistral: Pixtral Large (Vision) 🖼️",
+        "🇫🇷 Mistral: Large 2512 (Dez/25)",
+        "🇫🇷 Mistral: Codestral 2508",
+        "🔥 Local H200: Qwen 2.5 Coder 32B"
+    ]
+
     with gr.Row():
-        model_dropdown = gr.Dropdown(
-            choices=[
-                "✨ Google: Gemini 3.0 Pro (Experimental)",
-                "✨ Google: Gemini 2.5 Pro",
-                "✨ Google: Gemini 2.5 Flash",
-                "✨ Google: Gemini 2.0 Flash",
-                "☁️ Groq: GPT OSS 120B (OpenAI) 🆕",
-                "☁️ Groq: GPT OSS 20B (OpenAI) 🆕",
-                "☁️ Groq: Llama 3.3 70B",
-                "🇫🇷 Mistral: Magistral Medium 2509 🆕",
-                "🇫🇷 Mistral: Pixtral Large (Vision) 🖼️",
-                "🇫🇷 Mistral: Large 2512 (Dez/25)",
-                "🇫🇷 Mistral: Codestral 2508",
-                "🔥 Local H200: Qwen 2.5 Coder 32B"
-            ],
-            value="🔥 Local H200: Qwen 2.5 Coder 32B",
-            label="Escolha o Cérebro",
-            interactive=True
-        )
+        model_dropdown = gr.Dropdown(choices=models_list, value=models_list[-1], label="Cérebro", interactive=True)
     
+    # 1. Interface Visual (para debug no Space)
     chat = gr.ChatInterface(
         fn=router, 
         additional_inputs=[model_dropdown],
         multimodal=True 
     )
 
+    # 2. PONTE DE API (A CORREÇÃO DO JAVASCRIPT)
+    # Use gr.JSON em vez de gr.State para 'history' para não exigir retorno.
+    # Isso cria a rota "/chat" corretamente.
+    api_bridge = gr.Interface(
+        fn=router,
+        inputs=[
+            gr.MultimodalTextbox(label="message"), 
+            gr.JSON(value=[], label="history"), # <--- O SEGREDO ESTÁ AQUI. JSON aceita lista e não trava.
+            gr.Dropdown(choices=models_list, label="model_selector", value=models_list[-1])
+        ],
+        outputs=[gr.Textbox(label="response")],
+        api_name="chat" # <--- O JavaScript bate nessa porta aqui.
+    )
+
 if __name__ == "__main__":
     try: snapshot_download(repo_id=LOCAL_MODEL_ID)
     except: pass
-    demo.queue().launch()
+    demo.queue(api_open=True).launch(server_name="0.0.0.0", server_port=7860)