From 11e41e44be33afd5c8a19ed6b8513574a7934926 Mon Sep 17 00:00:00 2001
From: admtracksteel <admtracksteel@gmail.com>
Date: Tue, 24 Mar 2026 11:24:05 +0000
Subject: [PATCH] =?UTF-8?q?=F0=9F=9A=80=20Auto-deploy:=20BotVPS=20atualiza?=
 =?UTF-8?q?do=20em=2024/03/2026=2011:24:05?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 ai_agent.py | 31 +++++++------------------------
 1 file changed, 7 insertions(+), 24 deletions(-)

diff --git a/ai_agent.py b/ai_agent.py
index 7c05e2a..09b7a78 100644
--- a/ai_agent.py
+++ b/ai_agent.py
@@ -4,34 +4,17 @@ import httpx
 import asyncio
 import json
 from tools import AVAILABLE_TOOLS
+from llm_providers import call_llm, get_available_models, get_planner_llm
 from config import get_config
 
 async def get_llm_response_async(prompt: str, provider: str, cfg: dict) -> str:
-    """Invoca o provedor de LLM configurado (async)."""
-    async with httpx.AsyncClient(timeout=60) as client:
-        if provider == "gemini":
-            api_key = cfg.get("gemini_api_key") or os.getenv("GEMINI_API_KEY")
-            url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={api_key}"
-            payload = {"contents": [{"parts": [{"text": prompt}]}]}
-            try:
-                res = await client.post(url, json=payload)
-                if res.status_code == 200:
-                    data = res.json()
-                    return data["candidates"][0]["content"]["parts"][0]["text"]
-                return f"Erro Gemini: {res.text}"
-            except Exception as e: return f"Erro Gemini: {e}"
-        
-        elif provider == "ollama":
-            host = os.getenv("OLLAMA_HOST", "http://ollama:11434")
-            model = os.getenv("OLLAMA_MODEL", "llama3.2:1b")
-            try:
-                res = await client.post(f"{host}/api/generate", json={
-                    "model": model, "prompt": prompt, "stream": False
-                })
-                return res.json().get("response", "")
-            except Exception as e: return f"Erro Ollama: {e}"
+    """Invoca o provedor de LLM centralizado em llm_providers."""
+    # Garante o modelo gemini-2.5-flash como padrão para o agente Legado
+    model = cfg.get("model") or "gemini-2.5-flash"
+    if provider == "ollama":
+        model = os.getenv("OLLAMA_MODEL", "llama3.2:1b")
     
-    return "Provedor desconhecido."
+    return await call_llm(provider, model, prompt)
 
 def query_agent(prompt: str, override_provider=None, chat_history=None) -> str:
     """Wrapper síncrono para query_agent_async."""