feat: atualizando valor do gemini 2.5 pro

_utils/gerar_documento_utils/GerarDocumento.py

@@ -171,7 +171,7 @@ class GerarDocumentoUtils:
             )
         elif llm_ultimas_requests == "gemini-2.5-pro":
             llm = llm_instance.google_gemini(
-                "gemini-2.5-pro-preview-05-06", temperature=self.temperature
+                "gemini-2.5-pro-preview-06-05", temperature=self.temperature
             )
         elif llm_ultimas_requests == "gemini-2.5-flash":
             llm = llm_instance.google_gemini(

_utils/gerar_documento_utils/llm_calls.py

@@ -2,7 +2,7 @@ import os
 from typing import Literal, cast
 
 from pydantic import SecretStr
-from _utils.langchain_utils.LLM_class import LLM
+from _utils.langchain_utils.LLM_class import LLM, Google_llms
 from setup.environment import default_model
 from langchain_core.messages import HumanMessage
 from langchain_openai import ChatOpenAI
@@ -59,9 +59,7 @@ def gpt_answer(
 
 async def agemini_answer(
     prompt,
-    model: Literal[
-        "gemini-2.5-pro-preview-05-06", "gemini-2.0-flash", "gemini-2.0-flash-lite"
-    ] = "gemini-2.0-flash",
+    model: Google_llms = "gemini-2.0-flash",
     temperature=0.4,
 ) -> str:
     gemini = llm.google_gemini(model, temperature)

_utils/langchain_utils/LLM_class.py

@@ -11,7 +11,7 @@ google_api_key = cast(str, os.environ.get("GOOGLE_API_KEY_PEIXE"))
 open_ai_token = cast(str, os.environ.get("OPENAI_API_KEY"))
 
 Google_llms = Literal[
-    "gemini-2.5-pro-preview-05-06",
+    "gemini-2.5-pro-preview-06-05",
     "gemini-2.0-flash",
     "gemini-2.0-flash-lite",
     "gemini-2.5-flash-preview-04-17",