chore: updated gemini models in docs (#556)

Author: rapid-killer-9

packages/toolbox-core/README.md

@@ -301,7 +301,7 @@ async def main():
     async with ToolboxClient("http://127.0.0.1:5000") as toolbox:
         tools = await toolbox.load_toolset()
         wrapped_tools = [StructuredTool.from_function(tool, parse_docstring=True) for tool in tools]
-        model_with_tools = ChatVertexAI(model="gemini-2.5-flash").bind_tools(wrapped_tools)
+        model_with_tools = ChatVertexAI(model="gemini-3-flash-preview").bind_tools(wrapped_tools)
         tool_node = ToolNode(wrapped_tools)
 
         def call_agent(state: State):

packages/toolbox-langchain/README.md

@@ -63,7 +63,7 @@ from langgraph.prebuilt import create_react_agent
 async with ToolboxClient("http://127.0.0.1:5000") as toolbox:
     tools = toolbox.load_toolset()
 
-    model = ChatVertexAI(model="gemini-2.0-flash-001")
+    model = ChatVertexAI(model="gemini-3-flash-preview")
     agent = create_react_agent(model, tools)
 
     prompt = "How's the weather today?"
@@ -173,7 +173,7 @@ input. Include tools loaded from the Toolbox SDK in the agent's toolkit:
 ```py
 from langchain_google_vertexai import ChatVertexAI
 
-model = ChatVertexAI(model="gemini-2.0-flash-001")
+model = ChatVertexAI(model="gemini-3-flash-preview")
 
 # Initialize agent with tools
 agent = model.bind_tools(tools)
@@ -203,7 +203,7 @@ def call_model(state: MessagesState):
     response = model.invoke(messages)
     return {"messages": [response]}  # Return a list to add to existing messages
 
-model = ChatVertexAI(model="gemini-2.0-flash-001")
+model = ChatVertexAI(model="gemini-3-flash-preview")
 builder = StateGraph(MessagesState)
 tool_node = ToolNode(tools)
 

packages/toolbox-llamaindex/README.md

@@ -66,7 +66,7 @@ async def run_agent():
     tools = toolbox.load_toolset()
 
     vertex_model = GoogleGenAI(
-        model="gemini-2.0-flash-001",
+        model="gemini-3-flash-preview",
         vertexai_config={"project": "project-id", "location": "us-central1"},
     )
     agent = AgentWorkflow.from_tools_or_functions(
@@ -179,7 +179,7 @@ from llama_index.llms.google_genai import GoogleGenAI
 from llama_index.core.agent.workflow import AgentWorkflow
 
 vertex_model = GoogleGenAI(
-    model="gemini-2.0-flash-001",
+    model="gemini-3-flash-preview",
     vertexai_config={"project": "project-id", "location": "us-central1"},
 )
 
@@ -205,7 +205,7 @@ from llama_index.core.workflow import Context
 from llama_index.llms.google_genai import GoogleGenAI
 
 vertex_model = GoogleGenAI(
-    model="gemini-2.0-flash-001",
+    model="gemini-3-flash-preview",
     vertexai_config={"project": "project-id", "location": "us-central1"},
 )
 agent = AgentWorkflow.from_tools_or_functions(