chore: Update Gemini model to a stable version (#263)

* chore: Update Gemini model to a stable version

* chore(toolbox-llamaindex): Update project ID in README

Author: anubhav756

packages/toolbox-core/README.md

@@ -202,7 +202,7 @@ from langchain.tools import StructuredTool
 toolbox = ToolboxClient("http://127.0.0.1:5000")
 tools = await toolbox.load_toolset()
 wrapped_tools = [StructuredTool.from_function(tool, parse_docstring=True) for tool in tools]
-model_with_tools = ChatVertexAI(model="gemini-1.5-pro-002").bind_tools(wrapped_tools)
+model_with_tools = ChatVertexAI(model="gemini-2.0-flash-001").bind_tools(wrapped_tools)
 
 def call_model(state: MessagesState):
     messages = state["messages"]

packages/toolbox-langchain/README.md

@@ -54,7 +54,7 @@ from langgraph.prebuilt import create_react_agent
 toolbox = ToolboxClient("http://127.0.0.1:5000")
 tools = toolbox.load_toolset()
 
-model = ChatVertexAI(model="gemini-1.5-pro-002")
+model = ChatVertexAI(model="gemini-2.0-flash-001")
 agent = create_react_agent(model, tools)
 
 prompt = "How's the weather today?"
@@ -110,7 +110,7 @@ input. Include tools loaded from the Toolbox SDK in the agent's toolkit:
 ```py
 from langchain_google_vertexai import ChatVertexAI
 
-model = ChatVertexAI(model="gemini-1.5-pro-002")
+model = ChatVertexAI(model="gemini-2.0-flash-001")
 
 # Initialize agent with tools
 agent = model.bind_tools(tools)
@@ -140,7 +140,7 @@ def call_model(state: MessagesState):
     response = model.invoke(messages)
     return {"messages": [response]}  # Return a list to add to existing messages
 
-model = ChatVertexAI(model="gemini-1.5-pro-002")
+model = ChatVertexAI(model="gemini-2.0-flash-001")
 builder = StateGraph(MessagesState)
 tool_node = ToolNode(tools)
 

packages/toolbox-llamaindex/README.md

@@ -57,7 +57,7 @@ async def run_agent():
   tools = toolbox.load_toolset()
 
   vertex_model = GoogleGenAI(
-      model="gemini-1.5-pro",
+      model="gemini-2.0-flash-001",
       vertexai_config={"project": "project-id", "location": "us-central1"},
   )
   agent = AgentWorkflow.from_tools_or_functions(
@@ -116,7 +116,7 @@ from llama_index.llms.google_genai import GoogleGenAI
 from llama_index.core.agent.workflow import AgentWorkflow
 
 vertex_model = GoogleGenAI(
-    model="gemini-1.5-pro",
+    model="gemini-2.0-flash-001",
     vertexai_config={"project": "project-id", "location": "us-central1"},
 )
 
@@ -142,8 +142,8 @@ from llama_index.core.workflow import Context
 from llama_index.llms.google_genai import GoogleGenAI
 
 vertex_model = GoogleGenAI(
-    model="gemini-1.5-pro",
-    vertexai_config={"project": "twisha-dev", "location": "us-central1"},
+    model="gemini-2.0-flash-001",
+    vertexai_config={"project": "project-id", "location": "us-central1"},
 )
 agent = AgentWorkflow.from_tools_or_functions(
     tools,
@@ -321,4 +321,4 @@ async def main():
 
 if __name__ == "__main__":
     asyncio.run(main())
-```
+```