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Inlcude tag for sample agents

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Harsh Jha
2025-08-19 15:26:17 +05:30
parent fd9b0ea55b
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docs/en/getting-started/local_quickstart.md
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@@ -354,306 +354,16 @@ pip install google-genai
code to create an agent:
{{< tabpane persist=header >}}
{{< tab header="ADK" lang="python" >}}
from google.adk.agents import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.adk.artifacts.in_memory_artifact_service import InMemoryArtifactService
from google.genai import types
from toolbox_core import ToolboxSyncClient
import asyncio
import os
# TODO(developer): replace this with your Google API key
os.environ['GOOGLE_API_KEY'] = 'your-api-key'
async def main():
with ToolboxSyncClient("<http://127.0.0.1:5000>") as toolbox_client:
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel ids while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
root_agent = Agent(
model='gemini-2.0-flash-001',
name='hotel_agent',
description='A helpful AI assistant.',
instruction=prompt,
tools=toolbox_client.load_toolset("my-toolset"),
)
session_service = InMemorySessionService()
artifacts_service = InMemoryArtifactService()
session = await session_service.create_session(
state={}, app_name='hotel_agent', user_id='123'
)
runner = Runner(
app_name='hotel_agent',
agent=root_agent,
artifact_service=artifacts_service,
session_service=session_service,
)
queries = [
"Find hotels in Basel with Basel in its name.",
"Can you book the Hilton Basel for me?",
"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.",
"My check in dates would be from April 10, 2024 to April 19, 2024.",
]
for query in queries:
content = types.Content(role='user', parts=[types.Part(text=query)])
events = runner.run(session_id=session.id,
user_id='123', new_message=content)
responses = (
part.text
for event in events
for part in event.content.parts
if part.text is not None
)
for text in responses:
print(text)
asyncio.run(main())
{{< include "quickstart/python/adk/quickstart.py" >}}
{{< /tab >}}
{{< tab header="LangChain" lang="python" >}}
import asyncio
from langgraph.prebuilt import create_react_agent
# TODO(developer): replace this with another import if needed
from langchain_google_vertexai import ChatVertexAI
# from langchain_google_genai import ChatGoogleGenerativeAI
# from langchain_anthropic import ChatAnthropic
from langgraph.checkpoint.memory import MemorySaver
from toolbox_langchain import ToolboxClient
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel ids while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
queries = [
"Find hotels in Basel with Basel in its name.",
"Can you book the Hilton Basel for me?",
"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.",
"My check in dates would be from April 10, 2024 to April 19, 2024.",
]
async def run_application():
# TODO(developer): replace this with another model if needed
model = ChatVertexAI(model_name="gemini-2.0-flash-001")
# model = ChatGoogleGenerativeAI(model="gemini-2.0-flash-001")
# model = ChatAnthropic(model="claude-3-5-sonnet-20240620")
# Load the tools from the Toolbox server
async with ToolboxClient("http://127.0.0.1:5000") as client:
tools = await client.aload_toolset()
agent = create_react_agent(model, tools, checkpointer=MemorySaver())
config = {"configurable": {"thread_id": "thread-1"}}
for query in queries:
inputs = {"messages": [("user", prompt + query)]}
response = agent.invoke(inputs, stream_mode="values", config=config)
print(response["messages"][-1].content)
asyncio.run(run_application())
{{< include "quickstart/python/langchain/quickstart.py" >}}
{{< /tab >}}
{{< tab header="LlamaIndex" lang="python" >}}
import asyncio
import os
from llama_index.core.agent.workflow import AgentWorkflow
from llama_index.core.workflow import Context
# TODO(developer): replace this with another import if needed
from llama_index.llms.google_genai import GoogleGenAI
# from llama_index.llms.anthropic import Anthropic
from toolbox_llamaindex import ToolboxClient
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel ids while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
queries = [
"Find hotels in Basel with Basel in its name.",
"Can you book the Hilton Basel for me?",
"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.",
"My check in dates would be from April 10, 2024 to April 19, 2024.",
]
async def run_application():
# TODO(developer): replace this with another model if needed
llm = GoogleGenAI(
model="gemini-2.0-flash-001",
vertexai_config={"project": "project-id", "location": "us-central1"},
)
# llm = GoogleGenAI(
# api_key=os.getenv("GOOGLE_API_KEY"),
# model="gemini-2.0-flash-001",
# )
# llm = Anthropic(
# model="claude-3-7-sonnet-latest",
# api_key=os.getenv("ANTHROPIC_API_KEY")
# )
# Load the tools from the Toolbox server
async with ToolboxClient("http://127.0.0.1:5000") as client:
tools = await client.aload_toolset()
agent = AgentWorkflow.from_tools_or_functions(
tools,
llm=llm,
system_prompt=prompt,
)
ctx = Context(agent)
for query in queries:
response = await agent.run(user_msg=query, ctx=ctx)
print(f"---- {query} ----")
print(str(response))
asyncio.run(run_application())
{{< include "quickstart/python/llamaindex/quickstart.py" >}}
{{< /tab >}}
{{< tab header="Core" lang="python" >}}
import asyncio
from google import genai
from google.genai.types import (
Content,
FunctionDeclaration,
GenerateContentConfig,
Part,
Tool,
)
from toolbox_core import ToolboxClient
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel id while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
queries = [
"Find hotels in Basel with Basel in its name.",
"Please book the hotel Hilton Basel for me.",
"This is too expensive. Please cancel it.",
"Please book Hyatt Regency for me",
"My check in dates for my booking would be from April 10, 2024 to April 19, 2024.",
]
async def run_application():
async with ToolboxClient("<http://127.0.0.1:5000>") as toolbox_client:
# The toolbox_tools list contains Python callables (functions/methods) designed for LLM tool-use
# integration. While this example uses Google's genai client, these callables can be adapted for
# various function-calling or agent frameworks. For easier integration with supported frameworks
# (https://github.com/googleapis/mcp-toolbox-python-sdk/tree/main/packages), use the
# provided wrapper packages, which handle framework-specific boilerplate.
toolbox_tools = await toolbox_client.load_toolset("my-toolset")
genai_client = genai.Client(
vertexai=True, project="project-id", location="us-central1"
)
genai_tools = [
Tool(
function_declarations=[
FunctionDeclaration.from_callable_with_api_option(callable=tool)
]
)
for tool in toolbox_tools
]
history = []
for query in queries:
user_prompt_content = Content(
role="user",
parts=[Part.from_text(text=query)],
)
history.append(user_prompt_content)
response = genai_client.models.generate_content(
model="gemini-2.0-flash-001",
contents=history,
config=GenerateContentConfig(
system_instruction=prompt,
tools=genai_tools,
),
)
history.append(response.candidates[0].content)
function_response_parts = []
for function_call in response.function_calls:
fn_name = function_call.name
# The tools are sorted alphabetically
if fn_name == "search-hotels-by-name":
function_result = await toolbox_tools[3](**function_call.args)
elif fn_name == "search-hotels-by-location":
function_result = await toolbox_tools[2](**function_call.args)
elif fn_name == "book-hotel":
function_result = await toolbox_tools[0](**function_call.args)
elif fn_name == "update-hotel":
function_result = await toolbox_tools[4](**function_call.args)
elif fn_name == "cancel-hotel":
function_result = await toolbox_tools[1](**function_call.args)
else:
raise ValueError("Function name not present.")
function_response = {"result": function_result}
function_response_part = Part.from_function_response(
name=function_call.name,
response=function_response,
)
function_response_parts.append(function_response_part)
if function_response_parts:
tool_response_content = Content(role="tool", parts=function_response_parts)
history.append(tool_response_content)
response2 = genai_client.models.generate_content(
model="gemini-2.0-flash-001",
contents=history,
config=GenerateContentConfig(
tools=genai_tools,
),
)
final_model_response_content = response2.candidates[0].content
history.append(final_model_response_content)
print(response2.text)
asyncio.run(run_application())
{{< include "quickstart/python/core/quickstart.py" >}}
{{< /tab >}}
{{< /tabpane >}}

70
docs/en/getting-started/quickstart/python/adk/quickstart.py Normal file
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@@ -0,0 +1,70 @@
from google.adk.agents import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.adk.artifacts.in_memory_artifact_service import InMemoryArtifactService
from google.genai import types
from toolbox_core import ToolboxSyncClient
import asyncio
import os
# TODO(developer): replace this with your Google API key
os.environ['GOOGLE_API_KEY'] = 'your-api-key'
async def main():
with ToolboxSyncClient("<http://127.0.0.1:5000>") as toolbox_client:
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel ids while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
root_agent = Agent(
model='gemini-2.0-flash-001',
name='hotel_agent',
description='A helpful AI assistant.',
instruction=prompt,
tools=toolbox_client.load_toolset("my-toolset"),
)
session_service = InMemorySessionService()
artifacts_service = InMemoryArtifactService()
session = await session_service.create_session(
state={}, app_name='hotel_agent', user_id='123'
)
runner = Runner(
app_name='hotel_agent',
agent=root_agent,
artifact_service=artifacts_service,
session_service=session_service,
)
queries = [
"Find hotels in Basel with Basel in its name.",
"Can you book the Hilton Basel for me?",
"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.",
"My check in dates would be from April 10, 2024 to April 19, 2024.",
]
for query in queries:
content = types.Content(role='user', parts=[types.Part(text=query)])
events = runner.run(session_id=session.id,
user_id='123', new_message=content)
responses = (
part.text
for event in events
for part in event.content.parts
if part.text is not None
)
for text in responses:
print(text)
asyncio.run(main())

108
docs/en/getting-started/quickstart/python/core/quickstart.py Normal file
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@@ -0,0 +1,108 @@
import asyncio
from google import genai
from google.genai.types import (
Content,
FunctionDeclaration,
GenerateContentConfig,
Part,
Tool,
)
from toolbox_core import ToolboxClient
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel id while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
queries = [
"Find hotels in Basel with Basel in its name.",
"Please book the hotel Hilton Basel for me.",
"This is too expensive. Please cancel it.",
"Please book Hyatt Regency for me",
"My check in dates for my booking would be from April 10, 2024 to April 19, 2024.",
]
async def run_application():
async with ToolboxClient("<http://127.0.0.1:5000>") as toolbox_client:
# The toolbox_tools list contains Python callables (functions/methods) designed for LLM tool-use
# integration. While this example uses Google's genai client, these callables can be adapted for
# various function-calling or agent frameworks. For easier integration with supported frameworks
# (https://github.com/googleapis/mcp-toolbox-python-sdk/tree/main/packages), use the
# provided wrapper packages, which handle framework-specific boilerplate.
toolbox_tools = await toolbox_client.load_toolset("my-toolset")
genai_client = genai.Client(
vertexai=True, project="project-id", location="us-central1"
)
genai_tools = [
Tool(
function_declarations=[
FunctionDeclaration.from_callable_with_api_option(callable=tool)
]
)
for tool in toolbox_tools
]
history = []
for query in queries:
user_prompt_content = Content(
role="user",
parts=[Part.from_text(text=query)],
)
history.append(user_prompt_content)
response = genai_client.models.generate_content(
model="gemini-2.0-flash-001",
contents=history,
config=GenerateContentConfig(
system_instruction=prompt,
tools=genai_tools,
),
)
history.append(response.candidates[0].content)
function_response_parts = []
for function_call in response.function_calls:
fn_name = function_call.name
# The tools are sorted alphabetically
if fn_name == "search-hotels-by-name":
function_result = await toolbox_tools[3](**function_call.args)
elif fn_name == "search-hotels-by-location":
function_result = await toolbox_tools[2](**function_call.args)
elif fn_name == "book-hotel":
function_result = await toolbox_tools[0](**function_call.args)
elif fn_name == "update-hotel":
function_result = await toolbox_tools[4](**function_call.args)
elif fn_name == "cancel-hotel":
function_result = await toolbox_tools[1](**function_call.args)
else:
raise ValueError("Function name not present.")
function_response = {"result": function_result}
function_response_part = Part.from_function_response(
name=function_call.name,
response=function_response,
)
function_response_parts.append(function_response_part)
if function_response_parts:
tool_response_content = Content(role="tool", parts=function_response_parts)
history.append(tool_response_content)
response2 = genai_client.models.generate_content(
model="gemini-2.0-flash-001",
contents=history,
config=GenerateContentConfig(
tools=genai_tools,
),
)
final_model_response_content = response2.candidates[0].content
history.append(final_model_response_content)
print(response2.text)
asyncio.run(run_application())

52
docs/en/getting-started/quickstart/python/langchain/quickstart.py Normal file
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@@ -0,0 +1,52 @@
import asyncio
from langgraph.prebuilt import create_react_agent
# TODO(developer): replace this with another import if needed
from langchain_google_vertexai import ChatVertexAI
# from langchain_google_genai import ChatGoogleGenerativeAI
# from langchain_anthropic import ChatAnthropic
from langgraph.checkpoint.memory import MemorySaver
from toolbox_langchain import ToolboxClient
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel ids while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
queries = [
"Find hotels in Basel with Basel in its name.",
"Can you book the Hilton Basel for me?",
"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.",
"My check in dates would be from April 10, 2024 to April 19, 2024.",
]
async def run_application():
# TODO(developer): replace this with another model if needed
model = ChatVertexAI(model_name="gemini-2.0-flash-001")
# model = ChatGoogleGenerativeAI(model="gemini-2.0-flash-001")
# model = ChatAnthropic(model="claude-3-5-sonnet-20240620")
# Load the tools from the Toolbox server
async with ToolboxClient("http://127.0.0.1:5000") as client:
tools = await client.aload_toolset()
agent = create_react_agent(model, tools, checkpointer=MemorySaver())
config = {"configurable": {"thread_id": "thread-1"}}
for query in queries:
inputs = {"messages": [("user", prompt + query)]}
response = agent.invoke(inputs, stream_mode="values", config=config)
print(response["messages"][-1].content)
asyncio.run(run_application())

63
docs/en/getting-started/quickstart/python/llamaindex/quickstart.py Normal file
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@@ -0,0 +1,63 @@
import asyncio
import os
from llama_index.core.agent.workflow import AgentWorkflow
from llama_index.core.workflow import Context
# TODO(developer): replace this with another import if needed
from llama_index.llms.google_genai import GoogleGenAI
# from llama_index.llms.anthropic import Anthropic
from toolbox_llamaindex import ToolboxClient
prompt = """
You're a helpful hotel assistant. You handle hotel searching, booking and
cancellations. When the user searches for a hotel, mention it's name, id,
location and price tier. Always mention hotel ids while performing any
searches. This is very important for any operations. For any bookings or
cancellations, please provide the appropriate confirmation. Be sure to
update checkin or checkout dates if mentioned by the user.
Don't ask for confirmations from the user.
"""
queries = [
"Find hotels in Basel with Basel in its name.",
"Can you book the Hilton Basel for me?",
"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.",
"My check in dates would be from April 10, 2024 to April 19, 2024.",
]
async def run_application():
# TODO(developer): replace this with another model if needed
llm = GoogleGenAI(
model="gemini-2.0-flash-001",
vertexai_config={"project": "project-id", "location": "us-central1"},
)
# llm = GoogleGenAI(
# api_key=os.getenv("GOOGLE_API_KEY"),
# model="gemini-2.0-flash-001",
# )
# llm = Anthropic(
# model="claude-3-7-sonnet-latest",
# api_key=os.getenv("ANTHROPIC_API_KEY")
# )
# Load the tools from the Toolbox server
async with ToolboxClient("http://127.0.0.1:5000") as client:
tools = await client.aload_toolset()
agent = AgentWorkflow.from_tools_or_functions(
tools,
llm=llm,
system_prompt=prompt,
)
ctx = Context(agent)
for query in queries:
response = await agent.run(user_msg=query, ctx=ctx)
print(f"---- {query} ----")
print(str(response))
asyncio.run(run_application())