The site rendered one language under two names. Tab labels were split 137 `TypeScript` / 53 `Typescript`, with three pages carrying both spellings at once (custom-agents.md 7/7, patterns.md 1/7, function-tools.md 4/1), and the language-support badges were split 67/18 the same way. Because pymdownx.tabbed slugifies tab labels to lowercase, both variants rendered and linked fine, so no link check or build warning ever flagged it -- it was visible only to readers, as two names for one SDK. Every user-visible occurrence is normalized to `TypeScript`, plus the two inconsistencies that turned up while doing it. 80 changed lines, accounted for exactly: 53 tab label === "Typescript" -> === "TypeScript" 18 badge span lst-typescript">Typescript -> TypeScript 3 prose mention cloud-run.md, mcp-tools.md, workflows/patterns.md 2 api-reference/index.md card heading and link text 1 badge div attr title="...Python and Typescript." 1 mkdocs.yml nav Typescript ADK -> TypeScript ADK 1 code fence ```javascript -> ```typescript on a .ts include 1 artifacts/index.md closing summary sentence --- 80 The first six rows are pure casing: 78 lines that differ from their originals by nothing but `Typescript` -> `TypeScript`. The last two are not, and are the reason this is not a `sed`: llm-agents.md:872 fenced `--8<-- ".../capital_agent.ts"` as ```javascript. It was the only javascript-fenced `.ts` include in docs/ (the other 189 TypeScript fences are correct), and it cost that one snippet its TypeScript highlighting. artifacts/index.md:1084 closed the page by naming languages and got the list wrong. It described reaching the artifact methods "using Python's context objects or directly interacting with the `BaseArtifactService` in Java" -- a two-language enumeration at the end of a page that carries Python, TypeScript, Go, Java and Kotlin tabs (11/10/10/10/11), and one that contradicts :556, which correctly names four of them. The enumeration is dropped rather than extended: the sentence now describes the two ways to reach these methods -- through the context object, or through `BaseArtifactService` -- which is what the page actually teaches and does not rot when a sixth language is added. docs/api-reference/index.md is included even though the rest of docs/api-reference/ is generated output that must not be touched. That tree holds 3,140 generated HTML files and exactly one hand-authored page: this one. It is Markdown, it is the only api-reference entry mkdocs.yml lists as `.md` rather than `index.html` (:272, :441), it uses Material `grid cards` and `:fontawesome-*:` shortcodes, and it carries a `CONTRIBUTORS:` note citing issues #1716 and #1717. Its TypeScript card already said "TypeScript" twice in its body text while its heading and link text said "Typescript"; those two are now consistent with the body. No generated file is modified. Not in this change: the broken `SseConnectionParams` sample in mcp-tools.md (docs-ts/p6c-mcp-ts-sample) and the `@google/adk` example version bumps (docs-ts/p6b-example-versions). Only the casing of the prose line above that sample is touched here. Verified: `mkdocs build` exits 0 with an empty warning set on both main and this branch, and the two warning sets are identical. A rendered before/after diff of the whole site shows every `__tabbed_*` id, every tab radio id and every heading anchor unchanged. Zero `=== "Typescript"` and zero `lst-typescript">Typescript` remain anywhere in the repo. Co-authored-by: Amaad Martin <amaadmartin@google.com>
21 KiB
Build a multi-tool agent
This quickstart guides you through installing Agent Development Kit (ADK), setting up a basic agent with multiple tools, and running it locally either in the terminal or in the interactive, browser-based dev UI.
This quickstart assumes a local IDE (VS Code, PyCharm, IntelliJ IDEA, etc.) with Python 3.10+ or Java 17+ and terminal access. This method runs the application entirely on your machine and is recommended for internal development.
1. Set up Environment & Install ADK
=== "Python"
Create & Activate Virtual Environment (Recommended):
```bash
# Create
python3 -m venv .venv
# Activate (each new terminal)
# macOS/Linux: source .venv/bin/activate
# Windows CMD: .venv\Scripts\activate.bat
# Windows PowerShell: .venv\Scripts\Activate.ps1
```
Install ADK:
```bash
pip install google-adk
```
=== "TypeScript"
Create a new project directory, initialize it, and install dependencies:
```bash
mkdir my-adk-agent
cd my-adk-agent
npm init -y
npm install @google/adk @google/adk-devtools
npm install -D typescript
```
Create a `tsconfig.json` file with the following content. This configuration
ensures your project correctly handles modern Node.js modules.
```json title="tsconfig.json"
{
"compilerOptions": {
"target": "es2020",
"module": "nodenext",
"moduleResolution": "nodenext",
"esModuleInterop": true,
"strict": true,
"skipLibCheck": true,
// set to false to allow CommonJS module syntax:
"verbatimModuleSyntax": false
}
}
```
=== "Go"
## Create a new Go module
If you are starting a new project, you can create a new Go module:
```bash
mkdir my-adk-agent
cd my-adk-agent
go mod init example.com/my-agent
```
## Install ADK
To add the ADK to your project, run the following command:
```bash
go get google.golang.org/adk/v2
```
This will add the ADK as a dependency to your `go.mod` file.
=== "Java"
To install ADK Java and set up the environment, see the [Java
Quickstart](/get-started/java/).
=== "Kotlin"
To install ADK Kotlin and set up the environment, see the [Kotlin
Quickstart](/get-started/kotlin/).
2. Create Agent Project
Project structure
=== "Python"
You will need to create the following project structure:
```console
parent_folder/
multi_tool_agent/
__init__.py
agent.py
.env
```
Create the folder `multi_tool_agent`:
```bash
mkdir multi_tool_agent/
```
!!! info "Note for Windows users"
When using ADK on Windows for the next few steps, we recommend creating
Python files using File Explorer or an IDE because the following commands
(`mkdir`, `echo`) typically generate files with null bytes and/or incorrect
encoding.
### `__init__.py`
Now create an `__init__.py` file in the folder:
```shell
echo "from . import agent" > multi_tool_agent/__init__.py
```
Your `__init__.py` should now look like this:
```python title="multi_tool_agent/__init__.py"
--8<-- "examples/python/snippets/get-started/multi_tool_agent/__init__.py"
```
### `agent.py`
Create an `agent.py` file in the same folder:
=== "OS X & Linux"
```shell
touch multi_tool_agent/agent.py
```
=== "Windows"
```shell
type nul > multi_tool_agent/agent.py
```
Copy and paste the following code into `agent.py`:
```python title="multi_tool_agent/agent.py"
--8<-- "examples/python/snippets/get-started/multi_tool_agent/agent.py"
```
### `.env`
Create a `.env` file in the same folder:
=== "OS X & Linux"
```shell
touch multi_tool_agent/.env
```
=== "Windows"
```shell
type nul > multi_tool_agent\.env
```
More instructions about this file are described in the next section on [Set up the model](#set-up-the-model).
=== "TypeScript"
You will need to create the following project structure in your `my-adk-agent` directory:
```console
my-adk-agent/
agent.ts
.env
package.json
tsconfig.json
```
### `agent.ts`
Create an `agent.ts` file in your project folder:
=== "OS X & Linux"
```shell
touch agent.ts
```
=== "Windows"
```shell
type nul > agent.ts
```
Copy and paste the following code into `agent.ts`:
```typescript title="agent.ts"
--8<-- "examples/typescript/snippets/get-started/multi_tool_agent/agent.ts"
```
### `.env`
Create a `.env` file in the same folder:
=== "OS X & Linux"
```shell
touch .env
```
=== "Windows"
```shell
type nul > .env
```
More instructions about this file are described in the next section on [Set up the model](#set-up-the-model).
=== "Go"
You will need to create the following project structure:
```console
my-adk-agent/
agent.go
.env
go.mod
```
### `agent.go`
Create an `agent.go` file in your project folder:
=== "OS X & Linux"
```bash
touch agent.go
```
=== "Windows"
```console
type nul > agent.go
```
Copy and paste the following code into `agent.go`:
```go title="agent.go"
--8<-- "examples/go/snippets/get-started/multi_tool_agent/main.go:full_code"
```
### `.env`
Create a `.env` file in the same folder:
=== "OS X & Linux"
```bash
touch .env
```
=== "Windows"
```console
type nul > .env
```
=== "Java"
Java projects generally feature the following project structure:
```console
project_folder/
├── pom.xml (or build.gradle)
├── src/
├── └── main/
│ └── java/
│ └── agents/
│ └── multitool/
└── test/
```
### Create `MultiToolAgent.java`
Create a `MultiToolAgent.java` source file in the `agents.multitool` package
in the `src/main/java/agents/multitool/` directory.
Copy and paste the following code into `MultiToolAgent.java`:
```java title="agents/multitool/MultiToolAgent.java"
--8<-- "examples/java/cloud-run/src/main/java/agents/multitool/MultiToolAgent.java:full_code"
```
=== "Kotlin"
Kotlin projects generally feature the following project structure:
```console
project_folder/
├── build.gradle.kts
├── src/
├── └── main/
│ └── kotlin/
│ └── agents/
│ └── multitool/
```
### Create `MultiToolAgent.kt`
Create a `MultiToolAgent.kt` source file in the `src/main/kotlin/agents/multitool/` directory.
Copy and paste the following code into `MultiToolAgent.kt`:
```kotlin title="src/main/kotlin/agents/multitool/MultiToolAgent.kt"
--8<-- "examples/kotlin/snippets/get-started/multi_tool_agent/MultiToolAgent.kt"
```
3. Set up the model
Your agent's ability to understand user requests and generate responses is powered by a generative AI model or Large Language Model (LLM). This guide uses Gemini models as examples, but ADK is compatible with many AI models from Google and other providers. For more information on available models and how to configure them, see AI Models for ADK agents.
Model connection and authentication
When using an AI model through a service, such as the Gemini API or Gemini
Enterprise Agent Platform on Google Cloud, you must provide an API key or
authenticate with the service. The most direct way to provide this information
is to use environment variables or an .env file. The following examples show
the most common way to configure an agent for use with the Gemini API or Gemini
Enterprise Agent Platform.
=== "Gemini API"
```
# .env configuration file
GOOGLE_API_KEY="PASTE_YOUR_GEMINI_API_KEY_HERE"
```
=== "Google Cloud Agent Platform"
```
# .env configuration file
GOOGLE_CLOUD_PROJECT=your-project-id
GOOGLE_CLOUD_LOCATION=location-code # example: us-central1
GOOGLE_GENAI_USE_ENTERPRISE=True
```
For more details on connecting ADK agents to Google Cloud hosted models and services, including Gemini Enterprise Agent Platform, see the Connect to Google Cloud and Agent Platform guide.
4. Run Your Agent
=== "Python"
Using the terminal, navigate to the parent directory of your agent project
(e.g. using `cd ..`):
```console
parent_folder/ <-- navigate to this directory
multi_tool_agent/
__init__.py
agent.py
.env
```
There are multiple ways to interact with your agent:
=== "Dev UI (adk web)"
!!! success "Authentication Setup for Agent Platform Users"
If you selected **"Gemini - Google Cloud Agent Platform"** in the previous step, you must authenticate with Google Cloud before launching the dev UI.
Run this command and follow the prompts:
```bash
gcloud auth application-default login
```
**Note:** Skip this step if you're using "Gemini - Google AI Studio".
Run the following command to launch the **dev UI**.
```shell
adk web
```
!!! warning "Caution: ADK Web for development only"
ADK Web is ***not meant for use in production deployments***. You should
use ADK Web for development and debugging purposes only.
!!!info "Note for Windows users"
When hitting the `_make_subprocess_transport NotImplementedError`, consider using `adk web --no-reload` instead.
**Step 1:** Open the URL provided (usually `http://localhost:8000` or
`http://127.0.0.1:8000`) directly in your browser.
**Step 2.** In the top-left corner of the UI, you can select your agent in
the dropdown. Select "multi_tool_agent".
!!!note "Troubleshooting"
If you do not see "multi_tool_agent" in the dropdown menu, make sure you
are running `adk web` in the **parent folder** of your agent folder
(i.e. the parent folder of multi_tool_agent).
**Step 3.** Now you can chat with your agent using the textbox:

**Step 4.** By using the `Events` tab at the left, you can inspect
individual function calls, responses and model responses by clicking on the
actions:

On the `Events` tab, you can also click the `Trace` button to see the trace logs for each event that shows the latency of each function calls:

**Step 5.** You can also enable your microphone and talk to your agent:
!!!note "Model support for voice/video streaming"
In order to use voice/video streaming in ADK, you will need to use Gemini models that support the Live API. You can find the **model ID(s)** that supports the Gemini Live API in the documentation:
- [Google AI Studio: Gemini Live API](https://ai.google.dev/gemini-api/docs/models#live-api)
- [Agent Platform: Gemini Live API](https://cloud.google.com/vertex-ai/generative-ai/docs/live-api)
You can then replace the `model` string in `root_agent` in the `agent.py` file you created earlier ([jump to section](#agentpy)). Your code should look something like:
```py
root_agent = Agent(
name="weather_time_agent",
model="replace-me-with-model-id", #e.g. gemini-2.0-flash-live-001
...
```

=== "Terminal (adk run)"
!!! tip
When using `adk run` you can inject prompts into the agent to start by
piping text to the command like so:
```shell
echo "Please start by listing files" | adk run file_listing_agent
```
Run the following command, to chat with your Weather agent.
```
adk run multi_tool_agent
```

To exit, use Cmd/Ctrl+C.
=== "API Server (adk api_server)"
`adk api_server` enables you to create a local FastAPI server in a single
command, enabling you to test local cURL requests before you deploy your
agent.

To learn how to use `adk api_server` for testing, refer to the
[documentation on using the API server](/runtime/api-server/).
=== "TypeScript"
Using the terminal, navigate to your agent project directory:
```console
my-adk-agent/ <-- navigate to this directory
agent.ts
.env
package.json
tsconfig.json
```
There are multiple ways to interact with your agent:
=== "Dev UI (adk web)"
Run the following command to launch the **dev UI**.
```shell
npx adk web
```
**Step 1:** Open the URL provided (usually `http://localhost:8000` or
`http://127.0.0.1:8000`) directly in your browser.
**Step 2.** In the top-left corner of the UI, select your agent from the dropdown. The agents are listed by their filenames, so you should select "agent".
!!!note "Troubleshooting"
If you do not see "agent" in the dropdown menu, make sure you
are running `npx adk web` in the directory containing your `agent.ts` file.
**Step 3.** Now you can chat with your agent using the textbox:

**Step 4.** By using the `Events` tab at the left, you can inspect
individual function calls, responses and model responses by clicking on the
actions:

On the `Events` tab, you can also click the `Trace` button to see the trace logs for each event that shows the latency of each function calls:

=== "Terminal (adk run)"
Run the following command to chat with your agent.
```
npx adk run agent.ts
```

To exit, use Cmd/Ctrl+C.
=== "API Server (adk api_server)"
`npx adk api_server` enables you to create a local Express.js server in a single
command, enabling you to test local cURL requests before you deploy your
agent.

To learn how to use `api_server` for testing, refer to the
[documentation on testing](/runtime/api-server/).
=== "Go"
Using the terminal, navigate to your agent project directory:
```console
my-adk-agent/ <-- navigate to this directory
agent.go
.env
go.mod
```
There are multiple ways to interact with your agent:
=== "Dev UI (web)"
Run the following command to launch the **dev UI**. You must specify which sub-launchers to activate (e.g., `webui`, `api`).
```bash
go run agent.go web webui api
```
**Step 1:** Open the URL provided (usually `http://localhost:8080`) directly in your browser.
**Step 2.** In the top-left corner of the UI, select your agent from the dropdown. It should be "weather_time_agent".
**Step 3.** Now you can chat with your agent using the textbox.
=== "Terminal (console)"
Run the following command to chat with your agent in the terminal.
```bash
go run agent.go console
```
**Note:** If `console` is the first sublauncher in your code (as it is with `full.NewLauncher()`), you can also just run `go run agent.go`.
To exit, use Cmd/Ctrl+C.
=== "Java"
Using the terminal, navigate to the parent directory of your agent project
(e.g. using `cd ..`):
```console
project_folder/ <-- navigate to this directory
├── pom.xml (or build.gradle)
├── src/
├── └── main/
│ └── java/
│ └── agents/
│ └── multitool/
│ └── MultiToolAgent.java
└── test/
```
=== "Dev UI"
Run the following command from the terminal to launch the Dev UI.
**DO NOT change the main class name of the Dev UI server.**
```console title="terminal"
mvn exec:java \
-Dexec.mainClass="com.google.adk.web.AdkWebServer" \
-Dexec.args="--adk.agents.source-dir=src/main/java" \
-Dexec.classpathScope="compile"
```
**Step 1:** Open the URL provided (usually `http://localhost:8080` or
`http://127.0.0.1:8080`) directly in your browser.
**Step 2.** In the top-left corner of the UI, you can select your agent in
the dropdown. Select "multi_tool_agent".
!!!note "Troubleshooting"
If you do not see "multi_tool_agent" in the dropdown menu, make sure you
are running the `mvn` command at the location where your Java source code
is located (usually `src/main/java`).
**Step 3.** Now you can chat with your agent using the textbox:

**Step 4.** You can also inspect individual function calls, responses and
model responses by clicking on the actions:

!!! warning "Caution: ADK Web for development only"
ADK Web is ***not meant for use in production deployments***. You should
use ADK Web for development and debugging purposes only.
=== "Maven"
With Maven, run the `main()` method of your Java class
with the following command:
```console title="terminal"
mvn compile exec:java -Dexec.mainClass="agents.multitool.MultiToolAgent"
```
=== "Gradle"
With Gradle, the `build.gradle` or `build.gradle.kts` build file
should have the following Java plugin in its `plugins` section:
```groovy
plugins {
id('java')
// other plugins
}
```
Then, elsewhere in the build file, at the top-level,
create a new task to run the `main()` method of your agent:
```groovy
tasks.register('runAgent', JavaExec) {
classpath = sourceSets.main.runtimeClasspath
mainClass = 'agents.multitool.MultiToolAgent'
}
```
Finally, on the command-line, run the following command:
```console
gradle runAgent
```
=== "Kotlin"
Using the terminal, navigate to your agent project directory:
```console
project_folder/ <-- navigate to this directory
├── build.gradle.kts
├── src/
├── └── main/
│ └── kotlin/
│ └── agents/
│ └── multitool/
│ └── MultiToolAgent.kt
```
### Run your Agent
You can run the `main()` method of your Kotlin class using Gradle:
```console
./gradlew run
```
Or if you are using IntelliJ IDEA, you can just click the green run arrow next to the `main()` function.
📝 Example prompts to try
- What is the weather in New York?
- What is the time in New York?
- What is the weather in Paris?
- What is the time in Paris?
🎉 Congratulations!
You've successfully created and interacted with your first agent using ADK!
🛣️ Next steps
- Go to the tutorial: Learn how to add memory, session, state to your agent: tutorial.
- Delve into advanced configuration: Explore the setup section for deeper dives into project structure, configuration, and other interfaces.
- Understand Core Concepts: Learn about agents concepts.
