You've already forked adk-python
mirror of
https://github.com/encounter/adk-python.git
synced 2026-03-30 10:57:20 -07:00
58 lines
2.2 KiB
Markdown
58 lines
2.2 KiB
Markdown
|
|
# ADK Agent with Plugin
|
||
|
|
|
||
|
|
### What is ADK Plugin?
|
||
|
|
|
||
|
|
At its core, ADK extensibility is built on
|
||
|
|
[**callbacks**](https://google.github.io/adk-docs/callbacks/): functions you
|
||
|
|
write that ADK automatically executes at key stages of an agent's lifecycle.
|
||
|
|
**A Plugin is simply a class that packages these individual callback functions
|
||
|
|
together for a broader purpose.**
|
||
|
|
|
||
|
|
While a standard Agent Callback is configured on a *single agent, a single tool*
|
||
|
|
for a *specific task*, a Plugin is registered *once* on the `Runner` and its
|
||
|
|
callbacks apply *globally* to every agent, tool, and LLM call managed by that
|
||
|
|
runner. This makes Plugins the ideal solution for implementing horizontal
|
||
|
|
features that cut across your entire application.
|
||
|
|
|
||
|
|
### What can plugins do?
|
||
|
|
|
||
|
|
Plugins are incredibly versatile. By implementing different callback methods, you
|
||
|
|
can achieve a wide range of functionalities.
|
||
|
|
|
||
|
|
* **Logging & Tracing**: Create detailed logs of agent, tool, and LLM activity
|
||
|
|
for debugging and performance analysis.
|
||
|
|
* **Policy Enforcement**: Implement security guardrails. For example, a
|
||
|
|
before\_tool\_callback can check if a user is authorized to use a specific
|
||
|
|
tool and prevent its execution by returning a value.
|
||
|
|
* **Monitoring & Metrics**: Collect and export metrics on token usage,
|
||
|
|
execution times, and invocation counts to monitoring systems like Prometheus
|
||
|
|
or Stackdriver.
|
||
|
|
* **Caching**: In before\_model\_callback or before\_tool\_callback, you can
|
||
|
|
check if a request has been made before. If so, you can return a cached
|
||
|
|
response, skipping the expensive LLM or tool call entirely.
|
||
|
|
* **Request/Response Modification**: Dynamically add information to LLM prompts
|
||
|
|
(e.g., in before\_model\_callback) or standardize tool outputs (e.g., in
|
||
|
|
after\_tool\_callback).
|
||
|
|
|
||
|
|
### Run the agent
|
||
|
|
|
||
|
|
**Note: Plugin is NOT supported in `adk web`yet.**
|
||
|
|
|
||
|
|
Use following command to run the main.py
|
||
|
|
|
||
|
|
```bash
|
||
|
|
python3 -m contributing.samples.plugin_basic.main
|
||
|
|
```
|
||
|
|
|
||
|
|
It should output the following content. Note that the outputs from plugin are
|
||
|
|
printed.
|
||
|
|
|
||
|
|
```bash
|
||
|
|
[Plugin] Agent run count: 1
|
||
|
|
[Plugin] LLM request count: 1
|
||
|
|
** Got event from hello_world
|
||
|
|
Hello world: query is [hello world]
|
||
|
|
** Got event from hello_world
|
||
|
|
[Plugin] LLM request count: 2
|
||
|
|
** Got event from hello_world
|
||
|
|
```
|