---
title: "Component: Command"
---

Command components are triggered by user command messages starting with `!` (or other configured prefixes). Here's an example of triggering the `!help` command:

<img width="600" src="/images/zh/plugin/dev/components/command_use.png" />

## Adding Command Components

A single plugin can contain any number of commands. Execute the command `lbp comp Command` in the plugin directory and follow the prompts to enter the command configuration.

```bash
➜  HelloPlugin > lbp comp Command
Generating component Command...
Command name: info
Command description: Show information of the query
Component Command generated successfully.
组件 Command 生成成功。
```

This will generate `info.yaml` and `info.py` files in the `components/commands/` directory. The `.yaml` file defines the basic information for the `!info` command, and the `.py` file is the command handler:

```bash
➜  HelloPlugin > tree
...
├── components
│   ├── __init__.py
│   ├── commands
│   │   ├── __init__.py
│   │   ├── info.py
│   │   └── info.yaml
...
```

## Manifest File: Command Component

```yaml
apiVersion: v1  # Do not modify
kind: Command  # Do not modify
metadata:
  name: info  # Command name, users will trigger this command with !info
  label:  # Command display name, shown in LangBot UI, supports multilingual
    en_US: Info
    zh_Hans: Info
  description:  # Command description, shown in LangBot UI, supports multilingual. Optional.
    en_US: 'Show information of the query'
    zh_Hans: '发送此次消息的详细信息'
spec:
execution:
  python:
    path: info.py  # Command handler, do not modify
    attr: Info  # Command handler class name, matches the class name in info.py
```

## Plugin Processing

The following code is generated by default (`components/command/<command_name>.py`). You need to register and implement subcommand processing logic in the `initialize` method of the `Info` class.

```python
# Auto generated by LangBot Plugin SDK.
# Please refer to https://langbot.app/docs/en/plugin/dev/tutor.html for more details.
from __future__ import annotations

from typing import Any, AsyncGenerator

from langbot_plugin.api.definition.components.command.command import Command, Subcommand
from langbot_plugin.api.entities.builtin.command.context import ExecuteContext, CommandReturn


class Info(Command):
    
    async def initialize(self):
        await super().initialize()
        
        "Fill with your code here"
```

Adding subcommands:

```python
...
class Info(Command):
    
    async def initialize(self):
        await super().initialize()
        
        @self.subcommand(
            name="",  # Empty string represents root command
            help="Show information of the query", # Command help information
            usage="info", # Command usage example, displayed in command help
            aliases=["i"], # Command aliases
        )
        async def send(self, context: ExecuteContext) -> AsyncGenerator[CommandReturn, None]:
            print(context)

            reply_text = f"Query ID: {context.query_id}\n"
            reply_text += f"command: {context.command}\n"
            reply_text += f"command_text: {context.command_text}\n"
            reply_text += f"params: {context.params}\n"
            reply_text += f"crt_params: {context.crt_params}\n"
            reply_text += f"privilege: {context.privilege}\n"
            reply_text += f"session: {context.session.launcher_type.value}_{context.session.launcher_id}\n"
            
            yield CommandReturn(
                text=reply_text,
            )

        @self.subcommand(
            name="field",
            help="Show information of the field",
            usage="info field",
            aliases=["f"],
        )
        async def field(self, context: ExecuteContext) -> AsyncGenerator[CommandReturn, None]:
            print(context)

            field_name = context.crt_params[0]
            field_value = getattr(context, field_name)

            yield CommandReturn(
                text=f"{field_name}: {field_value}",
            )
```

In this code, the `send` function is registered as a subcommand through the `@self.subcommand` decorator, prints the command context (ExecuteContext) information, and concatenates it into a reply message.

### Subcommand Registration

`name` is the subcommand name. Leaving it empty means handling the main command. If not empty, it matches the second parameter as the command. For example:

- `!info` matches the subcommand with name=""
- `!info field` matches the subcommand with name="field"
- `!info field value` matches the subcommand with name="field", with `value` as the subcommand parameter
- Specialy, `name="*"` matches all unmatched first-level subcommands, and passes each section after `info` as parameters, for example `!info 123`, `!info abc`. You can get `['123']` or `['abc']` from `context.crt_params`, depending on the user's input.

In subcommand functions, you can read command parameters through the `context` variable.

The effect of the above command is shown in the image:

<img width="600" src="/images/zh/plugin/dev/components/info_command_demo.png" />

### Command Context

```python

class ExecuteContext(pydantic.BaseModel):
    """Single command execution context"""

    query_id: int
    """Request ID"""

    session: provider_session.Session
    """Session object for this message"""

    command_text: str
    """Complete command text"""

    command: str
    """Command name"""

    crt_command: str
    """Current command
    
    In multi-level commands, crt_command is the current command, command is the root command.
    Example: !plugin on Webwlkr
    When processing plugin, command is plugin, crt_command is plugin
    When processing on, command is plugin, crt_command is on
    """

    params: list[str]
    """Command parameters
    
    Parameter list after splitting the entire command by spaces
    """

    crt_params: list[str]
    """Current command parameters

    In multi-level commands, crt_params are current command parameters, params are root command parameters.
    Example: !plugin on Webwlkr
    When processing plugin, params is ['on', 'Webwlkr'], crt_params is ['on', 'Webwlkr']
    When processing on, params is ['on', 'Webwlkr'], crt_params is ['Webwlkr']
    """

    privilege: int
    """Session privilege level"""

    ...
```

### Command Return Values

Command return values (CommandReturn) currently support returning text, images (image_url, image links), and errors.

```python
yield CommandReturn(
    text=reply_text,
)

yield CommandReturn(
    image_url=image_url,
)
```

Command processing supports returning multiple messages, so please use `yield` statements to return messages.

For specific return values, please refer to the definition of `CommandReturn`: [langbot_plugin.api.entities.builtin.command.context.CommandReturn](https://github.com/langbot-app/langbot-plugin-sdk/tree/main/src/langbot_plugin/api/entities/builtin/command/context.py)

## One installation, many usages

A single command is triggered **concurrently by several conversations**:

- Read config per call; never read it in `initialize()` and cache it on the instance.
- Never leave command arguments, return values or conversation data on instance fields or module-level variables; `ExecuteContext` is valid only for the current execution.
- Concurrent triggering means instance fields get interleaved writes — do not use them to hold "current conversation" style state. Data that must survive calls belongs in Host storage, keyed with the conversation identity.
- If you keep per-installation process-local caches, release them in `on_installation_revoked(binding)`.

See [Certified plugins and shared runtime](/en/plugin/certified-plugins) for the full specification.

## What's Next

You have learned the basic information about command registration and command execution. Next, you can:

- See the complete [`ExecuteContext` API reference](/en/plugin/dev/apis/agent-run#command).
- Check out [Plugin Common APIs](/en/plugin/dev/apis/common).