> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pipecat.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# RTVIProcessor

> Core coordinator for RTVI protocol communication

The `RTVIProcessor` manages bidirectional communication between clients and your Pipecat application. It processes client messages, handles service configuration, executes actions, and coordinates function calls.

## Initialization

`RTVIProcessor` is automatically added to your pipeline when you create a `PipelineTask`. Access it via `task.rtvi`:

```python theme={null}
pipeline = Pipeline([
    transport.input(),
    stt,
    # ... other processors ...
    transport.output()
])

task = PipelineTask(pipeline)

# Access the processor
rtvi = task.rtvi
```

To provide a custom processor (e.g., for [Google RTVI](./google-rtvi-observer)):

```python theme={null}
from pipecat.services.google.rtvi import GoogleRTVIProcessor

task = PipelineTask(pipeline, rtvi_processor=GoogleRTVIProcessor())
```

To disable RTVI entirely, set `enable_rtvi=False`.

## Readiness Protocol

### Client Ready State

Clients indicate readiness by sending a `client-ready` message, triggering the `on_client_ready` event in the processor:

```python theme={null}
@rtvi.event_handler("on_client_ready")
async def on_client_ready(rtvi):
    # Handle client ready state
    await rtvi.set_bot_ready()
    # Initialize conversation
    await task.queue_frames([...])
```

<Note>
  The processor validates the client's RTVI protocol version during the handshake. If the client's major version doesn't match the server's protocol version, an error response is sent but the connection continues. Check server logs for version compatibility warnings.
</Note>

### Bot Ready State

The server must mark the bot as ready before it can process client messages:

```python theme={null}
await rtvi.set_bot_ready()
```

When marked ready, the bot sends a response containing:

* RTVI protocol version
* Current service configuration
* Available actions

## Services

Services represent configurable components of your application that clients can interact with.

### Registering Services

```python theme={null}
# 1. Define option handler
async def handle_voice_option(processor, service, option):
    voice_id = option.value
    # Apply configuration change
    logger.info(f"Voice ID updated to: {voice_id}")

# 2. Create RTVIService
voice_service = RTVIService(
    name="voice",
    options=[
        RTVIServiceOption(
            name="voice_id",
            type="string",
            handler=handle_voice_option
        )
    ]
)

# 3. Register with processor
rtvi.register_service(voice_service)
```

### Option Types

Services support multiple data types for configuration:

```python theme={null}
RTVIServiceOption(
    name="temperature",
    type="number",  # number, string, bool, array, object
    handler=handle_temperature
)
```

Option handlers receive:

* The processor instance
* The service name
* The option configuration with new value

## Actions

Actions are server-side functions that clients can trigger with arguments.

### Registering Actions

```python theme={null}
# 1. Define handler function
async def handle_print_message(processor, service, arguments):
    message = arguments.get("message", "Default message")
    logger.info(f"Print action triggered with message: {message}")
    return True

# 2. Create and register RTVIAction
print_action = RTVIAction(
    service="conversation",
    action="print_message",
    arguments=[
        RTVIActionArgument(name="message", type="string")
    ],
    result="bool",
    handler=handle_print_message
)
rtvi.register_action(print_action)
```

### Action Arguments

Actions can accept typed arguments from clients:

```python theme={null}
search_action = RTVIAction(
    service="knowledge",
    action="search",
    arguments=[
        RTVIActionArgument(name="query", type="string"),
        RTVIActionArgument(name="limit", type="number")
    ],
    result="array",
    handler=handle_search
)
```

## Function Calls

Handle LLM function calls with client interaction:

```python theme={null}

await processor.handle_function_call(
    function_name=function_name,
    tool_call_id=tool_call_id,
    arguments=arguments,
)

await processor.handle_function_call(params)
```

The function call process:

1. LLM requests a function call
2. Processor notifies client with `llm-function-call` message
3. Client executes function and returns result
4. Result is passed back to LLM via `FunctionCallResultFrame`
5. Conversation continues

## Error Handling

Send error messages to clients:

```python theme={null}
# General error
await processor.send_error("Invalid configuration")

# Request-specific error
await processor._send_error_response(request_id, "Invalid action arguments")
```

Error categories:

* Configuration errors
* Action execution errors
* Function call errors
* Protocol errors
* Fatal and non-fatal errors

## Bot Control

Manage bot state and handle interruptions:

```python theme={null}
# Set bot as ready
await processor.set_bot_ready()

# Handle interruptions
await processor.interrupt_bot()
```

## Custom Messaging

Server messages let you push unsolicited data from the server to the client at any time — notifications, status updates, real-time results, etc. They are distinct from **server responses**, which reply to a specific client request (see [Requesting Information from the Server](/client/guides/custom-messaging#requesting-information-from-the-server)).

### Sending server messages

Any `FrameProcessor` in the pipeline can push an `RTVIServerMessageFrame`. The `RTVIObserver` picks it up and delivers it to the client:

```python theme={null}
from pipecat.processors.frameworks.rtvi import RTVIServerMessageFrame

class MyProcessor(FrameProcessor):
    async def process_frame(self, frame, direction):
        await super().process_frame(frame, direction)
        if isinstance(frame, SomeEventFrame):
            await self.push_frame(
                RTVIServerMessageFrame(
                    data={"type": "event", "value": frame.value}
                )
            )
        await self.push_frame(frame, direction)
```

<Note>
  `RTVIServerMessageFrame` is a `SystemFrame`, so it uses the high-priority
  SystemFrame lane, remains ordered with other SystemFrames, and is not
  discarded by interruptions.
</Note>

### Client-side handling

The message arrives at the client with the wire format `{ label: "rtvi-ai", type: "server-message", data: ... }`. Handle it with the `onServerMessage` callback:

```javascript theme={null}
pcClient.onServerMessage((message) => {
  console.log("Server message:", message);
  // message.data contains whatever you passed on the server
});
```

See [Handling Custom Messages from the Server](/client/guides/custom-messaging#handling-custom-messages-from-the-server) for more details and examples.