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Client library for AI agent runtime communication over WebSocket

Project description

runtimeuse (Python)

Python client library for communicating with a runtimeuse agent runtime over WebSocket.

Handles the WebSocket connection lifecycle, message dispatch, artifact upload handshake, cancellation, and structured result parsing -- so you can focus on what to do with agent results rather than wire protocol details.

Installation

pip install runtimeuse-client

Quick Start

Start the runtime inside any sandbox, then connect from outside:

import asyncio
from runtimeuse_client import RuntimeUseClient, QueryOptions, TextResult, StructuredOutputResult

async def main():
    # Start the runtime in a sandbox (provider-specific)
    sandbox = Sandbox.create()
    sandbox.run("npx -y runtimeuse")
    ws_url = sandbox.get_url(8080)

    client = RuntimeUseClient(ws_url=ws_url)

    # Text response (no output schema)
    result = await client.query(
        prompt="What is the capital of France?",
        options=QueryOptions(
            system_prompt="You are a helpful assistant.",
            model="gpt-4.1",
        ),
    )
    assert isinstance(result.data, TextResult)
    print(result.data.text)

    # Structured response (with output schema)
    result = await client.query(
        prompt="Return the capital of France.",
        options=QueryOptions(
            system_prompt="You are a helpful assistant.",
            model="gpt-4.1",
            output_format_json_schema_str='{"type":"json_schema","schema":{"type":"object"}}',
        ),
    )
    assert isinstance(result.data, StructuredOutputResult)
    print(result.data.structured_output)
    print(result.metadata)  # execution metadata

asyncio.run(main())

For local development without a sandbox, connect directly:

client = RuntimeUseClient(ws_url="ws://localhost:8080")

Usage

RuntimeUseClient

Manages the WebSocket connection to the agent runtime and runs the message loop: sends a prompt, iterates the response stream, and returns a QueryResult. Raises AgentRuntimeError if the runtime returns an error.

query() returns a QueryResult with .data (a TextResult or StructuredOutputResult) and .metadata.

client = RuntimeUseClient(ws_url="ws://localhost:8080")

result = await client.query(
    prompt="Do the thing.",
    options=QueryOptions(
        system_prompt="You are a helpful assistant.",
        model="gpt-4.1",
        output_format_json_schema_str='...',         # optional -- omit for text response
        on_assistant_message=on_assistant,            # optional
        on_artifact_upload_request=on_artifact,       # optional -- return ArtifactUploadResult
        timeout=300,                                  # optional -- seconds
    ),
)

if isinstance(result.data, TextResult):
    print(result.data.text)
elif isinstance(result.data, StructuredOutputResult):
    print(result.data.structured_output)

print(result.metadata)  # execution metadata

Artifact Upload Handshake

When the agent runtime requests an artifact upload, provide a callback that returns a presigned URL and content type. The client sends the response back automatically.

from runtimeuse_client import ArtifactUploadResult

async def on_artifact(request: ArtifactUploadRequestMessageInterface) -> ArtifactUploadResult:
    presigned_url = await my_storage.create_presigned_url(request.filename)
    content_type = guess_content_type(request.filename)
    return ArtifactUploadResult(presigned_url=presigned_url, content_type=content_type)

Cancellation

Call client.abort() from any coroutine to cancel a running query. The client sends a cancel message to the runtime and query raises CancelledException.

from runtimeuse_client import CancelledException

async def cancel_after_delay(client, seconds):
    await asyncio.sleep(seconds)
    client.abort()

try:
    asyncio.create_task(cancel_after_delay(client, 30))
    result = await client.query(
        prompt="Do the thing.",
        options=QueryOptions(
            system_prompt="You are a helpful assistant.",
            model="gpt-4.1",
        ),
    )
except CancelledException:
    print("Run was cancelled")

API Reference

Types

Class Description
QueryOptions Configuration for client.query() (prompt options, callbacks, timeout)
QueryResult Return type of query() (.data, .metadata)
ResultMessageInterface Wire-format result message from the runtime
TextResult Result variant when no output schema is specified (.text)
StructuredOutputResult Result variant when an output schema is specified (.structured_output)

| AssistantMessageInterface | Intermediate assistant text messages | | ArtifactUploadRequestMessageInterface | Runtime requesting a presigned URL for artifact upload | | ArtifactUploadResponseMessageInterface | Response with presigned URL sent back to runtime | | ErrorMessageInterface | Error from the agent runtime | | CommandInterface | Pre/post invocation shell command | | RuntimeEnvironmentDownloadableInterface | File to download into the runtime before invocation |

Exceptions

Class Description
AgentRuntimeError Raised when the agent runtime returns an error (carries .error and .metadata)
CancelledException Raised when client.abort() is called during a query

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