Policies

import asyncio
from dedalus_labs import AsyncDedalus, DedalusRunner
from dedalus_labs.utils.stream import stream_async
from dotenv import load_dotenv

load_dotenv()

def policy(ctx: dict) -> dict:
    step = ctx.get("step", 1)

    if step >= 3:
        # After step 3, tell the model to wrap up
        return {
            "message_prepend": [
                {"role": "system", "content": "Provide your final answer now."}
            ],
            "max_steps": 4
        }

    return {}

async def main():
    client = AsyncDedalus()
    runner = DedalusRunner(client)

    result = runner.run(
        input="Research the history of the internet and summarize key milestones",
        model="openai/gpt-5.2",
        mcp_servers=["windsor/brave-search-mcp"],  # Web search via Brave Search MCP
        stream=True,
        policy=policy
    )

    await stream_async(result)

if __name__ == "__main__":
    asyncio.run(main())

import Dedalus from "dedalus-labs";
import { DedalusRunner } from "dedalus-labs";

const client = new Dedalus();
const runner = new DedalusRunner(client, true);

function policy(ctx: { step?: number }): object {
	const step = ctx.step ?? 1;

	if (step >= 3) {
		return {
			messagePrepend: [{ role: "system", content: "Provide your final answer now." }],
			maxSteps: 4,
		};
	}

	return {};
}

async function main() {
	const result = await runner.run({
		input: "Research the history of the internet and summarize key milestones",
		model: "openai/gpt-5.2",
		mcpServers: ["windsor/brave-search-mcp"], // Web search via Brave Search MCP
		stream: true,
		policy: policy,
	});

	if (Symbol.asyncIterator in result) {
		for await (const chunk of result) {
			if (chunk.choices?.[0]?.delta?.content) {
				process.stdout.write(chunk.choices[0].delta.content);
			}
		}
	}
}

main();

import json

def on_tool(evt: dict) -> None:
    print(f"Tool called: {json.dumps(evt)}")

result = runner.run(
    input="Calculate shipping costs for a 5kg package to London",
    model="openai/gpt-5.2",
    tools=[calculate_shipping],
    on_tool_event=on_tool,
    policy=policy
)

function onTool(evt: object): void {
	console.log("Tool called:", JSON.stringify(evt));
}

const result = await runner.run({
	input: "Calculate shipping costs for a 5kg package to London",
	model: "openai/gpt-5.2",
	tools: [calculateShipping],
	onToolEvent: onTool,
	policy: policy,
});