run

import asyncio

from narada import Agent, BrowserEnvironment
from pydantic import BaseModel, Field


class SearchResult(BaseModel):
    query: str = Field(description="The search query used")
    result_count: str = Field(description="Number of results found")
    top_result_title: str = Field(description="Title of the first result")
    top_result_url: str = Field(description="URL of the first result")


async def main() -> None:
    env = BrowserEnvironment()
    agent = Agent(environment=env)

    try:
        response = await agent.run(
            prompt="Search for AI research papers and extract search details",
            output_schema=SearchResult,
        )

        data = response.structured_output
        assert data is not None

        print(f"Query: {data.query}")
        print(f"Results: {data.result_count}")
        print(f"Top result: {data.top_result_title}")
        print(f"URL: {data.top_result_url}")
    finally:
        await env.close()


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

import asyncio

from narada import Agent, AgentKind, BrowserEnvironment


async def main() -> None:
    env = BrowserEnvironment()
    agent = Agent(environment=env, kind=AgentKind.CORE_AGENT)

    try:
        response = await agent.run(
            prompt="Pick a lucky number between 1 and 100 for me.",
        )
        print("Agent:", response.text)

        response = await agent.run(
            prompt="What did you pick again?",
            previous_request_id=response.request_id,
        )
        print("Agent:", response.text)

        response = await agent.run(
            prompt="What's double that number?",
            previous_request_id=response.request_id,
        )
        print("Agent:", response.text)
    finally:
        await env.close()


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

import asyncio

from narada import Agent, BrowserEnvironment, NaradaTimeoutError


async def main() -> None:
    env = BrowserEnvironment()
    agent = Agent(environment=env)

    try:
        max_attempts = 3
        for attempt in range(max_attempts):
            try:
                response = await agent.run(
                    prompt="Search for complex data analysis tutorials and summarize the top 3 results",
                    timeout=60,
                    generate_gif=True,
                )

                print("Task completed successfully!")
                print(response.text)
                break
            except NaradaTimeoutError:
                if attempt == max_attempts - 1:
                    raise

                print(f"Attempt {attempt + 1} timed out, retrying...")
                await agent.reset_agent_state()
    finally:
        await env.close()


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

import asyncio

from narada import Agent, AgentKind, BrowserEnvironment
from pydantic import BaseModel, Field


class InvoiceData(BaseModel):
    invoice_number: str = Field(description="Invoice number")
    date: str = Field(description="Invoice date")
    vendor_name: str = Field(description="Vendor or supplier name")
    total_amount: str = Field(description="Total amount with currency")
    line_items: list[str] = Field(description="List of items or services")


async def main() -> None:
    env = BrowserEnvironment()
    agent = Agent(environment=env, kind=AgentKind.CORE_AGENT)

    try:
        with open("/path/to/invoice.pdf", "rb") as f:
            response = await agent.run(
                prompt="Extract the invoice details from the attached document.",
                attachment=f,
                output_schema=InvoiceData,
            )

        invoice = response.structured_output
        assert invoice is not None

        print(f"Invoice: {invoice.invoice_number}")
        print(f"Date: {invoice.date}")
        print(f"Vendor: {invoice.vendor_name}")
        print(f"Total: {invoice.total_amount}")
        print(f"Items: {', '.join(invoice.line_items)}")
    finally:
        await env.close()


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

import asyncio

from narada import Agent, BrowserEnvironment


async def main() -> None:
    env = BrowserEnvironment()
    agent = Agent(environment=env, kind="/$USER/my-research-agent")

    try:
        response = await agent.run(
            prompt="Search for recent machine learning papers.",
        )
        print(response.text)
    finally:
        await env.close()


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