Python Agents

/agentMaker Create an agent that extracts product prices from amazon.com and saves them to a Google Sheet

from narada import Agent, BrowserEnvironment

env = BrowserEnvironment()
agent = Agent(environment=env)

# Navigate to a starting page. Use new_tab=True for the first navigation.
await agent.go_to_url(url="https://example.com", new_tab=True)

response = await agent.run(
    prompt="Extract the main heading from this page",
)

print(response.text)

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


class ProductInfo(BaseModel):
    name: str = Field(description="Product name")
    price: str = Field(description="Product price with currency")
    rating: str = Field(description="Product rating out of 5")


env = BrowserEnvironment()
agent = Agent(environment=env)

await agent.go_to_url(url="https://example.com/product", new_tab=True)

response = await agent.run(
    prompt="Extract the product information from this page",
    output_schema=ProductInfo,
)

product = response.structured_output
assert product is not None

print(f"{product.name}: {product.price} ({product.rating})")

from narada import Agent, BrowserEnvironment

env = BrowserEnvironment()
agent = Agent(environment=env)

# Access input variables with sensible defaults.
search_term = variables.get("searchTerm", "machine learning")
max_results = variables.get("maxResults", 5)

await agent.go_to_url(
    url=f"https://www.google.com/search?q={search_term}",
    new_tab=True,
)

response = await agent.run(
    prompt=f"Extract the top {max_results} search result titles",
)

print(response.text)

from narada import Agent, BrowserEnvironment

env = BrowserEnvironment()
agent = Agent(environment=env)

sheet_data = await agent.read_google_sheet(
    spreadsheet_id="your-spreadsheet-id",
    range="Sheet1!A2:A10",
)
companies = [row[0] for row in sheet_data.values]

results = []
for company in companies:
    await agent.go_to_url(
        url=f"https://www.google.com/search?q={company}+valuation",
    )
    response = await agent.run(
        prompt=f"What is {company}'s latest valuation?",
    )
    results.append([company, response.text])

await agent.write_google_sheet(
    spreadsheet_id="your-spreadsheet-id",
    range="Sheet1!B2",
    values=results,
)

await agent.print_message(message="Done! Results written to Google Sheet.")

from narada import Agent, AgentKind, BrowserEnvironment

env = BrowserEnvironment()

# Web automation (default)
operator = Agent(environment=env)
await operator.run(prompt="Click the Submit button")

# Read-only reasoning
core_agent = Agent(environment=env, kind=AgentKind.CORE_AGENT)
await core_agent.run(prompt="What products are listed?")

import asyncio

from narada import Agent, BrowserEnvironment


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

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


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

/$USER/my-research-agent Search for machine learning papers