LangDB

from pylangdb.agno import init

# Initialize LangDB tracing - must be called before creating agents
init()

from agno.agent import Agent
from agno.models.langdb import LangDB
from agno.tools.hackernews import HackerNewsTools

# Create agent with LangDB model (uses environment variables automatically)
agent = Agent(
    name="Hacker News Research Agent",
    model=LangDB(id="openai/gpt-4.1"),
    tools=[HackerNewsTools()],
    instructions="Answer questions using current Hacker News data."
)

# Use the agent
response = agent.run("What are the latest developments in AI agents?")
print(response)

from pylangdb.agno import init
init()

from agno.agent import Agent
from agno.team import Team
from agno.models.langdb import LangDB
from agno.tools.hackernews import HackerNewsTools
from agno.tools.yfinance import YFinanceTools

# Research Agent
web_agent = Agent(
    name="Market Research Agent",
    model=LangDB(id="openai/gpt-4.1"),
    tools=[HackerNewsTools()],
    instructions="Research current market conditions and news"
)

# Financial Analysis Agent
finance_agent = Agent(
    name="Financial Analyst",
    model=LangDB(id="xai/grok-4"),
    tools=[YFinanceTools(enable_stock_price=True, enable_company_info=True)],
    instructions="Perform quantitative financial analysis"
)

# Coordinated Team
reasoning_team = Team(
    name="Finance Reasoning Team",
    model=LangDB(id="xai/grok-4"),
    members=[web_agent, finance_agent],
    instructions=[
        "Collaborate to provide comprehensive financial insights",
        "Consider both fundamental analysis and market sentiment"
    ]
)

# Execute team workflow
reasoning_team.print_response("Analyze Apple (AAPL) investment potential")