financial_agent.py

# import openai
import os

from agno.agent import Agent
from agno.models.groq import Groq
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
from dotenv import load_dotenv

load_dotenv()

os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")

## Web Search Agent - Handles market research
web_search_agent = Agent(
    name="Web Search Agent",
    role="Search the web for the information",
    model=Groq(id="llama-3.1-8b-instant"),
    tools=[DuckDuckGoTools()],                  # Internet search capability
    instructions=["Always include sources"],
    show_tool_calls=True,
    markdown=True,
)

## Finance Agent - Handles financial data
finance_agent = Agent(
    name="Finance AI Agent",
    model=Groq(id="gemma2-9b-it"),
    tools=[
        YFinanceTools(                          # Yahoo Finance integration
            stock_price=True,                   # Real-time prices
            analyst_recommendations=True,       # Professional recommendations
            stock_fundamentals=True,            # Company metrics
            company_news=True,                  # Latest company news
        ),
    ],
    instructions="Use tables to display the data",
    show_tool_calls=True,
    markdown=True,
)

## Multi-Agent Team - Coordinates everything
multi_ai_agent = Agent(
    team=[web_search_agent, finance_agent],     # Combines both agents
    model=Groq(id="gemma2-9b-it"),
    instructions=["Always include sources", "Use table to display the data"],
    show_tool_calls=True,
    markdown=True,
)

multi_ai_agent.print_response(
    "Summarize the analyst recommendation and share the stock price, and market sentiment for AAPL",
)

# multi_ai_agent.print_response(
#     "Analyze companies like Tesla, NVDA, Apple and suggest which to buy for long term"
# )