wehub-resource-sync
77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
import mlflow
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mlflow.set_tracking_uri("http://localhost:5000")
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mlflow.set_experiment("AGNO Reasoning Finance Team")
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mlflow.agno.autolog()
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mlflow.anthropic.autolog()
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mlflow.openai.autolog()
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from agno.agent import Agent
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from agno.models.anthropic import Claude
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from agno.models.openai import OpenAIChat
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from agno.team.team import Team
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from agno.tools.duckduckgo import DuckDuckGoTools
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from agno.tools.reasoning import ReasoningTools
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from agno.tools.yfinance import YFinanceTools
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web_agent = Agent(
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name="Web Search Agent",
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role="Handle web search requests and general research",
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model=OpenAIChat(id="gpt-4.1"),
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tools=[DuckDuckGoTools()],
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instructions="Always include sources",
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add_datetime_to_instructions=True,
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)
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finance_agent = Agent(
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name="Finance Agent",
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role="Handle financial data requests and market analysis",
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model=OpenAIChat(id="gpt-4.1"),
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tools=[
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YFinanceTools(
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stock_price=True,
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stock_fundamentals=True,
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analyst_recommendations=True,
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company_info=True,
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)
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],
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instructions=[
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"Use tables to display stock prices, fundamentals (P/E, Market Cap), and recommendations.",
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"Clearly state the company name and ticker symbol.",
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"Focus on delivering actionable financial insights.",
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],
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add_datetime_to_instructions=True,
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)
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reasoning_finance_team = Team(
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name="Reasoning Finance Team",
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mode="coordinate",
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model=Claude(id="claude-sonnet-4-20250514"),
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members=[web_agent, finance_agent],
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tools=[ReasoningTools(add_instructions=True)],
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instructions=[
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"Collaborate to provide comprehensive financial and investment insights",
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"Consider both fundamental analysis and market sentiment",
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"Use tables and charts to display data clearly and professionally",
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"Present findings in a structured, easy-to-follow format",
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"Only output the final consolidated analysis, not individual agent responses",
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],
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markdown=True,
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show_members_responses=True,
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enable_agentic_context=True,
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add_datetime_to_instructions=True,
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success_criteria="The team has provided a complete financial analysis with data, visualizations, risk assessment, and actionable investment recommendations supported by quantitative analysis and market research.",
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)
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if __name__ == "__main__":
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reasoning_finance_team.print_response(
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"""Compare the tech sector giants (AAPL, GOOGL, MSFT) performance:
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1. Get financial data for all three companies
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2. Analyze recent news affecting the tech sector
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3. Calculate comparative metrics and correlations
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4. Recommend portfolio allocation weights""",
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stream=False,
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show_full_reasoning=True,
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)
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