Reasoning Finance Agent

Compares built-in chain-of-thought with a deepseek-reasoner reasoning model on gpt-4o YFinance agents writing an NVDA vs TSLA report.

Demonstrates DeepSeek-backed reasoning with tools for financial reporting.

finance_agent.py

"""
Reasoning Finance Agent
=======================

Demonstrates DeepSeek-backed reasoning with tools for financial reporting.
"""

from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIResponses
from agno.tools.yfinance import YFinanceTools

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    model=OpenAIResponses(id="gpt-5.6"),
    tools=[YFinanceTools()],
    instructions=["Use tables where possible"],
    reasoning_model=DeepSeek(id="deepseek-reasoner"),
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    agent.print_response(
        "Write a report comparing NVDA to TSLA",
        stream=True,
        show_full_reasoning=True,
    )

Run the Example

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
2. Install dependencies

   uv pip install -U agno openai yfinance
   
3. Export your API keys

   Mac/Linux

   export DEEPSEEK_API_KEY="your_deepseek_api_key_here"
   export OPENAI_API_KEY="your_openai_api_key_here"
   
4. Run the example

   Save the code above as finance_agent.py, then run:

   python finance_agent.py
   

Full source: cookbook/10_reasoning/agents/finance_agent.py