Groq Llama Finance Agent

This example shows how to use ReasoningTools with a Groq Llama model.

Code

cookbook/reasoning/tools/groq_llama_finance_agent.py

from textwrap import dedent

from agno.agent import Agent
from agno.models.groq import Groq
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.reasoning import ReasoningTools

thinking_llama = Agent(
    model=Groq(id="meta-llama/llama-4-scout-17b-16e-instruct"),
    tools=[
        ReasoningTools(),
        DuckDuckGoTools(),
    ],
    instructions=dedent("""\
    ## General Instructions
    - Always start by using the think tool to map out the steps needed to complete the task.
    - After receiving tool results, use the think tool as a scratchpad to validate the results for correctness
    - Before responding to the user, use the think tool to jot down final thoughts and ideas.
    - Present final outputs in well-organized tables whenever possible.

    ## Using the think tool
    At every step, use the think tool as a scratchpad to:
    - Restate the object in your own words to ensure full comprehension.
    - List the  specific rules that apply to the current request
    - Check if all required information is collected and is valid
    - Verify that the planned action completes the task\
    """),
    markdown=True,
)
thinking_llama.print_response("Write a report comparing NVDA to TSLA", stream=True)

Usage

1. Create a virtual environment

   Open the Terminal and create a python virtual environment.

   Mac

   python3 -m venv .venv
   source .venv/bin/activate
   
2. Set your API key

   export GROQ_API_KEY=xxx
   
3. Install libraries

   pip install -U groq agno ddgs
   
4. Run Example

   Mac

   python cookbook/reasoning/tools/groq_llama_finance_agent.py