> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Research Agent Exa

> Research a topic with Exa search on Groq and save the markdown report to a file.

```python research_agent_exa.py theme={null}
"""Run `uv pip install groq exa-py` to install dependencies."""

from datetime import datetime
from pathlib import Path
from textwrap import dedent

from agno.agent import Agent
from agno.models.groq import Groq
from agno.tools.exa import ExaTools

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

cwd = Path(__file__).parent.resolve()
tmp = cwd.joinpath("tmp")
if not tmp.exists():
    tmp.mkdir(exist_ok=True, parents=True)

today = datetime.now().strftime("%Y-%m-%d")

agent = Agent(
    model=Groq(id="openai/gpt-oss-120b"),
    tools=[ExaTools(start_published_date=today, type="keyword")],
    description="You are an advanced AI researcher writing a report on a topic.",
    instructions=[
        "For the provided topic, run 3 different searches.",
        "Read the results carefully and prepare a NYT worthy report.",
        "Focus on facts and make sure to provide references.",
    ],
    expected_output=dedent("""\
    An engaging, informative, and well-structured report in markdown format:

    ## Engaging Report Title

    ### Overview
    {give a brief introduction of the report and why the user should read this report}
    {make this section engaging and create a hook for the reader}

    ### Section 1
    {break the report into sections}
    {provide details/facts/processes in this section}

    ... more sections as necessary...

    ### Takeaways
    {provide key takeaways from the article}

    ### References
    - [Reference 1](link)
    - [Reference 2](link)
    - [Reference 3](link)

    ### About the Author
    {write a made up for yourself, give yourself a cyberpunk name and a title}

    - published on {date} in dd/mm/yyyy
    """),
    markdown=True,
    add_datetime_to_context=True,
    save_response_to_file=str(tmp.joinpath("{message}.md")),
)
agent.print_response("Llama 3.3 running on Groq", stream=True)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass
```

## Run the Example

<Snippet file="create-venv-step.mdx" />

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno exa-py groq
```

**2. Export your API keys**

```bash Mac/Linux theme={null}
export EXA_API_KEY="your_exa_api_key_here"
export GROQ_API_KEY="your_groq_api_key_here"
```

```bash Windows theme={null}
$Env:EXA_API_KEY="your_exa_api_key_here"
$Env:GROQ_API_KEY="your_groq_api_key_here"
```

**3. Run the example**

Save the code above as `research_agent_exa.py`, then run:

```bash theme={null}
python research_agent_exa.py
```

Full source: [cookbook/90\_models/groq/research\_agent\_exa.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/90_models/groq/research_agent_exa.py)


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