Skip to content

Exa Search

ExaToolkit gives an agent four related tools powered by the Exa neural search engine: web search, find-similar, content retrieval, and AI-powered answers — all sharing a single client.

Note

Requires the exa-py package and an API key: pip install "exa-py>=2.12.1,<3"

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
import os
from autogen.beta import Agent
from autogen.beta.config import AnthropicConfig
from autogen.beta.extensions.tools.search import ExaToolkit

agent = Agent(
    "researcher",
    config=AnthropicConfig(model="claude-sonnet-4-6"),
    tools=[ExaToolkit(api_key=os.environ["EXA_API_KEY"])],
)

If api_key is omitted, the Exa SDK reads EXA_API_KEY from the environment automatically.

Tools#

Tool Description
exa_search Neural web search with filters (domains, dates, type, category)
exa_find_similar Find pages similar to a given URL
exa_get_contents Fetch full text content for specific URLs
exa_answer Get an AI-generated answer with citations

Shared defaults#

num_results and max_characters on the constructor are applied to the default exa_search and exa_find_similar tools:

1
2
3
4
5
toolkit = ExaToolkit(
    api_key=...,
    num_results=10,         # applies to search & find_similar
    max_characters=2000,    # per-result text cap for search; None = metadata-only
)

Picking a subset of tools#

Each tool is exposed as a factory method on the toolkit (toolkit.search(), toolkit.find_similar(), toolkit.get_contents(), toolkit.answer()). Call the method to get a ready-to-use tool, then pass only the ones you need to the agent:

1
2
3
4
5
6
7
toolkit = ExaToolkit(api_key=...)

agent = Agent(
    "researcher",
    config=config,
    tools=[toolkit.search(), toolkit.answer()],
)

Per-tool configuration#

Per-call parameters (filters, domains, dates, num_results, max_characters, etc.) live on the factory methods, not on the toolkit itself:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
toolkit = ExaToolkit(api_key=...)

search_tool = toolkit.search(
    num_results=5,
    max_characters=2000,           # triggers search_and_contents for full text
    search_type="neural",          # "neural" | "keyword" | "hybrid" | "auto" | "fast" | "deep"
    category="research paper",     # e.g. "news", "github", "pdf", ...
    include_domains=["arxiv.org"],
    exclude_domains=["medium.com"],
    start_published_date="2024-01-01",
    end_published_date="2024-12-31",
    use_autoprompt=True,
    livecrawl="always",            # "never" | "fallback" | "always" | "preferred"
)

agent = Agent("researcher", config=config, tools=[search_tool, toolkit.answer()])

When max_characters is set, exa_search calls Exa's search_and_contents endpoint so each result carries text. When max_characters is None, only metadata is returned (cheaper and faster).

All runtime parameters accept Variable for deferred context resolution.