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Documentation Index

Fetch the complete documentation index at: https://exa.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

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What this doc covers

  1. What Phrase filters are and how they work
  2. Using ‘Phrase Filters’ to find specific results, in this case filtering by a foreign company suffix
In this simple example, we’ll demonstrate a company discovery search that helps find relevant companies incorporated in the Germany (and a few nearby countries) via Phrase Filters. This example will use the fact that companies incorporated in these locations have a suffix of GmbH, which is a term in the region similar to the US ‘incorporated’.

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How Phrase Filters work

Exa’s search combines semantic relevance with precise filtering: a semantic query first retrieves contextually relevant documents, then a phrase filter refines these results by checking for specific text in the content. This two-stage approach delivers highly targeted outputs by leveraging both semantic understanding and exact text matching.

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Running a query with phrase filter

Using Phrase Filters is super simple. As usual, install the exa_py library with pip install exa_py. Then instantiate the library:
Python
# Now, import the Exa class and pass your API key to it.
from exa_py import Exa

my_exa_api_key = "YOUR_API_KEY_HERE"
exa = Exa(api_key=my_exa_api_key)
Make a query, in this example searching for the most innovative climate tech companies. To use Phrase Filters, specify a string corresponding to the includeText input parameter
Python
result = exa.search(
  "Here is an innovative climate technology company",
  type="auto",
  num_results=10,
  contents={"highlights": True},
	include_text=["GmbH"]
)

print(result)
Which outputs: 
{
  "results": [
    {
      "title": "Sorption Technologies |",
      "id": "https://sorption-technologies.com/",
      "url": "https://sorption-technologies.com/",
      "publishedDate": "2024-02-10",
      "author": null,
      "highlights": [
        "Sorption Technologies GmbH develops materials for energy-efficient carbon capture and storage."
      ],
      "highlightScores": [0.86]
    },
    {
      "title": "intelligent fluids | LinkedIn",
      "id": "https://www.linkedin.com/company/intelligentfluids",
      "url": "https://www.linkedin.com/company/intelligentfluids",
      "publishedDate": "2023-06-08",
      "author": null,
      "highlights": [
        "intelligent fluids GmbH develops sustainable industrial cleaning fluids for reducing waste and emissions."
      ],
      "highlightScores": [0.79]
    },
    {
      "title": "Green City Solutions",
      "id": "https://www.greentalents.de/green-city-solutions.php",
      "url": "https://www.greentalents.de/green-city-solutions.php",
      "publishedDate": "2022-04-12",
      "author": null,
      "highlights": [
        "Green City Solutions GmbH combines moss with Internet of Things technology to clean and cool urban air."
      ],
      "highlightScores": [0.74]
    }
  ],
  "requestId": "a02fd414d9ca16454089e8720cd6ed2b"
}
Nice! On inspection, these results include companies located in Hamburg, Munich and other close by European locations. This example can be extended to any key phrase - have a play with filtering via other company suffixes - and see what interesting results you get back!