mirror of
https://github.com/hwchase17/langchain
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32 lines
999 B
Markdown
32 lines
999 B
Markdown
# elastic-query-generator
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We can use LLMs to interact with Elasticsearch analytics databases in natural language.
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This chain builds search queries via the Elasticsearch DSL API (filters and aggregations).
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The Elasticsearch client must have permissions for index listing, mapping description and search queries.
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## Setup
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## Installing Elasticsearch
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There are a number of ways to run Elasticsearch.
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### Elastic Cloud
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Create a free trial account on [Elastic Cloud](https://cloud.elastic.co/registration?utm_source=langchain&utm_content=langserve).
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With a deployment, update the connection string.
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Password and connection (elasticsearch url) can be found on the deployment console. Th
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## Populating with data
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If you want to populate the DB with some example info, you can run `python ingest.py`.
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This will create a `customers` index.
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In the chain, we specify indexes to generate queries against, and we specify `["customers"]`.
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This is specific to setting up your Elastic index in this
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