Support Databricks in SQLDatabase #4702
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gengliangwang
commented
May 17, 2023
mengxr
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May 18, 2023
dev2049
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May 19, 2023
langchain/sql_database.py
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| f"databricks://token:{api_token}@{host}?" | ||
| f"http_path={http_path}&catalog={catalog}&schema={schema}" | ||
| ) | ||
| return cls.from_uri(uri, engine_args=None, **kwargs) |
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out of curiosity are engine_args explicitly not allowed in this case?
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Thanks for pointing it out. I just added the engine_args
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I just verified it:
dev2049
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May 19, 2023
hwchase17
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May 21, 2023
# Add documentation for Databricks integration This is a follow-up of #4702 It documents the details of how to integrate Databricks using langchain. It also provides examples in a notebook. ## Who can review? @dev2049 @hwchase17 since you are aware of the context. We will promote the integration after this doc is ready. Thanks in advance!
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This PR adds support for Databricks runtime and Databricks SQL by using Databricks SQL Connector for Python.
As a cloud data platform, accessing Databricks requires a URL as follows
databricks://token:{api_token}@{hostname}?http_path={http_path}&catalog={catalog}&schema={schema}.The URL is complicated and it may take users a while to figure it out. Since the fields
api_token/hostname/http_pathfields are known in the Databricks notebook, I am proposing a new methodfrom_databricksto simplify the connection to Databricks.In Databricks Notebook
After changes, Databricks users only need to specify the
catalogandschemafield when using langchain.In Jupyter Notebook
The method can be used on the local setup as well:
