Skip to main content

An integration package connecting Snowflake and LangChain

Project description

langchain-snowflake

This package contains the LangChain integration with Snowflake

Installation

pip install -U langchain-snowflake

You can authenticate by one of the following ways:

  1. Configure credentials by setting the following environment variables:

SNOWFLAKE_USERNAME should hold your Snowflake username.

SNOWFLAKE_PASSWORD should hold your Snowflake password.

SNOWFLAKE_DATABASE should hold a Snowflake database to operate in.

SNOWFLAKE_SCHEMA should hold the name of the schema to operate in.

SNOWFLAKE_ROLE should contain the name of the appropriate Snowflake role.

SNOWFLAKE_AUTHENTICATOR should contain the name of Snowflake authentication method, if not using username/password authentication.

Any of these paramaters can also be passed directly into the CortexSearchRetriever constructor. Those not passed will be inferred from the environment. For instance:

from langchain_snowflake.search_retriever import CortexSearchRetriever

search = CortexSearchRetriever(
        role="snowflake_role",
        database="your_db",
        schema="your_schema",
        service="your_cortex_search_service_name",
        search_column="search_column_name",
)

Here, role, database, and schema are passed directly, while SNOWFLAKE_USERNAME, SNOWFLAKE_PASSWORD, and SNOWFLAKE_AUTHENTICATOR are inferred from the environment.

If the SNOWFLAKE_AUTHENTICATOR environment variable or authenticator property is set to externalbrowser, the SNOWFLAKE_PASSWORD/password need not be provided. externalbrowser auth will prompt to log in through an browser popup instead.

  1. Alternatively, you can pass in a snowflake.snowpark.Session directly into the constructor. See the Snowflake docs on how to create such a session.
from langchain_snowflake.search_retriever import CortexSearchRetriever
from snowflake.snowpark import Session

# Create a snowflake session
snowflake_session = Session.builder.config(...).create()

search = CortexSearchRetriever(
        session=snowflake_session,
        service="your_cortex_search_service_name",
        search_column="search_column_name",
)

Search Retriever

CortexSearchRetriever is a Third Party Retriever that allows users to utilize their Cortex Search Service within Langchain.

Given the service name and columns to search, the retriever will return matches found within the dataset with which the Cortex Search Service is associated.

from langchain_snowflake.search_retriever import CortexSearchRetriever

search = CortexSearchRetriever(
        service="your_cortex_search_service_name",
        search_column="<search_column_name>",
        columns=["<col1>", "<col2>"],
        filter={"@eq": {"<column>": "<value>"}},
        limit=5
)

query="foo bar"
result = search.invoke(query)
for doc in result:
    print(doc)

The class requires the arguments below: service corresponds to the name of your Cortex Search Service.

search_column is the search column of the Cortex Search Service.

columns corresponds to the columns to return in the search. If null or an empty list, only the search_column will be returned.

filter is an optional argument corresponding to any filters that should be utilized when searching.

limit corresponds to the number of search hits to return.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

langchain_snowflake-0.1.0.tar.gz (6.6 kB view details)

Uploaded Source

Built Distribution

langchain_snowflake-0.1.0-py3-none-any.whl (7.2 kB view details)

Uploaded Python 3

File details

Details for the file langchain_snowflake-0.1.0.tar.gz.

File metadata

  • Download URL: langchain_snowflake-0.1.0.tar.gz
  • Upload date:
  • Size: 6.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for langchain_snowflake-0.1.0.tar.gz
Algorithm Hash digest
SHA256 36014d48c635f60f4fd1e48b8610d2430da64f49893c9cf50ff995adbacdd8f2
MD5 bdac980eaef1321dc282fae1563753ff
BLAKE2b-256 95d9cb131e2f90cac084f4f6a29abcec7a808f07e9a0ccb1a9ad2b34ab3aafb4

See more details on using hashes here.

File details

Details for the file langchain_snowflake-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for langchain_snowflake-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8f65027e607eed317cf1127ae0de383608eec5c843257f64b05cab1c9d1b4d12
MD5 796db4d2aaba7fa9b01264ad06cf802c
BLAKE2b-256 d14669c27fe0cd6bc09c4810b6de07facef1978a43a7013d6154d2d6ffe8c0b6

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page