github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-09-06 21:43:44 +00:00
Code Issues Packages Projects Releases Wiki Activity

docs ecosystem/integrations update 4 (#5590)

Browse Source 
# docs `ecosystem/integrations` update 4

Added missed integrations. Fixed inconsistencies. 

## Who can review?

@hwchase17 
@dev2049
This commit is contained in:
Leonid Ganeline
2023-06-03 15:29:03 -07:00
committed by GitHub
parent ae3611730a
commit b201cfaa0f
32 changed files with 592 additions and 132 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
docs/integrations/databerry.md
View File

@@ -1,25 +1,17 @@
# Databerry
This page covers how to use the [Databerry](https://databerry.ai) within LangChain.
>[Databerry](https://databerry.ai) is an [open source](https://github.com/gmpetrov/databerry) document retrieval platform that helps to connect your personal data with Large Language Models.
## What is Databerry?
Databerry is an [open source](https://github.com/gmpetrov/databerry) document retrievial platform that helps to connect your personal data with Large Language Models.
## Installation and Setup
![Databerry](../_static/DataberryDashboard.png)
We need to sign up for Databerry, create a datastore, add some data and get your datastore api endpoint url.
We need the [API Key](https://docs.databerry.ai/api-reference/authentication).
## Quick start
## Retriever
Retrieving documents stored in Databerry from LangChain is very easy!
See a [usage example](../modules/indexes/retrievers/examples/databerry.ipynb).
```python
from langchain.retrievers import DataberryRetriever
retriever = DataberryRetriever(
datastore_url="https://api.databerry.ai/query/clg1xg2h80000l708dymr0fxc",
# api_key="DATABERRY_API_KEY", # optional if datastore is public
# top_k=10 # optional
)
docs = retriever.get_relevant_documents("What's Databerry?")
```