mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
26 lines
761 B
Markdown
26 lines
761 B
Markdown
|
# Databerry
|
||
|
|
|
||
|
|
This page covers how to use the [Databerry](https://databerry.ai) within LangChain.
|
||
|
|
|
||
|
|
## 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.
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
## Quick start
|
||
|
|
|
||
|
|
Retrieving documents stored in Databerry from LangChain is very easy!
|
||
|
|
|
||
|
|
```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?")
|
||
|
|
```
|