mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
45 lines
1.5 KiB
Plaintext
45 lines
1.5 KiB
Plaintext
# Neo4j
|
|
|
|
This page covers how to use the Neo4j ecosystem within LangChain.
|
|
|
|
What is Neo4j?
|
|
|
|
**Neo4j in a nutshell:**
|
|
|
|
- Neo4j is an open-source database management system that specializes in graph database technology.
|
|
- Neo4j allows you to represent and store data in nodes and edges, making it ideal for handling connected data and relationships.
|
|
- Neo4j provides a Cypher Query Language, making it easy to interact with and query your graph data.
|
|
- With Neo4j, you can achieve high-performance graph traversals and queries, suitable for production-level systems.
|
|
- Get started quickly with Neo4j by visiting [their website](https://neo4j.com/).
|
|
|
|
## Installation and Setup
|
|
|
|
- Install the Python SDK with `pip install neo4j`
|
|
|
|
## Wrappers
|
|
|
|
### VectorStore
|
|
|
|
There exists a wrapper around Neo4j vector index, allowing you to use it as a vectorstore,
|
|
whether for semantic search or example selection.
|
|
|
|
To import this vectorstore:
|
|
|
|
```python
|
|
from langchain.vectorstores import Neo4jVector
|
|
```
|
|
|
|
For a more detailed walkthrough of the Neo4j vector index wrapper, see [this notebook](/docs/integrations/vectorstores/neo4jvector.html)
|
|
|
|
### GraphCypherQAChain
|
|
|
|
There exists a wrapper around Neo4j graph database that allows you to generate Cypher statements based on the user input
|
|
and use them to retrieve relevant information from the database.
|
|
|
|
```python
|
|
from langchain.graphs import Neo4jGraph
|
|
from langchain.chains import GraphCypherQAChain
|
|
```
|
|
|
|
For a more detailed walkthrough of Cypher generating chain, see [this notebook](/docs/use_cases/more/graph/graph_cypher_qa.html)
|