mirror of
https://github.com/hwchase17/langchain
synced 2024-11-08 07:10:35 +00:00
91 lines
2.7 KiB
Markdown
91 lines
2.7 KiB
Markdown
|
|
# neo4j_cypher
|
|
|
|
This template allows you to interact with a Neo4j graph database in natural language, using an OpenAI LLM.
|
|
|
|
It transforms a natural language question into a Cypher query (used to fetch data from Neo4j databases), executes the query, and provides a natural language response based on the query results.
|
|
|
|
## Environment Setup
|
|
|
|
Define the following environment variables:
|
|
|
|
```
|
|
OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
|
|
NEO4J_URI=<YOUR_NEO4J_URI>
|
|
NEO4J_USERNAME=<YOUR_NEO4J_USERNAME>
|
|
NEO4J_PASSWORD=<YOUR_NEO4J_PASSWORD>
|
|
```
|
|
|
|
## Neo4j database setup
|
|
|
|
There are a number of ways to set up a Neo4j database.
|
|
|
|
### Neo4j Aura
|
|
|
|
Neo4j AuraDB is a fully managed cloud graph database service.
|
|
Create a free instance on [Neo4j Aura](https://neo4j.com/cloud/platform/aura-graph-database?utm_source=langchain&utm_content=langserve).
|
|
When you initiate a free database instance, you'll receive credentials to access the database.
|
|
|
|
## Populating with data
|
|
|
|
If you want to populate the DB with some example data, you can run `python ingest.py`.
|
|
This script will populate the database with sample movie data.
|
|
|
|
## Usage
|
|
|
|
To use this package, you should first have the LangChain CLI installed:
|
|
|
|
```shell
|
|
pip install -U langchain-cli
|
|
```
|
|
|
|
To create a new LangChain project and install this as the only package, you can do:
|
|
|
|
```shell
|
|
langchain app new my-app --package neo4j-cypher
|
|
```
|
|
|
|
If you want to add this to an existing project, you can just run:
|
|
|
|
```shell
|
|
langchain app add neo4j-cypher
|
|
```
|
|
|
|
And add the following code to your `server.py` file:
|
|
```python
|
|
from neo4j_cypher import chain as neo4j_cypher_chain
|
|
|
|
add_routes(app, neo4j_cypher_chain, path="/neo4j-cypher")
|
|
```
|
|
|
|
(Optional) Let's now configure LangSmith.
|
|
LangSmith will help us trace, monitor and debug LangChain applications.
|
|
LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
|
|
If you don't have access, you can skip this section
|
|
|
|
```shell
|
|
export LANGCHAIN_TRACING_V2=true
|
|
export LANGCHAIN_API_KEY=<your-api-key>
|
|
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
|
|
```
|
|
|
|
If you are inside this directory, then you can spin up a LangServe instance directly by:
|
|
|
|
```shell
|
|
langchain serve
|
|
```
|
|
|
|
This will start the FastAPI app with a server is running locally at
|
|
[http://localhost:8000](http://localhost:8000)
|
|
|
|
We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
|
|
We can access the playground at [http://127.0.0.1:8000/neo4j_cypher/playground](http://127.0.0.1:8000/neo4j_cypher/playground)
|
|
|
|
We can access the template from code with:
|
|
|
|
```python
|
|
from langserve.client import RemoteRunnable
|
|
|
|
runnable = RemoteRunnable("http://localhost:8000/neo4j-cypher")
|
|
```
|