langchain/templates/sql-llama2/README.md

73 lines
2.2 KiB
Markdown
Raw Normal View History

# SQL - LLamA2
This template enables a user to interact with a `SQL` database using natural language.
It uses `LLamA2-13b` hosted by [Replicate](https://python.langchain.com/docs/integrations/llms/replicate), but can be adapted to any API that supports LLaMA2 including [Fireworks](https://python.langchain.com/docs/integrations/chat/fireworks).
The template includes an example database of 2023 NBA rosters.
For more information on how to build this database, see [here](https://github.com/facebookresearch/llama-recipes/blob/main/demo_apps/StructuredLlama.ipynb).
2023-10-27 23:34:37 +00:00
## Environment Setup
2023-10-27 23:34:37 +00:00
Ensure the `REPLICATE_API_TOKEN` is set in your environment.
2023-10-27 23:34:37 +00:00
## Usage
2023-10-27 23:34:37 +00:00
To use this package, you should first have the LangChain CLI installed:
2023-10-27 23:34:37 +00:00
```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 sql-llama2
```
If you want to add this to an existing project, you can just run:
```shell
langchain app add sql-llama2
```
And add the following code to your `server.py` file:
```python
from sql_llama2 import chain as sql_llama2_chain
add_routes(app, sql_llama2_chain, path="/sql-llama2")
```
(Optional) Let's now configure LangSmith.
LangSmith will help us trace, monitor and debug LangChain applications.
You can sign up for LangSmith [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/sql-llama2/playground](http://127.0.0.1:8000/sql-llama2/playground)
We can access the template from code with:
```python
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/sql-llama2")
```