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# sql-llama2
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This template enables a user to interact with a SQL database using natural language.
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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 ).
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The template includes an example database of 2023 NBA rosters.
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For more information on how to build this database, see [here ](https://github.com/facebookresearch/llama-recipes/blob/main/demo_apps/StructuredLlama.ipynb ).
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## Environment Setup
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Ensure the `REPLICATE_API_TOKEN` is set in your environment.
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## Usage
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To use this package, you should first have the LangChain CLI installed:
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```shell
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pip install -U langchain-cli
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```
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.
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/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")
```