github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-09-16 06:53:16 +00:00
Code Issues Packages Projects Releases Wiki Activity

Readme rewrite (#12615)

Browse Source 
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Erick Friis
2023-10-31 00:06:02 -07:00
committed by GitHub
parent 00766c9f31
commit a1fae1fddd
60 changed files with 2669 additions and 675 deletions
Download Patch File Download Diff File Expand all files Collapse all files

74
templates/sql-llama2/README.md
View File

@@ -1,21 +1,73 @@
# SQL with LLaMA2
This template allows you to chat with a SQL database in natural language using LLaMA2.
# sql-llama2
It is configured to use [Replicate](https://python.langchain.com/docs/integrations/llms/replicate).
This template enables a user to interact with a SQL database using natural language.
But, it can be adapted to any API that support LLaMA2, including [Fireworks](https://python.langchain.com/docs/integrations/chat/fireworks) and others.
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).
See related templates `sql-ollama` and `sql-llamacpp` for private, local chat with SQL.
The template includes an example database of 2023 NBA rosters.
## Set up SQL DB
For more information on how to build this database, see [here](https://github.com/facebookresearch/llama-recipes/blob/main/demo_apps/StructuredLlama.ipynb).
This template includes an example DB of 2023 NBA rosters.
## Environment Setup
You can see instructions to build this DB [here](https://github.com/facebookresearch/llama-recipes/blob/main/demo_apps/StructuredLlama.ipynb).
Ensure the `REPLICATE_API_TOKEN` is set in your environment.
## LLM
## Usage
This template will use a `Replicate` [hosted version](https://replicate.com/meta/llama-2-13b-chat/versions/f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d) of LLaMA2.
To use this package, you should first have the LangChain CLI installed:
Be sure that `REPLICATE_API_TOKEN` is set in your environment.
```shell
pip install -U "langchain-cli[serve]"
```
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")
```