mirror of
https://github.com/hwchase17/langchain
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74 lines
2.2 KiB
Markdown
74 lines
2.2 KiB
Markdown
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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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```
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To create a new LangChain project and install this as the only package, you can do:
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```shell
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langchain app new my-app --package sql-llama2
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```
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If you want to add this to an existing project, you can just run:
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```shell
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langchain app add sql-llama2
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```
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And add the following code to your `server.py` file:
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```python
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from sql_llama2 import chain as sql_llama2_chain
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add_routes(app, sql_llama2_chain, path="/sql-llama2")
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```
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(Optional) Let's now configure LangSmith.
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LangSmith will help us trace, monitor and debug LangChain applications.
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LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
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If you don't have access, you can skip this section
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```shell
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export LANGCHAIN_TRACING_V2=true
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export LANGCHAIN_API_KEY=<your-api-key>
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export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
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```
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If you are inside this directory, then you can spin up a LangServe instance directly by:
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```shell
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langchain serve
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```
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This will start the FastAPI app with a server is running locally at
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[http://localhost:8000](http://localhost:8000)
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We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
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We can access the playground at [http://127.0.0.1:8000/sql-llama2/playground](http://127.0.0.1:8000/sql-llama2/playground)
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We can access the template from code with:
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```python
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from langserve.client import RemoteRunnable
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runnable = RemoteRunnable("http://localhost:8000/sql-llama2")
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```
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