mirror of
https://github.com/hwchase17/langchain
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138 lines
4.7 KiB
Markdown
138 lines
4.7 KiB
Markdown
# LangChain Templates
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LangChain Templates are the easiest and fastest way to build a production-ready LLM application.
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These templates serve as a set of reference architectures for a wide variety of popular LLM use cases.
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They are all in a standard format which make it easy to deploy them with [LangServe](https://github.com/langchain-ai/langserve).
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🚩 We will be releasing a hosted version of LangServe for one-click deployments of LangChain applications. [Sign up here](https://airtable.com/app0hN6sd93QcKubv/shrAjst60xXa6quV2) to get on the waitlist.
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## Quick Start
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To use, first install the LangChain CLI.
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```shell
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pip install -U langchain-cli
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```
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Next, create a new LangChain project:
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```shell
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langchain app new my-app
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```
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This will create a new directory called `my-app` with two folders:
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- `app`: This is where LangServe code will live
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- `packages`: This is where your chains or agents will live
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To pull in an existing template as a package, you first need to go into your new project:
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```shell
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cd my-app
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```
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And you can the add a template as a project.
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In this getting started guide, we will add a simple `pirate-speak` project.
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All this project does is convert user input into pirate speak.
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```shell
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langchain app add pirate-speak
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```
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This will pull in the specified template into `packages/pirate-speak`
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You will then be prompted if you want to install it.
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This is the equivalent of running `pip install -e packages/pirate-speak`.
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You should generally accept this (or run that same command afterwards).
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We install it with `-e` so that if you modify the template at all (which you likely will) the changes are updated.
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After that, it will ask you if you want to generate route code for this project.
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This is code you need to add to your app to start using this chain.
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If we accept, we will see the following code generated:
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```shell
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from pirate_speak.chain import chain as pirate_speak_chain
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add_routes(app, pirate_speak_chain, path="/pirate-speak")
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```
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You can now edit the template you pulled down.
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You can change the code files in `package/pirate-speak` to use a different model, different prompt, different logic.
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Note that the above code snippet always expects the final chain to be importable as `from pirate_speak.chain import chain`,
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so you should either keep the structure of the package similar enough to respect that or be prepared to update that code snippet.
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Once you have done as much of that as you want, it is
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In order to have LangServe use this project, you then need to modify `app/server.py`.
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Specifically, you should add the above code snippet to `app/server.py` so that file looks like:
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```python
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from fastapi import FastAPI
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from langserve import add_routes
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from pirate_speak.chain import chain as pirate_speak_chain
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app = FastAPI()
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add_routes(app, pirate_speak_chain, path="/pirate-speak")
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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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For this particular application, we will use OpenAI as the LLM, so we need to export our OpenAI API key:
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```shell
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export OPENAI_API_KEY=sk-...
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```
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You can then spin up production-ready endpoints, along with a playground, by running:
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```shell
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langchain serve
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```
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This now gives a fully deployed LangServe application.
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For example, you get a playground out-of-the-box at [http://127.0.0.1:8000/pirate-speak/playground/](http://127.0.0.1:8000/pirate-speak/playground/):
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Access API documentation at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
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Use the LangServe python or js SDK to interact with the API as if it were a regular [Runnable](https://python.langchain.com/docs/expression_language/).
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```python
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from langserve import RemoteRunnable
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api = RemoteRunnable("http://127.0.0.1:8000/pirate-speak")
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api.invoke({"text": "hi"})
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```
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That's it for the quick start!
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You have successfully downloaded your first template and deployed it with LangServe.
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## Additional Resources
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### [Index of Templates](docs/INDEX.md)
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Explore the many templates available to use - from advanced RAG to agents.
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### [Contributing](docs/CONTRIBUTING.md)
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Want to contribute your own template? It's pretty easy! These instructions walk through how to do that.
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### [Launching LangServe from a Package](docs/LAUNCHING_PACKAGE.md)
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You can also launch LangServe from a package directly (without having to create a new project).
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These instructions cover how to do that.
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