langchain/templates/plate-chain/README.md

68 lines
1.8 KiB
Markdown
Raw Normal View History

# plate-chain
This template enables parsing of data from laboratory plates.
In the context of biochemistry or molecular biology, laboratory plates are commonly used tools to hold samples in a grid-like format.
This can parse the resulting data into standardized (e.g., JSON) format for further processing.
## Environment Setup
Set the `OPENAI_API_KEY` environment variable to access the OpenAI models.
## Usage
To utilize plate-chain, you must have the LangChain CLI installed:
```shell
pip install -U "langchain-cli[serve]"
```
Creating a new LangChain project and installing plate-chain as the only package can be done with:
```shell
langchain app new my-app --package plate-chain
```
If you wish to add this to an existing project, simply run:
```shell
langchain app add plate-chain
```
Then add the following code to your `server.py` file:
```python
2023-10-31 15:34:46 +00:00
from plate_chain import chain as plate_chain
2023-10-31 15:34:46 +00:00
add_routes(app, plate_chain, path="/plate-chain")
```
(Optional) For configuring LangSmith, which helps trace, monitor and debug LangChain applications, use the following code:
```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're in this directory, you can start a LangServe instance directly by:
```shell
langchain serve
```
This starts the FastAPI app with a server running locally at
[http://localhost:8000](http://localhost:8000)
All templates can be viewed at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
Access the playground at [http://127.0.0.1:8000/plate-chain/playground](http://127.0.0.1:8000/plate-chain/playground)
You can access the template from code with:
```python
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/plate-chain")
```