langchain/templates/plate-chain/README.md

# 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
```

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
from plate_chain import chain as plate_chain

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")
```