https://github.com/maxtheman/langserve_test

https://github.com/maxtheman/langserve_test

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/maxtheman/langserve_test
• Owner: maxtheman
• Created: 2023-11-21T20:57:13.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-21T22:52:21.000Z (about 1 year ago)
• Last Synced: 2024-04-24T11:20:51.522Z (9 months ago)
• Language: Python
• Size: 90.8 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# langserve_test

## Installation

Install the LangChain CLI if you haven't yet

```bash

pip install -U langchain-cli

```

## Adding packages

```bash

# adding packages from 

# https://github.com/langchain-ai/langchain/tree/master/templates

langchain app add $PROJECT_NAME

# adding custom GitHub repo packages

langchain app add --repo $OWNER/$REPO

# or with whole git string (supports other git providers):

# langchain app add git+https://github.com/hwchase17/chain-of-verification

# with a custom api mount point (defaults to `/{package_name}`)

langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag

```

Note: you remove packages by their api path

```bash

langchain app remove my/custom/path/rag

```

## Setup LangSmith (Optional)

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=

export LANGCHAIN_PROJECT=  # if not specified, defaults to "default"

```

## Launch LangServe

```bash

langchain serve

```

## Running in Docker

This project folder includes a Dockerfile that allows you to easily build and host your LangServe app.

### Building the Image

To build the image, you simply:

```shell

docker build . -t my-langserve-app

```

If you tag your image with something other than `my-langserve-app`,

note it for use in the next step.

### Running the Image Locally

To run the image, you'll need to include any environment variables

necessary for your application.

In the below example, we inject the `OPENAI_API_KEY` environment

variable with the value set in my local environment

(`$OPENAI_API_KEY`)

We also expose port 8080 with the `-p 8080:8080` option.

```shell

docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app

```