mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
80 lines
1.9 KiB
Markdown
80 lines
1.9 KiB
Markdown
# __app_name__
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## Installation
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Install the LangChain CLI if you haven't yet
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```bash
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pip install -U langchain-cli
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```
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## Adding packages
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```bash
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# adding packages from
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# https://github.com/langchain-ai/langchain/tree/master/templates
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langchain app add $PROJECT_NAME
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# adding custom GitHub repo packages
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langchain app add --repo $OWNER/$REPO
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# or with whole git string (supports other git providers):
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# langchain app add git+https://github.com/hwchase17/chain-of-verification
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# with a custom api mount point (defaults to `/{package_name}`)
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langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag
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```
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Note: you remove packages by their api path
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```bash
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langchain app remove my/custom/path/rag
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```
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## Setup LangSmith (Optional)
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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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## Launch LangServe
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```bash
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langchain serve
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```
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## Running in Docker
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This project folder includes a Dockerfile that allows you to easily build and host your LangServe app.
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### Building the Image
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To build the image, you simply:
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```shell
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docker build . -t my-langserve-app
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```
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If you tag your image with something other than `my-langserve-app`,
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note it for use in the next step.
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### Running the Image Locally
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To run the image, you'll need to include any environment variables
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necessary for your application.
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In the below example, we inject the `OPENAI_API_KEY` environment
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variable with the value set in my local environment
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(`$OPENAI_API_KEY`)
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We also expose port 8080 with the `-p 8080:8080` option.
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```shell
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docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app
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```
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