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# my-app |
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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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