Spaces:
Runtime error
title: Chatbot AI
emoji: 🐠
colorFrom: purple
colorTo: purple
sdk: docker
pinned: false
license: mit
app_port: 8080
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app
Installation
Install the LangChain CLI if you haven't yet
pip install -U langchain-cli
Adding packages
# 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 $PROJECT_NAME --api_path=/my/custom/path/rag
Note: you remove packages by their api path
langchain app remove my/custom/path/rag
Setup LangSmith (Optional)
LangSmith will help us trace, monitor and debug LangChain applications. LangSmith is currently in private beta, you can sign up here. If you don't have access, you can skip this section
export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
Launch LangServe
langchain serve
Running in Docker
This project folder includes a Dockerfile that allows you to easily build and host your LangServe app.
Building the Image
To build the image, you simply:
docker build . -t my-langserve-app
If you tag your image with something other than my-langserve-app
,
note it for use in the next step.
Running the Image Locally
To run the image, you'll need to include any environment variables necessary for your application.
In the below example, we inject the OPENAI_API_KEY
environment
variable with the value set in my local environment
($OPENAI_API_KEY
)
We also expose port 8080 with the -p 8080:8080
option.
docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app