CodeGen¶
Helm chart for deploying CodeGen service.
CodeGen depends on LLM and tgi microservice, refer to llm-uservice and tgi for more config details.
Installing the Chart¶
To install the chart, run the following:
cd GenAIInfra/helm-charts/
./update_dependency.sh
helm dependency update codegen
export HFTOKEN="insert-your-huggingface-token-here"
export MODELDIR="/mnt/opea-models"
export MODELNAME="meta-llama/CodeLlama-7b-hf"
# To run on Xeon
helm install codegen codegen --set global.HUGGINGFACEHUB_API_TOKEN=${HFTOKEN} --set global.modelUseHostPath=${MODELDIR} --set tgi.LLM_MODEL_ID=${MODELNAME}
# To run on Gaudi
#helm install codegen codegen --set global.HUGGINGFACEHUB_API_TOKEN=${HFTOKEN} --set global.modelUseHostPath=${MODELDIR} --set tgi.LLM_MODEL_ID=${MODELNAME} -f codegen/gaudi-values.yaml
IMPORTANT NOTE¶
To use model
meta-llama/CodeLlama-7b-hf
, you should first goto the huggingface model card to apply for the model access first. You need to make sure your huggingface token has at least read access to that model.Make sure your
MODELDIR
exists on the node where your workload is schedueled so you can cache the downloaded model for next time use. Otherwise, setglobal.modelUseHostPath
to ‘null’ if you don’t want to cache the model.
Verify¶
To verify the installation, run the command kubectl get pod
to make sure all pods are running.
Curl command and UI are the two options that can be leveraged to verify the result.
Verify the workload through curl command¶
Then run the command kubectl port-forward svc/codegen 7778:7778
to expose the service for access.
Open another terminal and run the following command to verify the service if working:
curl http://localhost:7778/v1/codegen \
-H "Content-Type: application/json" \
-d '{"messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}'
Verify the workload through UI¶
The UI has already been installed via the Helm chart. To access it, use the external IP of one your Kubernetes node along with the NGINX port. You can find the NGINX port using the following command:
export port=$(kubectl get service codegen-nginx --output='jsonpath={.spec.ports[0].nodePort}')
echo $port
Open a browser to access http://<k8s-node-ip-address>:${port}
to play with the ChatQnA workload.
Values¶
Key |
Type |
Default |
Description |
---|---|---|---|
image.repository |
string |
|
|
service.port |
string |
|
|
tgi.LLM_MODEL_ID |
string |
|
Models id from https://huggingface.co/, or predownloaded model directory |