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add simple chatbot definition #156

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36 changes: 36 additions & 0 deletions kubernetes_yaml/chatbot/README.md
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## Simple chatbot

This folder holds the resource definitions to launch a chatbot.
Before deploying, update the values in [configmap.yaml](./configmap.yaml) and [secret-token.yaml](./secret-token.yaml)
Specifically, `model_endpoint` value must be provided.
Optionally, `model_name` and `api_key` can be provided.

Update the deployment as necessary and
run this from the root of the repository

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```bash
oc apply --kustomize ./kubernetes_yaml/chatbot
```

### Chatbot

The chatbot image is built from
[ai-lab-recipes repository chatbot](https://github.com/containers/ai-lab-recipes/blob/main/recipes/natural_language_processing/chatbot/app/Containerfile)
with the below system prompt line from
[chatbot_ui.py](https://github.com/containers/ai-lab-recipes/blob/main/recipes/natural_language_processing/chatbot/app/chatbot_ui.py)
commented out, since it's not compatible with vLLM:

```bash
prompt = ChatPromptTemplate.from_messages([
#("system", "You are world class technical advisor."),
MessagesPlaceholder(variable_name="history"),
("user", "{input}")
])
```


## Candidate model inference service

This folder also contains an example InferenceService definition. Modify [candidate-server.yaml](./candidate-server.yaml) as needed to launch a model
from `S3` with `vLLM`.
36 changes: 36 additions & 0 deletions kubernetes_yaml/chatbot/candidate-server.yaml
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apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
annotations:
openshift.io/display-name: candidate
serving.knative.openshift.io/enablePassthrough: "true"
sidecar.istio.io/inject: "true"
sidecar.istio.io/rewriteAppHTTPProbers: "true"
finalizers:
- inferenceservice.finalizers
labels:
opendatahub.io/dashboard: "true"
name: candidatemodel
spec:
predictor:
maxReplicas: 1
minReplicas: 1
model:
modelFormat:
name: vLLM
name: ""
resources:
limits:
cpu: "2"
memory: 8Gi
nvidia.com/gpu: "1"
requests:
cpu: "1"
memory: 4Gi
nvidia.com/gpu: "1"
runtime: candidatemodel
storage:
# Update to match project s3 storage
key: storage-s3
# Update path to match candidate-server location
path: xxxxxxxx/xxxxxxxxx/pvc-to-model-op/model/phase_2/model/hf_format/candidate_model/
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If you do helm chart instead of kustomize, you can easily template this from values/CLI params. Just a thought...

7 changes: 7 additions & 0 deletions kubernetes_yaml/chatbot/configmap.yaml
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apiVersion: v1
kind: ConfigMap
metadata:
name: chatbot-config
data:
model_name: UPDATE
model_endpoint: UPDATE
40 changes: 40 additions & 0 deletions kubernetes_yaml/chatbot/deployment.yaml
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apiVersion: apps/v1
kind: Deployment
metadata:
name: chatbot
labels:
app: chatbot
spec:
replicas: 1
selector:
matchLabels:
app: chatbot
template:
metadata:
labels:
app: chatbot
spec:
serviceAccountName: chatbot-sa
containers:
- name: chatbot-inference
image: quay.io/sallyom/chatbot:vllm
env:
- name: MODEL_NAME
valueFrom:
configMapKeyRef:
name: chatbot-config
key: model_name
- name: MODEL_ENDPOINT
valueFrom:
configMapKeyRef:
name: chatbot-config
key: model_endpoint
- name: MODEL_ENDPOINT_BEARER
valueFrom:
secretKeyRef:
name: model-token
key: api_key
ports:
- containerPort: 8501
securityContext:
runAsNonRoot: true
10 changes: 10 additions & 0 deletions kubernetes_yaml/chatbot/kustomization.yaml
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apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization

resources:
- deployment.yaml
- service.yaml
- route.yaml
- sa.yaml
- configmap.yaml
- secret-token.yaml
14 changes: 14 additions & 0 deletions kubernetes_yaml/chatbot/route.yaml
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apiVersion: route.openshift.io/v1
kind: Route
metadata:
name: chatbot
labels:
app: chatbot
spec:
to:
kind: Service
name: chatbot-service
port:
targetPort: 8501
tls:
termination: edge
4 changes: 4 additions & 0 deletions kubernetes_yaml/chatbot/sa.yaml
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apiVersion: v1
kind: ServiceAccount
metadata:
name: chatbot-sa
7 changes: 7 additions & 0 deletions kubernetes_yaml/chatbot/secret-token.yaml
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apiVersion: v1
kind: Secret
metadata:
name: model-token
type: Opaque
stringData:
api_key: "xxx"
13 changes: 13 additions & 0 deletions kubernetes_yaml/chatbot/service.yaml
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apiVersion: v1
kind: Service
metadata:
name: chatbot-service
labels:
app: chatbot
spec:
selector:
app: chatbot
ports:
- protocol: TCP
port: 8501
targetPort: 8501
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