237 lines
No EOL
6.1 KiB
Markdown
237 lines
No EOL
6.1 KiB
Markdown
## Deployment bigdl-llm serving service in K8S environment
|
|
|
|
|
|
## Image
|
|
|
|
To deploy BigDL-LLM-serving cpu in Kubernetes environment, please use this image: `intelanalytics/bigdl-llm-serving-cpu:2.4.0-SNAPSHOT`
|
|
|
|
## Before deployment
|
|
|
|
### Models
|
|
|
|
In this document, we will use `vicuna-7b-v1.5` as the deployment model.
|
|
|
|
After downloading the model, please change name from `vicuna-7b-v1.5` to `vicuna-7b-v1.5-bigdl` to use `bigdl-llm` as the backend. The `bigdl-llm` backend will be used if model path contains `bigdl`. Otherwise, the original transformer-backend will be used.
|
|
|
|
You can download the model from [here](https://huggingface.co/lmsys/vicuna-7b-v1.5).
|
|
|
|
For ChatGLM models, users do not need to add `bigdl` into model path. We have already used the `BigDL-LLM` backend for this model.
|
|
|
|
### Kubernetes config
|
|
|
|
We recommend to setup your kubernetes cluster before deployment. Mostly importantly, please set `cpu-management-policy` to `static` by using this [tutorial](https://kubernetes.io/docs/tasks/administer-cluster/cpu-management-policies/). Also, it would be great to also set the `topology management policy` to `single-numa-node`.
|
|
|
|
### Machine config
|
|
|
|
Set hyper-threading to off, ensure that only physical cores are used during deployment.
|
|
|
|
## Deployment
|
|
|
|
### Reminder on `OMP_NUM_THREADS`
|
|
|
|
The entrypoint of the image will try to set `OMP_NUM_THREADS` to the correct number by reading configs from the `runtime`. However, this only happens correctly if the `core-binding` feature is enabled. If not, please set environment variable `OMP_NUM_THREADS` manually in the yaml file.
|
|
|
|
|
|
### Controller
|
|
|
|
We use the following yaml file for controller deployment:
|
|
|
|
```yaml
|
|
apiVersion: v1
|
|
kind: Pod
|
|
metadata:
|
|
name: bigdl-fschat-a1234bd-controller
|
|
labels:
|
|
fastchat-appid: a1234bd
|
|
fastchat-app-type: controller
|
|
spec:
|
|
dnsPolicy: "ClusterFirst"
|
|
containers:
|
|
- name: fastchat-controller # fixed
|
|
image: intelanalytics/bigdl-llm-serving-cpu:2.4.0-SNAPSHOT
|
|
imagePullPolicy: IfNotPresent
|
|
env:
|
|
- name: CONTROLLER_HOST # fixed
|
|
value: "0.0.0.0"
|
|
- name: CONTROLLER_PORT # fixed
|
|
value: "21005"
|
|
- name: API_HOST # fixed
|
|
value: "0.0.0.0"
|
|
- name: API_PORT # fixed
|
|
value: "8000"
|
|
ports:
|
|
- containerPort: 21005
|
|
name: con-port
|
|
- containerPort: 8000
|
|
name: api-port
|
|
resources:
|
|
requests:
|
|
memory: 16Gi
|
|
cpu: 4
|
|
limits:
|
|
memory: 16Gi
|
|
cpu: 4
|
|
args: ["-m", "controller"]
|
|
restartPolicy: "Never"
|
|
---
|
|
# Service for the controller
|
|
apiVersion: v1
|
|
kind: Service
|
|
metadata:
|
|
name: bigdl-a1234bd-fschat-controller-service
|
|
spec:
|
|
# You may also want to change this to use the cluster's feature
|
|
type: NodePort
|
|
selector:
|
|
fastchat-appid: a1234bd
|
|
fastchat-app-type: controller
|
|
ports:
|
|
- name: cont-port
|
|
protocol: TCP
|
|
port: 21005
|
|
targetPort: 21005
|
|
- name: api-port
|
|
protocol: TCP
|
|
port: 8000
|
|
targetPort: 8000
|
|
```
|
|
|
|
### Worker
|
|
|
|
We use the following deployment for worker deployment:
|
|
|
|
```yaml
|
|
apiVersion: apps/v1
|
|
kind: Deployment
|
|
metadata:
|
|
name: bigdl-fschat-a1234bd-worker-deployment
|
|
spec:
|
|
# Change this to the number you want
|
|
replicas: 1
|
|
selector:
|
|
matchLabels:
|
|
fastchat: worker
|
|
template:
|
|
metadata:
|
|
labels:
|
|
fastchat: worker
|
|
spec:
|
|
dnsPolicy: "ClusterFirst"
|
|
containers:
|
|
- name: fastchat-worker # fixed
|
|
image: intelanalytics/bigdl-llm-serving-cpu:2.4.0-SNAPSHOT
|
|
imagePullPolicy: IfNotPresent
|
|
env:
|
|
- name: CONTROLLER_HOST # fixed
|
|
value: bigdl-a1234bd-fschat-controller-service
|
|
- name: CONTROLLER_PORT # fixed
|
|
value: "21005"
|
|
- name: WORKER_HOST # fixed
|
|
valueFrom:
|
|
fieldRef:
|
|
fieldPath: status.podIP
|
|
- name: WORKER_PORT # fixed
|
|
value: "21841"
|
|
- name: MODEL_PATH # Change this
|
|
value: "/llm/models/vicuna-7b-v1.5-bigdl/"
|
|
- name: OMP_NUM_THREADS
|
|
value: "16"
|
|
resources:
|
|
requests:
|
|
memory: 32Gi
|
|
cpu: 16
|
|
limits:
|
|
memory: 32Gi
|
|
cpu: 16
|
|
args: ["-m", "worker"]
|
|
volumeMounts:
|
|
- name: llm-models
|
|
mountPath: /llm/models/
|
|
restartPolicy: "Always"
|
|
volumes:
|
|
- name: llm-models
|
|
hostPath:
|
|
path: /home/llm/models # change this in other envs
|
|
```
|
|
|
|
You may want to change the `MODEL_PATH` variable in the yaml. Also, please remember to change the volume path accordingly.
|
|
|
|
|
|
### Testing
|
|
|
|
#### Using openai-python
|
|
|
|
First, install openai-python:
|
|
```bash
|
|
pip install --upgrade openai
|
|
```
|
|
|
|
Then, interact with model vicuna-7b-v1.5-bigdl:
|
|
```python
|
|
import openai
|
|
openai.api_key = "EMPTY"
|
|
openai.api_base = "http://localhost:8000/v1"
|
|
|
|
model = "vicuna-7b-v1.5-bigdl"
|
|
prompt = "Once upon a time"
|
|
|
|
# create a completion
|
|
completion = openai.Completion.create(model=model, prompt=prompt, max_tokens=64)
|
|
# print the completion
|
|
print(prompt + completion.choices[0].text)
|
|
|
|
# create a chat completion
|
|
completion = openai.ChatCompletion.create(
|
|
model=model,
|
|
messages=[{"role": "user", "content": "Hello! What is your name?"}]
|
|
)
|
|
# print the completion
|
|
print(completion.choices[0].message.content)
|
|
```
|
|
|
|
#### cURL
|
|
cURL is another good tool for observing the output of the api.
|
|
|
|
For the following examples, you may also change the service deployment address.
|
|
|
|
List Models:
|
|
```bash
|
|
curl http://localhost:8000/v1/models
|
|
```
|
|
|
|
If you have `jq` installed, you can use it to format the output like this:
|
|
```bash
|
|
curl http://localhost:8000/v1/models | jq
|
|
```
|
|
|
|
Chat Completions:
|
|
```bash
|
|
curl http://localhost:8000/v1/chat/completions \
|
|
-H "Content-Type: application/json" \
|
|
-d '{
|
|
"model": "YOUR_MODEL",
|
|
"messages": [{"role": "user", "content": "Hello! What is your name?"}]
|
|
}'
|
|
```
|
|
|
|
Text Completions:
|
|
```bash
|
|
curl http://localhost:8000/v1/completions \
|
|
-H "Content-Type: application/json" \
|
|
-d '{
|
|
"model": "YOUR_MODEL",
|
|
"prompt": "Once upon a time",
|
|
"max_tokens": 41,
|
|
"temperature": 0.5
|
|
}'
|
|
```
|
|
|
|
Embeddings:
|
|
```bash
|
|
curl http://localhost:8000/v1/embeddings \
|
|
-H "Content-Type: application/json" \
|
|
-d '{
|
|
"model": "YOUR_MODEL",
|
|
"input": "Hello world!"
|
|
}'
|
|
``` |