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Restful API

Launch Service

The user can open the http url print by the following command in a browser.

  • Please check the http url for the detailed api usage!!!
  • Please check the http url for the detailed api usage!!!
  • Please check the http url for the detailed api usage!!!
lmdeploy serve api_server ./workspace --server_name 0.0.0.0 --server_port ${server_port} --instance_num 64 --tp 1

We provide some RESTful APIs. Three of them are in OpenAI format.

  • /v1/chat/completions
  • /v1/models
  • /v1/completions

However, we recommend users try our own api /v1/chat/interactive which provides more arguments for users to modify. The performance is comparatively better.

Note please, if you want to launch multiple requests, you'd better set different session_id for both /v1/chat/completions and /v1/chat/interactive apis. Or, we will set them random values.

python

We have integrated the client-side functionalities of these services into the APIClient class. Below are some examples demonstrating how to invoke the api_server service on the client side.

If you want to use the /v1/chat/completions endpoint, you can try the following code:

from lmdeploy.serve.openai.api_client import APIClient
api_client = APIClient('http://{server_ip}:{server_port}')
model_name = api_client.available_models[0]
messages = [{"role": "user", "content": "Say this is a test!"}]
for item in api_client.chat_completions_v1(model=model_name, messages=messages):
    print(item)

For the /v1/completions endpoint. If you want to use the /v1/completions endpoint, you can try:

from lmdeploy.serve.openai.api_client import APIClient
api_client = APIClient('http://{server_ip}:{server_port}')
model_name = api_client.available_models[0]
for item in api_client.completions_v1(model=model_name, prompt='hi'):
    print(item)

Lmdeploy supports maintaining session histories on the server for /v1/chat/interactive api. We disable the feature by default.

  • On interactive mode, the chat history is kept on the server. In a multiple rounds of conversation, you should set interactive_mode = True and the same session_id (can't be -1, it's the default number) to /v1/chat/interactive for requests.
  • On normal mode, no chat history is kept on the server.

The interactive mode can be controlled by the interactive_mode boolean parameter. The following is an example of normal mode. If you want to experience the interactive mode, simply pass in interactive_mode=True.

from lmdeploy.serve.openai.api_client import APIClient
api_client = APIClient('http://{server_ip}:{server_port}')
for item in api_client.generate(prompt='hi'):
    print(item)

Java/Golang/Rust

May use openapi-generator-cli to convert http://{server_ip}:{server_port}/openapi.json to java/rust/golang client. Here is an example:

$ docker run -it --rm -v ${PWD}:/local openapitools/openapi-generator-cli generate -i /local/openapi.json -g rust -o /local/rust

$ ls rust/*
rust/Cargo.toml  rust/git_push.sh  rust/README.md

rust/docs:
ChatCompletionRequest.md  EmbeddingsRequest.md  HttpValidationError.md  LocationInner.md  Prompt.md
DefaultApi.md             GenerateRequest.md    Input.md                Messages.md       ValidationError.md

rust/src:
apis  lib.rs  models

cURL

cURL is a tool for observing the output of the api.

List Models:

curl http://{server_ip}:{server_port}/v1/models

Interactive Chat:

curl http://{server_ip}:{server_port}/v1/chat/interactive \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Hello! How are you?",
    "session_id": 1,
    "interactive_mode": true
  }'

Chat Completions:

curl http://{server_ip}:{server_port}/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "internlm-chat-7b",
    "messages": [{"role": "user", "content": "Hello! How are you?"}]
  }'

Text Completions:

curl http://{server_ip}:{server_port}/v1/completions \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "llama",
  "prompt": "two steps to build a house:"
}'

CLI client

There is a client script for restful api server.

# restful_api_url is what printed in api_server.py, e.g. http://localhost:23333
lmdeploy serve api_client api_server_url

webui

You can also test restful-api through webui.

# api_server_url is what printed in api_server.py, e.g. http://localhost:23333
# server_ip and server_port here are for gradio ui
# example: lmdeploy serve gradio http://localhost:23333 --server_name localhost --server_port 6006
lmdeploy serve gradio api_server_url --server_name ${gradio_ui_ip} --server_port ${gradio_ui_port}

FAQ

  1. When user got "finish_reason":"length", it means the session is too long to be continued. The session length can be modified by passing --session_len to api_server.

  2. When OOM appeared at the server side, please reduce the number of instance_num when lanching the service.

  3. When the request with the same session_id to /v1/chat/interactive got a empty return value and a negative tokens, please consider setting interactive_mode=false to restart the session.

  4. The /v1/chat/interactive api disables engaging in multiple rounds of conversation by default. The input argument prompt consists of either single strings or entire chat histories.