suifei / chatglm-6b-api

chatglm-6b-api

ChatGLM-6B API

chatbot-ui to chat.

chatbot-ui

CPU&GPU

download model

1.llm

git clone https://huggingface.co/THUDM/chatglm-6b-int4

2. text2vec

git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese

run prod server

Running on port 6006, for the convenience of deployment on audodl.

gunicorn -c gunicorn.conf.py main:app

实现的接口

List models

GET /v1/models

Example request

curl https://127.0.0.1:8000/v1/models \
  -H "Authorization: Bearer $API_KEY"

Response

{
  "data": [
    {
      "id": "model-id-0",
      "object": "model",
      "owned_by": "organization-owner",
      "permission": [...]
    },
    {
      "id": "model-id-1",
      "object": "model",
      "owned_by": "organization-owner",
      "permission": [...]
    },
    {
      "id": "model-id-2",
      "object": "model",
      "owned_by": "openai",
      "permission": [...]
    },
  ],
  "object": "list"
}

Create Chat Completion

POST /v1/chat/completions Example request

curl https://127.0.0.1:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $API_KEY" \
  -d '{
    "model": "gpt-3.5-turbo",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Parameters

{
  "model": "gpt-3.5-turbo",
  "messages": [{"role": "user", "content": "Hello!"}]
}

Response

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "\n\nHello there, how may I assist you today?",
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 12,
    "total_tokens": 21
  }
}

Create embeddings

POST /v1/embeddings

Example request

curl https://127.0.0.1:8000/v1/embeddings \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "The food was delicious and the waiter...",
    "model": "text-embedding-ada-002"
  }'

Parameters

{
  "model": "text-embedding-ada-002",
  "input": "The food was delicious and the waiter..."
}

Response

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        .... (1536 floats total for ada-002)
        -0.0028842222,
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-ada-002",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}

create conda env

conda create -n llm_py38 python=3.8
conda activate llm_py38

poetry env

pip install poetry
poetry config virtualenvs.create false

arm macos torch

Accelerated PyTorch training on Mac

conda install pytorch torchvision torchaudio -c pytorch-nightly

check if torch is installed

import torch
if torch.backends.mps.is_available():
    mps_device = torch.device("mps")
    x = torch.ones(1, device=mps_device)
    print (x)
else:
    print ("MPS device not found.")

output

tensor([1.], device='mps:0')

fix charset-normalizer error

pip install --force-reinstall charset-normalizer==3.1.0

poe install

poetry install

dev start server

uvicorn main:app --reload

test streaming response

echo '{
  "model": "gpt-3.5-turbo",
  "messages": [
    {"role": "system", "content": "你是一个上海旅游专家"},
    {"role": "user", "content": "上海哪里好玩"},
    {"role": "assistant", "content": "城隍庙不错"},
    {"role": "user", "content": "那里是玩什么的"}
  ],
  "stream": true
}' | http -S POST http://localhost:8000/v1/chat/completions/