spirit-gpu


Namespirit-gpu JSON
Version 0.0.6 PyPI version JSON
download
home_pagehttps://github.com/datastone-spirit
SummaryPython serverless framework for Datastone Spirit GPU.
upload_time2024-11-15 06:18:14
maintainerNone
docs_urlNone
authorspirit
requires_python>=3.9
licenseMIT License
keywords serverless ai gpu machine learning sdk library python api
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Spirit-GPU

- [Spirit-GPU](#spirit-gpu)
  - [Install](#install)
  - [Usage example](#usage-example)
  - [Logging](#logging)
  - [API](#api)
  - [Builder](#builder)

## Install
```
pip install spirit-gpu
```

## Usage example

```python
from spirit_gpu import start
from spirit_gpu.env import Env
from typing import Dict, Any

def handler(request: Dict[str, Any], env: Env):
    """
    request: Dict[str, Any], from client http request body.
    request["input"]: Required.
    request["webhook"]: Optional string for asynchronous requests.

    returned object to be serialized into JSON and sent to the client.
    in this case: '{"output": "hello"}'
    """
    return {"output": "hello"}


def gen_handler(request: Dict[str, Any], env: Env):
    """
    append yield output to array, serialize into JSON and send to client.
    in this case: [0, 1, 2, 3, 4]
    """
    for i in range(5):
        yield i


async def async_handler(request: Dict[str, Any], env: Env):
    """
    returned object to be serialized into JSON and sent to the client.
    """
    return {"output": "hello"}


async def async_gen_handler(request: Dict[str, Any], env: Env):
    """
    append yield output to array, serialize into JSON and send to client.
    """
    for i in range(10):
        yield i


def concurrency_modifier(current_allowed_concurrency: int) -> int:
    """
    Adjusts the allowed concurrency level based on the current state.
    For example, if the current allowed concurrency is 3 and resources are sufficient,
    it can be increased to 5, allowing 5 tasks to run concurrently.
    """
    allowed_concurrency = ...
    return allowed_concurrency


"""
Register the handler with serverless.start().
Handlers can be synchronous, asynchronous, generators, or asynchronous generators.
"""
start({
    "handler": async_handler, "concurrency_modifier": concurrency_modifier
})
```

## Logging
We provide a tool to log information. Default logging level is "INFO", you can call `logger.set_level(logging.DEBUG)` to change it.

> Please make sure you update to the `latest` version to use this feature.
```python
from spirit_gpu import start, logger
from spirit_gpu.env import Env
from typing import Dict, Any


def handler(request: Dict[str, Any], env: Env):
    """
    request: Dict[str, Any], from client http request body.
    request["input"]: Required.
    request["webhook"]: Optional string for asynchronous requests.

    we will only add request["meta"]["requestID"] if it not exist in your request.
    """
    request_id = request["meta"]["requestID"]
    logger.info("start to handle", request_id = request_id, caller=True)
    return {"output": "hello"}

start({"handler": handler})
```

## API
Please read [API](https://github.com/datastone-spirit/spirit-gpu/blob/main/API.md) or [中文 API](https://github.com/datastone-spirit/spirit-gpu/blob/main/API.zh.md) for how to use spirit-gpu serverless apis and some other import policies.

## Builder

The `spirit-gpu-builder` allows you to quickly generate templates and skeleton code for `spirit-gpu` using OpenAPI or JSON schema definitions. Built on `datamodel-code-generator`, this tool simplifies the setup for serverless functions.

> `spirit-gpu-builder` is installed when you install `spirit-gpu >= 0.0.6`.

```
usage: spirit-gpu-builder [-h] [-i INPUT_FILE]
                          [--input-type {auto,openapi,jsonschema,json,yaml,dict,csv,graphql}]
                          [-o OUTPUT_DIR]
                          [--data-type {pydantic_v2.BaseModel,dataclasses.dataclass}]
                          [--handler-type {sync,async,sync_generator,async_generator}]
                          [--model-only]

Generate spirit-gpu skeleton code from a OpenAPI or JSON schema, built on top of `datamodel-code-generator`. 
```

Options:
- `-h, --help`: show this help message and exit
- `-i INPUT_FILE, --input-file INPUT_FILE` Path to the input file. Supported types: ['auto', 'openapi', 'jsonschema', 'json', 'yaml', 'dict', 'csv', 'graphql']. If not provided, will try to find default file in current directory, default files ['api.yaml', 'api.yml', 'api.json'].
- `--input-type {auto,openapi,jsonschema,json,yaml,dict,csv,graphql}`: Specific the type of input file. Default: 'auto'.
- `-o OUTPUT_DIR, --output-dir OUTPUT_DIR`: Path to the output Python file. Default is current directory.
- `--data-type {pydantic_v2.BaseModel,dataclasses.dataclass}` Type of data model to generate. Default is 'pydantic_v2.BaseModel'.
- `--handler-type {sync,async,sync_generator,async_generator}` Type of handler to generate. Default is 'sync'.
- `--model-only`: Only generate the model file and skip the template repo and main file generation. Useful when update the api file.

The input file is the `input` part of body of your request to serverless of spirit-gpu, it can be json format, json schema format or openapi file.

**Examples**

The input file should define the expected `input` part request body for your serverless spirit-gpu function. Supported formats include JSON, JSON schema, or OpenAPI.

```yaml
openapi: 3.1.0·
components:
  schemas:
    RequestInput:
      type: object
      required:
        - audio
      properties:
        audio:
          type: string
          description: URL to the audio file.
          nullable: false
        model:
          type: string
          description: Identifier for the model to be used.
          default: null
          nullable: true
```

Your request body to `spirit-gpu`:

```json
{
    "input": {
        "audio": "http://your-audio.wav",
        "model": "base",
    },
    "webhook": "xxx"
}
```

Generated python model file:
```python
class RequestInput(BaseModel):
    audio: str = Field(..., description='URL to the audio file.')
    model: Optional[str] = Field(
        None, description='Identifier for the model to be used.'
    )
```

If using OpenAPI, ensure the main object in your YAML file is named RequestInput to allow automatic code generation.

```python
def get_request_input(request: Dict[str, Any]) -> RequestInput:
    return RequestInput(**request["input"])

def handler_impl(request_input: RequestInput, request: Dict[str, Any], env: Env):
    """
    Your handler implementation goes here.
    """
    pass

def handler(request: Dict[str, Any], env: Env):
    request_input = get_request_input(request)
    return handler_impl(request_input, request, env)
```



All generated code like this.
```
├── Dockerfile
├── LICENSE
├── README.md
├── api.json
├── requirements.txt
├── scripts
│   ├── build.sh
│   └── start.sh
└── src
    ├── build.py
    ├── main.py
    └── spirit_generated_model.py
```

            

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    "description": "# Spirit-GPU\n\n- [Spirit-GPU](#spirit-gpu)\n  - [Install](#install)\n  - [Usage example](#usage-example)\n  - [Logging](#logging)\n  - [API](#api)\n  - [Builder](#builder)\n\n## Install\n```\npip install spirit-gpu\n```\n\n## Usage example\n\n```python\nfrom spirit_gpu import start\nfrom spirit_gpu.env import Env\nfrom typing import Dict, Any\n\ndef handler(request: Dict[str, Any], env: Env):\n    \"\"\"\n    request: Dict[str, Any], from client http request body.\n    request[\"input\"]: Required.\n    request[\"webhook\"]: Optional string for asynchronous requests.\n\n    returned object to be serialized into JSON and sent to the client.\n    in this case: '{\"output\": \"hello\"}'\n    \"\"\"\n    return {\"output\": \"hello\"}\n\n\ndef gen_handler(request: Dict[str, Any], env: Env):\n    \"\"\"\n    append yield output to array, serialize into JSON and send to client.\n    in this case: [0, 1, 2, 3, 4]\n    \"\"\"\n    for i in range(5):\n        yield i\n\n\nasync def async_handler(request: Dict[str, Any], env: Env):\n    \"\"\"\n    returned object to be serialized into JSON and sent to the client.\n    \"\"\"\n    return {\"output\": \"hello\"}\n\n\nasync def async_gen_handler(request: Dict[str, Any], env: Env):\n    \"\"\"\n    append yield output to array, serialize into JSON and send to client.\n    \"\"\"\n    for i in range(10):\n        yield i\n\n\ndef concurrency_modifier(current_allowed_concurrency: int) -> int:\n    \"\"\"\n    Adjusts the allowed concurrency level based on the current state.\n    For example, if the current allowed concurrency is 3 and resources are sufficient,\n    it can be increased to 5, allowing 5 tasks to run concurrently.\n    \"\"\"\n    allowed_concurrency = ...\n    return allowed_concurrency\n\n\n\"\"\"\nRegister the handler with serverless.start().\nHandlers can be synchronous, asynchronous, generators, or asynchronous generators.\n\"\"\"\nstart({\n    \"handler\": async_handler, \"concurrency_modifier\": concurrency_modifier\n})\n```\n\n## Logging\nWe provide a tool to log information. Default logging level is \"INFO\", you can call `logger.set_level(logging.DEBUG)` to change it.\n\n> Please make sure you update to the `latest` version to use this feature.\n```python\nfrom spirit_gpu import start, logger\nfrom spirit_gpu.env import Env\nfrom typing import Dict, Any\n\n\ndef handler(request: Dict[str, Any], env: Env):\n    \"\"\"\n    request: Dict[str, Any], from client http request body.\n    request[\"input\"]: Required.\n    request[\"webhook\"]: Optional string for asynchronous requests.\n\n    we will only add request[\"meta\"][\"requestID\"] if it not exist in your request.\n    \"\"\"\n    request_id = request[\"meta\"][\"requestID\"]\n    logger.info(\"start to handle\", request_id = request_id, caller=True)\n    return {\"output\": \"hello\"}\n\nstart({\"handler\": handler})\n```\n\n## API\nPlease read [API](https://github.com/datastone-spirit/spirit-gpu/blob/main/API.md) or [\u4e2d\u6587 API](https://github.com/datastone-spirit/spirit-gpu/blob/main/API.zh.md) for how to use spirit-gpu serverless apis and some other import policies.\n\n## Builder\n\nThe `spirit-gpu-builder` allows you to quickly generate templates and skeleton code for `spirit-gpu` using OpenAPI or JSON schema definitions. Built on `datamodel-code-generator`, this tool simplifies the setup for serverless functions.\n\n> `spirit-gpu-builder` is installed when you install `spirit-gpu >= 0.0.6`.\n\n```\nusage: spirit-gpu-builder [-h] [-i INPUT_FILE]\n                          [--input-type {auto,openapi,jsonschema,json,yaml,dict,csv,graphql}]\n                          [-o OUTPUT_DIR]\n                          [--data-type {pydantic_v2.BaseModel,dataclasses.dataclass}]\n                          [--handler-type {sync,async,sync_generator,async_generator}]\n                          [--model-only]\n\nGenerate spirit-gpu skeleton code from a OpenAPI or JSON schema, built on top of `datamodel-code-generator`. \n```\n\nOptions:\n- `-h, --help`: show this help message and exit\n- `-i INPUT_FILE, --input-file INPUT_FILE` Path to the input file. Supported types: ['auto', 'openapi', 'jsonschema', 'json', 'yaml', 'dict', 'csv', 'graphql']. If not provided, will try to find default file in current directory, default files ['api.yaml', 'api.yml', 'api.json'].\n- `--input-type {auto,openapi,jsonschema,json,yaml,dict,csv,graphql}`: Specific the type of input file. Default: 'auto'.\n- `-o OUTPUT_DIR, --output-dir OUTPUT_DIR`: Path to the output Python file. Default is current directory.\n- `--data-type {pydantic_v2.BaseModel,dataclasses.dataclass}` Type of data model to generate. Default is 'pydantic_v2.BaseModel'.\n- `--handler-type {sync,async,sync_generator,async_generator}` Type of handler to generate. Default is 'sync'.\n- `--model-only`: Only generate the model file and skip the template repo and main file generation. Useful when update the api file.\n\nThe input file is the `input` part of body of your request to serverless of spirit-gpu, it can be json format, json schema format or openapi file.\n\n**Examples**\n\nThe input file should define the expected `input` part request body for your serverless spirit-gpu function. Supported formats include JSON, JSON schema, or OpenAPI.\n\n```yaml\nopenapi: 3.1.0\u00b7\ncomponents:\n  schemas:\n    RequestInput:\n      type: object\n      required:\n        - audio\n      properties:\n        audio:\n          type: string\n          description: URL to the audio file.\n          nullable: false\n        model:\n          type: string\n          description: Identifier for the model to be used.\n          default: null\n          nullable: true\n```\n\nYour request body to `spirit-gpu`:\n\n```json\n{\n    \"input\": {\n        \"audio\": \"http://your-audio.wav\",\n        \"model\": \"base\",\n    },\n    \"webhook\": \"xxx\"\n}\n```\n\nGenerated python model file:\n```python\nclass RequestInput(BaseModel):\n    audio: str = Field(..., description='URL to the audio file.')\n    model: Optional[str] = Field(\n        None, description='Identifier for the model to be used.'\n    )\n```\n\nIf using OpenAPI, ensure the main object in your YAML file is named RequestInput to allow automatic code generation.\n\n```python\ndef get_request_input(request: Dict[str, Any]) -> RequestInput:\n    return RequestInput(**request[\"input\"])\n\ndef handler_impl(request_input: RequestInput, request: Dict[str, Any], env: Env):\n    \"\"\"\n    Your handler implementation goes here.\n    \"\"\"\n    pass\n\ndef handler(request: Dict[str, Any], env: Env):\n    request_input = get_request_input(request)\n    return handler_impl(request_input, request, env)\n```\n\n\n\nAll generated code like this.\n```\n\u251c\u2500\u2500 Dockerfile\n\u251c\u2500\u2500 LICENSE\n\u251c\u2500\u2500 README.md\n\u251c\u2500\u2500 api.json\n\u251c\u2500\u2500 requirements.txt\n\u251c\u2500\u2500 scripts\n\u2502   \u251c\u2500\u2500 build.sh\n\u2502   \u2514\u2500\u2500 start.sh\n\u2514\u2500\u2500 src\n    \u251c\u2500\u2500 build.py\n    \u251c\u2500\u2500 main.py\n    \u2514\u2500\u2500 spirit_generated_model.py\n```\n",
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