only Python3.10 is supported, Other versions may face compatibility issues while using some libraries.
It is now possible to run your code remotely using Inferless. This feature is extremely useful when you want to run your code partly or entirely on a remote server. By introducing a few annotations in your code, you can run your code on a remote server with the command inferless remote-run app.py -c config.yaml. There are 2 ways to use Remote run
  • Function Method
  • Class Method

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Function Method

@inferless.method(gpu="T4") is used to specify the function that you want to run for inference you can specify the gpu to be used here. 
import inferless

@inferless.method(gpu="T4")
def my_agent():
    return "Hello World"

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Class Method

You can use the following annotations to specify the code that you want to run on the remote server. The annotations accept a gpu parameter which specifies the GPU that you want to use on the remote server. Currently, the supported GPUs are T4 & A10 & A100 Create a new app object with inferless.Cls @app.load is used to specify the function that you want to load the model before inference @app.infer is used to specify the function that you want to run for inference. @inferless.local_entry_point annotation lets you mark a module-level function as the local entry point for remote run. @inferless.local_entry_point annotation lets you mark a module-level function as the local entry point for remote run.

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Examples

from pydantic import BaseModel, Field
import inferless

@inferless.request
class RequestObjects(BaseModel):
    prompt: str = Field(default="a horse near a beach")

@inferless.response
class ResponseObjects(BaseModel):
    generated_txt: str = Field(default='Test output')

app = inferless.Cls(gpu="T4")
class InferlessPythonModel:
    @app.load
    def initialize(self):
        import torch
        from transformers import pipeline
        self.generator = pipeline("text-generation", model="EleutherAI/gpt-neo-125M",device=0)
    @app.infer
    def infer(self, inputs: RequestObjects) -> ResponseObjects:
        pipeline_output = self.generator(inputs.prompt, do_sample=True, min_length=128)
        generateObject = ResponseObjects(generated_txt = pipeline_output[0]["generated_text"])
        return generateObject


@inferless.local_entry_point
def my_local_entry(dynamic_params):
    model_instance = InferlessPythonModel()
    return model_instance.infer(RequestObjects(**dynamic_params))

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Runtime Configuration

You can configure the runtime for remote run using a configuration file. The configuration file is a YAML file through which you can specify custom packages that you want to install on the remote server. You can specify system packages (packages installed using apt-get) python packages (packages installed using pip) and run commands (shell commands) that you want to configure on the remote server. runtime.yaml 
build:
    system_packages:
    - libssl-dev
    python_packages:
        - transformers
        - torch
        - accelerate
        - inferless
        - pydantic

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Working Directory

By default, the files from the working directory are copied to the server excluding: “.git”, “*.pyc”, “pycache” If a .gitignore file is present in the working directory, the files mentioned in the .gitignore file will not be copied to the server. You can also specify a custom ignore file using the --exclude -e option. inferless remote-run app.py -c runtime.yaml -e custom_ignore_file.txt --gpu A10 --prompt "Hello, Write a story about a dragon"
Maximum file size that can be copied to the server is 10MB.

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Notes

Try to avoid unnecessary packages in config file as it may increase the time to setup the environment.