TypeError: __call__() missing 1 required positional argument: 'context' error when deploying on GCP

I want to deploy a FastAPI app in Google Cloud Platform (GCP), specifically with Vertex AI.

These are my files:

main.py

import os

import uvicorn
from dotenv import load_dotenv
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from mangum import Mangum

from app.api.api_v0.api import router as api_v0_router

load_dotenv()

root_path = os.getenv('ENV', default="")
app = FastAPI(root_path=f"/{root_path}")

app.add_middleware(
    CORSMiddleware,
    allow_origins=['*'],
    allow_methods=["*"],
    allow_headers=["*"],
)

app.include_router(api_v0_router, prefix="/api/v0")

handler = Mangum(app)

if __name__ == "__main__":
    uvicorn.run(app, port=8000)

api_v0_router

from fastapi import APIRouter

from app.api.api_v0.endpoints.process import router as process_router
from app.api.api_v0.endpoints.test import router as test_router

router = APIRouter()

router.include_router(process_router)
router.include_router(test_router)

process_router.py

import json
from typing import List

import numpy as np
from fastapi import APIRouter, UploadFile

from app.utils.utils import convert_file_to_image
from onnxruntime import InferenceSession

MODEL_PATH = "./model/last.onnx"

router = APIRouter(prefix="/process", tags=["Process"])

@router.on_event("startup")
def load_inference_session():
    global session
    session = InferenceSession(MODEL_PATH)

@router.post("")
async def root(
        files: List[UploadFile]
):
    file_read = await files[0].read()
    np_image = convert_file_to_image(file_read)
    np_image = np_image.astype(np.float32)
    input_name = session.get_inputs()[0].name
    output_name = session.get_outputs()[0].name

    result = session.run([output_name], {input_name: np_image})

    return json.dumps({"result": str(np.array(result).shape)})

Dockerfile

FROM python:3.9

COPY requirements.txt .

RUN pip install --no-cache-dir Bottleneck==1.3.5
RUN pip install --no-cache-dir -r requirements.txt

COPY ./app /app

EXPOSE 8080

CMD ["uvicorn", "app.main:handler", "--host", "0.0.0.0", "--port", "8080"]

Then I'm deploying my project using the following command:

gcloud builds submit . --tag=<YOUR_REGION>-docker.pkg.dev/<YOUR_PROJECT>/<YOUR_REPOSITORY>/<PROJECT> --machine-type='n1-highcpu-32' --timeout=900s --verbosity=info

On GCP I am:

1. Creating a Model Registry in Vertex AI
2. Deploying the model

After some time, these are the logs:

INFO: Started server process [1]
INFO: Waiting for application startup.
INFO: ASGI 'lifespan' protocol appears unsupported.
INFO: Application startup complete.
INFO: Uvicorn running on http://0.0.0.0:8080 (Press CTRL+C to quit)
ERROR: Exception in ASGI application
Traceback (most recent call last):
File "/usr/local/lib/python3.9/site-packages/uvicorn/protocols/http/h11_impl.py", line 408, in run_asgi
result = await app( # type: ignore[func-returns-value]
File "/usr/local/lib/python3.9/site-packages/uvicorn/middleware/proxy_headers.py", line 84, in __call__
return await self.app(scope, receive, send)
File "/usr/local/lib/python3.9/site-packages/uvicorn/middleware/asgi2.py", line 16, in __call__
instance = self.app(scope)
TypeError: __call__() missing 1 required positional argument: 'context'

According to the logs the error is related to Uvicorn. I've taken a look at different tutorials using their approach, but this error is never mentioned.

I don't have experience at all with GCP so I'm not sure if I'm doing something wrong.

Mangum handler is designed for AWS Lambda, but you are using GCP, so you don't need it and could use a standard FastAPI application:

import os

import uvicorn.protocols.http.h11_impl
from dotenv import load_dotenv
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

from app.api.api_v0.api import router as api_v0_router

load_dotenv()

root_path = os.getenv('ENV', default="")
app = FastAPI(root_path=f"/{root_path}")

app.add_middleware(
    CORSMiddleware,
    allow_origins=['*'],
    allow_methods=["*"],
    allow_headers=["*"],
)

app.include_router(api_v0_router, prefix="/api/v0")


if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8080)

After this, you should change the command inside of a Dockerfile:

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8080"]

P.S. Dont forget to rebuild and push your docker image after this:

docker build -t gcr.io/PROJECT_ID/YOUR_IMAGE_NAME .
docker push gcr.io/PROJECT_ID/YOUR_IMAGE_NAME