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import spaces | |
import json | |
import os | |
from pathlib import Path | |
from typing import Callable, NoReturn | |
from asgi_correlation_id import CorrelationIdMiddleware | |
import gradio as gr | |
from starlette.responses import JSONResponse | |
import structlog | |
import uvicorn | |
from dotenv import load_dotenv | |
from fastapi import FastAPI, HTTPException, Request, status | |
from fastapi.exceptions import RequestValidationError | |
from fastapi.responses import FileResponse, HTMLResponse | |
from fastapi.staticfiles import StaticFiles | |
from fastapi.templating import Jinja2Templates | |
from pydantic import ValidationError | |
from samgis_core.utilities import create_folders_if_not_exists | |
from samgis_core.utilities import frontend_builder | |
from samgis_core.utilities.session_logger import setup_logging | |
from samgis_web.utilities.constants import GRADIO_EXAMPLES_TEXT_LIST, GRADIO_MARKDOWN, GRADIO_EXAMPLE_BODY_STRING_PROMPT | |
from samgis_web.utilities.type_hints import StringPromptApiRequestBody | |
load_dotenv() | |
project_root_folder = Path(globals().get("__file__", "./_")).absolute().parent | |
workdir = Path(os.getenv("WORKDIR", project_root_folder)) | |
model_folder = Path(project_root_folder / "machine_learning_models") | |
log_level = os.getenv("LOG_LEVEL", "INFO") | |
setup_logging(log_level=log_level) | |
app_logger = structlog.stdlib.get_logger() | |
app_logger.info(f"PROJECT_ROOT_FOLDER:{project_root_folder}, WORKDIR:{workdir}.") | |
folders_map = os.getenv("FOLDERS_MAP", "{}") | |
markdown_text = os.getenv("MARKDOWN_TEXT", "") | |
examples_text_list = os.getenv("EXAMPLES_TEXT_LIST", "").split("\n") | |
example_body = json.loads(os.getenv("EXAMPLE_BODY", "{}")) | |
mount_gradio_app = bool(os.getenv("MOUNT_GRADIO_APP", "")) | |
static_dist_folder = workdir / "static" / "dist" | |
input_css_path = os.getenv("INPUT_CSS_PATH", "src/input.css") | |
vite_gradio_url = os.getenv("VITE_GRADIO_URL", "/gradio") | |
vite_index_url = os.getenv("VITE_INDEX_URL", "/") | |
vite_samgis_url = os.getenv("VITE_SAMGIS_URL", "/samgis") | |
vite_lisa_url = os.getenv("VITE_LISA_URL", "/lisa") | |
fastapi_title = "samgis-lisa-on-zero" | |
app = FastAPI(title=fastapi_title, version="1.0") | |
async def request_middleware(request, call_next): | |
from samgis_web.web.middlewares import logging_middleware | |
return await logging_middleware(request, call_next) | |
def gpu_initialization() -> None: | |
app_logger.info("GPU initialization...") | |
def get_example_complete(example_text): | |
example_dict = dict(**GRADIO_EXAMPLE_BODY_STRING_PROMPT) | |
example_dict["string_prompt"] = example_text | |
return json.dumps(example_dict) | |
def get_gradio_interface_geojson(fn_inference: Callable): | |
with gr.Blocks() as gradio_app: | |
gr.Markdown(GRADIO_MARKDOWN) | |
with gr.Row(): | |
with gr.Column(): | |
text_input = gr.Textbox(lines=1, placeholder=None, label="Payload input") | |
btn = gr.Button(value="Submit") | |
with gr.Column(): | |
text_output = gr.Textbox(lines=1, placeholder=None, label="Geojson Output") | |
gr.Examples( | |
examples=[ | |
get_example_complete(example) for example in GRADIO_EXAMPLES_TEXT_LIST | |
], | |
inputs=[text_input], | |
) | |
btn.click( | |
fn_inference, | |
inputs=[text_input], | |
outputs=[text_output] | |
) | |
return gradio_app | |
def handle_exception_response(exception: Exception) -> NoReturn: | |
import subprocess | |
project_root_folder_content = subprocess.run( | |
f"ls -l {project_root_folder}/", shell=True, universal_newlines=True, stdout=subprocess.PIPE | |
) | |
app_logger.error(f"project_root folder 'ls -l' command output: {project_root_folder_content.stdout}.") | |
workdir_folder_content = subprocess.run( | |
f"ls -l {workdir}/", shell=True, universal_newlines=True, stdout=subprocess.PIPE | |
) | |
app_logger.error(f"workdir folder 'ls -l' command stdout: {workdir_folder_content.stdout}.") | |
app_logger.error(f"workdir folder 'ls -l' command stderr: {workdir_folder_content.stderr}.") | |
app_logger.error(f"inference error:{exception}.") | |
raise HTTPException( | |
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Internal server error on inference" | |
) | |
async def health() -> JSONResponse: | |
from samgis_web.__version__ import __version__ as version_web | |
from samgis_core.__version__ import __version__ as version_core | |
from lisa_on_cuda.__version__ import __version__ as version_lisa_on_cuda | |
from samgis_lisa.__version__ import __version__ as version_samgis_lisa | |
app_logger.info(f"still alive, version_web:{version_web}, version_core:{version_core}.") | |
app_logger.info(f"still alive, version_lisa_on_cuda:{version_lisa_on_cuda}, version_samgis_lisa:{version_samgis_lisa}.") | |
return JSONResponse(status_code=200, content={"msg": "still alive..."}) | |
# try executingx gpu_initialization() not within infer_lisa_gradio() | |
# gpu_initialization() | |
def infer_lisa_gradio(request_input: StringPromptApiRequestBody) -> str: | |
from samgis_lisa.io_package.wrappers_helpers import get_parsed_bbox_points_with_string_prompt | |
from samgis_lisa.prediction_api import lisa | |
from samgis_lisa.utilities.constants import LISA_INFERENCE_FN | |
app_logger.info("starting lisa inference request...") | |
try: | |
import time | |
time_start_run = time.time() | |
body_request = get_parsed_bbox_points_with_string_prompt(request_input) | |
app_logger.info(f"lisa body_request:{body_request}.") | |
try: | |
source = body_request["source"] | |
source_name = body_request["source_name"] | |
app_logger.debug(f"body_request:type(source):{type(source)}, source:{source}.") | |
app_logger.debug(f"body_request:type(source_name):{type(source_name)}, source_name:{source_name}.") | |
app_logger.debug(f"lisa module:{lisa}.") | |
# gpu_initialization() | |
output = lisa.lisa_predict( | |
bbox=body_request["bbox"], prompt=body_request["prompt"], zoom=body_request["zoom"], | |
source=source, source_name=source_name, inference_function_name_key=LISA_INFERENCE_FN, | |
inference_decorator=spaces.GPU | |
) | |
duration_run = time.time() - time_start_run | |
app_logger.info(f"duration_run:{duration_run}.") | |
body = { | |
"duration_run": duration_run, | |
"output": output | |
} | |
dumped = json.dumps(body) | |
app_logger.info(f"json.dumps(body) type:{type(dumped)}, len:{len(dumped)}.") | |
app_logger.debug(f"complete json.dumps(body):{dumped}.") | |
return dumped | |
except Exception as inference_exception: | |
app_logger.error(f"inference_exception:{inference_exception}.") | |
app_logger.error(f"inference_exception, request_input:{request_input}.") | |
raise HTTPException(status_code=500, detail="Internal Server Error") | |
except ValidationError as va1: | |
app_logger.error(f"validation error: {str(va1)}.") | |
app_logger.error(f"ValidationError, request_input:{request_input}.") | |
raise RequestValidationError("Unprocessable Entity") | |
def infer_lisa(request_input: StringPromptApiRequestBody) -> JSONResponse: | |
dumped = infer_lisa_gradio(request_input=request_input) | |
app_logger.info(f"json.dumps(body) type:{type(dumped)}, len:{len(dumped)}.") | |
app_logger.debug(f"complete json.dumps(body):{dumped}.") | |
return JSONResponse(status_code=200, content={"body": dumped}) | |
def request_validation_exception_handler(request: Request, exc: RequestValidationError) -> JSONResponse: | |
from samgis_web.web import exception_handlers | |
return exception_handlers.request_validation_exception_handler(request, exc) | |
def http_exception_handler(request: Request, exc: HTTPException) -> JSONResponse: | |
from samgis_web.web import exception_handlers | |
return exception_handlers.http_exception_handler(request, exc) | |
create_folders_if_not_exists.folders_creation(folders_map) | |
write_tmp_on_disk = os.getenv("WRITE_TMP_ON_DISK", "") | |
app_logger.info(f"write_tmp_on_disk:{write_tmp_on_disk}.") | |
if bool(write_tmp_on_disk): | |
try: | |
assert Path(write_tmp_on_disk).is_dir() | |
app.mount("/vis_output", StaticFiles(directory=write_tmp_on_disk), name="vis_output") | |
templates = Jinja2Templates(directory=str(project_root_folder / "static")) | |
def list_files(request: Request): | |
files = os.listdir(write_tmp_on_disk) | |
files_paths = sorted([f"{request.url._url}/{f}" for f in files]) | |
print(files_paths) | |
return templates.TemplateResponse( | |
"list_files.html", {"request": request, "files": files_paths} | |
) | |
except (AssertionError, RuntimeError) as rerr: | |
app_logger.error(f"{rerr} while loading the folder write_tmp_on_disk:{write_tmp_on_disk}...") | |
raise rerr | |
frontend_builder.build_frontend( | |
project_root_folder=workdir, | |
input_css_path=input_css_path, | |
output_dist_folder=static_dist_folder | |
) | |
app_logger.info("build_frontend ok!") | |
templates = Jinja2Templates(directory="templates") | |
app.mount("/static", StaticFiles(directory=static_dist_folder, html=True), name="static") | |
# important: the index() function and the app.mount MUST be at the end | |
# samgis.html | |
app.mount(vite_samgis_url, StaticFiles(directory=static_dist_folder, html=True), name="samgis") | |
async def samgis() -> FileResponse: | |
return FileResponse(path=str(static_dist_folder / "samgis.html"), media_type="text/html") | |
# lisa.html | |
app.mount(vite_lisa_url, StaticFiles(directory=static_dist_folder, html=True), name="lisa") | |
async def lisa() -> FileResponse: | |
return FileResponse(path=str(static_dist_folder / "lisa.html"), media_type="text/html") | |
# index.html (lisa.html copy) | |
app.mount(vite_index_url, StaticFiles(directory=static_dist_folder, html=True), name="index") | |
async def index() -> FileResponse: | |
return FileResponse(path=str(static_dist_folder / "index.html"), media_type="text/html") | |
app_logger.info(f"creating gradio interface...") | |
gr_interface = get_gradio_interface_geojson(infer_lisa_gradio) | |
app_logger.info(f"gradio interface created, mounting gradio app on url {vite_gradio_url} within FastAPI...") | |
app = gr.mount_gradio_app(app, gr_interface, path=vite_gradio_url) | |
app_logger.info("mounted gradio app within fastapi") | |
# add the CorrelationIdMiddleware AFTER the @app.middleware("http") decorated function to avoid missing request id | |
app.add_middleware(CorrelationIdMiddleware) | |
if __name__ == '__main__': | |
try: | |
uvicorn.run(host="0.0.0.0", port=7860, app=app) | |
except Exception as ex: | |
app_logger.error(f"fastapi/gradio application {fastapi_title}, exception:{ex}.") | |
print(f"fastapi/gradio application {fastapi_title}, exception:{ex}.") | |
raise ex | |