import json
import uuid

import uvicorn
from fastapi import FastAPI, HTTPException, Request, status
from fastapi.exceptions import RequestValidationError
from fastapi.responses import FileResponse, JSONResponse
from fastapi.staticfiles import StaticFiles
from pydantic import ValidationError

from samgis_lisa_on_cuda import PROJECT_ROOT_FOLDER, WORKDIR
from samgis_lisa_on_cuda.utilities.type_hints import ApiRequestBody, StringPromptApiRequestBody
from samgis_core.utilities.fastapi_logger import setup_logging


app_logger = setup_logging(debug=True)
app = FastAPI()


@app.middleware("http")
async def request_middleware(request, call_next):
    request_id = str(uuid.uuid4())
    with app_logger.contextualize(request_id=request_id):
        app_logger.info("Request started")

        try:
            response = await call_next(request)

        except Exception as ex:
            app_logger.error(f"Request failed: {ex}")
            response = JSONResponse(content={"success": False}, status_code=500)

        finally:
            response.headers["X-Request-ID"] = request_id
            app_logger.info("Request ended")

        return response


@app.post("/post_test_dictlist")
def post_test_dictlist2(request_input: ApiRequestBody) -> JSONResponse:
    from samgis_lisa_on_cuda.io.wrappers_helpers import get_parsed_bbox_points_with_dictlist_prompt

    request_body = get_parsed_bbox_points_with_dictlist_prompt(request_input)
    app_logger.info(f"request_body:{request_body}.")
    return JSONResponse(
        status_code=200,
        content=request_body
    )


@app.get("/health")
async def health() -> JSONResponse:
    import importlib.metadata
    from importlib.metadata import PackageNotFoundError

    try:
        core_version = importlib.metadata.version('samgis_core')
        lisa_on_cuda_version = importlib.metadata.version('lisa-on-cuda')
        samgis_lisa_on_cuda_version = importlib.metadata.version('samgis-lisa-on-cuda')
    except PackageNotFoundError as pe:
        app_logger.error(f"pe:{pe}.")
        samgis_lisa_on_cuda_version = "0.0.0"

    msg = "still alive, "
    msg += f"""version:{samgis_lisa_on_cuda_version}, core version:{core_version},"""
    msg += f"""lisa-on-cuda version:{lisa_on_cuda_version},"""

    app_logger.info(msg)
    return JSONResponse(status_code=200, content={"msg": "still alive..."})


@app.post("/post_test_string")
def post_test_string(request_input: StringPromptApiRequestBody) -> JSONResponse:
    from lisa_on_cuda.utils import app_helpers
    from samgis_lisa_on_cuda.io.wrappers_helpers import get_parsed_bbox_points_with_string_prompt

    request_body = get_parsed_bbox_points_with_string_prompt(request_input)
    app_logger.info(f"request_body:{request_body}.")
    custom_args = app_helpers.parse_args([])
    request_body["content"] = {**request_body, "precision": str(custom_args.precision)}
    return JSONResponse(
        status_code=200,
        content=request_body
    )


@app.post("/infer_lisa")
def infer_lisa(request_input: StringPromptApiRequestBody) -> JSONResponse:
    from samgis_lisa_on_cuda.prediction_api import lisa
    from samgis_lisa_on_cuda.io.wrappers_helpers import get_parsed_bbox_points_with_string_prompt, get_source_name

    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}.")
        app_logger.info(f"lisa module:{lisa}.")
        try:
            source_name = get_source_name(request_input.source_type)
            app_logger.info(f"source_name = {source_name}.")
            output = lisa.lisa_predict(
                bbox=body_request["bbox"], prompt=body_request["prompt"], zoom=body_request["zoom"],
                source=body_request["source"], source_name=source_name
            )
            duration_run = time.time() - time_start_run
            app_logger.info(f"duration_run:{duration_run}.")
            body = {
                "duration_run": duration_run,
                "output": output
            }
            return JSONResponse(status_code=200, content={"body": json.dumps(body)})
        except Exception as inference_exception:
            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 output: {workdir_folder_content.stdout}.")
            app_logger.error(f"inference error:{inference_exception}.")
            raise HTTPException(
                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Internal server error on inference")
    except ValidationError as va1:
        app_logger.error(f"validation error: {str(va1)}.")
        raise ValidationError("Unprocessable Entity")


@app.post("/infer_samgis")
def infer_samgis(request_input: ApiRequestBody) -> JSONResponse:
    from samgis_lisa_on_cuda.prediction_api import predictors
    from samgis_lisa_on_cuda.io.wrappers_helpers import get_parsed_bbox_points_with_dictlist_prompt, get_source_name

    app_logger.info("starting plain samgis inference request...")

    try:
        import time

        time_start_run = time.time()
        body_request = get_parsed_bbox_points_with_dictlist_prompt(request_input)
        app_logger.info(f"body_request:{body_request}.")
        try:
            source_name = get_source_name(request_input.source_type)
            app_logger.info(f"source_name = {source_name}.")
            output = predictors.samexporter_predict(
                bbox=body_request["bbox"], prompt=body_request["prompt"], zoom=body_request["zoom"],
                source=body_request["source"], source_name=source_name
            )
            duration_run = time.time() - time_start_run
            app_logger.info(f"duration_run:{duration_run}.")
            body = {
                "duration_run": duration_run,
                "output": output
            }
            return JSONResponse(status_code=200, content={"body": json.dumps(body)})
        except Exception as inference_exception:
            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 output: {workdir_folder_content.stdout}.")
            app_logger.error(f"inference error:{inference_exception}.")
            raise HTTPException(
                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Internal server error on inference")
    except ValidationError as va1:
        app_logger.error(f"validation error: {str(va1)}.")
        raise ValidationError("Unprocessable Entity")


@app.exception_handler(RequestValidationError)
async def request_validation_exception_handler(request: Request, exc: RequestValidationError) -> JSONResponse:
    app_logger.error(f"exception errors: {exc.errors()}.")
    app_logger.error(f"exception body: {exc.body}.")
    headers = request.headers.items()
    app_logger.error(f'request header: {dict(headers)}.')
    params = request.query_params.items()
    app_logger.error(f'request query params: {dict(params)}.')
    return JSONResponse(
        status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
        content={"msg": "Error - Unprocessable Entity"}
    )


@app.exception_handler(HTTPException)
async def http_exception_handler(request: Request, exc: HTTPException) -> JSONResponse:
    app_logger.error(f"exception: {str(exc)}.")
    headers = request.headers.items()
    app_logger.error(f'request header: {dict(headers)}.')
    params = request.query_params.items()
    app_logger.error(f'request query params: {dict(params)}.')
    return JSONResponse(
        status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
        content={"msg": "Error - Internal Server Error"}
    )


# important: the index() function and the app.mount MUST be at the end
# samgis.html
app.mount("/samgis", StaticFiles(directory=WORKDIR / "static" / "dist", html=True), name="samgis")


@app.get("/samgis")
async def samgis() -> FileResponse:
    return FileResponse(path=WORKDIR / "static" / "dist" / "samgis.html", media_type="text/html")


# lisa.html
app.mount("/lisa", StaticFiles(directory=WORKDIR / "static" / "dist", html=True), name="lisa")


@app.get("/lisa")
async def lisa() -> FileResponse:
    return FileResponse(path=WORKDIR / "static" / "dist" / "lisa.html", media_type="text/html")


# index.html (lisa.html copy)
app.mount("/", StaticFiles(directory=WORKDIR / "static" / "dist", html=True), name="index")


@app.get("/")
async def index() -> FileResponse:
    return FileResponse(path=WORKDIR / "static" / "dist" / "index.html", media_type="text/html")


if __name__ == '__main__':
    try:
        uvicorn.run(host="0.0.0.0", port=7860, app=app)
    except Exception as e:
        app_logger.error("e:", e)
        raise e