import json
import os
from multiprocessing.pool import ThreadPool

from nostr_sdk import Kind

from nostr_dvm.backends.discover.utils import check_server_status, send_request_to_server
from nostr_dvm.interfaces.dvmtaskinterface import DVMTaskInterface, process_venv
from nostr_dvm.utils.admin_utils import AdminConfig
from nostr_dvm.utils.definitions import EventDefinitions
from nostr_dvm.utils.dvmconfig import DVMConfig, build_default_config
from nostr_dvm.utils.nip88_utils import NIP88Config
from nostr_dvm.utils.nip89_utils import NIP89Config, check_and_set_d_tag

"""
This File contains a Module to extract a prompt from an image from an url.

Accepted Inputs: link to image (url)
Outputs: An textual description of the image

"""


class ImageInterrogator(DVMTaskInterface):
    KIND: Kind = EventDefinitions.KIND_NIP90_EXTRACT_TEXT
    TASK: str = "image-to-text"
    FIX_COST: float = 80

    async def init_dvm(self, name, dvm_config: DVMConfig, nip89config: NIP89Config, nip88config: NIP88Config = None,
                       admin_config: AdminConfig = None, options=None):
        dvm_config.SCRIPT = os.path.abspath(__file__)

    async def is_input_supported(self, tags, client=None, dvm_config=None):
        hasurl = False
        for tag in tags:
            if tag.as_vec()[0] == 'i':
                input_value = tag.as_vec()[1]
                input_type = tag.as_vec()[2]
                if input_type == "url":
                    hasurl = True

        if not hasurl:
            return False

        return True

    async def create_request_from_nostr_event(self, event, client=None, dvm_config=None):
        request_form = {"jobID": event.id().to_hex() + "_" + self.NAME.replace(" ", "")}
        request_form["trainerFilePath"] = r'modules\image_interrogator\image_interrogator.trainer'
        url = ""
        method = "prompt"
        mode = "best"

        for tag in event.tags().to_vec():
            if tag.as_vec()[0] == 'i':
                input_type = tag.as_vec()[2]
                if input_type == "url":
                    url = tag.as_vec()[1]
            elif tag.as_vec()[0] == 'param':
                print("Param: " + tag.as_vec()[1] + ": " + tag.as_vec()[2])
                if tag.as_vec()[1] == "method":
                    method = tag.as_vec()[2]
                elif tag.as_vec()[1] == "mode":
                    mode = tag.as_vec()[2]

        io_input_image = {
            "id": "input_image",
            "type": "input",
            "src": "url:Image",
            "uri": url
        }

        io_output = {
            "id": "output",
            "type": "output",
            "src": "request:text"
        }

        request_form['data'] = json.dumps([io_input_image, io_output])

        options = {
            "kind": method,
            "mode": mode

        }
        request_form['options'] = json.dumps(options)

        return request_form

    async def process(self, request_form):
        try:
            # Call the process route of NOVA-Server with our request form.
            response = send_request_to_server(request_form, self.options['server'])
            if bool(json.loads(response)['success']):
                print("Job " + request_form['jobID'] + " sent to server")

            pool = ThreadPool(processes=1)
            thread = pool.apply_async(check_server_status, (request_form['jobID'], self.options['server']))
            print("Wait for results of server...")
            result = thread.get()
            return result

        except Exception as e:
            raise Exception(e)


# We build an example here that we can call by either calling this file directly from the main directory,
# or by adding it to our playground. You can call the example and adjust it to your needs or redefine it in the
# playground or elsewhere
def build_example(name, identifier, admin_config, server_address):
    dvm_config = build_default_config(identifier)
    dvm_config.USE_OWN_VENV = False
    admin_config.LUD16 = dvm_config.LN_ADDRESS

    nip89info = {
        "name": name,
        "picture": "https://image.nostr.build/229c14e440895da30de77b3ca145d66d4b04efb4027ba3c44ca147eecde891f1.jpg",
        "about": "I analyse Images an return a prompt or a prompt analysis",
        "supportsEncryption": True,
        "acceptsNutZaps": dvm_config.ENABLE_NUTZAP,
        "nip90Params": {
            "method": {
                "required": False,
                "values": ["prompt", "analysis"]
            },
            "mode": {
                "required": False,
                "values": ["best", "classic", "fast", "negative"]
            }
        }
    }

    # A module might have options it can be initialized with, here we set a default model, lora and the server
    options = {'server': server_address}

    nip89config = NIP89Config()
    nip89config.DTAG = check_and_set_d_tag(identifier, name, dvm_config.PRIVATE_KEY, nip89info["picture"])
    nip89config.CONTENT = json.dumps(nip89info)

    return ImageInterrogator(name=name, dvm_config=dvm_config, nip89config=nip89config,
                             admin_config=admin_config, options=options)


if __name__ == '__main__':
    process_venv(ImageInterrogator)