nostrdvm/nostr_dvm/tasks/textextraction_google.py

import json
import os
import time
from pathlib import Path

import dotenv

from nostr_dvm.interfaces.dvmtaskinterface import DVMTaskInterface
from nostr_dvm.utils.admin_utils import AdminConfig
from nostr_dvm.utils.backend_utils import keep_alive
from nostr_dvm.utils.dvmconfig import DVMConfig
from nostr_dvm.utils.mediasource_utils import organize_input_media_data
from nostr_dvm.utils.nip89_utils import NIP89Config, check_and_set_d_tag
from nostr_dvm.utils.definitions import EventDefinitions
from nostr_dvm.utils.nostr_utils import check_and_set_private_key
from nostr_dvm.utils.zap_utils import check_and_set_ln_bits_keys
from nostr_sdk import Keys

"""
This File contains a Module to transform a media file input on Google Cloud

Accepted Inputs: Url to media file (url)
Outputs: Transcribed text

"""


class SpeechToTextGoogle(DVMTaskInterface):
    KIND: int = EventDefinitions.KIND_NIP90_EXTRACT_TEXT
    TASK: str = "speech-to-text"
    FIX_COST: float = 10
    PER_UNIT_COST: float = 0.1

    def __init__(self, name, dvm_config: DVMConfig, nip89config: NIP89Config,
                 admin_config: AdminConfig = None, options=None):
        super().__init__(name, dvm_config, nip89config, admin_config, options)
        if options is None:
            options = {}

    def is_input_supported(self, tags):
        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":
                    return False

            elif tag.as_vec()[0] == 'output':
                output = tag.as_vec()[1]
                if output == "" or not (output == "text/plain"):
                    print("Output format not supported, skipping..")
                    return False

        return True

    def create_request_from_nostr_event(self, event, client=None, dvm_config=None):
        request_form = {"jobID": event.id().to_hex() + "_" + self.NAME.replace(" ", "")}

        url = ""
        input_type = "url"
        start_time = 0
        end_time = 0
        media_format = "audio/wav"
        language = "en-US"

        for tag in event.tags():
            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] == "language":
                    language = tag.as_vec()[2]
                elif tag.as_vec()[1] == "range":
                    try:
                        t = time.strptime(tag.as_vec()[2], "%H:%M:%S")
                        seconds = t.tm_hour * 60 * 60 + t.tm_min * 60 + t.tm_sec
                        start_time = float(seconds)
                    except:
                        try:
                            t = time.strptime(tag.as_vec()[2], "%M:%S")
                            seconds = t.tm_min * 60 + t.tm_sec
                            start_time = float(seconds)
                        except:
                            start_time = tag.as_vec()[2]
                            try:
                                t = time.strptime(tag.as_vec()[3], "%H:%M:%S")
                                seconds = t.tm_hour * 60 * 60 + t.tm_min * 60 + t.tm_sec
                                end_time = float(seconds)
                            except:
                                try:
                                    t = time.strptime(tag.as_vec()[3], "%M:%S")
                                    seconds = t.tm_min * 60 + t.tm_sec
                                    end_time = float(seconds)
                                except:
                                    end_time = float(tag.as_vec()[3])

        filepath = organize_input_media_data(url, input_type, start_time, end_time, dvm_config, client, True,
                                             media_format)
        options = {
            "filepath": filepath,
            "language": language,
        }
        request_form['options'] = json.dumps(options)
        return request_form

    def process(self, request_form):
        import speech_recognition as sr
        if self.options.get("api_key"):
            api_key = self.options['api_key']
        else:
            api_key = None
        options = DVMTaskInterface.set_options(request_form)
        # Speech recognition instance
        asr = sr.Recognizer()
        with sr.AudioFile(options["filepath"]) as source:
            audio = asr.record(source)  # read the entire audio file

        try:
            # Use Google Web Speech API to recognize speech from audio data
            result = asr.recognize_google(audio, language=options["language"], key=api_key)
        except Exception as e:
            print(e)
            # If an error occurs during speech recognition, return False and the type of the exception
            return "error"

        return result

# 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):
    dvm_config = DVMConfig()
    dvm_config.PRIVATE_KEY = check_and_set_private_key(identifier)
    npub = Keys.from_sk_str(dvm_config.PRIVATE_KEY).public_key().to_bech32()
    invoice_key, admin_key, wallet_id, user_id, lnaddress = check_and_set_ln_bits_keys(identifier, npub)
    dvm_config.LNBITS_INVOICE_KEY = invoice_key
    dvm_config.LNBITS_ADMIN_KEY = admin_key  # The dvm might pay failed jobs back
    dvm_config.LNBITS_URL = os.getenv("LNBITS_HOST")
    admin_config.LUD16 = lnaddress
    options = {'api_key': None}
    # A module might have options it can be initialized with, here we set a default model, and the nova-server
    # address it should use. These parameters can be freely defined in the task component

    nip90params = {
        "language": {
            "required": False,
            "values": ["en-US"]
        }
    }
    nip89info = {
        "name": name,
        "image": "https://image.nostr.build/c33ca6fc4cc038ca4adb46fdfdfda34951656f87ee364ef59095bae1495ce669.jpg",
        "about": "I extract text from media files with the Google API. I understand English by default",
        "encryptionSupported": True,
        "cashuAccepted": True,
        "nip90Params": nip90params
    }
    nip89config = NIP89Config()
    nip89config.DTAG = check_and_set_d_tag(identifier, name, dvm_config.PRIVATE_KEY,
                                                              nip89info["image"])
    nip89config.CONTENT = json.dumps(nip89info)
    return SpeechToTextGoogle(name=name, dvm_config=dvm_config, nip89config=nip89config,
                              admin_config=admin_config, options=options)


if __name__ == '__main__':
    env_path = Path('.env')
    if env_path.is_file():
        print(f'loading environment from {env_path.resolve()}')
        dotenv.load_dotenv(env_path, verbose=True, override=True)
    else:
        raise FileNotFoundError(f'.env file not found at {env_path} ')

    admin_config = AdminConfig()
    admin_config.REBROADCAST_NIP89 = False
    admin_config.UPDATE_PROFILE = False
    dvm = build_example("Transcriptor", "speech_recognition", admin_config)
    dvm.run()

    keep_alive()