added google speech-to-text

tasks/README.md

@@ -6,13 +6,14 @@ Reusable backend functions can be defined in backends (e.g. API calls)
 
 Current List of Tasks:
 
-| Module                   | Kind | Description                                    | Backend     |
-|--------------------------|------|------------------------------------------------|-------------| 
-| TextExtractionPDF        | 5000 | Extracts Text from a PDF file                  | local       |
-| SpeechToTextWhisperX     | 5000 | Extracts Speech from Media files               | nova-server |
-| TranslationGoogle        | 5002 | Translates Inputs to another language          | googleAPI   |
-| TranslationLibre         | 5002 | Translates Inputs to another language          | libreAPI    |
-| ImageGenerationSDXL      | 5100 | Generates an Image with StableDiffusionXL      | nova-server |
-| ImageGenerationDALLE     | 5100 | Generates an Image with Dall-E                 | openAI      |
-| MediaConverter           | 5200 | Converts a link of a media file and uploads it | openAI      |
-| DiscoverInactiveFollows  | 5301 | Find inactive Nostr users                      | local       |
+| Module                  | Kind | Description                                    | Backend     |
+|-------------------------|------|------------------------------------------------|-------------| 
+| TextExtractionPDF       | 5000 | Extracts Text from a PDF file                  | local       |
+| SpeechToTextWhisperX    | 5000 | Extracts Speech from Media files               | nova-server |
+| SpeechToTextGoogle      | 5000 | Extracts Speech from Media files via Google    | googleAPI   |
+| TranslationGoogle       | 5002 | Translates Inputs to another language          | googleAPI   |
+| TranslationLibre        | 5002 | Translates Inputs to another language          | libreAPI    |
+| ImageGenerationSDXL     | 5100 | Generates an Image with StableDiffusionXL      | nova-server |
+| ImageGenerationDALLE    | 5100 | Generates an Image with Dall-E                 | openAI      |
+| MediaConverter          | 5200 | Converts a link of a media file and uploads it | openAI      |
+| DiscoverInactiveFollows | 5301 | Find inactive Nostr users                      | local       |

tasks/textextraction_google.py

@@ -0,0 +1,125 @@
+import json
+import os
+import time
+from multiprocessing.pool import ThreadPool
+from pathlib import Path
+
+from backends.nova_server import check_nova_server_status, send_request_to_nova_server, send_file_to_nova_server
+from interfaces.dvmtaskinterface import DVMTaskInterface
+from utils.admin_utils import AdminConfig
+from utils.dvmconfig import DVMConfig
+from utils.mediasource_utils import organize_input_media_data
+from utils.nip89_utils import NIP89Config
+from utils.definitions import EventDefinitions
+
+"""
+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_form_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