From 465c2602bfb79a7b72117b7914c090c28ac02f4b Mon Sep 17 00:00:00 2001
From: Sharrnah <55756126+Sharrnah@users.noreply.github.com>
Date: Fri, 4 Nov 2022 21:49:11 +0100
Subject: [PATCH 1/2] [TASK] Added max queue size and timeout, in case too many
 tasks are queued [FEATURE] Added FLAN-T5 A.I. Model [FEATURE] Added
 settings.yaml file [TASK] default ascii conversion disabled now, since VRChat
 supports it now. [TASK] Added VRChat chat notification signal

---
 README.md                                     |   4 +-
 VRC_OSCLib.py                                 |   3 +-
 audioWhisper.py                               |  47 +++--
 audioprocessor.py                             |  79 +++++++--
 flanLanguageModel.py                          | 128 ++++++++++++++
 requirements.txt                              |   2 +-
 settings.py                                   |  82 ++++++++-
 texttranslate.py                              |   2 +-
 websocket.py                                  |   9 +
 .../streaming-overlay-01/index.html           |  50 ++++--
 .../streaming-overlay-01/main.css             |  10 +-
 websocket_clients/websocket-remote/index.html | 167 +++++++++++-------
 websocket_clients/websocket-remote/main.css   |  10 +-
 13 files changed, 462 insertions(+), 131 deletions(-)
 create mode 100644 flanLanguageModel.py

diff --git a/README.md b/README.md
index 955cc9e..ba47f09 100644
--- a/README.md
+++ b/README.md
@@ -62,14 +62,16 @@ _(because of the 2 GB Limit, no direct release files on GitHub)_
 |           `--osc_ip`           |       0        |                     IP to send OSC messages to. Set to '0' to disable. (For VRChat this should mostly be 127.0.0.1)                      |
 |          `--osc_port`          |      9000      |                                       Port to send OSC message to. ('9000' as default for VRChat)                                        |
 |        `--osc_address`         | /chatbox/input |                            The Address the OSC messages are send to. ('/chatbox/input' as default for VRChat)                            |
-|     `--osc_convert_ascii`      |      True      |     Convert Text to ASCII compatible when sending over OSC. (Can be set to 'False' as soon as VRChat supports non-ASCII characters)      |
+|     `--osc_convert_ascii`      |     False      |                                         Convert Text to ASCII compatible when sending over OSC.                                          |
 |        `--websocket_ip`        |       0        |                                       IP where Websocket Server listens on. Set to '0' to disable.                                       |
 |       `--websocket_port`       |      5000      |                                                 Port where Websocket Server listens on.                                                  |
 |       `--txt_translator`       |     M2M100     |                          The Model the AI is loading for text translations. can be 'M2M100', 'ARGOS' or 'None'.                          |
 |        `--m2m100_size`         |     small      |         The Model size if M2M100 text translator is used. can be 'small' or 'large'. (has no effect with --txt_translator ARGOS)         |
 |       `--m2m100_device`        |      auto      |            The device used for M2M100 translation. can be 'auto', 'cuda' or 'cpu' (has no effect with --txt_translator ARGOS)            |
 |      `--ocr_window_name`       |     VRChat     |                                           Window name of the application for OCR translations.                                           |
+|        `--flan_enabled`        |     False      |                               Enable FLAN-T5 A.I. (General A.I. which can be used for Question Answering.)                               |
 |        `--open_browser`        |     False      |                     Open default Browser with websocket-remote on start. (requires --websocket_ip to be set as well)                     |
+|           `--config`           |      None      |    Use the specified config file instead of the default 'settings.yaml' (relative to the current path) [overwrites without asking!!!]    |
 |          `--verbose`           |     False      |                                                     Whether to print verbose output.                                                     |
 
 ## Usage with 3rd Party Applications
diff --git a/VRC_OSCLib.py b/VRC_OSCLib.py
index 3ddd519..d49c380 100644
--- a/VRC_OSCLib.py
+++ b/VRC_OSCLib.py
@@ -106,7 +106,7 @@ def Message(data="example", address="/example", IP='127.0.0.1', PORT=9000):
 
 
 # OSC Send Chat
-def Chat(data="example", send=True, address="/chatbox/input", IP='127.0.0.1', PORT=9000, convert_ascii=True):
+def Chat(data="example", send=True, nofify=True, address="/chatbox/input", IP='127.0.0.1', PORT=9000, convert_ascii=True):
     # OSC Bild
     client = udp_client.UDPClient(IP, PORT)
     msg = OscMessageBuilder(address=address)
@@ -115,6 +115,7 @@ def Chat(data="example", send=True, address="/chatbox/input", IP='127.0.0.1', PO
     else:
         msg.add_arg(data)
     msg.add_arg(send)
+    msg.add_arg(nofify)
     m = msg.build()
 
     # OSC Send
diff --git a/audioWhisper.py b/audioWhisper.py
index 79bffdf..af1242f 100644
--- a/audioWhisper.py
+++ b/audioWhisper.py
@@ -3,6 +3,7 @@
 import speech_recognition as sr
 import audioprocessor
 import os
+from pathlib import Path
 import click
 import VRC_OSCLib
 import websocket
@@ -31,7 +32,7 @@
 @click.option("--osc_ip", default="0", help="IP to send OSC message to. Set to '0' to disable", type=str)
 @click.option("--osc_port", default=9000, help="Port to send OSC message to. ('9000' as default for VRChat)", type=int)
 @click.option("--osc_address", default="/chatbox/input", help="The Address the OSC messages are send to. ('/chatbox/input' as default for VRChat)", type=str)
-@click.option("--osc_convert_ascii", default='True', help="Convert Text to ASCII compatible when sending over OSC.", type=str)
+@click.option("--osc_convert_ascii", default='False', help="Convert Text to ASCII compatible when sending over OSC.", type=str)
 @click.option("--websocket_ip", default="0", help="IP where Websocket Server listens on. Set to '0' to disable", type=str)
 @click.option("--websocket_port", default=5000, help="Port where Websocket Server listens on. ('5000' as default)", type=int)
 @click.option("--ai_device", default=None, help="The Device the AI is loaded on. can be 'cuda' or 'cpu'. default does autodetect", type=click.Choice(["cuda", "cpu"]))
@@ -39,10 +40,18 @@
 @click.option("--m2m100_size", default="small", help="The Model size if M2M100 text translator is used. can be 'small' or 'large'. default is small. (has no effect with ARGOS)", type=click.Choice(["small", "large"]))
 @click.option("--m2m100_device", default="auto", help="The device used for M2M100 translation. (has no effect with ARGOS)", type=click.Choice(["auto", "cuda", "cpu"]))
 @click.option("--ocr_window_name", default="VRChat", help="Window name of the application for OCR translations. (Default: 'VRChat')", type=str)
+@click.option("--flan_enabled", default=False, help="Enable FLAN-T5 A.I. (General A.I. which can be used for Question Answering.)", type=bool)
 @click.option("--open_browser", default=False, help="Open default Browser with websocket-remote on start. (requires --websocket_ip to be set as well)", is_flag=True, type=bool)
+@click.option("--config", default=None, help="Use the specified config file instead of the default 'settings.yaml' (relative to the current path) [overwrites without asking!!!]", type=str)
 @click.option("--verbose", default=False, help="Whether to print verbose output", is_flag=True, type=bool)
-def main(devices, device_index, sample_rate, task, model, language, condition_on_previous_text, energy, pause, dynamic_energy, phrase_time_limit, osc_ip, osc_port,
-         osc_address, osc_convert_ascii, websocket_ip, websocket_port, ai_device, txt_translator, m2m100_size, m2m100_device, ocr_window_name, open_browser, verbose):
+@click.pass_context
+def main(ctx, devices, device_index, sample_rate, task, model, language, condition_on_previous_text, energy, dynamic_energy, pause, phrase_time_limit, osc_ip, osc_port,
+         osc_address, osc_convert_ascii, websocket_ip, websocket_port, ai_device, txt_translator, m2m100_size, m2m100_device, ocr_window_name, flan_enabled, open_browser, config, verbose):
+
+    # Load settings from file
+    if config is not None:
+        settings.SETTINGS_PATH = Path(Path.cwd() / config)
+    settings.LoadYaml(settings.SETTINGS_PATH)
 
     if str2bool(devices):
         audio = pyaudio.PyAudio()
@@ -64,11 +73,12 @@ def main(devices, device_index, sample_rate, task, model, language, condition_on
     print("###################################")
 
     # set initial settings
-    settings.SetOption("whisper_task", task)
-    settings.SetOption("condition_on_previous_text", condition_on_previous_text)
-    settings.SetOption("model", model)
+    settings.IsArgumentSetting(ctx, "task") and settings.SetOption("whisper_task", task)
+
+    settings.IsArgumentSetting(ctx, "condition_on_previous_text") and settings.SetOption("condition_on_previous_text", condition_on_previous_text)
+    settings.IsArgumentSetting(ctx, "model") and settings.SetOption("model", model)
 
-    settings.SetOption("current_language", language)
+    settings.IsArgumentSetting(ctx, "language") and settings.SetOption("current_language", language)
 
     # check if english only model is loaded, and configure whisper languages accordingly.
     if model.endswith(".en") and language not in {"en", "English"}:
@@ -81,23 +91,24 @@ def main(devices, device_index, sample_rate, task, model, language, condition_on
     else:
         settings.SetOption("whisper_languages", audioprocessor.whisper_get_languages())
 
-    settings.SetOption("ai_device", ai_device)
+    settings.IsArgumentSetting(ctx, "ai_device") and settings.SetOption("ai_device", ai_device)
     settings.SetOption("verbose", verbose)
 
-    settings.SetOption("osc_ip", osc_ip)
-    settings.SetOption("osc_port", osc_port)
-    settings.SetOption("osc_address", osc_address)
-    settings.SetOption("osc_convert_ascii", str2bool(osc_convert_ascii))
+    settings.IsArgumentSetting(ctx, "osc_ip") and settings.SetOption("osc_ip", osc_ip)
+    settings.IsArgumentSetting(ctx, "osc_port") and settings.SetOption("osc_port", osc_port)
+    settings.IsArgumentSetting(ctx, "osc_address") and settings.SetOption("osc_address", osc_address)
+    settings.IsArgumentSetting(ctx, "osc_convert_ascii") and settings.SetOption("osc_convert_ascii", str2bool(osc_convert_ascii))
 
-    settings.SetOption("websocket_ip", websocket_ip)
-    settings.SetOption("websocket_port", websocket_port)
+    settings.IsArgumentSetting(ctx, "websocket_ip") and settings.SetOption("websocket_ip", websocket_ip)
+    settings.IsArgumentSetting(ctx, "websocket_port") and settings.SetOption("websocket_port", websocket_port)
 
-    settings.SetOption("txt_translator", txt_translator)
-    settings.SetOption("m2m100_size", m2m100_size)
+    settings.IsArgumentSetting(ctx, "txt_translator") and settings.SetOption("txt_translator", txt_translator)
+    settings.IsArgumentSetting(ctx, "m2m100_size") and settings.SetOption("m2m100_size", m2m100_size)
     texttranslate.SetDevice(m2m100_device)
 
-    settings.SetOption("ocr_window_name", ocr_window_name)
+    settings.IsArgumentSetting(ctx, "ocr_window_name") and settings.SetOption("ocr_window_name", ocr_window_name)
 
+    settings.IsArgumentSetting(ctx, "flan_enabled") and settings.SetOption("flan_enabled", flan_enabled)
 
     if websocket_ip != "0":
         websocket.StartWebsocketServer(websocket_ip, websocket_port)
@@ -137,7 +148,7 @@ def main(devices, device_index, sample_rate, task, model, language, condition_on
             audioprocessor.q.put(audio_data)
 
             # set typing indicator for VRChat
-            if osc_ip != "0":
+            if osc_ip != "0" and settings.GetOption("osc_typing_indicator"):
                 VRC_OSCLib.Bool(True, "/chatbox/typing", IP=osc_ip, PORT=osc_port)
             # send start info for processing indicator in websocket client
             websocket.BroadcastMessage(json.dumps({"type": "processing_start", "data": True}))
diff --git a/audioprocessor.py b/audioprocessor.py
index c302c03..a0762b2 100644
--- a/audioprocessor.py
+++ b/audioprocessor.py
@@ -10,6 +10,7 @@
 from pydub import AudioSegment
 from whisper.tokenizer import LANGUAGES, TO_LANGUAGE_CODE
 import io
+import flanLanguageModel
 
 # some regular mistakenly recognized words/sentences on mostly silence audio, which are ignored in processing
 blacklist = [
@@ -23,7 +24,10 @@
 # make all list entries lowercase for later comparison
 blacklist = list((map(lambda x: x.lower(), blacklist)))
 
-q = queue.Queue()
+max_queue_size = 5
+queue_timeout = 5
+
+q = queue.Queue(maxsize=max_queue_size)
 
 
 def whisper_get_languages_list_keys():
@@ -46,11 +50,10 @@ def whisper_get_languages():
 def whisper_result_handling(result):
     verbose = settings.GetOption("verbose")
     osc_ip = settings.GetOption("osc_ip")
-    osc_address = settings.GetOption("osc_address")
-    osc_port = settings.GetOption("osc_port")
-    websocket_ip = settings.GetOption("websocket_ip")
+    flan_whisper_answer = settings.GetOption("flan_whisper_answer")
 
     predicted_text = result.get('text').strip()
+    result["type"] = "transcript"
 
     if not predicted_text.lower() in blacklist:
         if not verbose:
@@ -68,13 +71,48 @@ def whisper_result_handling(result):
             result["txt_translation"] = predicted_text
             result["txt_translation_target"] = to_lang
 
-        # Send over OSC
-        if osc_ip != "0":
-            VRC_OSCLib.Chat(predicted_text, True, osc_address, IP=osc_ip, PORT=osc_port,
-                            convert_ascii=settings.GetOption("osc_convert_ascii"))
-        # Send to Websocket
-        if websocket_ip != "0":
-            websocket.BroadcastMessage(json.dumps(result))
+        # replace predicted_text with FLAN response
+        flan_loaded = False
+        # check if FLAN is enabled
+        if flan_whisper_answer and flanLanguageModel.init():
+            flan_osc_prefix = settings.GetOption("flan_osc_prefix")
+            flan_loaded = True
+            result["type"] = "flan_answer"
+            # Only process using FLAN if question is asked
+            if settings.GetOption("flan_process_only_questions"):
+                prompted_text, prompt_change = flanLanguageModel.flan.whisper_result_prompter(predicted_text)
+                if prompt_change:
+                    predicted_text = flanLanguageModel.flan.encode(prompted_text)
+                    result['flan_answer'] = predicted_text
+                    print("FLAN question: " + prompted_text)
+                    print("FLAN result: " + predicted_text)
+                    send_message(flan_osc_prefix + predicted_text, result)
+            # otherwise process every text with FLAN
+            else:
+                print("flan general processing")
+                predicted_text = flanLanguageModel.flan.encode(predicted_text)
+                result['text'] = predicted_text
+                print("FLAN result: " + predicted_text)
+                send_message(flan_osc_prefix + predicted_text, result)
+
+        # send regular message if flan was not loaded
+        if not flan_loaded:
+            send_message(predicted_text, result)
+
+
+def send_message(predicted_text, result_obj):
+    osc_ip = settings.GetOption("osc_ip")
+    osc_address = settings.GetOption("osc_address")
+    osc_port = settings.GetOption("osc_port")
+    websocket_ip = settings.GetOption("websocket_ip")
+
+    # Send over OSC
+    if osc_ip != "0":
+        VRC_OSCLib.Chat(predicted_text, True, True, osc_address, IP=osc_ip, PORT=osc_port,
+                        convert_ascii=settings.GetOption("osc_convert_ascii"))
+    # Send to Websocket
+    if websocket_ip != "0":
+        websocket.BroadcastMessage(json.dumps(result_obj))
 
 
 def load_whisper(model, ai_device):
@@ -97,10 +135,24 @@ def whisper_worker():
     whisper_ai_device = settings.GetOption("ai_device")
     audio_model = load_whisper(whisper_model, whisper_ai_device)
 
-    print("Say something!")
+    print("Whisper AI Ready. You can now say something!")
 
     while True:
-        audio_sample = convert_audio(q.get())
+        try:
+            audio = q.get(timeout=queue_timeout)
+        except queue.Empty:
+            # print("Queue processing timed out. Skipping...")
+            continue
+        except queue.Full:
+            print("Queue is full. Skipping...")
+            continue
+
+        # skip if queue is full
+        if q.qsize() >= max_queue_size:
+            q.task_done()
+            continue
+
+        audio_sample = convert_audio(audio)
 
         whisper_task = settings.GetOption("whisper_task")
 
@@ -112,6 +164,7 @@ def whisper_worker():
                                         condition_on_previous_text=whisper_condition_on_previous_text)
 
         whisper_result_handling(result)
+
         q.task_done()
 
 
diff --git a/flanLanguageModel.py b/flanLanguageModel.py
new file mode 100644
index 0000000..7c20114
--- /dev/null
+++ b/flanLanguageModel.py
@@ -0,0 +1,128 @@
+# pip install accelerate
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+import torch
+from pathlib import Path
+import os
+import settings
+import random
+import downloader
+
+# MODEL_LINKS = {
+#     "small": "google/flan-t5-small",
+#     "base": "google/flan-t5-base",
+#     "large": "google/flan-t5-large",
+#     "xl": "google/flan-t5-xl",
+#     "xxl": "google/flan-t5-xxl"
+# }
+
+MODEL_LINKS = {
+    "small": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/FLAN-T5%2Fsmall.zip",
+    "base": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/FLAN-T5%2Fbase.zip",
+    "large": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/FLAN-T5%2Flarge.zip",
+    "xl": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/FLAN-T5%2Fxl.zip",
+    "xxl": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/FLAN-T5%2Fxxl.zip"
+}
+
+cache_path = Path(Path.cwd() / ".cache" / "flan-t5-cache")
+os.makedirs(cache_path, exist_ok=True)
+weight_offload_folder = Path(cache_path / "weight_offload")
+os.makedirs(weight_offload_folder, exist_ok=True)
+
+flan = None
+
+PROMPT_FORMATTING = {
+    "question": ["about ", "across ", "after ", "against ", "along ", "am ", "amn't ", "among ", "are ", "aren't ", "around ", "at ", "before ", "behind ", "between ",
+                 "beyond ", "but ", "by ", "can ", "can't ", "concerning ", "could ", "couldn't ", "despite ", "did ", "didn't ", "do ", "does ", "doesn't ", "don't ",
+                 "down ", "during ", "except ", "following ", "for ", "from ", "had ", "hadn't ", "has ", "hasn't ", "have ", "haven't ", "how ", "how's ", "in ",
+                 "including ", "into ", "is ", "isn't ", "like ", "may ", "mayn't ", "might ", "mightn't ", "must ", "mustn't ", "near ", "of ", "off ", "on ", "out ",
+                 "over ", "plus ", "shall ", "shan't ", "should ", "shouldn't ", "since ", "through ", "throughout ", "to ", "towards ", "under ", "until ", "up ", "upon ",
+                 "was ", "wasn't ", "were ", "weren't ", "what ", "what's ", "when ", "when's ", "where ", "where's ", "which ", "which's ", "who ", "who's ", "why ",
+                 "why's ", "will ", "with ", "within ", "without ", "won't ", "would ", "wouldn't "]
+}
+
+
+class FlanLanguageModel:
+    tokenizer = None
+    model = None
+    model_size = "large"
+    max_length = 50  # max result token length. default is 20
+    bit_length = 32  # can be 32 = 32 float, 16 = 16 float or 8 = 8 int
+    device_map = "auto"  # can be "auto" or None
+    low_cpu_mem_usage = True
+
+    # Set the device. "cuda" for GPU or None for CPU
+    def __init__(self, model_size, device="auto", bit_length=32):
+        self.model_size = model_size
+        self.device_map = device
+        self.bit_length = bit_length
+
+        model_path = Path(cache_path / model_size)
+
+        if not model_path.exists():
+            print(f"Downloading {model_size} FLAN-T5 model...")
+            downloader.download_extract(MODEL_LINKS[model_size], str(cache_path.resolve()))
+
+        model_path_string = str(model_path.resolve())
+
+        self.tokenizer = T5Tokenizer.from_pretrained(model_path_string, cache_dir=str(cache_path.resolve()))
+
+        match self.bit_length:
+            case 16:  # 16 bit float
+                self.model = T5ForConditionalGeneration.from_pretrained(model_path_string, device_map=self.device_map, torch_dtype=torch.float16,
+                                                                        offload_folder=str(weight_offload_folder.resolve()))
+            case 8:  # 8 bit int
+                self.model = T5ForConditionalGeneration.from_pretrained(model_path_string, device_map=self.device_map, load_in_8bit=True,
+                                                                        offload_folder=str(weight_offload_folder.resolve()))
+            case _:  # 32 bit float
+                self.model = T5ForConditionalGeneration.from_pretrained(model_path_string, device_map=self.device_map,
+                                                                        offload_folder=str(weight_offload_folder.resolve()))
+
+    # Try to modify prompts to get better results
+    @staticmethod
+    def whisper_result_prompter(whisper_result: str):
+        prompt_change = False
+        question = whisper_result.strip().lower()
+        question_prompt = whisper_result.strip()
+
+        possible_prompt_prefixes = []
+        # looks like a question
+        if "?" in question and any(ele in question for ele in PROMPT_FORMATTING['question']):
+            possible_prompt_prefixes.append("Answer the following question by reasoning step-by-step. ")
+            possible_prompt_prefixes.append("Answer the following question. ")
+            possible_prompt_prefixes.append("Question: ")
+            possible_prompt_prefixes.append("Q: ")
+            prompt_change = True
+
+        if prompt_change:
+            question_prompt = random.choice(possible_prompt_prefixes) + question_prompt
+
+        return question_prompt, prompt_change
+
+    def encode(self, input_text, token_length=max_length):
+        if self.device_map == "auto":
+            input_ids = self.tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
+        else:
+            input_ids = self.tokenizer(input_text, return_tensors="pt").input_ids
+
+        outputs = self.model.generate(input_ids, max_new_tokens=token_length)
+        result = self.tokenizer.decode(outputs[0]).replace("<pad>", "").replace("</s>", "").replace("<unk>", "").strip()
+
+        return result
+
+
+def init():
+    global flan
+    if settings.GetOption("flan_enabled") and flan is None:
+        model_size = settings.GetOption("flan_size")
+        flan_bits = settings.GetOption("flan_bits")
+        flan_device = "auto" if settings.GetOption("flan_device") == "cuda" or settings.GetOption("flan_device") == "auto" else None
+        print(f"Flan {model_size} is Loading to {('GPU' if flan_device == 'auto' else 'CPU')} using {flan_bits} bit {('INT' if flan_bits == 8 else 'float')} precision...")
+
+        flan = FlanLanguageModel(model_size, bit_length=flan_bits, device=flan_device)
+        print("Flan loaded.")
+        return True
+    else:
+        if flan is not None:
+            return True
+        else:
+            return False
diff --git a/requirements.txt b/requirements.txt
index 1a568fa..f729cd3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -18,7 +18,7 @@ pykakasi>=2.2.1
 ctranslate2>=2.17.0
 fairseq
 sentencepiece>=0.1.96
-protobuf
+protobuf==3.20.1
 progressbar2
 
 pywin32
diff --git a/settings.py b/settings.py
index 6e82518..0f199bb 100644
--- a/settings.py
+++ b/settings.py
@@ -1,22 +1,88 @@
+# noinspection PyPackageRequirements
+import yaml
+import os
+from pathlib import Path
+from click import core
+
+SETTINGS_PATH = Path(Path.cwd() / 'settings.yaml')
+
 TRANSLATE_SETTINGS = {
-    # argostranslate settings
-    "txt_translate": False,
-    "src_lang": "en",
-    "trg_lang": "fr",
-    "txt_ascii": False,
+    # text translate settings
+    "txt_translate": False,  # if enabled, pipes whisper A.I. results through text translator
+    "src_lang": "en",  # source language for text translator (Whisper A.I. in translation mode always translates to "en")
+    "trg_lang": "fr",  # target language for text translator
+    "txt_ascii": False,  # if enabled, text translator will convert text to romaji.
     "txt_translator": "M2M100",  # can be "M2M100" or "ARGOS"
+    "m2m100_size": "small",  # M2M100 model size. Can be "small" or "large"
 
     # ocr settings
-    "ocr_lang": "en",
+    "ocr_lang": "en",  # language for OCR image to text recognition.
+    "ocr_window_name": "VRChat",  # window name for OCR image to text recognition.
 
     # whisper settings
-    "whisper_task": "transcribe"
+    "ai_device": None,  # can be None (auto), "cuda" or "cpu".
+    "whisper_task": "transcribe",  # Whisper A.I. Can do "transcribe" or "translate"
+    "current_language": None,  # can be None (auto) or any Whisper supported language.
+    "model": "small",  # Whisper model size. Can be "tiny", "base", "small", "medium" or "large"
+    "condition_on_previous_text": False,  # if enabled, Whisper will condition on previous text. (more prone to loops or getting stuck)
+
+    # OSC settings
+    "osc_ip": "0",
+    "osc_port": 9000,
+    "osc_address": "/chatbox/input",
+    "osc_typing_indicator": True,
+    "osc_convert_ascii": "False",
+
+    # websocket settings
+    "websocket_ip": "0",
+    "websocket_port": 5000,
+
+    # FLAN settings
+    "flan_enabled": False,  # Enable FLAN A.I.
+    "flan_size": "xl",  # FLAN model size. Can be "small", "base", "large", "xl" or "xxl"
+    "flan_bits": 32,  # precision can be set to 32 (float), 16 (float) or 8 (int) bits. 8 bits is the fastest but least precise
+    "flan_device": "cpu",  # can be "cpu", "cuda" or "auto". ("cuda" and "auto" doing the same)
+    "flan_whisper_answer": True,  # if True, the FLAN A.I. will answer to results from the Whisper A.I.
+    "flan_process_only_questions": True,  # if True, the FLAN A.I. will only answer to questions
+    "flan_osc_prefix": "AI: "  # prefix for OSC messages
 }
 
 
 def SetOption(setting, value):
-    TRANSLATE_SETTINGS[setting] = value
+    if setting in TRANSLATE_SETTINGS:
+        if TRANSLATE_SETTINGS[setting] != value:
+            TRANSLATE_SETTINGS[setting] = value
+            # Save settings
+            SaveYaml(SETTINGS_PATH)
+    else:
+        TRANSLATE_SETTINGS[setting] = value
+        # Save settings
+        SaveYaml(SETTINGS_PATH)
 
 
 def GetOption(setting):
     return TRANSLATE_SETTINGS[setting]
+
+
+def LoadYaml(path):
+    print(path)
+    if os.path.exists(path):
+        with open(path, "r") as f:
+            TRANSLATE_SETTINGS.update(yaml.safe_load(f))
+
+
+def SaveYaml(path):
+    to_save_settings = TRANSLATE_SETTINGS.copy()
+    if "whisper_languages" in to_save_settings:
+        del to_save_settings['whisper_languages']
+    if "lang_swap" in to_save_settings:
+        del to_save_settings['lang_swap']
+    if "verbose" in to_save_settings:
+        del to_save_settings['verbose']
+
+    with open(path, "w") as f:
+        yaml.dump(to_save_settings, f)
+
+
+def IsArgumentSetting(ctx, argument_name):
+    return ctx.get_parameter_source(argument_name) == core.ParameterSource.COMMANDLINE
diff --git a/texttranslate.py b/texttranslate.py
index 90f127f..341bd40 100644
--- a/texttranslate.py
+++ b/texttranslate.py
@@ -1,7 +1,7 @@
 import settings
 import pykakasi
 import texttranslateARGOS
-#import texttranslateM2M100
+# import texttranslateM2M100
 import texttranslateM2M100_CTranslate2
 
 
diff --git a/websocket.py b/websocket.py
index 28acf5f..7ddba8a 100644
--- a/websocket.py
+++ b/websocket.py
@@ -2,16 +2,20 @@
 import asyncio
 import websockets
 import json
+
 import texttranslate
 import imagetranslate
 from windowcapture import WindowCapture
 import settings
 import VRC_OSCLib
+import flanLanguageModel
+
 
 WS_CLIENTS = set()
 
 
 def websocketMessageHandler(msgObj):
+
     if msgObj["type"] == "setting_change":
         settings.SetOption(msgObj["name"], msgObj["value"])
         BroadcastMessage(json.dumps({"type": "translate_settings", "data": settings.TRANSLATE_SETTINGS}))  # broadcast updated settings to all clients
@@ -26,6 +30,11 @@ def websocketMessageHandler(msgObj):
         translate_result = (texttranslate.TranslateLanguage(" -- ".join(ocr_result), msgObj["from_lang"], msgObj["to_lang"]))
         BroadcastMessage(json.dumps({"type": "translate_result", "original_text": "\n".join(ocr_result), "translate_result": "\n".join(translate_result.split(" -- "))}))
 
+    if msgObj["type"] == "flan_req":
+        if flanLanguageModel.init():
+            flan_result = flanLanguageModel.flan.encode(msgObj["text"])
+            BroadcastMessage(json.dumps({"type": "flan_result", "flan_result": flan_result}))
+
     if msgObj["type"] == "get_windows_list":
         windows_list = WindowCapture.list_window_names()
         BroadcastMessage(json.dumps({"type": "windows_list", "data": windows_list}))
diff --git a/websocket_clients/streaming-overlay-01/index.html b/websocket_clients/streaming-overlay-01/index.html
index 14466b0..913be10 100644
--- a/websocket_clients/streaming-overlay-01/index.html
+++ b/websocket_clients/streaming-overlay-01/index.html
@@ -13,7 +13,10 @@
       <link rel="stylesheet" media="all" href="main.css">
 
       <script type = "text/javascript">
-         var websocketServer = "ws://127.0.0.1:5000"
+         let websocketServer = "ws://127.0.0.1:5000"
+
+         let hideTimeouts = [];
+         let loaderTimeouts = [];
          
          // url argument handling
          function getParameter(name) {
@@ -28,7 +31,7 @@
             return undefined;
          }
          function clearAllTimeouts(timeoutList) {
-             for (var i = 0; i < timeoutList.length; i++) {
+             for (let i = 0; i < timeoutList.length; i++) {
                 clearTimeout(timeoutList[i]);
              }
          }
@@ -41,7 +44,6 @@
          auto_hide_message = getParameter("auto_hide_message");
          if (typeof auto_hide_message != 'undefined') {
             auto_hide_msg_time = auto_hide_message;
-            var hideTimeouts = [];
          } else {
             auto_hide_msg_time = 0;
          }
@@ -69,7 +71,6 @@
             }
 
             // loader animation
-            var loaderTimeouts = [];
             function showLoader(hideTime = 5) {
                document.querySelector('#loader').classList.remove("hidden");
                loaderTimeouts.push(
@@ -87,7 +88,7 @@
             function addMessage(message, type, deleteTime = 0, hideTime = 0) {
 
                 if ('content' in document.createElement('template')) {
-                    var el = document.querySelector('#sse .transcriptions');
+                    let el = document.querySelector('#sse .transcriptions');
                     // Instantiate the table with the existing HTML tbody
                     // and the row with the template
                     const template = document.querySelector('#transcript-part');
@@ -127,8 +128,8 @@
                 } else {
                     // Find another way to add the rows to the table because
                     // the HTML template element is not supported.
-                    var el = document.getElementById('sse');
-                    var elemDiv = document.createElement('p');
+                    let el = document.getElementById('sse');
+                    let elemDiv = document.createElement('p');
                     elemDiv.style.cssText = 'width:100%;z-index:100;background:#fff;color:#000;';
                     elemDiv.innerText = message;
                     el.appendChild(elemDiv);
@@ -139,7 +140,7 @@
                function showAllTranscriptions() {
                   clearAllTimeouts(hideTimeouts);
                   // first reshow all messages when a new message appears.
-                  var transcriptElements = document.querySelectorAll('#sse .transcriptions .transcript');
+                  let transcriptElements = document.querySelectorAll('#sse .transcriptions .transcript');
                   transcriptElements.forEach((transcriptElement) => {
                      transcriptElement.classList.remove("hide-transcript");
                      hideTimeouts.push(
@@ -155,7 +156,7 @@
             function WebSocketStart() {
                if ("WebSocket" in window) {               
                   // Let us open a web socket
-                  var ws = new ReconnectingWebSocket(websocketServer, null, {reconnectInterval: 5000});
+                  let ws = new ReconnectingWebSocket(websocketServer, null, {reconnectInterval: 5000});
                
                   ws.onopen = function() {
                      // Web Socket is connected.
@@ -163,13 +164,14 @@
                   };
                
                   ws.onmessage = function (evt) {
-                     var received_msg = JSON.parse(evt.data);
+                     let received_msg = JSON.parse(evt.data);
                      
-                     // receiving a transcitption message
-                     if (typeof received_msg.text != 'undefined') {
+                     // receiving a transcription message
+                     if (typeof received_msg.type != 'undefined' && received_msg.type === "transcript" && typeof received_msg.text != 'undefined') {
                         console.log(received_msg);
 
-                        message_text = received_msg.text.trim();
+                        let message_text = received_msg.text.trim();
+                        let txt_translation_html = "";
                         // use argos translate text result if received
                         if (typeof received_msg.txt_translation != 'undefined' && received_msg.txt_translation.trim() !== '') {
                            message_text = received_msg.txt_translation.trim();
@@ -177,6 +179,7 @@
                            txt_translation_html = "<br /><small><sup>[" + received_msg.txt_translation_target + "]</sup> " + received_msg.txt_translation.trim() + "</small>";
                         }
 
+                        let messageHtml = "";
                         switch (show_transl_results) {
                             case 'both':
                                 messageHtml = "<sup class=\"mainsup\">[" + received_msg.language + "]</sup> " + received_msg.text.trim() + txt_translation_html;
@@ -198,6 +201,27 @@
                         );
                      }
 
+
+                      // receiving a flan answer
+                      if (typeof received_msg.type != 'undefined' && received_msg.type === "flan_answer") {
+                         let message_text = received_msg.text.trim();
+                         if (typeof received_msg.txt_translation != 'undefined' && received_msg.txt_translation !== '') {
+                            message_text = received_msg.txt_translation;
+                         }
+                         let question = message_text;
+                         let answer = received_msg.flan_answer;
+
+                         let messageHtml = "<small>Q: " + question + "</small><br /><sup class=\"mainsup\">[" + received_msg.language + "]</sup>A: " + answer;
+
+                         hideLoader();
+                         addMessage(
+                            messageHtml,
+                            "alert-warning",
+                            auto_remove_msg_time,
+                            auto_hide_msg_time
+                         );
+                      }
+
                      // receiving other messages
                      if (!no_loader && typeof received_msg.type != 'undefined' && received_msg.type === "processing_start") {
                          clearAllTimeouts(loaderTimeouts);
diff --git a/websocket_clients/streaming-overlay-01/main.css b/websocket_clients/streaming-overlay-01/main.css
index 287f96f..9a6d3b5 100644
--- a/websocket_clients/streaming-overlay-01/main.css
+++ b/websocket_clients/streaming-overlay-01/main.css
@@ -90,10 +90,10 @@ body.noscroll {
 
 .alert-simple.alert-warning {
   border: 1px solid rgba(241, 142, 6, 0.81);
-  background-color: rgba(220, 128, 1, 0.16);
+  background-color: rgb(227, 176, 104);
   box-shadow: 0px 0px 2px #ffb103;
-  color: #ffb103;
-  text-shadow: 2px 1px #00040a;
+  color: #352500;
+  /*text-shadow: 2px 1px #00040a;*/
   transition: 0.5s;
   cursor: pointer;
 }
@@ -113,8 +113,8 @@ body.noscroll {
   border: 1px solid rgba(241, 6, 6, 0.81);
   background-color: rgba(220, 17, 1, 0.16);
   box-shadow: 0px 0px 2px #ff0303;
-  color: #ff0303;
-  text-shadow: 2px 1px #00040a;
+  color: #4c0000;
+  /*text-shadow: 2px 1px #00040a;*/
   transition: 0.5s;
   cursor: pointer;
 }
diff --git a/websocket_clients/websocket-remote/index.html b/websocket_clients/websocket-remote/index.html
index 9909a18..7c19410 100644
--- a/websocket_clients/websocket-remote/index.html
+++ b/websocket_clients/websocket-remote/index.html
@@ -15,13 +15,17 @@
    <link rel="stylesheet" media="all" href="main.css">
 
    <script type="text/javascript">
-      var websocketServer = "ws://127.0.0.1:5000"
+      let websocketServer = "ws://127.0.0.1:5000";
 
-      var settings = null;
+      let settings = null;
+
+      let hideTimeouts = [];
+      let loaderTimeouts = [];
 
       HTMLSelectElement.prototype.contains = function( value ) {
-          for (var i = 0, l = this.options.length; i < l; i++) {
-              if (this.options[i].value == value) {
+          for (let i = 0, l = this.options.length; i < l; i++) {
+             // noinspection EqualityComparisonWithCoercionJS,JSIncompatibleTypesComparison
+             if (this.options[i].value == value) {
                   return true;
               }
           }
@@ -42,7 +46,7 @@
       }
 
       function clearAllTimeouts(timeoutList) {
-         for (var i = 0; i < timeoutList.length; i++) {
+         for (let i = 0; i < timeoutList.length; i++) {
             clearTimeout(timeoutList[i]);
          }
       }
@@ -55,7 +59,6 @@
       auto_hide_message = getParameter("auto_hide_message");
       if (typeof auto_hide_message != 'undefined') {
          auto_hide_msg_time = auto_hide_message;
-         var hideTimeouts = [];
       } else {
          auto_hide_msg_time = 0;
       }
@@ -84,7 +87,6 @@
          }
 
          // loader animation
-         var loaderTimeouts = [];
          function showLoader(hideTime = 5) {
             document.querySelector('#loader').classList.remove("hidden");
             loaderTimeouts.push(
@@ -102,7 +104,7 @@
          function addMessage(message, type, deleteTime = 0, hideTime = 0, clickEvent = undefined) {
 
             if ('content' in document.createElement('template')) {
-               var el = document.querySelector('#sse .transcriptions');
+               let el = document.querySelector('#sse .transcriptions');
                // Instantiate the table with the existing HTML tbody
                // and the row with the template
                const template = document.querySelector('#transcript-part');
@@ -135,9 +137,8 @@
                // prepend (should not require scrolling)
                el.firstChild.before(clone);
 
-               console.log(clickEvent);
                // add click event
-               if (typeof clickEvent != 'undefined') {
+               if (typeof clickEvent !== 'undefined') {
                   transcriptEl[0].addEventListener("click", clickEvent);
                }
 
@@ -148,8 +149,8 @@
             } else {
                // Find another way to add the rows to the table because
                // the HTML template element is not supported.
-               var el = document.getElementById('sse');
-               var elemDiv = document.createElement('p');
+               let el = document.getElementById('sse');
+               let elemDiv = document.createElement('p');
                elemDiv.style.cssText = 'width:100%;z-index:100;background:#fff;color:#000;';
                elemDiv.innerText = message;
                el.appendChild(elemDiv);
@@ -160,7 +161,7 @@
             function showAllTranscriptions() {
                clearAllTimeouts(hideTimeouts);
                // first reshow all messages when a new message appears.
-               var transcriptElements = document.querySelectorAll('#sse .transcriptions .transcript');
+               let transcriptElements = document.querySelectorAll('#sse .transcriptions .transcript');
                transcriptElements.forEach((transcriptElement) => {
                   transcriptElement.classList.remove("hide-transcript");
                   hideTimeouts.push(
@@ -216,10 +217,10 @@
          function WebSocketStart() {
             if ("WebSocket" in window) {
                // Let us open a web socket
-               var ws = new ReconnectingWebSocket(websocketServer, null, { reconnectInterval: 5000 });
+               let ws = new ReconnectingWebSocket(websocketServer, null, { reconnectInterval: 5000 });
 
                function addWSSettingEvent(elementSelector, eventListener) {
-                  elements = document.querySelectorAll(elementSelector);
+                  let elements = document.querySelectorAll(elementSelector);
                   elements.forEach(element => {
                      element.addEventListener(eventListener, changeSettings);
                   });
@@ -253,9 +254,9 @@
                // send text translation request
                document.querySelector("button#translate_do").addEventListener("click", sendTranslateTask);
                function sendTranslateTask() {
-                  var src_lang = document.querySelector('#settings #src_lang').value;
-                  var trg_lang = document.querySelector('#settings #trg_lang').value;
-                  var translate_text = document.querySelector('#translate_textarea').value;
+                  let src_lang = document.querySelector('#settings #src_lang').value;
+                  let trg_lang = document.querySelector('#settings #trg_lang').value;
+                  let translate_text = document.querySelector('#translate_textarea').value;
 
                   let sendData = { type: "translate_req", text: translate_text, from_lang: src_lang, to_lang: trg_lang };
                   ws.send(JSON.stringify(sendData));
@@ -264,9 +265,9 @@
                // send OCR translation request
                document.querySelector("button#ocr_transl_do").addEventListener("click", sendOCRTranslateTask);
                function sendOCRTranslateTask() {
-                  var ocr_lang = document.querySelector('#settings #ocr_lang').value;
-                  var src_lang = document.querySelector('#settings #src_lang').value;
-                  var trg_lang = document.querySelector('#settings #trg_lang').value;
+                  let ocr_lang = document.querySelector('#settings #ocr_lang').value;
+                  let src_lang = document.querySelector('#settings #src_lang').value;
+                  let trg_lang = document.querySelector('#settings #trg_lang').value;
 
                   let sendData = { type: "ocr_req", ocr_lang: ocr_lang, from_lang: src_lang, to_lang: trg_lang };
                   ws.send(JSON.stringify(sendData));
@@ -284,9 +285,19 @@
                   ws.send(JSON.stringify(sendData));
                }
 
+               // send FLAN request
+               document.querySelector("button#flan_do").addEventListener("click", sendFlanTask);
+               function sendFlanTask() {
+                  let src_text = document.querySelector('#translate_textarea').value;
+
+                  let sendData = { type: "flan_req", text: src_text};
+                  ws.send(JSON.stringify(sendData));
+               }
+
+               // send OCR message
                document.querySelector("button#transl_result_textarea_sendosc").addEventListener("click", sendOSCTask);
                function sendOSCTask() {
-                  var translated_text = document.querySelector('#transl_result_textarea').value;
+                  let translated_text = document.querySelector('#transl_result_textarea').value;
 
                   let sendData = { type: "send_osc", text: translated_text };
                   ws.send(JSON.stringify(sendData));
@@ -301,20 +312,20 @@
                };
 
                ws.onmessage = function (evt) {
-                  var received_msg = JSON.parse(evt.data);
+                  let received_msg = JSON.parse(evt.data);
 
                   // receiving a transcription message
-                  if (typeof received_msg.text != 'undefined') {
+                  if (typeof received_msg.type != 'undefined' && received_msg.type === "transcript" && typeof received_msg.text != 'undefined') {
                      console.log(received_msg);
 
-                     message_text = received_msg.text.trim();
-                     txt_translation_html = "";
+                     let message_text = received_msg.text.trim();
+                     let txt_translation_html = "";
                      if (typeof received_msg.txt_translation != 'undefined' && received_msg.txt_translation !== '') {
                         message_text = received_msg.txt_translation;
 
                         txt_translation_html = "<br /><small><sup>[" + received_msg.txt_translation_target + "]</sup> " + received_msg.txt_translation + "</small>";
                      }
-                     clickEvent = function () {
+                     let clickEvent = function () {
                         document.querySelector('#translate_textarea').value = received_msg.text.trim();
                         if (typeof received_msg.txt_translation != 'undefined') {
                            document.querySelector('#transl_result_textarea').value = received_msg.txt_translation.trim();
@@ -323,6 +334,7 @@
                         }
                      };
 
+                     let messageHtml = "";
                      switch (show_transl_results) {
                          case 'both':
                              messageHtml = "<sup class=\"mainsup\">[" + received_msg.language + "]</sup> " + received_msg.text.trim() + txt_translation_html;
@@ -345,35 +357,45 @@
                      );
                   }
 
+                  // receiving a flan answer
+                  if (typeof received_msg.type != 'undefined' && received_msg.type === "flan_answer") {
+                     let message_text = received_msg.text.trim();
+                     if (typeof received_msg.txt_translation != 'undefined' && received_msg.txt_translation !== '') {
+                        message_text = received_msg.txt_translation;
+                     }
+                     let question = message_text;
+                     let answer = received_msg.flan_answer;
+
+                     let messageHtml = "<small>Q: " + question + "</small><br /><sup class=\"mainsup\">[" + received_msg.language + "]</sup>A: " + answer;
+
+                     let clickEvent = function () {
+                        document.querySelector('#translate_textarea').value = question;
+                        document.querySelector('#transl_result_textarea').value = answer;
+                     };
+
+                     hideLoader();
+                     addMessage(
+                        messageHtml,
+                        "alert-warning",
+                        auto_remove_msg_time,
+                        auto_hide_msg_time,
+                        clickEvent
+                     );
+                  }
+
                   // receiving other messages
-                  // if (typeof received_msg.type != 'undefined' && received_msg.type === "whisper_languages") {
-                  //    // list all available langauges
-                  //    var whisper_lang_el = document.querySelector('#settings #current_language');
-                  //
-                  //    whisper_lang_el.replaceChildren("");
-                  //
-                  //    for (var i = 0; i < received_msg.data.length; i++) {
-                  //       var opt = received_msg.data[i];
-                  //
-                  //       var el = document.createElement("option");
-                  //       el.textContent = "[" + opt.code + "] " + opt.name;
-                  //       el.value = opt.code;
-                  //
-                  //       whisper_lang_el.appendChild(el);
-                  //    }
-                  // }
                   if (typeof received_msg.type != 'undefined' && received_msg.type === "installed_languages") {
                      // list all available langauges
-                     var src_lang_el = document.querySelector('#settings #src_lang');
-                     var trg_lang_el = document.querySelector('#settings #trg_lang');
+                     let src_lang_el = document.querySelector('#settings #src_lang');
+                     let trg_lang_el = document.querySelector('#settings #trg_lang');
 
                      src_lang_el.replaceChildren("");
                      trg_lang_el.replaceChildren("");
 
-                     for (var i = 0; i < received_msg.data.length; i++) {
-                        var opt = received_msg.data[i];
+                     for (let i = 0; i < received_msg.data.length; i++) {
+                        let opt = received_msg.data[i];
 
-                        var el = document.createElement("option");
+                        let el = document.createElement("option");
                         el.textContent = "[" + opt.code + "] " + opt.name;
                         el.value = opt.code;
 
@@ -383,14 +405,14 @@
                   }
                   if (typeof received_msg.type != 'undefined' && received_msg.type === "available_img_languages") {
                      // list all available langauges
-                     var img_lang_el = document.querySelector('#settings #ocr_lang');
+                     let img_lang_el = document.querySelector('#settings #ocr_lang');
 
                      img_lang_el.replaceChildren("");
 
-                     for (var i = 0; i < received_msg.data.length; i++) {
-                        var opt = received_msg.data[i];
+                     for (let i = 0; i < received_msg.data.length; i++) {
+                        let opt = received_msg.data[i];
 
-                        var el = document.createElement("option");
+                        let el = document.createElement("option");
                         el.textContent = "[" + opt.code + "] " + opt.name;
                         el.value = opt.code;
 
@@ -421,13 +443,13 @@
 
                         // populate whisper languages
                         if (settingKey === 'whisper_languages') {
-                           var whisper_lang_el = document.querySelector('#settings #current_language');
+                           let whisper_lang_el = document.querySelector('#settings #current_language');
 
                            whisper_lang_el.replaceChildren("");
-                           for (var i = 0; i < settingValue.length; i++) {
-                              var opt = settingValue[i];
+                           for (let i = 0; i < settingValue.length; i++) {
+                              let opt = settingValue[i];
 
-                              var el = document.createElement("option");
+                              let el = document.createElement("option");
 
                               el.textContent = "[" + opt.code + "] " + opt.name;
                               if (opt.code === '') {
@@ -454,10 +476,17 @@
                         }
                      }
 
-                     var osc_ip = received_msg.data.osc_ip;
+                     // disable send osc button if no osc server is defined
+                     let osc_ip = received_msg.data.osc_ip;
                      if (osc_ip === 0) {
                         document.querySelector('button#transl_result_textarea_sendosc').disabled = true;
                      }
+
+                     // disable flan button if flan is disabled
+                     let flan_enabled = received_msg.data.flan_enabled;
+                     if (!flan_enabled) {
+                        document.querySelector('button#flan_do').disabled = true;
+                     }
                   }
                   if (typeof received_msg.type != 'undefined' && received_msg.type === "translate_result") {
                      document.querySelector('#transl_result_textarea').value = received_msg.translate_result;
@@ -466,14 +495,14 @@
                      }
                   }
                   if (typeof received_msg.type != 'undefined' && received_msg.type === "windows_list") {
-                     var ocr_window_el = document.querySelector('select#ocr_window_name');
-                     var ocr_current_window = ocr_window_el.value;
+                     let ocr_window_el = document.querySelector('select#ocr_window_name');
+                     let ocr_current_window = ocr_window_el.value;
                      ocr_window_el.replaceChildren("");
 
-                     for (var i = 0; i < received_msg.data.length; i++) {
-                        var opt = received_msg.data[i];
+                     for (let i = 0; i < received_msg.data.length; i++) {
+                        let opt = received_msg.data[i];
 
-                        var el = document.createElement("option");
+                        let el = document.createElement("option");
 
                         //el.textContent = "[" + opt.hwnd + "] " + opt.title;
                         el.textContent = opt.title;
@@ -490,6 +519,11 @@
                      ocr_window_el.value = ocr_current_window;
                   }
 
+                  // get flan result
+                  if (typeof received_msg.type != 'undefined' && received_msg.type === "flan_result") {
+                     document.querySelector('#transl_result_textarea').value = received_msg.flan_result;
+                  }
+
                   // activate loading animation on processing_start message
                   if (!no_loader && typeof received_msg.type != 'undefined' && received_msg.type === "processing_start") {
                      clearAllTimeouts(loaderTimeouts);
@@ -541,7 +575,9 @@
                      name="condition_on_previous_text" value="1" />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
                   <label for="current_language">speaker language:</label> <select name="current_language" id="current_language">
                         <option value="">Auto</option>
-                  </select>
+                  </select>&nbsp;&nbsp;&nbsp;&nbsp;
+                  <label for="flan_whisper_answer">FLAN-T5 answering:</label> <input type="checkbox" id="flan_whisper_answer"
+                     name="flan_whisper_answer" value="1" />
                   <hr />
                </div>
             </div>
@@ -580,7 +616,7 @@
    <div id="manual_translate" class="hidden">
       <section>
          <div class="container mt-3">
-            Translate:
+            Input:
             <div id="text_translate_form" class="container lt-2" style="padding: 0;">
                <div class="row no-gutters">
                   <div class="col-5">
@@ -588,7 +624,8 @@
                   </div>
                   <div class="col-1">
                      <button name="translate_do" id="translate_do" value="1" style="width: 100%;">translate</button>
-                     <div style="text-align:center;"><button name="ocr_transl_do" id="ocr_transl_do" value="1" title="OCR translation">OCR transl.</button></div>
+                     <div style="text-align:center;"><button name="ocr_transl_do" id="ocr_transl_do" value="1" title="Optical Character Recognition processing" style="width: 100%;">OCR</button></div>
+                     <div style="text-align:center;"><button name="flan_do" id="flan_do" value="1" title="Ask FLAN A.I." style="width: 100%;">ask FLAN</button></div>
                   </div>
                   <div class="col-5">
                      <textarea style="width:100%;" name="transl_result_textarea" id="transl_result_textarea"></textarea>
diff --git a/websocket_clients/websocket-remote/main.css b/websocket_clients/websocket-remote/main.css
index 287f96f..9a6d3b5 100644
--- a/websocket_clients/websocket-remote/main.css
+++ b/websocket_clients/websocket-remote/main.css
@@ -90,10 +90,10 @@ body.noscroll {
 
 .alert-simple.alert-warning {
   border: 1px solid rgba(241, 142, 6, 0.81);
-  background-color: rgba(220, 128, 1, 0.16);
+  background-color: rgb(227, 176, 104);
   box-shadow: 0px 0px 2px #ffb103;
-  color: #ffb103;
-  text-shadow: 2px 1px #00040a;
+  color: #352500;
+  /*text-shadow: 2px 1px #00040a;*/
   transition: 0.5s;
   cursor: pointer;
 }
@@ -113,8 +113,8 @@ body.noscroll {
   border: 1px solid rgba(241, 6, 6, 0.81);
   background-color: rgba(220, 17, 1, 0.16);
   box-shadow: 0px 0px 2px #ff0303;
-  color: #ff0303;
-  text-shadow: 2px 1px #00040a;
+  color: #4c0000;
+  /*text-shadow: 2px 1px #00040a;*/
   transition: 0.5s;
   cursor: pointer;
 }

From ddf29651580cb9700b3d2a735a5fd825b1f310be Mon Sep 17 00:00:00 2001
From: Sharrnah <55756126+Sharrnah@users.noreply.github.com>
Date: Sun, 13 Nov 2022 15:15:25 +0100
Subject: [PATCH 2/2] [TASK] Add NLLB200 text translator [TASK] Update
 dependencies [TASK] Add language classifier for autodetecting language of
 text [TASK] Add Flan feature - responding in speaker language

---
 README.md                                     |  65 +--
 VRC_OSCLib.py                                 |   2 +-
 audioWhisper.py                               |  12 +-
 audioprocessor.py                             |   9 +-
 documentation/settings-file.md                |  46 ++
 documentation/websocket-clients.md            |  24 +-
 flanLanguageModel.py                          |  18 +-
 images/remote_control.png                     | Bin 29311 -> 40182 bytes
 languageClassification.py                     |  24 +
 requirements.txt                              |   5 +-
 settings.py                                   |  15 +-
 texttranslate.py                              |  13 +-
 texttranslateNLLB200.py                       | 482 ++++++++++++++++++
 websocket.py                                  |   8 +-
 .../streaming-overlay-01/index.html           |   7 +
 .../streaming-overlay-01/main.css             |  16 +
 websocket_clients/websocket-remote/index.html |  63 ++-
 websocket_clients/websocket-remote/main.css   |  16 +
 18 files changed, 746 insertions(+), 79 deletions(-)
 create mode 100644 documentation/settings-file.md
 create mode 100644 languageClassification.py
 create mode 100644 texttranslateNLLB200.py

diff --git a/README.md b/README.md
index ba47f09..f3588cb 100644
--- a/README.md
+++ b/README.md
@@ -13,6 +13,7 @@ It allows connecting to OSC (for VRChat for example) and Websockets (For Streami
 - [Usage](#usage)
 - [Websocket Clients](documentation/websocket-clients.md)
 - [Command-line flags](#command-line-flags)
+- [Settings File](documentation/settings-file.md)
 - [Usage with 3rd Party Applications](#usage-with-3rd-party-applications)
   - [VRChat](#vrchat)
   - [Live Streaming Applications (OBS, vMix, XSplit ...)](#live-streaming-applications-obs-vmix-xsplit-)
@@ -38,41 +39,43 @@ _(because of the 2 GB Limit, no direct release files on GitHub)_
 2. run `audioWhisper\audioWhisper.exe`. By default, it tries to find your default Microphone. Otherwise, you need to add `--device_index *` to the run command where the `*` is the device index found at step 3. Find more command-line flags in the following table.
 3. If websocket option is enabled, you can control the whisper task (translate or transcript) as well as textual translation options while the AI is running.
    
-   <img src=images/remote_control.png width=600>
+   <img src=images/remote_control.png width=750>
    
    For this: open the `websocket_clients/websocket-remote/` folder and start the index.html there.
    
    _If you have the AI running on a secondary PC, open the HTML file with the IP as parameter like this: `index.html?ws_server=ws://127.0.0.1:5000`_
 
 ## Command-line flags
-|            --flags             | Default Value  |                                                               Description                                                                |
-|:------------------------------:|:--------------:|:----------------------------------------------------------------------------------------------------------------------------------------:|
-|          `--devices`           |     False      |                                                       Print all available devices.                                                       |
-|        `--device_index`        |       -1       |             Choose the output device to listen to and transcribe the audio from this device. '-1' = auto-select by default.              |
-|        `--sample_rate`         |     16000      |                                                   Sample rate of the audio recording.                                                    |
-|         `--ai_device`          |      None      |                         defines on which device the AI is loaded. can be `cuda` or `cpu`. auto-select by default                         |
-|            `--task`            |   transcribe   |                                  Choose between to `transcribe` or to `translate` the audio to English.                                  |
-|           `--model`            |     small      |           Select model list. can be `tiny, base, small, medium, large`. where large models are not available for english only.           |
-|          `--language`          |      None      |                                 language spoken in the audio, specify None to perform language detection                                 |
-| `--condition_on_previous_text` |     False      | Feed it the previous result to keep it consistent across recognition windows, but makes it more prone to getting stuck in a failure loop |
-|           `--energy`           |      300       |                                                     Energy level for mic to detect.                                                      |
-|       `--dynamic_energy`       |     False      |                                                          Enable dynamic energy.                                                          |
-|           `--pause`            |      0.8       |                                                      Pause time before entry ends.                                                       |
-|     `--phrase_time_limit`      |      None      |                           Phrase time limit (in seconds) before entry ends to break up long recognition tasks.                           |
-|           `--osc_ip`           |       0        |                     IP to send OSC messages to. Set to '0' to disable. (For VRChat this should mostly be 127.0.0.1)                      |
-|          `--osc_port`          |      9000      |                                       Port to send OSC message to. ('9000' as default for VRChat)                                        |
-|        `--osc_address`         | /chatbox/input |                            The Address the OSC messages are send to. ('/chatbox/input' as default for VRChat)                            |
-|     `--osc_convert_ascii`      |     False      |                                         Convert Text to ASCII compatible when sending over OSC.                                          |
-|        `--websocket_ip`        |       0        |                                       IP where Websocket Server listens on. Set to '0' to disable.                                       |
-|       `--websocket_port`       |      5000      |                                                 Port where Websocket Server listens on.                                                  |
-|       `--txt_translator`       |     M2M100     |                          The Model the AI is loading for text translations. can be 'M2M100', 'ARGOS' or 'None'.                          |
-|        `--m2m100_size`         |     small      |         The Model size if M2M100 text translator is used. can be 'small' or 'large'. (has no effect with --txt_translator ARGOS)         |
-|       `--m2m100_device`        |      auto      |            The device used for M2M100 translation. can be 'auto', 'cuda' or 'cpu' (has no effect with --txt_translator ARGOS)            |
-|      `--ocr_window_name`       |     VRChat     |                                           Window name of the application for OCR translations.                                           |
-|        `--flan_enabled`        |     False      |                               Enable FLAN-T5 A.I. (General A.I. which can be used for Question Answering.)                               |
-|        `--open_browser`        |     False      |                     Open default Browser with websocket-remote on start. (requires --websocket_ip to be set as well)                     |
-|           `--config`           |      None      |    Use the specified config file instead of the default 'settings.yaml' (relative to the current path) [overwrites without asking!!!]    |
-|          `--verbose`           |     False      |                                                     Whether to print verbose output.                                                     |
+_These take precedence to the [settings file](documentation/settings-file.md). But not all options are available as command-line flags._
+
+|            --flags             | Default Value  |                                                                                        Description                                                                                        |
+|:------------------------------:|:--------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+|          `--devices`           |     False      |                                                                               Print all available devices.                                                                                |
+|        `--device_index`        |       -1       |                                      Choose the output device to listen to and transcribe the audio from this device. '-1' = auto-select by default.                                      |
+|        `--sample_rate`         |     16000      |                                                                            Sample rate of the audio recording.                                                                            |
+|         `--ai_device`          |      None      |                                                 defines on which device the AI is loaded. can be `cuda` or `cpu`. auto-select by default                                                  |
+|            `--task`            |   transcribe   |                                                          Choose between to `transcribe` or to `translate` the audio to English.                                                           |
+|           `--model`            |     small      |                                   Select model list. can be `tiny, base, small, medium, large`. where large models are not available for english only.                                    |
+|          `--language`          |      None      |                                                         language spoken in the audio, specify None to perform language detection                                                          |
+| `--condition_on_previous_text` |     False      |                         Feed it the previous result to keep it consistent across recognition windows, but makes it more prone to getting stuck in a failure loop                          |
+|           `--energy`           |      300       |                                                                              Energy level for mic to detect.                                                                              |
+|       `--dynamic_energy`       |     False      |                                                                                  Enable dynamic energy.                                                                                   |
+|           `--pause`            |      0.8       |                                                                               Pause time before entry ends.                                                                               |
+|     `--phrase_time_limit`      |      None      |                                                   Phrase time limit (in seconds) before entry ends to break up long recognition tasks.                                                    |
+|           `--osc_ip`           |       0        |                                              IP to send OSC messages to. Set to '0' to disable. (For VRChat this should mostly be 127.0.0.1)                                              |
+|          `--osc_port`          |      9000      |                                                                Port to send OSC message to. ('9000' as default for VRChat)                                                                |
+|        `--osc_address`         | /chatbox/input |                                                    The Address the OSC messages are send to. ('/chatbox/input' as default for VRChat)                                                     |
+|     `--osc_convert_ascii`      |     False      |                                                                  Convert Text to ASCII compatible when sending over OSC.                                                                  |
+|        `--websocket_ip`        |       0        |                                                               IP where Websocket Server listens on. Set to '0' to disable.                                                                |
+|       `--websocket_port`       |      5000      |                                                                          Port where Websocket Server listens on.                                                                          |
+|       `--txt_translator`       |     M2M100     |                                                  The Model the AI is loading for text translations. can be 'M2M100', 'ARGOS' or 'None'.                                                   |
+|    `--txt_translator_size`     |     small      | The Model size of M2M100 or NLLB200 text translator is used. can be 'small', 'medium', 'large' for NLLB200, or 'small' or 'large' for M2M100. (has no effect with --txt_translator ARGOS) |
+|   `--txt_translator_device`    |      auto      |                               The device used for M2M100 translation. can be 'auto', 'cuda' or 'cpu' (has no effect with --txt_translator ARGOS or NLLB200)                               |
+|      `--ocr_window_name`       |     VRChat     |                                                                   Window name of the application for OCR translations.                                                                    |
+|        `--flan_enabled`        |     False      |                                                       Enable FLAN-T5 A.I. (General A.I. which can be used for Question Answering.)                                                        |
+|        `--open_browser`        |     False      |                                             Open default Browser with websocket-remote on start. (requires --websocket_ip to be set as well)                                              |
+|           `--config`           |      None      |                            Use the specified config file instead of the default 'settings.yaml' (relative to the current path) [overwrites without asking!!!]                             |
+|          `--verbose`           |     False      |                                                                             Whether to print verbose output.                                                                              |
 
 ## Usage with 3rd Party Applications
 ### VRChat
@@ -89,7 +92,9 @@ _(because of the 2 GB Limit, no direct release files on GitHub)_
 
    > `audioWhisper\audioWhisper.exe --model medium --task translate --device_index 4 --energy 300 --phrase_time_limit 15 --websocket_ip 127.0.0.1`
 2. Find a streaming overlay website in the `websocket_clients` folder. (So far only `streaming-overlay-01` is optimized as overlay with transparent background.)
-3. Add the HTML file to your streaming application.
+3. Add the HTML file to your streaming application. (With some additional arguments if needed. See [[Websocket Clients]](documentation/websocket-clients.md#all-possible-configuration-url-arguments) for all possible arguments.)
+   
+   _For example:_ `websocket_clients/streaming-overlay-01/index.html?no_scroll=1&no_loader=1&bottom_align=1&auto_rm_message=15`
 
 ### Desktop+ (Currently only new-ui Beta with embedded Browser)
 1. Run the Application listening on your Audio-Device with the VRChat Sound.
diff --git a/VRC_OSCLib.py b/VRC_OSCLib.py
index d49c380..d924cc8 100644
--- a/VRC_OSCLib.py
+++ b/VRC_OSCLib.py
@@ -106,7 +106,7 @@ def Message(data="example", address="/example", IP='127.0.0.1', PORT=9000):
 
 
 # OSC Send Chat
-def Chat(data="example", send=True, nofify=True, address="/chatbox/input", IP='127.0.0.1', PORT=9000, convert_ascii=True):
+def Chat(data="example", send=True, nofify=True, address="/chatbox/input", IP='127.0.0.1', PORT=9000, convert_ascii=False):
     # OSC Bild
     client = udp_client.UDPClient(IP, PORT)
     msg = OscMessageBuilder(address=address)
diff --git a/audioWhisper.py b/audioWhisper.py
index af1242f..9e2c2f3 100644
--- a/audioWhisper.py
+++ b/audioWhisper.py
@@ -36,9 +36,9 @@
 @click.option("--websocket_ip", default="0", help="IP where Websocket Server listens on. Set to '0' to disable", type=str)
 @click.option("--websocket_port", default=5000, help="Port where Websocket Server listens on. ('5000' as default)", type=int)
 @click.option("--ai_device", default=None, help="The Device the AI is loaded on. can be 'cuda' or 'cpu'. default does autodetect", type=click.Choice(["cuda", "cpu"]))
-@click.option("--txt_translator", default="M2M100", help="The Model the AI is loading for text translations. can be 'M2M100', 'ARGOS' or 'None'. default is M2M100", type=click.Choice(["M2M100", "ARGOS"]))
-@click.option("--m2m100_size", default="small", help="The Model size if M2M100 text translator is used. can be 'small' or 'large'. default is small. (has no effect with ARGOS)", type=click.Choice(["small", "large"]))
-@click.option("--m2m100_device", default="auto", help="The device used for M2M100 translation. (has no effect with ARGOS)", type=click.Choice(["auto", "cuda", "cpu"]))
+@click.option("--txt_translator", default="NLLB200", help="The Model the AI is loading for text translations. can be 'NLLB200', 'M2M100', 'ARGOS' or 'None'. default is M2M100", type=click.Choice(["NLLB200", "M2M100", "ARGOS"]))
+@click.option("--txt_translator_size", default="small", help="The Model size if M2M100 or NLLB200 text translator is used. can be 'small', 'medium' or 'large' for NLLB200 or 'small' or 'large' for M2M100. default is small. (has no effect with ARGOS)", type=click.Choice(["small", "medium", "large"]))
+@click.option("--txt_translator_device", default="auto", help="The device used for M2M100 translation. (has no effect with ARGOS or NLLB200)", type=click.Choice(["auto", "cuda", "cpu"]))
 @click.option("--ocr_window_name", default="VRChat", help="Window name of the application for OCR translations. (Default: 'VRChat')", type=str)
 @click.option("--flan_enabled", default=False, help="Enable FLAN-T5 A.I. (General A.I. which can be used for Question Answering.)", type=bool)
 @click.option("--open_browser", default=False, help="Open default Browser with websocket-remote on start. (requires --websocket_ip to be set as well)", is_flag=True, type=bool)
@@ -46,7 +46,7 @@
 @click.option("--verbose", default=False, help="Whether to print verbose output", is_flag=True, type=bool)
 @click.pass_context
 def main(ctx, devices, device_index, sample_rate, task, model, language, condition_on_previous_text, energy, dynamic_energy, pause, phrase_time_limit, osc_ip, osc_port,
-         osc_address, osc_convert_ascii, websocket_ip, websocket_port, ai_device, txt_translator, m2m100_size, m2m100_device, ocr_window_name, flan_enabled, open_browser, config, verbose):
+         osc_address, osc_convert_ascii, websocket_ip, websocket_port, ai_device, txt_translator, txt_translator_size, txt_translator_device, ocr_window_name, flan_enabled, open_browser, config, verbose):
 
     # Load settings from file
     if config is not None:
@@ -103,8 +103,8 @@ def main(ctx, devices, device_index, sample_rate, task, model, language, conditi
     settings.IsArgumentSetting(ctx, "websocket_port") and settings.SetOption("websocket_port", websocket_port)
 
     settings.IsArgumentSetting(ctx, "txt_translator") and settings.SetOption("txt_translator", txt_translator)
-    settings.IsArgumentSetting(ctx, "m2m100_size") and settings.SetOption("m2m100_size", m2m100_size)
-    texttranslate.SetDevice(m2m100_device)
+    settings.IsArgumentSetting(ctx, "txt_translator_size") and settings.SetOption("txt_translator_size", txt_translator_size)
+    texttranslate.SetDevice(txt_translator_device)
 
     settings.IsArgumentSetting(ctx, "ocr_window_name") and settings.SetOption("ocr_window_name", ocr_window_name)
 
diff --git a/audioprocessor.py b/audioprocessor.py
index a0762b2..cd9e2b4 100644
--- a/audioprocessor.py
+++ b/audioprocessor.py
@@ -67,8 +67,9 @@ def whisper_result_handling(result):
             from_lang = settings.GetOption("src_lang")
             to_lang = settings.GetOption("trg_lang")
             to_romaji = settings.GetOption("txt_ascii")
-            predicted_text = texttranslate.TranslateLanguage(predicted_text, from_lang, to_lang, to_romaji)
+            predicted_text, txt_from_lang, txt_to_lang = texttranslate.TranslateLanguage(predicted_text, from_lang, to_lang, to_romaji)
             result["txt_translation"] = predicted_text
+            result["txt_translation_source"] = txt_from_lang
             result["txt_translation_target"] = to_lang
 
         # replace predicted_text with FLAN response
@@ -83,6 +84,10 @@ def whisper_result_handling(result):
                 prompted_text, prompt_change = flanLanguageModel.flan.whisper_result_prompter(predicted_text)
                 if prompt_change:
                     predicted_text = flanLanguageModel.flan.encode(prompted_text)
+
+                    # translate from auto-detected language to speaker language
+                    if settings.GetOption("flan_translate_to_speaker_language"):
+                        predicted_text, txt_from_lang, txt_to_lang = texttranslate.TranslateLanguage(predicted_text, "auto", result['language'], False, True)
                     result['flan_answer'] = predicted_text
                     print("FLAN question: " + prompted_text)
                     print("FLAN result: " + predicted_text)
@@ -91,7 +96,7 @@ def whisper_result_handling(result):
             else:
                 print("flan general processing")
                 predicted_text = flanLanguageModel.flan.encode(predicted_text)
-                result['text'] = predicted_text
+                result['flan_answer'] = predicted_text
                 print("FLAN result: " + predicted_text)
                 send_message(flan_osc_prefix + predicted_text, result)
 
diff --git a/documentation/settings-file.md b/documentation/settings-file.md
new file mode 100644
index 0000000..b8ad95e
--- /dev/null
+++ b/documentation/settings-file.md
@@ -0,0 +1,46 @@
+# Settings File
+All possible options of the settings file.
+
+_Default name is `settings.yaml`, but can be customized with the `--config` option._
+
+```yaml
+# whisper settings
+ai_device: null  # can be null (auto), "cuda" or "cpu".
+whisper_task: translate  # Whisper A.I. Can do "transcribe" or "translate"
+current_language: null  # can be null (auto) or any Whisper supported language.
+model: small  # Whisper model size. Can be "tiny", "base", "small", "medium" or "large"
+condition_on_previous_text: true  # if enabled, Whisper will condition on previous text. (more prone to loops or getting stuck)
+
+# text translate settings
+txt_translate: false  # if enabled, pipes whisper A.I. results through text translator
+src_lang: auto  # source language for text translator
+trg_lang: fra_Latn  # target language for text translator
+txt_ascii: false  # if enabled, text translator will convert text to romaji.
+txt_translator: NLLB200  # can be "NLLB200", "M2M100" or "ARGOS"
+txt_translator_size: small  # for M2M100 model size: Can be "small" or "large", for NLLB200 model size: Can be "small", "medium", "large".
+
+# websocket settings
+websocket_ip: 127.0.0.1
+websocket_port: 5000
+
+# OSC settings
+osc_ip: '0'
+osc_port: 9000
+osc_address: /chatbox/input
+osc_typing_indicator: true
+osc_convert_ascii: false
+
+# OCR settings
+ocr_lang: en  # language for OCR image to text recognition.
+ocr_window_name: VRChat  # window name for OCR image to text recognition.
+
+# FLAN-T5 settings
+flan_enabled: false  # Enable FLAN A.I.
+flan_size: large  # FLAN model size. Can be "small", "base", "large", "xl" or "xxl"
+flan_bits: 32  # precision can be set to 32 (float), 16 (float) or 8 (int) bits. 8 bits is the fastest but least precise
+flan_device: cpu  # can be "cpu", "cuda" or "auto". ("cuda" and "auto" doing the same)
+flan_whisper_answer: true  # if True, the FLAN A.I. will answer to results from the Whisper A.I.
+flan_process_only_questions: true  # if True, the FLAN A.I. will only answer to questions
+flan_osc_prefix: 'AI: '  # prefix for OSC messages
+flan_translate_to_speaker_language: false  # Translate from english to speaker language
+```
diff --git a/documentation/websocket-clients.md b/documentation/websocket-clients.md
index fec9bef..cb136c7 100644
--- a/documentation/websocket-clients.md
+++ b/documentation/websocket-clients.md
@@ -39,17 +39,19 @@ _(first option is added with a `?`, all following with a `&`)_
 
 ## All possible Configuration URL arguments
 
-|       Arguments       |                    Default Value                     |                                                                                                                      Description                                                                                                                      |
-|:---------------------:|:----------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
-|      `ws_server`      |                 ws://127.0.0.1:5000                  |                                                                                                 Sets the Websocket Server IP and Port to connect to.                                                                                                  |
-|      `no_scroll`      |                         None                         |                                                                                                             Removes the Scrollbar if set.                                                                                                             |
-|      `no_loader`      |                         None                         |                                                                                                    Disables the audio processing indicator if set.                                                                                                    |
-|  `auto_hide_message`  |                          0                           |                                            Sets the Seconds after which Transcriptions are hidden, but not removed. (Can be shown again by clicking in the lower part where the Boxes appear) 0 = Disabled                                            |
-|   `auto_rm_message`   |                          0                           |                                                                   Sets the Seconds after which Transcriptions are removed. (makes it impossible to access them again) 0 = Disabled                                                                    |
-| `show_transl_results` | websocket-remote=`both`<hr/>streaming-overlay=`auto` | Sets what is shown as translation / transcription result. Can be:<br/>`both` = shows both whisper and text translations.<br/>`whisper_only` = shows only Whisper results.<br/>`auto` = shows text translation if available, otherwise Whisper result. |
-
-
-## Other Use-Cases
+|        Arguments        |                    Default Value                     |                                                                                                                      Description                                                                                                                      |
+|:-----------------------:|:----------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+|       `ws_server`       |                 ws://127.0.0.1:5000                  |                                                                                                 Sets the Websocket Server IP and Port to connect to.                                                                                                  |
+|       `no_scroll`       |                         None                         |                                                                                                             Removes the Scrollbar if set.                                                                                                             |
+|     `bottom_align`      |                         None                         |                                                                                                   align to bottom of page (also removes scrolling)                                                                                                    |
+|       `no_loader`       |                         None                         |                                                                                                    Disables the audio processing indicator if set.                                                                                                    |
+|   `auto_hide_message`   |                          0                           |                                            Sets the Seconds after which Transcriptions are hidden, but not removed. (Can be shown again by clicking in the lower part where the Boxes appear) 0 = Disabled                                            |
+|    `auto_rm_message`    |                          0                           |                                                                   Sets the Seconds after which Transcriptions are removed. (makes it impossible to access them again) 0 = Disabled                                                                    |
+|  `show_transl_results`  | websocket-remote=`both`<hr/>streaming-overlay=`auto` | Sets what is shown as translation / transcription result. Can be:<br/>`both` = shows both whisper and text translations.<br/>`whisper_only` = shows only Whisper results.<br/>`auto` = shows text translation if available, otherwise Whisper result. |
+
+
+## Use-Cases
+### Parallel processing of A.I. Transcriptions
 Since it is possible to run multiple AI's concurrently, it is possible to combine multiple Websocket Clients.
 
 For Example, you can create a HTML Page with I-Frames that show the different Websocket Clients.
diff --git a/flanLanguageModel.py b/flanLanguageModel.py
index 7c20114..a0f68e9 100644
--- a/flanLanguageModel.py
+++ b/flanLanguageModel.py
@@ -37,7 +37,18 @@
                  "including ", "into ", "is ", "isn't ", "like ", "may ", "mayn't ", "might ", "mightn't ", "must ", "mustn't ", "near ", "of ", "off ", "on ", "out ",
                  "over ", "plus ", "shall ", "shan't ", "should ", "shouldn't ", "since ", "through ", "throughout ", "to ", "towards ", "under ", "until ", "up ", "upon ",
                  "was ", "wasn't ", "were ", "weren't ", "what ", "what's ", "when ", "when's ", "where ", "where's ", "which ", "which's ", "who ", "who's ", "why ",
-                 "why's ", "will ", "with ", "within ", "without ", "won't ", "would ", "wouldn't "]
+                 "why's ", "will ", "with ", "within ", "without ", "won't ", "would ", "wouldn't "],
+    "statement": ["i ", "i am ", "i am not ", "i was ", "i was not ", "i will ", "i will not ", "i would ", "i would not ", "i have ", "i have not ", "i had ", "i had not ",
+                  "i can ", "i want ", "i need ", "i like ", "i love ", "i hate ", "i don't like ", "i don't love ", "i don't hate ", "i don't want ", "i don't need ", "i don't ",
+                  "i do ", "i do not ", "i did ", "i did not ", "i will ", "i will not ", "i would ", "i would not ", "i have ", "i have not ", "i had ", "i had not ", "i can ",
+                  "i can not ", "i cannot ", "i am not ", "i am ", "i am not ", "i was ", "i was not ", "i will ", "i will not ", "i would ", "i would not ", "i have ",
+                  "i have not ", "i had ", "i had not ", "i can ", "i can not ", "i cannot ", "i am not ", "i am ", "i am not ", "i was ", "i was not ", "i will ", "i will not ",
+                  "i would ", "i would not ", "i have ", "i have not ", "i had ", "i had not ", "i can ", "i can not ", "i cannot ", "i am not ", "i am ", "i am not ", "i was ",
+                  "i was not ", "i will ", "i will not ", "i would ", "i would not ", "i have ", "i have not ", "i had ", "i had not ", "i can ", "i can not ", "i cannot ",
+                  "i am not ", "i am ", "i am not ", "i was ", "i was not ", "i will ", "i will not ", "i would ", "i would not ", "i have ", "i have not ", "i had ", "i had not ",
+                  "i can ", "i can not ", "i cannot ", "i am not ", "i am ", "i am not ", "i was ", "i was not ", "i will ", "i will not ", "i would ", "i would not ", "i have ",
+                  "i have not ", "i had ", "i had not ", "i can ", "i can not ", "i cannot ", "i am not ", "i am ", "i am not ", "i was "],
+    "command": ["you have ", "you should ", "you do ", "ai ", "artificial intelligence"],
 }
 
 
@@ -87,7 +98,7 @@ def whisper_result_prompter(whisper_result: str):
         possible_prompt_prefixes = []
         # looks like a question
         if "?" in question and any(ele in question for ele in PROMPT_FORMATTING['question']):
-            possible_prompt_prefixes.append("Answer the following question by reasoning step-by-step. ")
+            # possible_prompt_prefixes.append("Answer the following question by reasoning step-by-step. ")
             possible_prompt_prefixes.append("Answer the following question. ")
             possible_prompt_prefixes.append("Question: ")
             possible_prompt_prefixes.append("Q: ")
@@ -107,6 +118,9 @@ def encode(self, input_text, token_length=max_length):
         outputs = self.model.generate(input_ids, max_new_tokens=token_length)
         result = self.tokenizer.decode(outputs[0]).replace("<pad>", "").replace("</s>", "").replace("<unk>", "").strip()
 
+        # remove A: from the start of the result (if used by Q: prefix in question)
+        result = result.removeprefix("A: ")
+
         return result
 
 
diff --git a/images/remote_control.png b/images/remote_control.png
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diff --git a/languageClassification.py b/languageClassification.py
new file mode 100644
index 0000000..6daec65
--- /dev/null
+++ b/languageClassification.py
@@ -0,0 +1,24 @@
+# noinspection PyPackageRequirements
+import fasttext
+import os
+import downloader
+from pathlib import Path
+
+ct_model_path = Path(Path.cwd() / ".cache" / "lid")
+os.makedirs(ct_model_path, exist_ok=True)
+
+MODEL_LINKS = {
+    "lid218e": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/LID%2Flid218e.zip"
+}
+
+
+def classify(text):
+    pretrained_lang_model_file = Path(ct_model_path / "lid218e.bin")
+    if not pretrained_lang_model_file.exists():
+        print(f"Downloading LID (language identification) model...")
+        downloader.download_extract(MODEL_LINKS["lid218e"], str(ct_model_path.resolve()))
+
+    model = fasttext.load_model(str(pretrained_lang_model_file.resolve()))
+    predictions = model.predict(text, k=1)
+
+    return predictions[0][0].replace('__label__', '')
diff --git a/requirements.txt b/requirements.txt
index f729cd3..cabe9ac 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,7 +1,7 @@
 numpy>=1.23.4
 tqdm
 more-itertools
-transformers>=4.19.0
+transformers>=4.24.0
 ffmpeg-python==0.2.0
 click>=8.1.3
 PyAudio
@@ -18,8 +18,9 @@ pykakasi>=2.2.1
 ctranslate2>=2.17.0
 fairseq
 sentencepiece>=0.1.96
-protobuf==3.20.1
+protobuf==3.20.2
 progressbar2
+fasttext-wheel
 
 pywin32
 easyocr
diff --git a/settings.py b/settings.py
index 0f199bb..e4a808e 100644
--- a/settings.py
+++ b/settings.py
@@ -9,11 +9,11 @@
 TRANSLATE_SETTINGS = {
     # text translate settings
     "txt_translate": False,  # if enabled, pipes whisper A.I. results through text translator
-    "src_lang": "en",  # source language for text translator (Whisper A.I. in translation mode always translates to "en")
-    "trg_lang": "fr",  # target language for text translator
+    "src_lang": "auto",  # source language for text translator (Whisper A.I. in translation mode always translates to "en")
+    "trg_lang": "fra_Latn",  # target language for text translator
     "txt_ascii": False,  # if enabled, text translator will convert text to romaji.
-    "txt_translator": "M2M100",  # can be "M2M100" or "ARGOS"
-    "m2m100_size": "small",  # M2M100 model size. Can be "small" or "large"
+    "txt_translator": "NLLB200",  # can be "NLLB200", "M2M100" or "ARGOS"
+    "txt_translator_size": "small",  # for M2M100 model size: Can be "small" or "large", for NLLB200 model size: Can be "small", "medium", "large".
 
     # ocr settings
     "ocr_lang": "en",  # language for OCR image to text recognition.
@@ -31,7 +31,7 @@
     "osc_port": 9000,
     "osc_address": "/chatbox/input",
     "osc_typing_indicator": True,
-    "osc_convert_ascii": "False",
+    "osc_convert_ascii": False,
 
     # websocket settings
     "websocket_ip": "0",
@@ -39,12 +39,13 @@
 
     # FLAN settings
     "flan_enabled": False,  # Enable FLAN A.I.
-    "flan_size": "xl",  # FLAN model size. Can be "small", "base", "large", "xl" or "xxl"
+    "flan_size": "large",  # FLAN model size. Can be "small", "base", "large", "xl" or "xxl"
     "flan_bits": 32,  # precision can be set to 32 (float), 16 (float) or 8 (int) bits. 8 bits is the fastest but least precise
     "flan_device": "cpu",  # can be "cpu", "cuda" or "auto". ("cuda" and "auto" doing the same)
     "flan_whisper_answer": True,  # if True, the FLAN A.I. will answer to results from the Whisper A.I.
     "flan_process_only_questions": True,  # if True, the FLAN A.I. will only answer to questions
-    "flan_osc_prefix": "AI: "  # prefix for OSC messages
+    "flan_osc_prefix": "AI: ",  # prefix for OSC messages
+    "flan_translate_to_speaker_language": False  # Translate from english to speaker language
 }
 
 
diff --git a/texttranslate.py b/texttranslate.py
index 341bd40..8636b67 100644
--- a/texttranslate.py
+++ b/texttranslate.py
@@ -3,6 +3,7 @@
 import texttranslateARGOS
 # import texttranslateM2M100
 import texttranslateM2M100_CTranslate2
+import texttranslateNLLB200
 
 
 def get_current_translator():
@@ -25,7 +26,9 @@ def InstallLanguages():
         case "ARGOS":
             texttranslateARGOS.InstallLanguages()
         case "M2M100":
-            texttranslateM2M100_CTranslate2.load_model(settings.GetOption("m2m100_size"))
+            texttranslateM2M100_CTranslate2.load_model(settings.GetOption("txt_translator_size"))
+        case "NLLB200":
+            texttranslateNLLB200.load_model(settings.GetOption("txt_translator_size"))
 
 
 def GetInstalledLanguageNames():
@@ -34,19 +37,23 @@ def GetInstalledLanguageNames():
             return texttranslateARGOS.GetInstalledLanguageNames()
         case "M2M100":
             return texttranslateM2M100_CTranslate2.get_installed_language_names()
+        case "NLLB200":
+            return texttranslateNLLB200.get_installed_language_names()
 
 
-def TranslateLanguage(text, from_code, to_code, to_romaji=False):
+def TranslateLanguage(text, from_code, to_code, to_romaji=False, as_iso1=False):
     translation_text = ""
     match get_current_translator():
         case "ARGOS":
             translation_text = texttranslateARGOS.TranslateLanguage(text, from_code, to_code)
         case "M2M100":
             translation_text = texttranslateM2M100_CTranslate2.translate_language(text, from_code, to_code)
+        case "NLLB200":
+            translation_text, from_code, to_code = texttranslateNLLB200.translate_language(text, from_code, to_code, as_iso1)
     if to_romaji:
         translation_text = convert_to_romaji(translation_text)
 
-    return translation_text.strip()
+    return translation_text.strip(), from_code, to_code
 
 
 def SetDevice(option):
diff --git a/texttranslateNLLB200.py b/texttranslateNLLB200.py
new file mode 100644
index 0000000..8fa662f
--- /dev/null
+++ b/texttranslateNLLB200.py
@@ -0,0 +1,482 @@
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, models
+import os
+import downloader
+from pathlib import Path
+import languageClassification
+
+LANGUAGES = {
+    "Achinese (Arab)": "ace_Arab",
+    "Achinese (Latn)": "ace_Latn",
+    "Mesopotamian": "acm_Arab",
+    "Ta’izzi-Adeni": "acq_Arab",
+    "Tunisian": "aeb_Arab",
+    "Afrikaans": "afr_Latn",
+    "South Levantine": "ajp_Arab",
+    "Akan": "aka_Latn",
+    "Amharic": "amh_Ethi",
+    "North Levantine Arabic": "apc_Arab",
+    "Modern Standard Arabic": "arb_Arab",
+    "Najdi Arabic": "ars_Arab",
+    "Moroccan Arabic": "ary_Arab",
+    "Egyptian Arabic": "arz_Arab",
+    "Assamese": "asm_Beng",
+    "Asturian": "ast_Latn",
+    "Awadhi": "awa_Deva",
+    "Aymara": "ayr_Latn",
+    "Azerbaijani (South)": "azb_Arab",
+    "Azerbaijani (North)": "azj_Latn",
+    "Bashkir": "bak_Cyrl",
+    "Bambara": "bam_Latn",
+    "Balinese": "ban_Latn",
+    "Belarusian": "bel_Cyrl",
+    "Bemba": "bem_Latn",
+    "Bengali": "ben_Beng",
+    "Bhojpuri": "bho_Deva",
+    "Banjarese (Arab)": "bjn_Arab",
+    "Banjarese (Latn)": "bjn_Latn",
+    "Tibetan": "bod_Tibt",
+    "Bosnian": "bos_Latn",
+    "Buginese": "bug_Latn",
+    "Bulgarian": "bul_Cyrl",
+    "Catalan": "cat_Latn",
+    "Cebuano": "ceb_Latn",
+    "Czech": "ces_Latn",
+    "Chokwe": "cjk_Latn",
+    "Sorani": "ckb_Arab",
+    "Crimean": "crh_Latn",
+    "Welsh": "cym_Latn",
+    "Danish": "dan_Latn",
+    "German": "deu_Latn",
+    "Dinka": "dik_Latn",
+    "Dyula": "dyu_Latn",
+    "Dzongkha": "dzo_Tibt",
+    "Greek (Modern)": "ell_Grek",
+    "English": "eng_Latn",
+    "Esperanto": "epo_Latn",
+    "Estonian": "est_Latn",
+    "Basque": "eus_Latn",
+    "Ewe": "ewe_Latn",
+    "Faroese": "fao_Latn",
+    "Persian": "pes_Arab",
+    "Fijian": "fij_Latn",
+    "Finnish": "fin_Latn",
+    "Fon": "fon_Latn",
+    "French": "fra_Latn",
+    "Friulian": "fur_Latn",
+    "Fula": "fuv_Latn",
+    "Gaelic": "gla_Latn",
+    "Irish": "gle_Latn",
+    "Galician": "glg_Latn",
+    "Guarani": "grn_Latn",
+    "Gujarati": "guj_Gujr",
+    "Haitian": "hat_Latn",
+    "Hausa": "hau_Latn",
+    "Hebrew": "heb_Hebr",
+    "Hindi": "hin_Deva",
+    "Chhattisgarhi": "hne_Deva",
+    "Croatian": "hrv_Latn",
+    "Hungarian": "hun_Latn",
+    "Armenian": "hye_Armn",
+    "Igbo": "ibo_Latn",
+    "Iloko": "ilo_Latn",
+    "Indonesian": "ind_Latn",
+    "Icelandic": "isl_Latn",
+    "Italian": "ita_Latn",
+    "Javanese": "jav_Latn",
+    "Japanese": "jpn_Jpan",
+    "Kabyle": "kab_Latn",
+    "Kachin": "kac_Latn",
+    "Kamba": "kam_Latn",
+    "Kannada": "kan_Knda",
+    "Kashmiri (Arab)": "kas_Arab",
+    "Kashmiri (Deva)": "kas_Deva",
+    "Georgian": "kat_Geor",
+    "Kanuri (Arab)": "knc_Arab",
+    "Kanuri (Latn)": "knc_Latn",
+    "Kazakh": "kaz_Cyrl",
+    "Kabiye": "kbp_Latn",
+    "Kriolu": "kea_Latn",
+    "Central Khmer": "khm_Khmr",
+    "Kikuyu": "kik_Latn",
+    "Kinyarwanda": "kin_Latn",
+    "Kirghiz": "kir_Cyrl",
+    "Kimbundu": "kmb_Latn",
+    "Kongo": "kon_Latn",
+    "Korean": "kor_Hang",
+    "Kurmanji": "kmr_Latn",
+    "Lao": "lao_Laoo",
+    "Latvian": "lvs_Latn",
+    "Ligurian": "lij_Latn",
+    "Limburgan": "lim_Latn",
+    "Lingala": "lin_Latn",
+    "Lithuanian": "lit_Latn",
+    "Lombard": "lmo_Latn",
+    "Latgalian": "ltg_Latn",
+    "Luxembourgish": "ltz_Latn",
+    "Luba-Lulua": "lua_Latn",
+    "Ganda": "lug_Latn",
+    "Luo": "luo_Latn",
+    "Lushai": "lus_Latn",
+    "Magahi": "mag_Deva",
+    "Maithili": "mai_Deva",
+    "Malayalam": "mal_Mlym",
+    "Marathi": "mar_Deva",
+    "Minangkabau": "min_Latn",
+    "Macedonian": "mkd_Cyrl",
+    "Malagasy": "plt_Latn",
+    "Maltese": "mlt_Latn",
+    "Manipuri": "mni_Beng",
+    "Mongolian": "khk_Cyrl",
+    "Mossi": "mos_Latn",
+    "Māori": "mri_Latn",
+    "Malaysian Malay": "zsm_Latn",
+    "Burmese": "mya_Mymr",
+    "Dutch": "nld_Latn",
+    "Norwegian Nynorsk": "nno_Latn",
+    "Norwegian Bokmål": "nob_Latn",
+    "Nepali": "npi_Deva",
+    "Northern Sotho": "nso_Latn",
+    "Nuer": "nus_Latn",
+    "Chichewa, Nyanja": "nya_Latn",
+    "Occitan": "oci_Latn",
+    "Oromo": "gaz_Latn",
+    "Odia": "ory_Orya",
+    "Pangasinan": "pag_Latn",
+    "Panjabi": "pan_Guru",
+    "Papiamento": "pap_Latn",
+    "Polish": "pol_Latn",
+    "Portuguese": "por_Latn",
+    "Dari": "prs_Arab",
+    "Southern Pashto": "pbt_Arab",
+    "Ayacucho Quechua": "quy_Latn",
+    "Romanian": "ron_Latn",
+    "Rundi": "run_Latn",
+    "Russian": "rus_Cyrl",
+    "Sango": "sag_Latn",
+    "Sanskrit": "san_Deva",
+    "Santali": "sat_Beng",
+    "Sicilian": "scn_Latn",
+    "Shan": "shn_Mymr",
+    "Sinhala": "sin_Sinh",
+    "Slovak": "slk_Latn",
+    "Slovenian": "slv_Latn",
+    "Samoan": "smo_Latn",
+    "Shona": "sna_Latn",
+    "Sindhi": "snd_Arab",
+    "Somali": "som_Latn",
+    "Sotho": "sot_Latn",
+    "Spanish": "spa_Latn",
+    "Tosk Albanian": "als_Latn",
+    "Sardinian": "srd_Latn",
+    "Serbian": "srp_Cyrl",
+    "Swati": "ssw_Latn",
+    "Sundanese": "sun_Latn",
+    "Swedish": "swe_Latn",
+    "Swahili": "swh_Latn",
+    "Silesian": "szl_Latn",
+    "Tamil": "tam_Taml",
+    "Tatar": "tat_Cyrl",
+    "Telugu": "tel_Telu",
+    "Tajik": "tgk_Cyrl",
+    "Tagalog": "tgl_Latn",
+    "Thai": "tha_Thai",
+    "Tigrinya": "tir_Ethi",
+    "Tamasheq (Latn)": "taq_Latn",
+    "Tamasheq": "taq_Tfng",
+    "Tok Pisin, Pidgin": "tpi_Latn",
+    "Tswana": "tsn_Latn",
+    "Tsonga": "tso_Latn",
+    "Turkmen": "tuk_Latn",
+    "Tumbuka": "tum_Latn",
+    "Turkish": "tur_Latn",
+    "Twi": "twi_Latn",
+    "Atlasic": "tzm_Tfng",
+    "Uighur": "uig_Arab",
+    "Ukrainian": "ukr_Cyrl",
+    "Umbundu": "umb_Latn",
+    "Urdu": "urd_Arab",
+    "Uzbek": "uzn_Latn",
+    "Venetian": "vec_Latn",
+    "Vietnamese": "vie_Latn",
+    "Waray": "war_Latn",
+    "Wolof": "wol_Latn",
+    "Xhosa": "xho_Latn",
+    "Yiddish": "ydd_Hebr",
+    "Yoruba": "yor_Latn",
+    "Yue Chinese": "yue_Hant",
+    "Chinese (Simplified)": "zho_Hans",
+    "Chinese (Traditional)": "zho_Hant",
+    "Zulu": "zul_Latn"
+}
+
+# mapping from ISO 639-1 to ISO 639-3.
+LANGUAGES_ISO1_TO_ISO3 = {
+    "ace": ["ace_Arab", "ace_Latn"],
+    "acm": ["acm_Arab"],
+    "acq": ["acq_Arab"],
+    "aeb": ["aeb_Arab"],
+    "af": ["afr_Latn"],
+    "ajp": ["ajp_Arab"],
+    "ak": ["aka_Latn"],
+    "am": ["amh_Ethi"],
+    "apc": ["apc_Arab"],
+    "arb": ["arb_Arab"],
+    "ars": ["ars_Arab"],
+    "ary": ["ary_Arab"],
+    "arz": ["arz_Arab"],
+    "as": ["asm_Beng"],
+    "ast": ["ast_Latn"],
+    "awa": ["awa_Deva"],
+    "ayr": ["ayr_Latn"],
+    "azb": ["azb_Arab"],
+    "azj": ["azj_Latn"],
+    "ba": ["bak_Cyrl"],
+    "bm": ["bam_Latn"],
+    "ban": ["ban_Latn"],
+    "be": ["bel_Cyrl"],
+    "bem": ["bem_Latn"],
+    "bn": ["ben_Beng"],
+    "bho": ["bho_Deva"],
+    "bjn": ["bjn_Arab", "bjn_Latn"],
+    "bo": ["bod_Tibt"],
+    "bs": ["bos_Latn"],
+    "bug": ["bug_Latn"],
+    "bg": ["bul_Cyrl"],
+    "ca": ["cat_Latn"],
+    "ceb": ["ceb_Latn"],
+    "cs": ["ces_Latn"],
+    "cjk": ["cjk_Latn"],
+    "ckb": ["ckb_Arab"],
+    "crh": ["crh_Latn"],
+    "cy": ["cym_Latn"],
+    "da": ["dan_Latn"],
+    "de": ["deu_Latn"],
+    "dik": ["dik_Latn"],
+    "dyu": ["dyu_Latn"],
+    "dz": ["dzo_Tibt"],
+    "el": ["ell_Grek"],
+    "en": ["eng_Latn"],
+    "eo": ["epo_Latn"],
+    "et": ["est_Latn"],
+    "eu": ["eus_Latn"],
+    "ee": ["ewe_Latn"],
+    "fo": ["fao_Latn"],
+    "pes": ["pes_Arab"],
+    "fj": ["fij_Latn"],
+    "fi": ["fin_Latn"],
+    "fon": ["fon_Latn"],
+    "fr": ["fra_Latn"],
+    "fur": ["fur_Latn"],
+    "fuv": ["fuv_Latn"],
+    "gd": ["gla_Latn"],
+    "ga": ["gle_Latn"],
+    "gl": ["glg_Latn"],
+    "gn": ["grn_Latn"],
+    "gu": ["guj_Gujr"],
+    "ht": ["hat_Latn"],
+    "ha": ["hau_Latn"],
+    "he": ["heb_Hebr"],
+    "hi": ["hin_Deva"],
+    "hne": ["hne_Deva"],
+    "hr": ["hrv_Latn"],
+    "hu": ["hun_Latn"],
+    "hy": ["hye_Armn"],
+    "ig": ["ibo_Latn"],
+    "ilo": ["ilo_Latn"],
+    "id": ["ind_Latn"],
+    "is": ["isl_Latn"],
+    "it": ["ita_Latn"],
+    "jv": ["jav_Latn"],
+    "ja": ["jpn_Jpan"],
+    "kab": ["kab_Latn"],
+    "kac": ["kac_Latn"],
+    "kam": ["kam_Latn"],
+    "kn": ["kan_Knda"],
+    "ks": ["kas_Arab", "kas_Deva"],
+    "ka": ["kat_Geor"],
+    "knc": ["knc_Arab", "knc_Latn"],
+    "kk": ["kaz_Cyrl"],
+    "kbp": ["kbp_Latn"],
+    "kea": ["kea_Latn"],
+    "km": ["khm_Khmr"],
+    "ki": ["kik_Latn"],
+    "rw": ["kin_Latn"],
+    "ky": ["kir_Cyrl"],
+    "kmb": ["kmb_Latn"],
+    "kg": ["kon_Latn"],
+    "ko": ["kor_Hang"],
+    "kmr": ["kmr_Latn"],
+    "lo": ["lao_Laoo"],
+    "lvs": ["lvs_Latn"],
+    "lij": ["lij_Latn"],
+    "li": ["lim_Latn"],
+    "ln": ["lin_Latn"],
+    "lt": ["lit_Latn"],
+    "lmo": ["lmo_Latn"],
+    "ltg": ["ltg_Latn"],
+    "lb": ["ltz_Latn"],
+    "lua": ["lua_Latn"],
+    "lg": ["lug_Latn"],
+    "luo": ["luo_Latn"],
+    "lus": ["lus_Latn"],
+    "mag": ["mag_Deva"],
+    "mai": ["mai_Deva"],
+    "ml": ["mal_Mlym"],
+    "mr": ["mar_Deva"],
+    "min": ["min_Latn"],
+    "mk": ["mkd_Cyrl"],
+    "plt": ["plt_Latn"],
+    "mt": ["mlt_Latn"],
+    "mni": ["mni_Beng"],
+    "khk": ["khk_Cyrl"],
+    "mos": ["mos_Latn"],
+    "mi": ["mri_Latn"],
+    "zsm": ["zsm_Latn"],
+    "my": ["mya_Mymr"],
+    "nl": ["nld_Latn"],
+    "nn": ["nno_Latn"],
+    "nb": ["nob_Latn"],
+    "npi": ["npi_Deva"],
+    "nso": ["nso_Latn"],
+    "nus": ["nus_Latn"],
+    "ny": ["nya_Latn"],
+    "oc": ["oci_Latn"],
+    "gaz": ["gaz_Latn"],
+    "ory": ["ory_Orya"],
+    "pag": ["pag_Latn"],
+    "pa": ["pan_Guru"],
+    "pap": ["pap_Latn"],
+    "pl": ["pol_Latn"],
+    "pt": ["por_Latn"],
+    "prs": ["prs_Arab"],
+    "pbt": ["pbt_Arab"],
+    "quy": ["quy_Latn"],
+    "ro": ["ron_Latn"],
+    "rn": ["run_Latn"],
+    "ru": ["rus_Cyrl"],
+    "sg": ["sag_Latn"],
+    "sa": ["san_Deva"],
+    "sat": ["sat_Beng"],
+    "scn": ["scn_Latn"],
+    "shn": ["shn_Mymr"],
+    "si": ["sin_Sinh"],
+    "sk": ["slk_Latn"],
+    "sl": ["slv_Latn"],
+    "sm": ["smo_Latn"],
+    "sn": ["sna_Latn"],
+    "sd": ["snd_Arab"],
+    "so": ["som_Latn"],
+    "st": ["sot_Latn"],
+    "es": ["spa_Latn"],
+    "als": ["als_Latn"],
+    "sc": ["srd_Latn"],
+    "sr": ["srp_Cyrl"],
+    "ss": ["ssw_Latn"],
+    "su": ["sun_Latn"],
+    "sv": ["swe_Latn"],
+    "swh": ["swh_Latn"],
+    "szl": ["szl_Latn"],
+    "ta": ["tam_Taml"],
+    "tt": ["tat_Cyrl"],
+    "te": ["tel_Telu"],
+    "tg": ["tgk_Cyrl"],
+    "tl": ["tgl_Latn"],
+    "th": ["tha_Thai"],
+    "ti": ["tir_Ethi"],
+    "taq": ["taq_Tfng", "taq_Latn"],
+    "tpi": ["tpi_Latn"],
+    "tn": ["tsn_Latn"],
+    "ts": ["tso_Latn"],
+    "tk": ["tuk_Latn"],
+    "tum": ["tum_Latn"],
+    "tr": ["tur_Latn"],
+    "tw": ["twi_Latn"],
+    "tzm": ["tzm_Tfng"],
+    "ug": ["uig_Arab"],
+    "uk": ["ukr_Cyrl"],
+    "umb": ["umb_Latn"],
+    "ur": ["urd_Arab"],
+    "uzn": ["uzn_Latn"],
+    "vec": ["vec_Latn"],
+    "vi": ["vie_Latn"],
+    "war": ["war_Latn"],
+    "wo": ["wol_Latn"],
+    "xh": ["xho_Latn"],
+    "ydd": ["ydd_Hebr"],
+    "yo": ["yor_Latn"],
+    "yue": ["yue_Hant"],
+    "zh": ["zho_Hans", "zho_Hant"],
+    "zu": ["zul_Latn"]
+}
+
+# MODEL_LINKS = {
+#     "small": "facebook/nllb-200-distilled-600M",
+#     "medium": "facebook/nllb-200-distilled-1.3B",
+#     "large": "facebook/nllb-200-3.3B",
+#     "xxl": "facebook/nllb-200-54.5B"
+# }
+
+MODEL_LINKS = {
+    "small": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/NLLB-200%2Fsmall.zip",
+    "medium": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/NLLB-200%2Fmedium.zip",
+    "large": "https://eu2.contabostorage.com/bf1a89517e2643359087e5d8219c0c67:ai-models/NLLB-200%2Flarge.zip"
+}
+
+# [Modify] Set paths to the CTranslate2 and SentencePiece models
+ct_model_path = Path(Path.cwd() / ".cache" / "nllb200")
+os.makedirs(ct_model_path, exist_ok=True)
+
+model = AutoModelForSeq2SeqLM
+tokenizer: models.nllb.NllbTokenizer = AutoTokenizer  # type: ignore
+
+
+def get_installed_language_names():
+    return tuple([{"code": code, "name": language} for language, code in LANGUAGES.items()])
+
+
+def load_model(size="small"):
+    global model
+    global tokenizer
+
+    model_path = Path(ct_model_path / size)
+
+    print(f"Initializing {size} NLLB-200 model.")
+
+    if not model_path.exists():
+        print(f"Downloading {size} NLLB-200 model...")
+        downloader.download_extract(MODEL_LINKS[size], str(ct_model_path.resolve()))
+
+    model_path_string = str(model_path.resolve())
+
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_path_string)
+    tokenizer = AutoTokenizer.from_pretrained(model_path_string)
+
+    print(f"NLLB-200 model loaded.")
+
+
+def translate_language(text, from_code, to_code, as_iso1=False):
+    if as_iso1 and from_code in LANGUAGES_ISO1_TO_ISO3:
+        from_code = LANGUAGES_ISO1_TO_ISO3[from_code][0]
+    if as_iso1 and to_code in LANGUAGES_ISO1_TO_ISO3:
+        to_code = LANGUAGES_ISO1_TO_ISO3[to_code][0]
+
+    if from_code == "auto":
+        from_code = languageClassification.classify(text)
+
+    language_unsupported = False
+    if from_code not in tokenizer.lang_code_to_id:
+        print(f"error translating. {from_code} not supported.")
+        language_unsupported = True
+    if to_code not in tokenizer.lang_code_to_id:
+        print(f"error translating. {to_code} not supported.")
+        language_unsupported = True
+    if language_unsupported:
+        return text
+
+    tokenizer.src_lang = from_code
+    inputs = tokenizer(text, return_tensors="pt")
+    translated_tokens = model.generate(** inputs, forced_bos_token_id=tokenizer.lang_code_to_id[to_code], max_length=200)
+
+    translation_text = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
+    translation_text = translation_text.removeprefix("- ")
+    return translation_text, from_code, to_code
diff --git a/websocket.py b/websocket.py
index 7ddba8a..2eaa56f 100644
--- a/websocket.py
+++ b/websocket.py
@@ -21,14 +21,14 @@ def websocketMessageHandler(msgObj):
         BroadcastMessage(json.dumps({"type": "translate_settings", "data": settings.TRANSLATE_SETTINGS}))  # broadcast updated settings to all clients
 
     if msgObj["type"] == "translate_req":
-        translate_result = texttranslate.TranslateLanguage(msgObj["text"], msgObj["from_lang"], msgObj["to_lang"])
-        BroadcastMessage(json.dumps({"type": "translate_result", "translate_result": translate_result}))
+        translate_result, txt_from_lang, txt_to_lang = texttranslate.TranslateLanguage(msgObj["text"], msgObj["from_lang"], msgObj["to_lang"])
+        BroadcastMessage(json.dumps({"type": "translate_result", "translate_result": translate_result, "txt_from_lang": txt_from_lang, "txt_to_lang": txt_to_lang}))
 
     if msgObj["type"] == "ocr_req":
         window_name = settings.GetOption("ocr_window_name")
         ocr_result = imagetranslate.run_image_processing(window_name, ['en', msgObj["ocr_lang"]])
-        translate_result = (texttranslate.TranslateLanguage(" -- ".join(ocr_result), msgObj["from_lang"], msgObj["to_lang"]))
-        BroadcastMessage(json.dumps({"type": "translate_result", "original_text": "\n".join(ocr_result), "translate_result": "\n".join(translate_result.split(" -- "))}))
+        translate_result, txt_from_lang, txt_to_lang = (texttranslate.TranslateLanguage(" -- ".join(ocr_result), msgObj["from_lang"], msgObj["to_lang"]))
+        BroadcastMessage(json.dumps({"type": "translate_result", "original_text": "\n".join(ocr_result), "translate_result": "\n".join(translate_result.split(" -- ")), "txt_from_lang": txt_from_lang, "txt_to_lang": txt_to_lang}))
 
     if msgObj["type"] == "flan_req":
         if flanLanguageModel.init():
diff --git a/websocket_clients/streaming-overlay-01/index.html b/websocket_clients/streaming-overlay-01/index.html
index 913be10..946e959 100644
--- a/websocket_clients/streaming-overlay-01/index.html
+++ b/websocket_clients/streaming-overlay-01/index.html
@@ -63,12 +63,19 @@
          // no_loader argument. If set to "true", the loader is not shown
          no_loader = typeof getParameter("no_loader") != 'undefined';
 
+         // disable scrolling
          no_scroll = getParameter("no_scroll");
 
+         // align to bottom of page (has no scrolling)
+         bottom_align = getParameter("bottom_align");
+
          document.addEventListener("DOMContentLoaded", () => {
             if (typeof no_scroll != 'undefined') {
                document.querySelector('body').classList.add("noscroll");
             }
+            if (typeof bottom_align != 'undefined') {
+               document.querySelector('body').classList.add("bottom-align");
+            }
 
             // loader animation
             function showLoader(hideTime = 5) {
diff --git a/websocket_clients/streaming-overlay-01/main.css b/websocket_clients/streaming-overlay-01/main.css
index 9a6d3b5..80e42bd 100644
--- a/websocket_clients/streaming-overlay-01/main.css
+++ b/websocket_clients/streaming-overlay-01/main.css
@@ -4,6 +4,22 @@ body {
   overflow-x: hidden;
 }
 
+body select {
+  max-width: 13rem;
+}
+body textarea {
+  min-height: 5rem;
+}
+
+body.bottom-align {
+  position: absolute;
+  bottom: 0;
+  margin-left: auto;
+  margin-right: auto;
+  left: 0;
+  right: 0;
+}
+
 body.noscroll {
   overflow-y: hidden;
 }
diff --git a/websocket_clients/websocket-remote/index.html b/websocket_clients/websocket-remote/index.html
index 7c19410..8a8d567 100644
--- a/websocket_clients/websocket-remote/index.html
+++ b/websocket_clients/websocket-remote/index.html
@@ -45,6 +45,19 @@
          return undefined;
       }
 
+      function getTextFromSelectOptionValue(elem, value) {
+         let result = undefined;
+         Object.values(elem.options).every(option => {
+            if (option.value === value) {
+               result = option.text;
+               return false;
+            }
+            // continue iterating
+            return true;
+         });
+         return result;
+      }
+
       function clearAllTimeouts(timeoutList) {
          for (let i = 0; i < timeoutList.length; i++) {
             clearTimeout(timeoutList[i]);
@@ -78,13 +91,19 @@
       // no_loader argument. If set to "true", the loader is not shown
       no_loader = typeof getParameter("no_loader") != 'undefined';
 
-
+      // disable scrolling
       no_scroll = getParameter("no_scroll");
 
+      // align to bottom of page (has no scrolling)
+      bottom_align = getParameter("bottom_align");
+
       document.addEventListener("DOMContentLoaded", () => {
          if (typeof no_scroll != 'undefined') {
             document.querySelector('body').classList.add("noscroll");
          }
+         if (typeof bottom_align != 'undefined') {
+               document.querySelector('body').classList.add("bottom-align");
+         }
 
          // loader animation
          function showLoader(hideTime = 5) {
@@ -392,6 +411,13 @@
                      src_lang_el.replaceChildren("");
                      trg_lang_el.replaceChildren("");
 
+                     // add autodetect option
+                     let el = document.createElement("option");
+                     el.textContent = "[auto] " + "Autodetect";
+                     el.value = "auto";
+                     src_lang_el.appendChild(el);
+
+                     // add all available languages
                      for (let i = 0; i < received_msg.data.length; i++) {
                         let opt = received_msg.data[i];
 
@@ -488,11 +514,23 @@
                         document.querySelector('button#flan_do').disabled = true;
                      }
                   }
+                  // receive translation result
                   if (typeof received_msg.type != 'undefined' && received_msg.type === "translate_result") {
                      document.querySelector('#transl_result_textarea').value = received_msg.translate_result;
                      if (typeof received_msg.original_text != 'undefined') {
                         document.querySelector('#translate_textarea').value = received_msg.original_text;
                      }
+                     // show recognized language if set to autodetect
+                     if (typeof received_msg.txt_from_lang != 'undefined' && document.querySelector('#settings #src_lang').value === "auto") {
+                        let languageNameText = "";
+                        let languageName = getTextFromSelectOptionValue(document.querySelector('#settings #src_lang'), received_msg.txt_from_lang);
+                        if (languageName !== received_msg.txt_from_lang) {
+                            languageNameText = languageName;
+                        }
+                        document.querySelector('#auto_from_lang').textContent = languageNameText;
+                     } else {
+                        document.querySelector('#auto_from_lang').textContent = "";
+                     }
                   }
                   if (typeof received_msg.type != 'undefined' && received_msg.type === "windows_list") {
                      let ocr_window_el = document.querySelector('select#ocr_window_name');
@@ -566,18 +604,21 @@
          <div class="container mt-5">
             <div class="row no-gutters">
                <div class="col">
-                  WhisperAI Task:
-                  <select name="whisper_task" id="whisper_task">
+                  <strong>WhisperAI:</strong>&nbsp;Task: <select name="whisper_task" id="whisper_task">
                      <option value="transcribe">transcribe</option>
                      <option value="translate">translate (to en)</option>
-                  </select>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
-                  <label for="condition_on_previous_text">condition on previous text:</label> <input type="checkbox" id="condition_on_previous_text"
-                     name="condition_on_previous_text" value="1" />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
-                  <label for="current_language">speaker language:</label> <select name="current_language" id="current_language">
+                  </select>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+                  <label for="condition_on_previous_text" title="Condition WhisperAI with previous response. (makes it more prone to looping or freezing.)">condition on previous text:</label> <input type="checkbox" id="condition_on_previous_text"
+                     name="condition_on_previous_text" value="1" />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+                  <label for="current_language" title="Set speaker language. Helps with WhisperAI precision as it does not have to guess the language.">speaker language:</label> <select name="current_language" id="current_language">
                         <option value="">Auto</option>
-                  </select>&nbsp;&nbsp;&nbsp;&nbsp;
-                  <label for="flan_whisper_answer">FLAN-T5 answering:</label> <input type="checkbox" id="flan_whisper_answer"
-                     name="flan_whisper_answer" value="1" />
+                  </select><br />
+                  <strong>FLAN-T5:</strong>&nbsp;<label for="flan_whisper_answer" title="enable FLAN-T5 to answer WhisperAI transcriptions or translations.">answering:</label> <input type="checkbox" id="flan_whisper_answer"
+                     name="flan_whisper_answer" value="1" />&nbsp;&nbsp;&nbsp;
+                  <label for="flan_process_only_questions" title="process only questions. FLAN-T5 only responses if a question-word and question-mark are found.">only questions:</label> <input type="checkbox" id="flan_process_only_questions"
+                     name="flan_process_only_questions" value="1" />&nbsp;&nbsp;&nbsp;
+                  <label for="flan_translate_to_speaker_language" title="Requires WhisperAI to return english. So for other languages, set task to 'translate'">reply in speaker lang.:</label> <input type="checkbox" id="flan_translate_to_speaker_language"
+                     name="flan_translate_to_speaker_language" value="1" />
                   <hr />
                </div>
             </div>
@@ -616,7 +657,7 @@
    <div id="manual_translate" class="hidden">
       <section>
          <div class="container mt-3">
-            Input:
+            Input: <small id="auto_from_lang"></small>
             <div id="text_translate_form" class="container lt-2" style="padding: 0;">
                <div class="row no-gutters">
                   <div class="col-5">
diff --git a/websocket_clients/websocket-remote/main.css b/websocket_clients/websocket-remote/main.css
index 9a6d3b5..80e42bd 100644
--- a/websocket_clients/websocket-remote/main.css
+++ b/websocket_clients/websocket-remote/main.css
@@ -4,6 +4,22 @@ body {
   overflow-x: hidden;
 }
 
+body select {
+  max-width: 13rem;
+}
+body textarea {
+  min-height: 5rem;
+}
+
+body.bottom-align {
+  position: absolute;
+  bottom: 0;
+  margin-left: auto;
+  margin-right: auto;
+  left: 0;
+  right: 0;
+}
+
 body.noscroll {
   overflow-y: hidden;
 }