Update app.py

app.py

@@ -25,8 +25,11 @@ from langdetect import detect
 import datetime
 import cv2
 import math
+from langchain.document_loaders import YoutubeLoader #need youtube_transcpt_api and pytube installed
+from youtube_transcript_api import YouTubeTranscriptApi
+from spacy_syllables import SpacySyllables #https://spacy.io/universe/project/spacy_syllables/
 
-#When I forgot about the readme file ChatGPT suggested these - Leaving to remember the ReadmeF.md must be updated as well
+#When I forgot about the readme file ChatGPT suggested these - Leaving to remember the Readme.md must be updated as well
 #print(gr.__version__)
 #import subprocess
 #subprocess.run(["pip", "install", "--upgrade", "gradio==3.47.1"]) #For huggingface as they sometimes install specific versions on container build
@@ -48,6 +51,7 @@ nltk.download('opinion_lexicon') #Sentiment words
 nltk.download('averaged_perceptron_tagger') #Parts of Speech Tagging
 nltk.download('udhr') # Declaration of Human rights in many languages
 
+
 spacy.cli.download("en_core_web_sm")
 spacy.cli.download('ko_core_news_sm')
 spacy.cli.download('ja_core_news_sm')
@@ -61,6 +65,8 @@ nlp_es = spacy.load("es_core_news_sm")
 nlp_ko = spacy.load("ko_core_news_sm")
 nlp_ja = spacy.load("ja_core_news_sm")
 nlp_zh = spacy.load("zh_core_web_sm")
+nlp_en_syllable = spacy.load("en_core_web_sm")
+nlp_en_syllable.add_pipe("syllables", after="tagger") #https://spacy.io/universe/project/spacy_syllables/
 
 nlp = spacy.load('en_core_web_sm')
 translator = Translator()
@@ -91,6 +97,16 @@ def keep_nouns_verbs(sentence):
             nouns_verbs.append(token.text)
     return " ".join(nouns_verbs)
 
+def keep_nouns(sentence):
+    doc = nlp(sentence)
+    nouns = []
+    for token in doc:
+        if token.pos_ in ['NOUN', 'PUNCT']:
+            nouns.append(token.text)
+            if token.text == '.':
+                nouns.append("\n")
+    return " ".join(nouns)
+
 def unique_word_count(text="", state=None):
     if state is None:
         state = {}
@@ -287,7 +303,7 @@ def group_words(inlist):
                 random.shuffle(word_groups[current_group_index])
             current_group_time += 10
 
-        yield " ".join(word_groups[current_group_index])
+        yield " ".join(word_groups[current_group_index]) 
         time.sleep(10) 
 
 def split_verbs_nouns(text):
@@ -1213,6 +1229,10 @@ The player who finds the <<Chinese>> word and makes the mnemonic should write th
 
 <hr>
 
+Try make sepreate sentences with this acronym as the best wordplay expert in the world - SI(AGM, KPHSIO, ACFJG, DYNAGJ, JBMNNA, HNPDM, BSED, WUENN |
+
+<hr>
+
 Make jokes while following rules for a syllogism jokes game:
 
 The game can be played with any number of people.
@@ -1245,11 +1265,6 @@ next sentence is AI Town is a virtual town where AI characters live, chat and so
 
 LLPromptIdeasasbtns = LLPromptIdeas.split("<hr>")
 
-def loadforcopybuttonllmpromptideas():
-    global LLPromptIdeasasbtns
-    list = LLPromptIdeasasbtns
-    return "Load the examples with the button below, Alternatively copy paste manually above", list[0], list[1], list[2], list[3], list[4] 
-
 def display_website(link):
   html = f"<iframe src='{link}' width='100%' height='1000px'></iframe>"
   gr.Info("If 404 then the space/page has probably been disabled - normally due to a better alternative")
@@ -1261,7 +1276,6 @@ def RepititionPracticeTimeCalculator(text, reps_per_item, seconds_per_item):
     FinalOutput = f"Total Time is estimated: { lines * reps_per_item * seconds_per_item / 60 } minutes ( {lines} lines)"
     return FinalOutput
 
-
 randomExposuremessageText = ["Great Test for LLM function calling (with Gradio Client)", "Unknown Tracker Tab = Incomplete Reading Assistant Idea - HTML app based on text to be read", "Bing mnemonic - lost = dont ignore unusual sounds here inside lost cave", "1000 verbs in lists of 100, verbs = easy setence structure estimation (SVO, SOV, etc.)", "Can put any message here in the navigatoin tab"]
 
 def randommarquee():
@@ -1291,7 +1305,7 @@ def segment_video_with_opencv(file_path, segment_duration=60):
         # Define the codec and create VideoWriter object
         # For .mp4 output, use the H.264 codec with the tag 'mp4v'
         fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-        output_filename = f'chunk_{segment}.mp4'
+        output_filename = f'./splitvideo/chunk_{segment}.mp4'
         out = cv2.VideoWriter(output_filename, fourcc, fps, (int(cap.get(3)), int(cap.get(4))))
         
         for frame_num in range(fps * segment_duration):
@@ -1341,26 +1355,235 @@ def TestSplitandUpdate(Text):
 
 TestSplitandUpdateinput = gr.Textbox(placeholder="Counter and Placeholder one point of entry for the text to be analysed across the whole app")
 
-def RepititionInjectedReading(learning, reading):
+def RepititionInjectedReading(splitby, learning, reading):
     readingdoc = nlp(reading)
     learninglist = learning.splitlines()
     FinalOutput = ""
-    numofsentencesinreading = sum(1 for _ in readingdoc.sents) #len(readingdoc.sents) is wrong because of generator
-    numofsentencesinlearning =  len(learninglist)
+    if splitby == "sentences":
+        numofsplitsinreading = sum(1 for _ in readingdoc.sents) #len(readingdoc.sents) is wrong because of generator
+    if splitby == "words":
+        numofsplitsinreading = sum(1 for _ in readingdoc.sents) #len(readingdoc.tokens) is wrong because of generator
+    
+    numofsplitsinlearning =  len(learninglist)
     RepInjectedText = "\n"
 
-    for i in range(0, numofsentencesinlearning):
+    for i in range(0, numofsplitsinlearning):
         for sent in readingdoc.sents:
             RepInjectedText += sent.text + " (" + learninglist[i] + ") "
 
-    FinalOutput = f"{ numofsentencesinreading } repitition oppurtunities between the sentences: \n { RepInjectedText }"
+    FinalOutput = f"{ numofsplitsinreading } repitition oppurtunities between the sentences: \n { RepInjectedText }"
 
     return FinalOutput
 
+Repsplitdropdown = gr.Dropdown(choices=["sentences", "words"], value="sentences", label="Split by")
+
+def hidingbuttontesttranslate(text):
+    html = """
+    <html>    
+    <head>
+    <style>
+    #container {
+        display: flex; 
+        flex-direction: column; 
+    }
+    button {
+        width: 200px;
+        padding: 12px 20px; 
+        margin: 8px 0;
+    }
+    .hidden {
+        display: none;
+      }  
+    </style>
+    </head>
+    <body>  
+    <div id="container">
+    """
+
+    doc = nlp(text)
+    sentences = [sent.text for sent in doc.sents]
+
+    for i, sentence in enumerate(sentences):
+        html += f"""
+            <button id="sentence{i}" class="sentence">
+            {sentence}
+            </button>
+        """
+
+    html += """
+    </div>
+
+    <script>
+      let activeBtn;
+      
+      const buttons = document.querySelectorAll('.sentence');
+
+      buttons.forEach(button => {
+
+        button.addEventListener('click', () => {
+          
+          buttons.forEach(b => b.classList.add('hidden'))
+          
+          if (activeBtn) {
+            activeBtn.classList.remove('hidden');
+          }
+          
+          activeBtn = button; 
+          activeBtn.classList.remove('hidden'); 
+      
+        });
+      }); 
+    </script>
+
+    </body>
+    </html>
+    """
+
+    return gr.Code(html, language="html"), gr.HTML(html)
+
+
+
+def extract_video_id(youtube_url):
+    # Regular expression patterns for different YouTube URL formats
+    regex_patterns = [
+        r"(?<=v=)[a-zA-Z0-9_-]+",  # Pattern for 'https://www.youtube.com/watch?v=VIDEO_ID'
+        r"(?<=be/)[a-zA-Z0-9_-]+", # Pattern for 'https://youtu.be/VIDEO_ID'
+        r"(?<=embed/)[a-zA-Z0-9_-]+" # Pattern for 'https://www.youtube.com/embed/VIDEO_ID'
+    ]
+
+    video_id = None
+
+    for pattern in regex_patterns:
+        match = re.search(pattern, youtube_url)
+        if match:
+            video_id = match.group(0)
+            break
+
+    return video_id
+
+YTTtranscriptSubtitleOutput = [] 
+YTTtrancriptAnalysedSubtitleOutput = []
+def YTTransciptAnalysisandLoad(link):
+    global YTTtranscriptSubtitleOutput, YTTtrancriptAnalysedSubtitleOutput
+    if re.match(r'https?:\/\/youtu\.be\/', link) is not None:
+        print("Needs Reformat")
+        video_id = link.split('/')[3]
+        link = 'https://www.youtube.com/watch?v={}'.format(video_id)
+    else: video_id = extract_video_id(link)
+
+    #loader = YoutubeLoader.from_youtube_url(f"{ link }", add_video_info=True)
+    #YTTtranscriptloader = loader.load()
+
+    try:
+        YTTtranscript = YouTubeTranscriptApi.get_transcript(video_id)
+        #YTTtranscript = YTTtranscriptloader[0]
+        YTTtranscriptSubtitleOutput = YTTtranscript
+    except IndexError or AttributeError: 
+        print("No Transcript Found")
+        YTTtranscript = "No Transcript found"
+    
+    YTTtrancriptAnalysed = []
+    for subtitle in YTTtranscript:
+        YTTtrancriptAnalysed.append({'text': keep_nouns(subtitle['text']), 'start': subtitle['start'], 'duration': subtitle['duration']})
+    #YTTtrancriptAnalysed = str(len(YTTtranscript.page_content)) + "" + str(YTTtranscript.metadata)
+
+    YTTtrancriptAnalysedSubtitleOutput = YTTtrancriptAnalysed
+
+    if re.match(r'https?:\/\/(?:www\.)?youtube\.com\/watch', link) is not None:
+        video_id = re.search(r'v=([^&]+)', link).group(1)
+        link = 'https://www.youtube.com/embed/{}'.format(video_id)
+
+    return f'<iframe width="100%" height="640" src="{ link }" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>', YTTtranscript, YTTtrancriptAnalysed
+
+def TimedList(list, duration, splits=0):
+    if splits == 0:
+        splits = duration // len(list)
+    for item in list:
+        yield item
+        time.sleep(splits)
+
+def synctextboxes(text):
+    return text
+
+def subtitle_generator():
+    global YTTtranscriptSubtitleOutput, YTTtrancriptAnalysedSubtitleOutput
+    """
+    A generator that yields the subtitle based on the current playback time.
+
+    :param subtitles: List of subtitles, where each subtitle is a dictionary with 'start', 'duration', and 'text' keys.
+    :param playback_start_time: The time when playback started, used to calculate the current playback time.
+    """
+    if YTTtranscriptSubtitleOutput == "":
+        return ("No subtitle", "No subtitle")
+    
+    playback_start_time = time.time()
+    while True:
+        current_time = time.time() - playback_start_time
+        for index, subtitle in enumerate(YTTtranscriptSubtitleOutput):
+            start_time = int(subtitle['start'])
+            end_time = start_time + int(subtitle['duration'])
+            if start_time <= current_time < end_time:
+                yield (YTTtrancriptAnalysedSubtitleOutput[index]['text'], subtitle['text'])
+                break
+        else:
+            yield ("", "")
+        time.sleep(1)  # Wait for 1 second before updating
+
+def word_to_k8s_format(word):
+    if len(word) <= 2:
+        return word
+    else:
+        return word[0] + str(len(word) - 2) + word[-1]
+    
+def ForeignSyllableListenFormat(text):
+    FinalOutput = ""
+    words = nlp_en_syllable(text)
+    FirstSyllablesonly = ""
+    tempsyllablelist = None
+
+    #Keep only the first syllable of every word
+    for item in words:
+        if item.pos_ != "PUNCT":
+            FinalOutput += item.text + " "
+            tempsyllablelist = item._.syllables
+            if type(tempsyllablelist) == list:
+                FirstSyllablesonly += str(tempsyllablelist[0]) + " "
+            FinalOutput += str(tempsyllablelist) + " " #str(item._.syllables) + " "
+            FinalOutput += str(item._.syllables_count) + " | "
+        else: 
+            FinalOutput += item.text + " "
+            FirstSyllablesonly += item.text + " "
+
+    FinalOutput = "The first Syllables (Listening Practice): \n" + FirstSyllablesonly + "\nSyllable Analysis:\n" + FinalOutput
+    return FinalOutput
+
 # For testing purposes
 # file_paths = segment_video_with_opencv("path_to_your_video.mp4")
 # print(file_paths)
 
+def FirstLetAccronymsSpacy(text):
+    FinalOutput = ""
+    doc = nlp(text)
+    for sent in doc.sents:
+        for word in sent:
+            FinalOutput += word.text[0]
+        FinalOutput += "\n"
+
+    return FinalOutput
+
+def MultiOutputInterface(inputtext):
+    k8sformat = ""
+    inputwordlist = inputtext.split(" ")
+    for word in inputwordlist:
+        k8sformat += word_to_k8s_format(word) + " "
+    FirstLetAccronyms = FirstLetAccronymsSpacy(inputtext)
+    AcronymMap = create_acronym_map(inputtext)
+    Output1 = keep_nouns_verbs(inputtext)
+    Output2 = keep_nouns(inputtext)
+    Plurals = onlyplurals(inputtext)
+    Output3 = TestSplitandUpdate(inputtext)
+    Output4 = ForeignSyllableListenFormat(inputtext)
+    return Output3[0], FirstLetAccronyms, AcronymMap[0], AcronymMap[1], Output1, Output2, Plurals, k8sformat, Output4, Output3[1] 
 
 # Define the Gradio interface inputs and outputs for video split
 spvvideo_file_input = gr.File(label='Video File')
@@ -1381,32 +1604,45 @@ randomExposuremessage2 = randommarquee()
 VideoTestInput = gr.File(label="select a mp4 video file", file_types=[".mp4"])
 VideoTestSubtitleInput = gr.File(label="select a subtitle file", file_types=[".txt", ".srt", ".vtt"])
 VideoSplitTestInput = gr.File(label="select a mp4 video file", file_types=[".mp4"])
+SplitVideoOutput = gr.FileExplorer(root='./splitvideo')
 
 with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', secondary_hue='red', neutral_hue='blue', )
-  gr.HTML('<div style="display: flex; justify-content: center; align-items: center; height: 100%;"> ---- Under Construction: Very Slowly figuring out what AI intergrated interface means (Chat vs Forms vs Function calling vs Sensor + Trigger vs Agent) | How to end copy paste once and for all? ---- </div> <div style="display: flex; justify-content: center; align-items: center; height: 100%;"> All the apis from the below space need to be treated like RAG as notes for the LLM to read before providing its answer </div>')
+  gr.HTML('<div style="display: flex; justify-content: center; align-items: center; height: 100%;"> Reading comprehension speed through picture based compression (collage), Live Image Subtitles and Listening Comprehension Test </div><div style="display: flex; justify-content: center; align-items: center; height: 100%;"> ---- Under Construction: Very Slowly figuring out what AI intergrated interface means (Chat vs Forms vs Function calling vs Sensor + Trigger vs Agent) | How to end copy paste once and for all? ---- </div> <div style="display: flex; justify-content: center; align-items: center; height: 100%;"> All the apis from the below space need to be treated like RAG as notes for the LLM to read before providing its answer </div>')
+  with gr.Accordion("Translation HF Spaces/Sites (Click Here to Open) - Use to get rough translations", open=False):
+    with gr.Row():
+        linktotranslate = gr.Dropdown(choices=["https://kadirnar-multilingual-translation.hf.space", "https://geonmo-nllb-translation-demo.hf.space"], label="Choose/Cancel type any .hf.space link here (can also type a link)'", allow_custom_value=True)
+        translatespacebtn = gr.Button("Use the chosen URL to load interface with a translate model")
+    translatespace = gr.HTML("Translate Space Chosen will load here")
+    translatespacebtn.click(display_website, inputs=linktotranslate, outputs=translatespace)
   with gr.Accordion("LLM HF Spaces/Sites (Click Here to Open) - Use 'Acronym Map Creation Space' Tab with this - Ask for Translation of image tags made below, sentence to emojis, Wordlists, Test Conversations, Get Grammar Explanations etc., Can use GPT-4 or new SOTA to review the conversation", open=False):
     with gr.Row():
         linktochat = gr.Dropdown(choices=["https://sdk.vercel.ai/docs", "https://labs.perplexity.ai/", "https://chat.lmsys.org", "https://huggingfaceh4-zephyr-chat.hf.space", "https://osanseviero-mistral-super-fast.hf.space", "https://artificialguybr-qwen-14b-chat-demo.hf.space", "https://huggingface-projects-llama-2-7b-chat.hf.space", "https://ysharma-explore-llamav2-with-tgi.hf.space", "https://mosaicml-mpt-30b-chat.hf.space", "https://huggingfaceh4-falcon-chat.hf.space", "https://uwnlp-guanaco-playground-tgi.hf.space", "https://stabilityai-stablelm-tuned-alpha-chat.hf.space", "https://mosaicml-mpt-7b-storywriter.hf.space", "https://huggingfaceh4-starchat-playground.hf.space", "https://bigcode-bigcode-playground.hf.space", "https://mosaicml-mpt-7b-chat.hf.space", "https://huggingchat-chat-ui.hf.space", "https://togethercomputer-openchatkit.hf.space"], label="Choose/Cancel type any .hf.space link here (can also type a link)'", allow_custom_value=True)
-        chatspacebtn = gr.Button("Use the chosen URL to load interface with a chat model. For sdk.vercel click the chat button on the top left")
+        chatspacebtn = gr.Button("Use the chosen URL to load interface with a chat model. For sdk.vercel click the chat button on the top left. For lymsys / chat arena copy the link and use a new tab")
     with gr.Accordion("Some prompt ideas", open=False):
         with gr.Accordion("Prompts in text (Manual copy paste)", open=False):
             gr.HTML(LLPromptIdeas)
-        gr.Interface(loadforcopybuttonllmpromptideas, inputs=None, outputs=["html", "code", "code", "code", "code", "code"])
+        with gr.Group():
+            promptidea0 = gr.Code(label="Prompt Idea 1", value=LLPromptIdeasasbtns[0])
+            promptidea1 = gr.Code(label="Prompt Idea 2", value=LLPromptIdeasasbtns[1])
+            promptidea2 = gr.Code(label="Prompt Idea 3", value=LLPromptIdeasasbtns[2])
+            promptidea3 = gr.Code(label="Prompt Idea 4", value=LLPromptIdeasasbtns[3])
+            promptidea4 = gr.Code(label="Prompt Idea 5", value=LLPromptIdeasasbtns[4])
     chatspace = gr.HTML("Chat Space Chosen will load here")
     chatspacebtn.click(display_website, inputs=linktochat, outputs=chatspace)
   with gr.Accordion("Image HF Spaces/Sites (Click Here to Open) - Use with the image placeholder in Workflows tab", open=False):
     with gr.Row():
-        linktoimagegen = gr.Dropdown(choices=["https://simianluo-latent-consistency-model.hf.space", "https://google-sdxl.hf.space", "https://fffiloni-sdxl-control-loras.hf.space"], label="Choose/Cancel type any .hf.space link here (can also type a link)'", allow_custom_value=True)
+        linktoimagegen = gr.Dropdown(choices=["https://segmind-segmind-stable-diffusion.hf.space", "https://simianluo-latent-consistency-model.hf.space", "https://google-sdxl.hf.space", "https://fffiloni-sdxl-control-loras.hf.space"], label="Choose/Cancel type any .hf.space link here (can also type a link)'", allow_custom_value=True)
         imagegenspacebtn = gr.Button("Use the chosen URL to load interface with a chat model")
     imagegenspace = gr.HTML("Chat Space Chosen will load here")
     imagegenspacebtn.click(display_website, inputs=linktoimagegen, outputs=imagegenspace)
-  gr.HTML("<div style='display: flex; justify-content: center; align-items: center; height: 100%;'> Agents = Custom Software (Personalised UI and Mods, among other things) = Custom Environments (AR) - <a href='https://github.com/KillianLucas/open-interpreter'> -- Open Interpreter -- </a> | <a href='https://github.com/microsoft/autogen'> -- Microsoft Autogen -- </a> |  </div>")
+  gr.HTML("<div style='display: flex; justify-content: center; align-items: center; height: 100%;'> Agents = Custom Software (Personalised UI and Mods, among other things) = Custom Environments (AR)  <a href='https://github.com/KillianLucas/open-interpreter'> -- Open Interpreter -- </a> | <a href='https://github.com/microsoft/autogen'> -- Microsoft Autogen -- </a> |  </div>")
   with gr.Row():
     with gr.Column(scale=1):
+        gr.HTML(""" <a href='https://github.com/eugeneyan/open-llms'> -- Opensource List -- </a> | <a href='https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard'> -- Open LLM Leaderboard -- </a> | <a href='https://huggingface.co/spaces/sanchit-gandhi/whisper-jax'> -- Whisper JAX -- </a> | <a href="https://translate.google.com/?hl=en&tab=TT"> -- Google Translate -- </a> | <a href='https://huggingface.co/spaces/damo-vilab/modelscope-text-to-video-synthesis'> -- Modelscope Text to Video -- </a> | <a href='https://huggingface.co/spaces/stabilityai/stable-diffusion'> -- stable-diffusion 2 -- </a> | <a href='https://huggingface.co/spaces/stabilityai/stable-diffusion-1'> -- stable-diffusion 1 -- </a> | <a href='https://huggingface.co/spaces/kakaobrain/karlo'> -- karlo 1 -- </a> | <a href='https://huggingface.co/spaces/suno/bark'> -- Bark (TTS) -- </a> | <a href='https://chat.lmsys.org/'> -- Offline Text Model Demos -- </a> | <a href='https://huggingface.co/spaces/curt-park/segment-anything-with-clip'> -- SAM with Clip -- </a> | <a href='https://beta.elevenlabs.io/'> -- Eleven Labs -- </a> | <a href='https://www.d-id.com/'> -- Animate an Image -- </a> | <a href='https://voice.ai/'> -- Clone a voice -- </a> | <a href='https://openai.com/pricing'> -- OpenAI pricing -- </a> | <a href='https://huggingface.co/spaces/sohojoe/soho-clip-embeddings-explorer'> -- Image Training Data Search -- </a> | <a href='https://huggingface.co/spaces/huggingchat/chat-ui'> -- Huggingface Chat -- </a> | <a href='https://huggingface.co/spaces/bguisard/stable-diffusion-nano'> -- 128x128 Stable Diffusion (Fast) -- </a> | <a href='https://huggingface.co/spaces/colonelwatch/abstracts-index'> -- Search 95 million research abstracts -- </a> | <a href='https://huggingface.co/datasets/roneneldan/TinyStories'> -- Tiny Stories Dataset -- </a> | <a href='https://huggingface.co/spaces/lykeven/visualglm-6b'> -- Visualglm6b - Discuss images -- </a> | <a href='https://huggingface.co/spaces/xinyu1205/Recognize_Anything-Tag2Text'> -- RAM and Tag2Text -- </a> | <a href='https://huggingface.co/camenduru/potat1'> -- Potat1 Text2vid -- </a> | <a href='https://twitter.com/willdepue/status/1661781355452325889'> -- Alexandria Prohect (Will Deque) - Free Embeddings -- </a> |  <a href='https://artsandculture.google.com/'> -- Google Arts and Culture Portal -- </a> | <a href='https://huggingface.co/spaces/Matthijs/whisper_word_timestamps'> -- Word Level Timestamps  -- </a> | <a href='https://huggingface.co/spaces/zaanind/NLLB-translation'> -- NLLB 600M Demo -- </a> = <a href='https://github.com/facebookresearch/fairseq/tree/nllb'> -- NLLB Github -- </a> | <a href='https://huggingface.co/spaces/hysts/zeroscope-v2'> -- Zeroscope v2 Text to video -- </a> | <a href='https://huggingface.co/spaces/SpacesExamples/ComfyUI'> -- ComfyUI Text to Image -- </a> | <a href='https://huggingface.co/spaces/DeepFloyd/IF'> -- Deepfloyd IF - Text in image -- </a> | <a href='https://huggingface.co/spaces/ysharma/ChatGPT-Plugins-in-Gradio'> -- ChatGPT Custom Plugins Test Space -- </a> | <a href='https://www.reddit.com/r/LocalLLaMA/'> -- r/LocalLlama -- </a> | <a href='https://www.reddit.com/r/singularity/'> -- r/Singularity -- </a> | <a href='https://huggingface.co/spaces/hysts/SD-XL'> -- SD-XL Test Space -- </a> | <a href='https://huggingface.co/spaces/facebook/seamless_m4t'> -- Seamless M4T - Translation one stop shop -- </a> | <a href='https://huggingface.co/spaces/codellama/codellama-playground'> -- Code Llama playground -- </a> | <a href='https://huggingface.co/spaces/Voicemod/Text-to-Sing'> -- Text to sing -- </a> | <a href='https://huggingface.co/spaces/camenduru-com/webui'> -- Stable Diffusion Webui (Camenduru Space) -- </a> | <a href='https://huggingface.co/spaces/ysharma/WizardCoder34b'> -- Wizard Coder 34B -- </a> | <a href='https://huggingface.co/spaces/chansung/co-write-with-llama2'> -- Cowrite with llama2 -- </a> | <a href='https://huggingface.co/spaces/fffiloni/Image-to-Story'> -- Image to Story -- </a> | <a href='https://huggingface.co/spaces/fffiloni/CLIP-Interrogator-2'> -- Clip interrogator 2 -- </a> | <a href='https://github.com/THUDM/AgentBench'> -- Agent Benchmarks -- </a> | <a href='https://www.convex.dev/ai-town'> -- AI Town Live Demo -- </a> = <a href='https://github.com/a16z-infra/ai-town'> -- AI Town Repository (Deployment]) -- </a> | <a href='https://github.com/joonspk-research/generative_agents/tree/main'> -- Generative Agents: Interactive Simulacra of Human Behavior (Research paper Repository) -- </a> | <a href='https://huggingface.co/spaces/HuggingFaceM4/idefics_playground'> -- IDEFICS - open Multimodal model -- </a> | <a href='https://github.com/facebookresearch/belebele'> -- Belebele (Meta Dataset) -- </a> | <a href='https://huggingface.co/spaces/jbilcke-hf/ai-comic-factory'> -- AI Comic Factory -- </a> | <a href='https://github.com/camenduru'> -- CAMENDURU REPOS -- </a> | <a href='https://huggingface.co/datasets/b-mc2/sql-create-context'> -- SQL Dataset - A list of simple questions -- </a> | <a href='https://github.com/KillianLucas/open-interpreter'> -- Open Interpreter (alt to ChatGPT Pro) -- </a> | <a href='https://easywithai.com/fun-ai-tools/'> -- List - Easy with AI -- </a> | <a href='https://huggingface.co/spaces/Xenova/whisper-web'> -- Whisper Web (UI) -- </a> | <a href='https://blog.roblox.com/2023/09/revolutionizing-creation-roblox/'> -- Roblox Assistant -- </a> | <a href='https://huggingface.co/spaces/AP123/IllusionDiffusion'> -- Illusion Diffusion (Hide words or shapes in the image) -- </a> | <a href='https://huggingface.co/spaces/Shopify/background-replacement'> -- Background replacement - Shopify -- </a> |  <a href='https://huggingface.co/spaces/multimodalart/LoraTheExplorer'> -- Lora The Explorer (SDXL) -- </a> | <a href='https://huggingface.co/spaces/XCLiu/InstaFlow'> -- InstaFlow (Under 1 second Inference) -- </a> | <a href='https://github.com/tairov/llama2.mojo'> -- TinyStories on mojo (230+ tk/s) -- </a> | <a href='https://emojis.alexandru.so/p/OHVEmfMwQl'> -- Any Emoji you want - emojijs -- </a> | <a href='https://huggingface.co/spaces/google/sdxl'> -- SDXL on TPUv5 -- </a> | <a href='https://huggingface.co/spaces/SimianLuo/Latent_Consistency_Model'> -- LCM - SD1.5 at 7secs per 4 images (after coldstart)  -- </a> | <a href='https://huggingface.co/spaces/fffiloni/sdxl-control-loras'> -- SDXL Control Lora -- </a> | <a href='https://huggingface.co/spaces/aadnk/faster-whisper-webui'> -- Whisper WebUI -- </a> |  """)
         with gr.Tabs()  as nav1:
             with gr.Tab("Rep - HTML"):
                 gr.HTML("UNNWFWO = Unknown Native Word Foreign Word Order i.e. during active listening practice you only need the words you dont know")
-                gr.HTML("""<iframe height="1200" style="width: 100%;" scrolling="no" title="Memorisation Aid" src="https://codepen.io/kwabs22/embed/GRXKQgj?default-tab=result&editable=true" frameborder="no" loading="lazy" allowtransparency="true" allowfullscreen="true">
+                gr.HTML("""<iframe height="1200" style="width: 100%;" scrolling="no" title="Memorisation Aid" src="https://codepen.io/kwabs22/embed/preview/GRXKQgj?default-tab=result&editable=true" frameborder="no" loading="lazy" allowtransparency="true" allowfullscreen="true">
                         See the Pen <a href="https://codepen.io/kwabs22/pen/GRXKQgj"> Memorisation Aid</a> by kwabs22 (<a href="https://codepen.io/kwabs22">@kwabs22</a>) on <a href="https://codepen.io">CodePen</a>. </iframe>""")  
             with gr.Tab("Rep - Gradio"):
                 gr.Interface(fn=group_words, inputs=groupinput_text, outputs=groupoutput_text, description="Word Grouping and Rotation - Group a list of words into sets of 10 and rotate them every 60 seconds.") #.queue() 
@@ -1425,47 +1661,63 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
             with gr.Tab("Vector Database = Memorisation"):
                 gr.HTML("Phrasebook on demand in realtime <br><br> Open AI - 10000 * 1000tokens (+- 4000 characters) = 1$ (0.0001 per 1000 tokens / 750 words), Cohere Multilingual = free for personal use / Commercial use =    \n Vector Database query = Better than text search but not for logical relationships")           
             with gr.Tab("Time Estimate Calculator"):
-                gr.HTML("Repitition = A subconcious time gaame - transparent screens + below repitition assist (Vision) or  (Audio) ")
+                gr.HTML("Repitition = A subconcious time gaame - transparent screens + below repitition assist (Vision) or (Audio)")
                 gr.Interface(fn=RepititionPracticeTimeCalculator, inputs=["text", "number", "number"], outputs="text")
-    with gr.Column(scale=3): 
-        with gr.Tab("Workflows"):
-            with gr.Row():    
-                gr.HTML("<span style:{'fontsize: 20'}>Start at Unkown Tracker if unseure<span> <br> UNNWFWO = Unknown Native Word Foreign Word Order i.e. during active listening practice you only need the words you dont know <br><br> General Ideas in this space - Speed of Learning = Avoid Things you know like the plague -- How to track what you know -- Counter is easiest and How you feel is the hardest (The more you know, the more confusion on what you dont know as you probably werent keeping track) <br><br> Visulisation of long text - Bottom of this page  <br> Wordlist - 1 new word at a time per minute in the space to the left  <br> Youtube Video Watching - Subtitles Tab <br> Reading - Unknown Tracker Tabs <br> Longer Text Memorising - Acronym Map Creation Tab and Transition Tab <br> Brainstorming - Reading Assistant <br> Random Exposure <br> ")
-                gr.Interface(fn=TestSplitandUpdate, inputs=TestSplitandUpdateinput, outputs=["text", "button"])
-            with gr.Row():
+        with gr.Row():
                 PracticeExposure = gr.HTML(randomExposuremessage)
                 PracticeExposure2 = gr.HTML(randomExposuremessage2)
                 PracticeExposurebtn.click(fn=changeexposuretext, inputs=PracticeExposureInput, outputs=PracticeExposure)
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.HTML("Advanced Repitition = Combinatorics --> to understand a sentence properly you need understanding of every word --> in language that means use with other words --> Combos within the unique words in a sentence, paragraph, page, etc. --> as close to 3 word sentences")
-                with gr.Column(scale=1):
-                    gr.HTML("<p>Timing Practice - Repitition: Run from it, Dread it, Repitition is inevitable - Thanos --> Repitition of reaction - Foreign in eyes/ears native in mind (For beginners) | Repitition is a multitask activity like driving must be subconcious process to show mastery </p>")
-            gr.HTML(""" <a href='https://github.com/eugeneyan/open-llms'> -- Opensource List -- </a> | <a href='https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard'> -- Open LLM Leaderboard -- </a> | <a href='https://huggingface.co/spaces/sanchit-gandhi/whisper-jax'> -- Whisper JAX -- </a> | <a href="https://translate.google.com/?hl=en&tab=TT"> -- Google Translate -- </a> | <a href='https://huggingface.co/spaces/damo-vilab/modelscope-text-to-video-synthesis'> -- Modelscope Text to Video -- </a> | <a href='https://huggingface.co/spaces/stabilityai/stable-diffusion'> -- stable-diffusion 2 -- </a> | <a href='https://huggingface.co/spaces/stabilityai/stable-diffusion-1'> -- stable-diffusion 1 -- </a> | <a href='https://huggingface.co/spaces/kakaobrain/karlo'> -- karlo 1 -- </a> | <a href='https://huggingface.co/spaces/suno/bark'> -- Bark (TTS) -- </a> | <a href='https://chat.lmsys.org/'> -- Offline Text Model Demos -- </a> | <a href='https://huggingface.co/spaces/curt-park/segment-anything-with-clip'> -- SAM with Clip -- </a> | <a href='https://beta.elevenlabs.io/'> -- Eleven Labs -- </a> | <a href='https://www.d-id.com/'> -- Animate an Image -- </a> | <a href='https://voice.ai/'> -- Clone a voice -- </a> | <a href='https://openai.com/pricing'> -- OpenAI pricing -- </a> | <a href='https://huggingface.co/spaces/sohojoe/soho-clip-embeddings-explorer'> -- Image Training Data Search -- </a> | <a href='https://huggingface.co/spaces/huggingchat/chat-ui'> -- Huggingface Chat -- </a> | <a href='https://huggingface.co/spaces/bguisard/stable-diffusion-nano'> -- 128x128 Stable Diffusion (Fast) -- </a> | <a href='https://huggingface.co/spaces/colonelwatch/abstracts-index'> -- Search 95 million research abstracts -- </a> | <a href='https://huggingface.co/datasets/roneneldan/TinyStories'> -- Tiny Stories Dataset -- </a> | <a href='https://huggingface.co/spaces/lykeven/visualglm-6b'> -- Visualglm6b - Discuss images -- </a> | <a href='https://huggingface.co/spaces/xinyu1205/Recognize_Anything-Tag2Text'> -- RAM and Tag2Text -- </a> | <a href='https://huggingface.co/camenduru/potat1'> -- Potat1 Text2vid -- </a> | <a href='https://twitter.com/willdepue/status/1661781355452325889'> -- Alexandria Prohect (Will Deque) - Free Embeddings -- </a> |  <a href='https://artsandculture.google.com/'> -- Google Arts and Culture Portal -- </a> | <a href='https://huggingface.co/spaces/Matthijs/whisper_word_timestamps'> -- Word Level Timestamps  -- </a> | <a href='https://huggingface.co/spaces/zaanind/NLLB-translation'> -- NLLB 600M Demo -- </a> = <a href='https://github.com/facebookresearch/fairseq/tree/nllb'> -- NLLB Github -- </a> | <a href='https://huggingface.co/spaces/hysts/zeroscope-v2'> -- Zeroscope v2 Text to video -- </a> | <a href='https://huggingface.co/spaces/SpacesExamples/ComfyUI'> -- ComfyUI Text to Image -- </a> | <a href='https://huggingface.co/spaces/DeepFloyd/IF'> -- Deepfloyd IF - Text in image -- </a> | <a href='https://huggingface.co/spaces/ysharma/ChatGPT-Plugins-in-Gradio'> -- ChatGPT Custom Plugins Test Space -- </a> | <a href='https://www.reddit.com/r/LocalLLaMA/'> -- r/LocalLlama -- </a> | <a href='https://www.reddit.com/r/singularity/'> -- r/Singularity -- </a> | <a href='https://huggingface.co/spaces/hysts/SD-XL'> -- SD-XL Test Space -- </a> | <a href='https://huggingface.co/spaces/facebook/seamless_m4t'> -- Seamless M4T - Translation one stop shop -- </a> | <a href='https://huggingface.co/spaces/codellama/codellama-playground'> -- Code Llama playground -- </a> | <a href='https://huggingface.co/spaces/Voicemod/Text-to-Sing'> -- Text to sing -- </a> | <a href='https://huggingface.co/spaces/camenduru-com/webui'> -- Stable Diffusion Webui (Camenduru Space) -- </a> | <a href='https://huggingface.co/spaces/ysharma/WizardCoder34b'> -- Wizard Coder 34B -- </a> | <a href='https://huggingface.co/spaces/chansung/co-write-with-llama2'> -- Cowrite with llama2 -- </a> | <a href='https://huggingface.co/spaces/fffiloni/Image-to-Story'> -- Image to Story -- </a> | <a href='https://huggingface.co/spaces/fffiloni/CLIP-Interrogator-2'> -- Clip interrogator 2 -- </a> | <a href='https://github.com/THUDM/AgentBench'> -- Agent Benchmarks -- </a> | <a href='https://www.convex.dev/ai-town'> -- AI Town Live Demo -- </a> = <a href='https://github.com/a16z-infra/ai-town'> -- AI Town Repository (Deployment]) -- </a> | <a href='https://github.com/joonspk-research/generative_agents/tree/main'> -- Generative Agents: Interactive Simulacra of Human Behavior (Research paper Repository) -- </a> | <a href='https://huggingface.co/spaces/HuggingFaceM4/idefics_playground'> -- IDEFICS - open Multimodal model -- </a> | <a href='https://github.com/facebookresearch/belebele'> -- Belebele (Meta Dataset) -- </a> | <a href='https://huggingface.co/spaces/jbilcke-hf/ai-comic-factory'> -- AI Comic Factory -- </a> | <a href='https://github.com/camenduru'> -- CAMENDURU REPOS -- </a> | <a href='https://huggingface.co/datasets/b-mc2/sql-create-context'> -- SQL Dataset - A list of simple questions -- </a> | <a href='https://github.com/KillianLucas/open-interpreter'> -- Open Interpreter (alt to ChatGPT Pro) -- </a> | <a href='https://easywithai.com/fun-ai-tools/'> -- List - Easy with AI -- </a> | <a href='https://huggingface.co/spaces/Xenova/whisper-web'> -- Whisper Web (UI) -- </a> | <a href='https://blog.roblox.com/2023/09/revolutionizing-creation-roblox/'> -- Roblox Assistant -- </a> | <a href='https://huggingface.co/spaces/AP123/IllusionDiffusion'> -- Illusion Diffusion (Hide words or shapes in the image) -- </a> | <a href='https://huggingface.co/spaces/Shopify/background-replacement'> -- Background replacement - Shopify -- </a> |  <a href='https://huggingface.co/spaces/multimodalart/LoraTheExplorer'> -- Lora The Explorer (SDXL) -- </a> | <a href='https://huggingface.co/spaces/XCLiu/InstaFlow'> -- InstaFlow (Under 1 second Inference) -- </a> | <a href='https://github.com/tairov/llama2.mojo'> -- TinyStories on mojo (230+ tk/s) -- </a> | <a href='https://emojis.alexandru.so/p/OHVEmfMwQl'> -- Any Emoji you want - emojijs -- </a> | <a href='https://huggingface.co/spaces/google/sdxl'> -- SDXL on TPUv5 -- </a> | <a href='https://huggingface.co/spaces/SimianLuo/Latent_Consistency_Model'> -- LCM - SD1.5 at 7secs per 4 images (after coldstart)  -- </a> | <a href='https://huggingface.co/spaces/fffiloni/sdxl-control-loras'> -- SDXL Control Lora -- </a> | <a href='https://huggingface.co/spaces/aadnk/faster-whisper-webui'> -- Whisper WebUI -- </a> |  """)          
-            gr.HTML("Placeholder for every images of each sentence - Good ChatGPT + Dall-E ")
-            with gr.Row():
-                with gr.Column(scale=4):
-                    imageplaceholderinput = gr.TextArea()
-                with gr.Column(scale=1):
-                    gr.Label("Enter Text and Get a line by line placeholder for image associated with the text")
-                    imageplaceholderdownload = gr.File()
-            imageplaceholderbtn = gr.Button("Create the image placeholder")
-            with gr.Row():
-                with gr.Column(scale=3):
-                    imageplaceholderoutput = gr.HTML("Preview will load here")
-                with gr.Column(scale=2):
-                    imageplaceholdertextoutput = gr.Code("The code for the HTML created will come here")
-            imageplaceholderbtn.click(fn=imagebasedreading, inputs=[imageplaceholderinput], outputs=[imageplaceholderdownload, imageplaceholderoutput, imageplaceholdertextoutput])
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.HTML("Advanced Repitition = Combinatorics --> to understand a sentence properly you need understanding of every word --> in language that means use with other words --> Combos within the unique words in a sentence, paragraph, page, etc. --> as close to 3 word sentences")
+            with gr.Column(scale=1):
+                gr.HTML("<p>Timing Practice - Repitition: Run from it, Dread it, Repitition is inevitable - Thanos --> Repitition of reaction - Foreign in eyes/ears native in mind (For beginners) | Repitition is a multitask activity like driving must be subconcious process to show mastery </p>")
+    with gr.Column(scale=3): 
+        with gr.Tab("General"):
+            with gr.Row():    
+                gr.HTML("<span style:{'fontsize: 20'}>Start at Unkown Tracker if unseure<span> <br> UNNWFWO = Unknown Native Word Foreign Word Order i.e. during active listening practice you only need the words you dont know <br><br> General Ideas in this space - Speed of Learning = Avoid Things you know like the plague -- How to track what you know -- Counter is easiest and How you feel is the hardest (The more you know, the more confusion on what you dont know as you probably werent keeping track) <br><br> Visulisation of long text - Bottom of this page  <br> Wordlist - 1 new word at a time per minute in the space to the left  <br> Youtube Video Watching - Subtitles Tab <br> Reading - Unknown Tracker Tabs <br> Longer Text Memorising - Acronym Map Creation Tab and Transition Tab <br> Brainstorming - Reading Assistant <br> Random Exposure <br> ")
+                gr.Interface(fn=MultiOutputInterface, inputs=TestSplitandUpdateinput, outputs=["text", "text", "text", "text", "text", "text", "text", "text", "text", "button"])
+            gr.Interface(fn=LoadNLTKUDHRText, inputs=NLTKudhr, outputs=["text", "textarea"], description="UDHR as some test texts")
+        with gr.Tab("Speed through Imagery"):
+            gr.HTML("Categories for Image Creation <br>1. Extract only nouns <br>2. Extract Acronyms <br>3. Convert verbs to Careers <br>Dall-E 3 best for multi concept images - every thing else = one picture at a time <br>Ask the llm to create a prompt from the nouns extracted or to create english words ot sentences from the acronyms")
+            ImageryInput = gr.Textbox(placeholder='Enter the text here and use in this tab')
+            with gr.Tab("Filter Text"):
+                gr.Interface(fn=onlyplurals, inputs=["text"], outputs=["text"], description="Only plurals = optimal concepts to learn first as LT work = repitition")
+                gr.Interface(fn=create_acronym_map, inputs="textbox", outputs="textbox", description="Acronyms")
+                gr.Interface(fn=keep_nouns, inputs="textbox", outputs="textbox", description="Nouns only")
+            with gr.Tab("Placeholder Genration"):
+                gr.HTML("Placeholder for every images of each sentence - Good ChatGPT + Dall-E ")
+                with gr.Row():
+                    with gr.Column(scale=4):
+                        imageplaceholderinput = gr.TextArea()
+                    with gr.Column(scale=1):
+                        gr.Label("Enter Text and Get a line by line placeholder for image associated with the text")
+                        imageplaceholderdownload = gr.File()
+                imageplaceholderbtn = gr.Button("Create the image placeholder")
+                with gr.Row():
+                    with gr.Column(scale=3):
+                        imageplaceholderoutput = gr.HTML("Preview will load here")
+                    with gr.Column(scale=2):
+                        imageplaceholdertextoutput = gr.Code("The code for the HTML created will come here")
+                imageplaceholderbtn.click(fn=imagebasedreading, inputs=[imageplaceholderinput], outputs=[imageplaceholderdownload, imageplaceholderoutput, imageplaceholdertextoutput])
+            with gr.Tab('Picture Subtitles / Image Slide Show'):
+                gr.Image()
+                gr.HTML('placeholder for button to start generator for time based image recognition i.e. Picture Subtitles')
         with gr.Tab("Repetition Injected Text"):
             gr.Label("Optimal Study Reps is inbetween new information acquisition - i.e. any thing you havent read already")
-            gr.Interface(fn=RepititionInjectedReading, inputs=["text", "text"], outputs="text")
-        with gr.Tab("Progress Tracking"):
+            gr.Interface(fn=RepititionInjectedReading, inputs=[Repsplitdropdown, "text", "text"], outputs="text")
+        with gr.Tab("Stateful Reading - Progress Tracking"):
+            gr.HTML("The problem is to learn you need to repeat things you know that you didnt know thiss morning - The repitition space to the right is only half of solution <br>You need to read new stuff while revising the stuff you didnt know that you just learned aka the things you write as notes")
+            gr.HTML("The sentences used as notes repitition interface then can count as recently known sentences that you can ignore in favour of the sentences you didnt interact with")
+            gr.Label("Some Tests - click to hide - unknown word only list")     
+            gr.Interface(fn=hidingbuttontesttranslate, inputs="text", outputs=["code", "html"])
             gr.Label("Missing is database integration for the counter and non-english - ALSO TODO - Parralell interface for the html and acronym creator")
             gr.Interface(fn=UnknownTrackTexttoApp, inputs="text", outputs=["file", "html", "text"], description="HTML mini App - UNNWFWO (To track verbs you dont know for listening practice). Use the text from here to create lists you use for the TTS section")
             gr.Interface(create_acronym_map, inputs='text', outputs=['text', 'text'])
             gr.HTML("On the Acronyms you need to underline the verbs")
             gr.HTML("Aim for 1000 reps per item in your mind - the end goal for full sentences is to identify the SOV equivalent ASAP")
             gr.Interface(fill_lines, inputs=["text", RepSched_Num_lines], outputs="text")
+
         with gr.Tab("Beginner - Listen + Read"):
             gr.Label("Closed Eye Recital per new word | 1 new word a minute while recycling the words from the previous minutes")
             with gr.Row():
@@ -1505,8 +1757,8 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
             with gr.Tab("Unique word ID - use in Infranodus"):
                 with gr.Accordion(label="Infranodus", open=False):
                     gr.HTML(" <a href='https://infranodus.com/'> -- Infranodus - Word Level Knowledge graphs -- </a> | <br> Use the below interfaces to find the items that dont have entries --> These will represent new concepts or people which need to be understood individually to fully understand the text --> Infranodus search will help find related and unrelated investigation paths <br><br> TODO Figure Output Zoom / Image Dimensions")
-                    gr.Image(source="upload", label="Open Infranodus Screenshot")
-                    gr.Image(source="upload", label="Open Infranodus Screenshot")
+                    gr.Image(label="Open Infranodus Screenshot")
+                    gr.Image(label="Open Infranodus Screenshot")
                 gr.Interface(fn=unique_word_count, inputs="text", outputs="text", description="Wordcounter")
                 gr.HTML("Use the below interface to fill in the space in this format and then use the chat iframe at the top to ask llm to analyse this: <br><br> Consider how the following sentence meaning will change if the each if the selected word is replaced with one hypernym at a time: <br>Sentence: <br>Hypernyms: ")
                 gr.Interface(fn=SepHypandSynExpansion, inputs="text", outputs=["text", "text"], description="Word suggestions - Analyse the unique words in infranodus")
@@ -1520,33 +1772,30 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                 gr.HTML("Parts of speech recognition = comprehension <br> Three word sentences will give a easier guessing chance")
             gr.HTML('<iframe src="https://spacy-gradio-pipeline-visualizer.hf.space" frameborder="0" width="100%" height="600"></iframe>')
         with gr.Tab("Advanced - Making Questions = Reading"):
-            gr.HTML("Some Example Prompts <br><br>Please make 10 questions baseed on this text: <br>")
+            gr.HTML("Some Example Prompts (Even Mistral 7b is good at this) <br><br>Please make a comprehension test for the following: <br>Please make 10 questions baseed on this text: <br>")
             with gr.Row():
                 gr.TextArea("Paste the text to read here", interactive=True)
                 gr.TextArea("Make as many questions on the text as you can in native language and then translate", interactive=True)
             gr.Dropdown(["Placeholder chunk 1", "Placeholder chunk 2", "Placeholder chunk 3"])
             gr.HTML("Load the current chunk here and Put a Dataframe where you have only one column for the questions")
-        with gr.Tab('Acronym Map Creation Space'):
-            gr.HTML("Acronym cant be read with previous attentive reading - accurate measure of known vs unknown")
-            with gr.Row():
-                with gr.Accordion('Acronym Map/Skeleton Creator'):
-                    gr.HTML("Moved to Progress for now")
-                with gr.Accordion('Test with LLM'):
-                    gr.Label('Letters are always easier to recall than whole words. GPT 4 and above best suited for this prompt but can test anywhere')
-                    gr.HTML('Please help me study by making a acronym map for the maths ontology (Ask if theres questions)')
-                    gr.TextArea('', label='Paste LLM response')
-                    gr.HTML('Good but we need to now create a 9 Acronym based words - 1 for the headings together and then one each for the subheadings')
-                    gr.TextArea('', label='Paste LLM response')
-            with gr.Accordion(''):
-                gr.HTML('If study content was a map the first letters shape of the whole text = Roads')
-                gr.HTML('Known = ability to match an item to a retrieval cue instantly - Retrieval cue for the whole text = Acronym Map')
         with gr.Tab("Advanced - Youtube - Subtitles - LingQ Addon Ideas"):
             gr.HTML("<a href='https://www.lingq.com/en/'>Find LingQ Here --> https://www.lingq.com/en/</a>")
-            with gr.Tab("Visual - Multiline Custom Video Subtitles"):
+            with gr.Tab("New - Learning with Youtube"):
+                gr.HTML("TODO: 1st syllable subtitle. First Syllable of any word is all you need to listen - pair this with Youtube subtitle interface - Listening is ability to spell really fast (real time)")
+                gr.HTML(" <a href='https://huggingface.co/spaces/artificialguybr/VIDEO-TRANSLATION-TRANSCRIPTION'> -- artificialguybr's Video Translation/Transcription Space -- </a> | ")
+                YTTransciptOutDropdown = gr.Dropdown(choices=["https://www.youtube.com/watch?v=UYk43fncV68&pp=ygULcnVubmluZyBtYW4%3D", "https://youtu.be/dxVaP0-aFIE"], value="https://www.youtube.com/watch?v=UYk43fncV68&pp=ygULcnVubmluZyBtYW4%3D", allow_custom_value=True)
+                YTTransciptOutbtn = gr.Button("Transcript to text")
+                YTTransciptOutVid = gr.HTML('Video will load Here')
+                gr.Interface(fn=subtitle_generator, inputs=None, outputs=["textbox", "textbox"], description='Modified Subtitles Test - will only work after video has been loaded')
+                with gr.Row():
+                    YTTransciptAnalysedOut = gr.Textbox(placeholder="Place the translated transcript here (Click on the youtube logo to open the video and copy)")
+                    YTTransciptOut = gr.Textbox(placeholder="Place the translated transcript here (Click on the youtube logo to open the video and copy)")
+                YTTransciptOutbtn.click(fn=YTTransciptAnalysisandLoad, inputs=YTTransciptOutDropdown, outputs=[YTTransciptOutVid, YTTransciptOut, YTTransciptAnalysedOut])
+            with gr.Tab("Old - Visual - Multiline Custom Video Subtitles"):
                 gr.HTML("LingQ Companion Idea - i.e. Full Translation Read along, and eventually Videoplayer watch along like RAMUS whisper space <br><br>Extra functions needed - Persitent Sentence translation, UNWFWO, POS tagging and Word Count per user of words in their account. Macaronic Text is also another way to practice only the important information")
                 gr.HTML("""<hr> <p>For Transcripts to any video on youtube use the link below ⬇️</p> <a href="https://huggingface.co/spaces/RASMUS/Whisper-youtube-crosslingual-subtitles">https://huggingface.co/spaces/RASMUS/Whisper-youtube-crosslingual-subtitles</a> | <a href="https://huggingface.co/spaces/vumichien/whisper-speaker-diarization">https://huggingface.co/spaces/vumichien/whisper-speaker-diarization</a>""")
                 #gr.HTML("<p>If Space not loaded its because of offline devopment errors please message for edit</p> <hr>")
-                with gr.Tab("Merged Subtitles"):
+                with gr.Tab("Merged Subtitles (Incomplete)"):
                     gr.HTML(""" Core Idea = Ability to follow one video from start to finish is more important than number of words (except for verbs) <hr>
                             Step 1 - Get foreign transcript - WHISPER (Need to download video though - booo) / Youtube / Youtube transcript api / SRT websites <br>
                             Step 2 - Get Translation of foreign transcript <br>
@@ -1564,13 +1813,13 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                         MacaronicFile = gr.File(label="Paste Macaronic Text")
                         SentGramFormula = gr.File(label="Paste Sentence Grammar Formula Text")
                     with gr.Row():
-                        MergeButton = gr.Button(label='Merge the seperate files into one interpolated file (Line by line merge)')
+                        MergeButton = gr.Button('Merge the seperate files into one interpolated file (Line by line merge)', )
                     with gr.Row():
                         MergeOutput = gr.TextArea(label="Output")
                         MergeButton.click(merge_lines, inputs=[RomanFile, W4WFile, FullMeanFile, MacaronicFile], outputs=[MergeOutput], )
                     with gr.Row():
                         gr.Text("Make sure there are 4 spaces after the last subtitle block (Otherwise its skipped)")
-                        CleanedMergeButton = gr.Button(label='Create a Usable file for SRT')
+                        CleanedMergeButton = gr.Button('Create a Usable file for SRT')
                     with gr.Row():
                         CleanedMergeOutput = gr.TextArea(label="Output")
                         CleanedMergeButton.click(fn=SRTLineSort, inputs=[MergeOutput], outputs=[CleanedMergeOutput])
@@ -1600,15 +1849,6 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                     gr.HTML("<p> Spell multiple words simultaneously for simultaneous access </p> <p> Spelling Simplification - Use a dual language list? | Spelling is the end goal, you already know many letter orders called words so you need leverage them to remember random sequences")
                     gr.Interface(fn=create_dictionary, inputs="text", outputs="text", title="Sort Text by first two letters")
                     gr.Interface(fn=keep_nouns_verbs, inputs=["text"], outputs="text", description="Noun and Verbs only (Plus punctuation)")          
-        with gr.Tab("Thinking Practice (POS)"):
-            gr.HTML("By removing all nouns and verbs you get a format to practice thinking about your words to use to make sentences which make sense within constraints")      
-            with gr.Row():
-                with gr.Column():
-                    with gr.Tab("Sentence to Practice Format"):
-                        gr.Interface(fn=split_verbs_nouns , inputs="text", outputs=["text", "text", "text"], description="Comprehension reading and Sentence Format Creator")
-                with gr.Column():    
-                    gr.HTML("<a href='https://huggingface.co/datasets/b-mc2/sql-create-context'> -- SQL Dataset - A list of simple questions -- </a> |")
-                    gr.Textbox(label='Use this text to hold translations of the SQL rows in the above linked dataset (A kind of What I say vs what I want)')
         with gr.Tab("Knowledge Ideas - Notetaking"):
             gr.HTML("""<p>Good knowledge = ability to answer questions --> find Questions you cant answer and look for hidden answer within them </p>
             <p>My One Word Theory = We only use more words than needed when we have to or are bored --> Headings exist because title is not sufficient, subheadings exist because headings are not sufficient, Book Text exists because subheadings are not sufficient</p>
@@ -1619,18 +1859,21 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
             gr.Interface(fn=TextCompFormat, inputs=["textarea", HTMLCompMode], outputs="text", description="Convert Text to HTML Dropdown or Links which you paste in any html file")    
             gr.Interface(fn=create_collapsiblebutton, inputs=["textbox", "textbox", "textarea"], outputs="textbox", description="Button and Div HTML Generator, Generate the HTML for a button and the corresponding div element.")
         with gr.Tab("Real-Time AI - Video/Audio/AR"):
-                gr.HTML("HUD Experiment (Waiting for GPT4V API)- Full context of user situation + Ability to communicate in real-time to user using images (H100+ and low enough resolution and low enough steps - it/s = fps) - just like google maps but for real life")
+                gr.HTML("Pydroid and OpenCV and Tkinter = Frontend for OpenAI / OSS vision API as ChatGPT doesnt support video / real-time screenshot yet")
+                gr.HTML("HUD Experiment (Waiting for GPT4V API) - Full context of user situation + Ability to communicate in real-time to user using images (H100+ and low enough resolution and low enough steps - it/s = fps) - just like google maps but for real life")
+                gr.HTML("Some sample Open Interpreter Code - https://huggingface.co/spaces/ysharma/open-interpreter/blob/main/app.py")
                 gr.Interface(fn=ImageTranslationTest , inputs=[VideoTestInput, VideoTestSubtitleInput], outputs="video")
-                with gr.Accordion("Whisper Spaces"):
+                with gr.Accordion("Whisper Spaces (sanchit-gandhi spaces have microphone input)"):
                     Whisperspaceoptions = gr.Dropdown(choices=["https://sanchit-gandhi-whisper-jax-diarization.hf.space", "https://sanchit-gandhi-whisper-jax.hf.space", "https://sanchit-gandhi-whisper-large-v2.hf.space", "https://facebook-seamless-m4t.hf.space"], label="existing whisper spaces")
                     Whisperspaceoptionsbtn = gr.Button("Load Whisper Space")
                     WhisperspaceoptionsOut = gr.HTML()                    
                     Whisperspaceoptionsbtn.click(fn=display_website, inputs=Whisperspaceoptions, outputs=WhisperspaceoptionsOut)
                 with gr.Accordion("Image as prompt Spaces"):
-                    Imagepromptspaceoptions = gr.Dropdown(choices=["https://badayvedat-llava.hf.space", "https://xinyu1205-recognize-anything.hf.space"], label="existing whisper spaces")
+                    Imagepromptspaceoptions = gr.Dropdown(choices=["https://adept-fuyu-8b-demo.hf.space", "https://badayvedat-llava.hf.space", "https://xinyu1205-recognize-anything.hf.space"], label="existing Image prompt spaces")
                     Imagepromptspaceoptionsbtn = gr.Button("Load a Image as prompt Space")
                     ImagepromptspaceoptionsOut = gr.HTML()                    
                     Imagepromptspaceoptionsbtn.click(fn=display_website, inputs=Imagepromptspaceoptions, outputs=ImagepromptspaceoptionsOut)
+                gr.HTML("Video Dubbing - <a href='https://huggingface.co/spaces/artificialguybr/video-dubbing'> -- artificialguybr's video dubbing -- </a> | <br> Real Time video dubbing will be a true gamechanger")
                 with gr.Accordion("Old Ideas to consider", open=False):
                     gr.HTML("Nicolai Nielsen Youtube channel - aruco markers = position --> can test using premade ones from an image search")
                     gr.Textbox("Alpha Test version = Real time Lablling of All things in view using SAM and Clip Interrogator and OpenCV on pydroid --> Adjusted Demo")
@@ -1672,14 +1915,35 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                 gr.Interface(fn=FirstLetterSummary, inputs=["text"], outputs=["text"], title="Order fast fast practice --> 1 letter a word = fastest read")
                 gr.Interface(fn=imagebasedreading, inputs=["text"], outputs=["file", "html", "text"], title="Placeholder for every newline")
             with gr.Tab("Long Text Analysis"):
-                gr.Interface(fn=LoadNLTKUDHRText, inputs=NLTKudhr, outputs=["text", "textarea"])
                 gr.HTML("For Long text searches are useful under time pressure and also bring all direct interactions with search terms - a word is defined by those around it")
-                gr.Interface(fn=onlyplurals, inputs=["text"], outputs=["text"], title="Only plurals = optimal concepts to learn first as work = repitition")
                 gr.Label("Placeholder for old code for concordance and word counting in other test space")    
             with gr.Tab("Video Segmentation with OpenCV Test"):
-                gr.Interface(fn=segment_video_with_opencv, inputs=VideoSplitTestInput, outputs="fileexplorer")
+                gr.Interface(fn=segment_video_with_opencv, inputs=VideoSplitTestInput, outputs=SplitVideoOutput, description="Split video into even increments for better study tracking ")
             with gr.Tab("State Management and Education"):
                 gr.HTML("Education = Learning things you didnt know yesterday and not forgetting more than you learn <br><br> What you didnt know forms = <br> Glossary <br> Lists <br> Formulas <br> graphs <br> Procedures <br> <br> for each you will need a seperate way to track the progress but amount of times + recency = approximate state ")
+            with gr.Tab('Acronym Map Creation Space'):
+                gr.HTML("Acronym cant be read with previous attentive reading - accurate measure of known vs unknown")
+                with gr.Row():
+                    with gr.Accordion('Acronym Map/Skeleton Creator'):
+                        gr.HTML("Moved to Progress for now")
+                    with gr.Accordion('Test with LLM'):
+                        gr.Label('Letters are always easier to recall than whole words. GPT 4 and above best suited for this prompt but can test anywhere')
+                        gr.HTML('Please help me study by making a acronym map for the maths ontology (Ask if theres questions)')
+                        gr.TextArea('', label='Paste LLM response')
+                        gr.HTML('Good but we need to now create a 9 Acronym based words - 1 for the headings together and then one each for the subheadings')
+                        gr.TextArea('', label='Paste LLM response')
+                with gr.Accordion(''):
+                    gr.HTML('If study content was a map the first letters shape of the whole text = Roads')
+                    gr.HTML('Known = ability to match an item to a retrieval cue instantly - Retrieval cue for the whole text = Acronym Map')
+            with gr.Tab("Thinking Practice (POS)"):
+                gr.HTML("By removing all nouns and verbs you get a format to practice thinking about your words to use to make sentences which make sense within constraints")      
+                with gr.Row():
+                    with gr.Column():
+                        with gr.Tab("Sentence to Practice Format"):
+                            gr.Interface(fn=split_verbs_nouns , inputs="text", outputs=["text", "text", "text"], description="Comprehension reading and Sentence Format Creator")
+                    with gr.Column():    
+                        gr.HTML("<a href='https://huggingface.co/datasets/b-mc2/sql-create-context'> -- SQL Dataset - A list of simple questions -- </a> |")
+                        gr.Textbox(label='Use this text to hold translations of the SQL rows in the above linked dataset (A kind of What I say vs what I want)')
+                
 
-
-lliface.queue().launch(share="true") #(inbrowser="true")
+lliface.queue().launch() #(inbrowser="true")