Update

README.md

@@ -6,6 +6,8 @@ colorTo: yellow
 sdk: docker
 pinned: true
 fullWidth: true
+models:
+    facebook/nllb-200-distilled-600M
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -33,6 +33,8 @@ from spacy_syllables import SpacySyllables #https://spacy.io/universe/project/sp
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 from flores200_codes import flores_codes #- figure this out after it works
+import whisper
+import tempfile
 
 #When I forgot about the readme file ChatGPT suggested these - Leaving to remember the Readme.md must be updated as well
 #print(gr.__version__)
@@ -67,13 +69,12 @@ 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") #download in the docker file
+#spacy.cli.download("en_core_web_sm")
 #spacy.cli.download('ko_core_news_sm')
 #spacy.cli.download('ja_core_news_sm')
 #spacy.cli.download('zh_core_web_sm')
 #spacy.cli.download("es_core_news_sm")
 #spacy.cli.download("de_core_news_sm")
-#print(spacy.info()) #Docker install path debugging
 
 nlp_en = spacy.load("en_core_web_sm")
 nlp_de = spacy.load("de_core_news_sm")
@@ -246,8 +247,8 @@ def merge_lines(roman_file, w4w_file, full_mean_file, macaronic_file):
     
     return "\n".join(merged_lines)
 
-TTSLangOptions = gr.Dropdown(choices=langdropdown_choices, value="en", label="choose the language of the srt/text accent") #["en", "de", "es", "ja", "ko", "zh-cn"]
-TTSLangOptions2 = gr.Dropdown(choices=langdropdown_choices, value="en", label="choose the language of the srt/text accent")
+TTSLangOptions = gr.Dropdown(choices=langdropdown_choices, value="en: english", label="choose the language of the srt/text accent") #["en", "de", "es", "ja", "ko", "zh-cn"]
+TTSLangOptions2 = gr.Dropdown(choices=langdropdown_choices, value="en: english", label="choose the language of the srt/text accent")
 
 def TTSforListeningPractice(text, language = "en", Repeat10x = False):
     if Repeat10x:
@@ -1778,7 +1779,7 @@ def lingualinkassist(text, language):
 def w4wsidebysidereadergen(text, langdest):
     #FrontRevSentChunk  as reference
     FinalOutput = "Side by Side Version: "
-    Translated = "FWNWO: "
+    Translated = "FWNWO: \n"
     words = text.split()
     w4wsidebysidtranslator = Translator()
     translatedFWO = w4wsidebysidtranslator.translate(text, dest=langdest[:2])
@@ -1794,7 +1795,10 @@ def w4wsidebysidereadergen(text, langdest):
     #   print(f"Pronunciation: {obj.pronunciation}\n")
         FinalOutput += obj.origin + f" ({obj.text}) "
         Translated += obj.text + " "
-    return FinalOutput, Translated, "FWFWO: " + translatedFWO.text
+    speech = gTTS(text=text, lang=langdest[:2], slow="False")
+    speech.save("CurrentSidebySideTTSFile.mp3")
+    analysisPrompt = f"{ Translated } and \n\nFWFWO: \n{ translatedFWO.text } \n\nForeign Words Native Word Order and Foreign Word Order \nIf you had to make the notes on the word by word considerations to transform FWNWO to FWFWO what would that be? (A simple game idea where your response will be the rubrik to mark the players response against)"
+    return FinalOutput, Translated, "FWFWO: \n" + translatedFWO.text, "CurrentSidebySideTTSFile.mp3", analysisPrompt
 
 #https://huggingface.co/spaces/Geonmo/nllb-translation-demo/blob/main/app.py
 def nllbtranscload_models():
@@ -1844,7 +1848,18 @@ def nllbtransctranslation(source, target, text):
               'result': output}
     return result['result'], result['inference_time']
 
-#pip install tokenizers==0.13.3 protobuf==3.20.0
+def nllbtransctranslationoptionalw4w(source, target, text):
+    FinalOutput = ""
+    FinalInference = 0
+
+    textlist = text.split()
+    for item in textlist:
+        currentitem, currentinference = nllbtransctranslation(source, target, item)
+        FinalOutput += item + f" ({ str(currentitem) }) "
+        FinalInference += float(currentinference)
+        yield FinalOutput, str(FinalInference)
+
+#pip install tokenizers==0.13.3 protobuf==3.20.0 - dependency debugging before convert to docker
 
 #----------------------------------------------------------------------------------------------------------------------------
 
@@ -1936,14 +1951,45 @@ def letterbased_guess_word(target, guess):
 speedmastery_load_imagesinput = gr.Files(file_count="multiple", type="binary") #, file_types='image') 
 
 def speedmastery_load_images(image_files):
-    #return [image_file for image_file in image_files]
+    # print(image_files)
+    # #return [image_file for image_file in image_files]
+    # images = []
+    # for image_file in image_files:
+    #     # Read the image file and convert it to a PIL.Image object
+    #     image = Image.open(io.BytesIO(image_file))
+    #     images.append(image)
+    # return images
+    
     images = []
     for image_file in image_files:
-        # Read the image file and convert it to a PIL.Image object
-        image = Image.open(io.BytesIO(image_file))
+        # Save the file to a temporary directory
+        temp_dir = tempfile.gettempdir()
+        file_path = os.path.join(temp_dir, image_file.name)
+        with open(file_path, 'wb') as f:
+            f.write(image_file.read())
+
+        # Now you can use the file path
+        image = Image.open(file_path)
         images.append(image)
+
+        # Optionally, delete the file after processing if it's no longer needed
+        os.remove(file_path)
+
     return images
 
+#----------------------------------------------------------------------------------------------------------------------------
+
+def whisperlocaltts(filename):
+    model = whisper.load_model("base")
+    audio = whisper.load_audio(filename)
+    audio = whisper.pad_or_trim(audio)
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
+    options = whisper.DecodingOptions(language= 'en', fp16=False)
+
+    result = whisper.decode(model, mel, options)
+
+    if result.no_speech_prob < 0.5:
+        return  result.text
 
 # Define the Gradio interface inputs and outputs for video split
 spvvideo_file_input = gr.File(label='Video File')
@@ -1964,7 +2010,7 @@ 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')
+SplitVideoOutput = gr.FileExplorer(root_dir='./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%;"> Reading comprehension speed through picture based compression (collage), Live Image Subtitles and Listening Comprehension Test - <a href="https://chat.openai.com/g/g-bYMSVlb8y-lingua-link"> -- Lingua Link (Simple GPT for assistinng image creation) -- </a> |  </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>')
@@ -1976,7 +2022,7 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
     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://deepseek-ai-deepseek-coder-7b-instruct.hf.space", "https://01-ai-yi-34b-chat.hf.space", "https://ysharma-zephyr-playground.hf.space", "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)
+        linktochat = gr.Dropdown(choices=["https://sdk.vercel.ai/docs", "https://labs.perplexity.ai/", "https://chat.lmsys.org", "https://stabilityai-stablelm-2-1-6b-zephyr.hf.space", "https://deepseek-ai-deepseek-coder-7b-instruct.hf.space", "https://01-ai-yi-34b-chat.hf.space", "https://ysharma-zephyr-playground.hf.space", "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. 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):
@@ -1999,7 +2045,7 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
   #-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
   with gr.Row():
     with gr.Column(scale=1):
-        gr.HTML(""" <div style="height: 350px; width: 100%; border: 1px solid black; overflow: auto;"> Some useful links <br> <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://openxlab.org.cn/apps'> -- Openxlabs - Huggingface Alternative -- </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> | <a href='https://huggingface.co/spaces/guoyww/AnimateDiff'> -- AnimateDiff: Create an image make a video -- </a> | <a href='https://huggingface.co/spaces/facebook/seamless-m4t-v2-large'> -- Seamless m4t v2 -- </a> | <a href='https://huggingface.co/spaces/Otter-AI/OtterHD-Demo'> -- OtterHD: Multimodal model -- </a> | <a href='https://ai.meta.com/blog/ego-exo4d-video-learning-perception/'> -- Ego-exo4d Multimodal dataset -- </a> | <a href='https://imagine.meta.com/'> -- Meta Imagine images (Free)  -- </a> | <a href='https://www.mage.space/'> -- Mage Space images (Free)  -- </a> | <a href='https://www.bing.com/images/create?FORM=GENILP'> -- Bing Image Creator (Free)  -- </a> | <a href='https://jalammar.github.io/'> -- Jay Alammar Blog - Illustrated Transformer, Stable Diffusion and More -- </a> |   </div>""")
+        gr.HTML(""" <div style="height: 350px; width: 100%; border: 1px solid black; overflow: auto;"> Some useful links <br> <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://openxlab.org.cn/apps'> -- Openxlabs - Huggingface Alternative -- </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> | <a href='https://huggingface.co/spaces/guoyww/AnimateDiff'> -- AnimateDiff: Create an image make a video -- </a> | <a href='https://huggingface.co/spaces/facebook/seamless-m4t-v2-large'> -- Seamless m4t v2 -- </a> | <a href='https://huggingface.co/spaces/Otter-AI/OtterHD-Demo'> -- OtterHD: Multimodal model -- </a> | <a href='https://ai.meta.com/blog/ego-exo4d-video-learning-perception/'> -- Ego-exo4d Multimodal dataset -- </a> | <a href='https://imagine.meta.com/'> -- Meta Imagine images (Free)  -- </a> | <a href='https://www.mage.space/'> -- Mage Space images (Free)  -- </a> | <a href='https://www.bing.com/images/create?FORM=GENILP'> -- Bing Image Creator (Free)  -- </a> | <a href='https://jalammar.github.io/'> -- Jay Alammar Blog - Illustrated Transformer, Stable Diffusion and More -- </a> | <a href='https://huggingface.co/spaces/myshell-ai/OpenVoice'> -- OpenVoice - Open Source Voice Clone -- </a> |   </div>""")
         with gr.Tabs()  as nav1:
             with gr.Tab("Rep - HTML"):
                 gr.HTML("UNWFWO = Unknown Native Word Foreign Word Order i.e. during active listening practice you only need the words you dont know")
@@ -2037,43 +2083,61 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
     #-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
     with gr.Column(scale=3): 
         with gr.Tab("General Idea"):
-            gr.HTML("True mastery is from the relations between each item aka how every word relates to each other - Repitition in the form combinatorics ") 
-            with gr.Accordion("Memorisation by string comparison idea", open=False):
-                gr.HTML('Result of prompt chain starting with:  Lets say I have the strings "red" and "ppalgan" how can I guess the second from the first from just spelling (eg. similar words and distance in the alphabet, ...), how can I use python to do this i.e. output of no matching letters, closest letter to r, then e, then d, a dictionary of letters that look similar eg. d and p, l and I a and d etc.')
+            gr.HTML("<b>FINAL VERSION = Image placeholder + Merged Images + Side by Side Audio + UNWFWO Reader script + Spotify/Youtube integration in one interface</b>  <br>True mastery is from the relations between each item aka how every word relates to each other - Repitition in the form combinatorics - llm turns these into full sentences / ideas ") 
+            gr.HTML("Focus = Thinking = Audio = Repitition = This space is just ideas for optimising the audio content. - Audio of side by side version -- listen till you can say the foreign before the audio plays it (Knowledge version is Glossary as vocab you must mastering before reading)")
+            with gr.Accordion("Some Current Incomplete Tests", open=False):
+                with gr.Group():
+                    gr.HTML("Stable LM 2 zephyr 1.6 Placeholder - llama-cpp-python issues locally")
+                    gr.Interface(fn=lambda name: f"Placeholder to talk to Stable LM. Prompt = {name}", inputs="text", outputs="text")
+                gr.Interface(fn=whisperlocaltts, inputs="file", outputs="text", description="Incomplete - Whisper base Test - Can record and then copy the text for use")
+                gr.HTML('Memorisation by string comparison idea <br><br>Result of prompt chain starting with:  Lets say I have the strings "red" and "ppalgan" how can I guess the second from the first from just spelling (eg. similar words and distance in the alphabet, ...), how can I use python to do this i.e. output of no matching letters, closest letter to r, then e, then d, a dictionary of letters that look similar eg. d and p, l and I a and d etc.')
                 gr.Interface(fn=letterbased_guess_word, inputs=["text", "text"], outputs="text", description="letter based guess suggestions (one word to one word is the designed use case)")   
             gr.HTML("Side by side reading creator (Google Translate) TODO - Roman output of Non roman characters")
             with gr.Group():
                 with gr.Row():    
                     #gr.Interface(fn=w4wsidebysidereadergen, inputs=["text", w4wsidebysidelangdest], outputs=["text", "text", "text"], description="Side by side reading creator")
-                    w4wsidebysideinput = gr.Text(label="Paste Text you want to learn here (wordlists and UDHR can be used as )", placeholder="Enter Text Here")
+                    w4wsidebysideinput = gr.Text(label="Paste Text you want to learn here (wordlists and UDHR can be used as )", placeholder="Enter Text Here. One or Two Paragraphs at the longest ideally")
                 with gr.Row(): 
                     w4wsidebysidelangdest = gr.Dropdown(choices=langdropdown_choices, label="Choose destination language", value="de: german")
+                    #w4wsidebysideaudiosidebyside = gr.Checkbox(label="Audio for side by side")
                     w4wsidebysidebtn =  gr.Button("Create Side by Side, FWNWO, and FWFWO (Just read start to finish of each till you can read the FWFWO without assistance)")
                 with gr.Row():    
                     w4wsidebysideOutput = gr.Text(label="Side by side", placeholder="Side by side will display here")
                     w4wsidebysideFWNWOOutput = gr.Text(label="Foreign Word Native Word Order", placeholder="FW NWO will display here")
                     w4wsidebysideFWFWOOutput = gr.Text(label="Foreign Word Foreign Word Order", placeholder="FW FWO will display here")
-                    w4wsidebysidebtn.click(fn=w4wsidebysidereadergen, inputs=[w4wsidebysideinput, w4wsidebysidelangdest], outputs=[w4wsidebysideOutput, w4wsidebysideFWNWOOutput, w4wsidebysideFWFWOOutput])
                 with gr.Row():
-                    gr.HTML("Coming Soon")
+                    w4wsidebysideaudioOutput = gr.Audio(sources=["upload"], label="Side by Side in Audio form")
+                with gr.Row():
+                    w4wsidebysideAnalysisPromptOutput = gr.Text(label="Prompt for LLM analysis", placeholder="Prompt for LLM analysis will display here")
+                    w4wsidebysidebtn.click(fn=w4wsidebysidereadergen, inputs=[w4wsidebysideinput, w4wsidebysidelangdest], outputs=[w4wsidebysideOutput, w4wsidebysideFWNWOOutput, w4wsidebysideFWFWOOutput, w4wsidebysideaudioOutput, w4wsidebysideAnalysisPromptOutput])
+                with gr.Row():
+                    gr.HTML("To be Added")
+                with gr.Row():
+                    w4wsidebysideNatSentStructOutput = gr.Text(label="Native Closed class words as Native Sentence Structure", placeholder="Comparison is valuable")
+                    w4wsidebysideForSentStructOutput = gr.Text(label="Foreign Closed class words as Foreign Sentence Structure", placeholder="Comparison is valuable")
                 with gr.Row():
                     w4wsidebysideWordCountOutput = gr.Text(label="Word Count", placeholder="Word Count will display here")
                     w4wsidebysideRandomisedOutput = gr.Text(label="Random Order As Test", placeholder="Randomised version (Transition Tab most left bottom) will display here")
                     w4wsidebysideQueGenOutput = gr.Text(label="Questions generation as comprehension test", placeholder="Questions generated will display here")
                     w4wsidebysideUNWFWOOutput = gr.Text(label="HTML as UNWFWO assistant", placeholder="HTML as UNWFWO assistant download will display here")
-            gr.HTML("Side by side reading creator (NLLB-600M (+-3gb / setting has 400 tokens? as max length for inference optimisation?)- 200 languages vs 107 in googletrans) - <a href='https://github.com/facebookresearch/fairseq/tree/nllb'> -- Fairseq Github -- </a> |  inspired by - <a href='https://huggingface.co/spaces/Geonmo/nllb-translation-demo'> -- Geonmo NLLB Demo (Runtime Error Dec 23) -- </a> | <a href='https://huggingface.co/spaces/vutuka/nllb-vutuka-translation'> -- Vutuka demo (Working) -- </a>")
+            gr.HTML("Side by side reading creator (NLLB-600M (+-3gb / setting has 400 tokens? as max length for inference optimisation?)- 200 languages vs 107 in googletrans) - <a href='https://github.com/facebookresearch/fairseq/tree/nllb'> -- Fairseq Github -- </a> |  inspired by - <a href='https://huggingface.co/spaces/Geonmo/nllb-translation-demo'> -- Geonmo NLLB Demo -- </a> | <a href='https://huggingface.co/spaces/vutuka/nllb-vutuka-translation'> -- Vutuka demo -- </a>")
             with gr.Group():
                 gr.HTML("Under Construction - generator and cpu based to beat gpu cost, cpu wait time and network dependency for local use")
                 nllbtranscpuinput = gr.Text(label="Paste Text you want to learn here (wordlists and UDHR can be used as )", placeholder="Enter Text Here")
                 with gr.Row(): 
+                    nllbtranscpubtnword4word =  gr.Button("Create Side by Side Translation")
                     nllbtranscpulangsrc = gr.Dropdown(choices=nllb_lang_codes, label="Choose source language", value="English")
                     nllbtranscpulangdest = gr.Dropdown(choices=nllb_lang_codes, label="Choose target language", value="Akan")
-                    nllbtranscpubtn =  gr.Button("Create Side by Side, FWNWO, and FWFWO (Just read start to finish of each till you can read the FWFWO without assistance)")
+                    #nllbtranscpuword4word = gr.Checkbox(label="word for word?")
+                    nllbtranscpubtn =  gr.Button("Create Whole Translation (FWFWO)")
                 with gr.Row():    
-                    with gr.Column(scale=4): 
-                        nllbtranscpuOutput = gr.Text(label="Side by side", placeholder="Side by side will display here")
-                    with gr.Column(scale=1): 
+                    with gr.Column(): #scale=4
+                        nllbtranscpudetailsword4wordOutput = gr.Text(label="Side by side Inference Details", placeholder="Side by side Inference Details will display here")
+                        nllbtranscpuOutputword4word = gr.Text(label="Side by side", placeholder="Side by side will display here")
+                    with gr.Column(): 
                         nllbtranscpudetailsOutput = gr.Text(label="Inference Details", placeholder="Details will display here")
+                        nllbtranscpuOutput = gr.Text(label="Whole Translation of text", placeholder="Whole Translation will display here")
+                    nllbtranscpubtnword4word.click(fn=nllbtransctranslationoptionalw4w, inputs=[nllbtranscpulangsrc, nllbtranscpulangdest, nllbtranscpuinput], outputs=[nllbtranscpuOutputword4word, nllbtranscpudetailsword4wordOutput])
                     nllbtranscpubtn.click(fn=nllbtransctranslation, inputs=[nllbtranscpulangsrc, nllbtranscpulangdest, nllbtranscpuinput], outputs=[nllbtranscpuOutput, nllbtranscpudetailsOutput])
             gr.Interface(fn=LoadNLTKUDHRText, inputs=NLTKudhr, outputs=["text", "textarea"], description="UDHR as some test texts")
         with gr.Tab("Youtube Subs Listening Comprehension"):
@@ -2083,7 +2147,7 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                 gr.HTML(" <a href='https://huggingface.co/spaces/artificialguybr/VIDEO-TRANSLATION-TRANSCRIPTION'> -- artificialguybr's Video Translation/Transcription Space -- </a> | ")
                 with gr.Group():
                     gr.HTML("Custom Subtitles Ideas - Realtime Practice = Test (Pause to learn)")
-                    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)
+                    YTTransciptOutDropdown = gr.Dropdown(choices=["https://www.youtube.com/watch?v=UYk43fncV68", "https://youtu.be/dxVaP0-aFIE"], value="https://www.youtube.com/watch?v=UYk43fncV68", 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", "textbox"], description='Modified Subtitles Test - will only work after video has been loaded')
@@ -2138,21 +2202,49 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                 gr.HTML("For Audio Most productive is real time recall of native (where your full reasoning ability will always be) <br><hr> Find Replace new lines of the foreign text with full stops or | to get per word translation")
                 gr.Interface(fn=TTSforListeningPractice, inputs=["text", TTSLangOptions2], outputs="audio", description="Paste only english words in foreign order and then keep removing the words from this to practice as effectively")
         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')
-            gr.HTML("<a href='https://chat.openai.com/g/g-bYMSVlb8y-lingua-link'> -- Lingua Link (Simple GPT for assistinng image creation) -- </a> <br>Use with placeholder generator tab below ")
-            gr.Interface(fn=lingualinkassist, inputs=["text","text"], outputs="text", description="Lingua Link Prompt Assistance")
+            gr.HTML("<a href='https://chat.openai.com/g/g-bYMSVlb8y-lingua-link'> -- Lingua Link (Simple GPT for assistinng image creation) -- </a> <br>Use with placeholder generator tab below <br> Best for this is 2 nouns as one phrase i.e. nouns as adjectives and then you can a verb (1000 of those will take you far)")
+            with gr.Accordion("More Details - conversation example", open=False):
+                gr.Gallery(show_label=True, value=["adult-child-seong-in-namseong-DALL·E 2024-01-17.png", "adult child seong-in namseong DALL·E 2024-01-17 00.33.56.png", "adult (ɔpanyin) child (mmɔfra) DALL·E 2024-01-17 01.08.59.png", "adult (ɔpanyin) child (mmɔfra) DALL·E 2024-01-17 00.59.41.png"], label="Lingua Link Output - Mixed Spelling through Images")
+                gr.HTML(""" <h1>Adult Child is Seong-in Namseong</h1>
+                    <p>How do we visualize this in one image?</p>
+                    <h2>GPT's Concept</h2>
+                    <p>To visualize "adult child" translated to "seong-in namseong" in Korean, we can create an image that creatively incorporates elements representing both an adult and a child. Here's a concept:</p>
+                    <ul>
+                        <li><strong>Scene:</strong> A park setting with a clear distinction between two halves.</li>
+                        <li><strong>Adult Side:</strong> One half shows an adult man in a business suit, holding a briefcase, standing near a bench with a newspaper and a cup of coffee.</li>
+                        <li><strong>Child Side:</strong> The other half shows a young boy, dressed in playful, colorful clothes, holding a toy airplane, standing near a sandbox with a bucket and spade.</li>
+                        <li><strong>Transition Element:</strong> A tree in the middle, with its leaves transitioning from green (adult side) to vibrant colors (child side), symbolizing the growth and change from childhood to adulthood.</li>
+                    </ul>
+                    <p>This image will represent the concept of an "adult child" or "seong-in namseong" by juxtaposing the characteristics of both stages of life.</p>
+                    <h3>User's Inquiry</h3>
+                    <p>Thats but where are the near spelled words?</p>
+                    <h3>GPT's Revised Concept</h3>
+                    <p>To incorporate words that are spelled similarly to "seong-in namseong," I will first find words in English that are close in spelling to the Korean phrase. Here are three words that somewhat resemble "seong-in namseong" in spelling:</p>
+                    <ol>
+                        <li>Singing - Resembles 'seong-in' in the sound and somewhat in spelling.</li>
+                        <li>Seasoning - Shares some similarity in spelling and phonetics with 'seong-in namseong'.</li>
+                        <li>Song - Similar to 'seong' in 'seong-in'.</li>
+                    </ol>
+                    <p>Now, let's integrate these words into the image concept:</p>
+                    <ul>
+                        <li><strong>Singing:</strong> The adult can be depicted as softly singing or humming a tune, perhaps with a subtle musical note symbol floating in the air.</li>
+                        <li><strong>Seasoning:</strong> The child could be playfully pretending to cook in the sandbox, with toy seasoning bottles.</li>
+                        <li><strong>Song:</strong> There could be a book or a sheet of music with a song's title visible, lying on the bench beside the adult.</li>
+                    </ul>
+                    <p>This revised concept includes elements related to the words "singing," "seasoning," and "song," which are visually connected to the original phrase "seong-in namseong."</p> 
+                """)
+            gr.Interface(fn=lingualinkassist, inputs=["text","text"], outputs="text", description="Lingua Link Prompt Assistance (Simple Prompts)")
             with gr.Tab("Filter Text"):
+                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")
                 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 ")
+                gr.HTML("Placeholder for every image of each sentence - Good for ChatGPT + Dall-E  (First 16 Characters is part of the filename if you get error)")
                 with gr.Row():
                     with gr.Column(scale=4):
-                        imageplaceholderinput = gr.TextArea()
+                        imageplaceholderinput = gr.TextArea(placeholder="Enter Text and Get a line by line (stand in for sentences for now) placeholder for image associated with the text")
                     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():
@@ -2162,12 +2254,11 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                         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("Word level Placeholder Genration"):
-                gr.HTML("Placeholder for every images of each sentence - Good ChatGPT + Dall-E ")
+                gr.HTML("Placeholder for every image of each word - Good for ChatGPT + Dall-E (First 16 Characters is part of the filename if you get error)")
                 with gr.Row():
                     with gr.Column(scale=4):
-                        imageplaceholderinputwordlevel = gr.TextArea()
+                        imageplaceholderinputwordlevel = gr.TextArea(placeholder="Enter Text and Get a word by word placeholder for image associated with the text")
                     with gr.Column(scale=1):
-                        gr.Label("Enter Text and Get a line by line placeholder for image associated with the text")
                         imageplaceholderdownloadwordlevel = gr.File()
                 imageplaceholderbtnwordlevel = gr.Button("Create the image placeholder")
                 with gr.Row():
@@ -2177,26 +2268,30 @@ with gr.Blocks() as lliface: #theme=gr.themes.Glass(primary_hue='green', seconda
                         imageplaceholdertextoutputwordlevel = gr.Code("The code for the HTML created will come here")
                 imageplaceholderbtnwordlevel.click(fn=imagebasedreadingwordlevel, inputs=[imageplaceholderinputwordlevel], outputs=[imageplaceholderdownloadwordlevel, imageplaceholderoutputwordlevel, imageplaceholdertextoutputwordlevel])
             with gr.Tab('Picture Subtitles / Image Slide Show'):
-                gr.HTML("----------------------------------INCOMPLETE------------------------------------ runs into filepath error")
+                gr.HTML("----------------------------------INCOMPLETE------------------------------------ <br>runs into filepath error - The console error and download link in the files component in app have different paths and I dont know how to get the path in the interface")
                 gr.Interface(fn=speedmastery_load_images, inputs=speedmastery_load_imagesinput, outputs="gallery", description="Put the images you want to practice or work on")
-                gr.Image()
                 gr.HTML('placeholder for button to start generator for time based image recognition i.e. Picture Subtitles')
-                gr.Gallery()
         with gr.Tab("UNWFWO - 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 problem is to learn you need to repeat things you know that you didnt know this morning - Repititionis 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 <br> Blended Images can help")
+            gr.Interface(fn=UnknownTrackTexttoApp, inputs="text", outputs=["file", "html", "code"], description="HTML mini App - UNNWFWO (English grammar only for now)(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'], description="Acronym Map Generator (per line)")
             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.HTML("------------INCOMPLETE (javascript doesnt and unhide proprely)------------------------")
             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", "code"], 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("Kinesthetic / Mime Translation"):
-            gr.HTML("placeholder for prompt generator and tests for llama-cpp with slm")
+            gr.HTML("placeholder for prompt generator and tests for llama-cpp with slm OR even opencv + a face open pose comparison to viseme face open pose structure")
             gr.HTML("Keep nouns and verbs -- turn every noun into a verb -- turn every verb into a pose")
-            gr.HTML("Viseme Test with video recording screenshots judged LMM")
+            gr.HTML("""Viseme Test with video recording screenshots judged LMM <br><br> # https://melindaozel.com/viseme-cheat-sheet/
+                    <br><br> # https://developer.oculus.com/documentation/unity/audio-ovrlipsync-viseme-reference/
+                    <br><br> # https://docs.aws.amazon.com/polly/latest/dg/viseme.html
+                    <br><br> # https://docs.aws.amazon.com/polly/latest/dg/speechmarkexamples.html
+                    <br><br> # https://docs.aws.amazon.com/polly/latest/dg/ref-phoneme-tables-shell.html
+                    <br><br> # https://docs.aws.amazon.com/polly/latest/dg/ph-table-english-za.html
+                    <br><br> # https://docs.aws.amazon.com/polly/latest/dg/ph-table-korean.html""")
         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():
@@ -2328,8 +2423,10 @@ Each type of knowing involves different cognitive processes and levels of unders
             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("<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("Raspberry Pi / Pydroid and OpenCV and Tkinter = Frontend for OpenAI / OSS vision API as ChatGPT doesnt support video / real-time screenshot yet")
+                gr.HTML("Steerable Surveillance system = Assistant --- people will need to manage their own infrastructure or risk total invasion of privacy")
+                gr.HTML("Cheap: Raspberry Pi / Pydroid and OpenCV and Tkinter = Frontend for OpenAI / OSS vision API as ChatGPT doesnt support video / real-time screenshot yet <br>Expensive - XREAL Air 2, Quest 3, Vision Pro, ")
                 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("STT Spaces (sanchit-gandhi spaces have microphone input)"):
@@ -2350,7 +2447,13 @@ Each type of knowing involves different cognitive processes and levels of unders
                     gr.HTML("<a href='https://huggingface.co/spaces/xinyu1205/Recognize_Anything-Tag2Text'> -- RAM and Tag2Text -- </a> | <a href='https://huggingface.co/spaces/curt-park/segment-anything-with-clip'> -- SAM with Clip -- </a>")
         with gr.Tab("Incomplete Tests and Experiments"):
             with gr.Tab("Multi Output and other ideas"): 
-                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> ")
+                with gr.Row():
+                    with gr.Column():
+                        gr.HTML("Test using gradio space/interfaces through the api as function calls for gpt3.5 and 4</b>")
+                        gr.HTML("Roblox as test for ability to describe? - <a href='https://blog.roblox.com/2023/09/revolutionizing-creation-roblox/'> -- Roblox Assistant -- </a> | <br>  ")
+                        gr.HTML("State Management and Education <br> 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.Column():
+                        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=["button", "text", "text", "text", "text", "text", "text", "text", "text", "text"])
             with gr.Tab("Order based Forcing content into time (Time is the bottleneck)"):
                 gr.Label("Inspect the Transition Tab last item in left most column - RandomiseTextbyType - Incomplete, but this plus timer will work well achieve what this space aims to achieve - LLMs would choose the next set of words based on the last batch and its knowledge of your vocab level or even your current location (using phone as sensors) and can make image/audio prompts to make more engaging")
@@ -2366,17 +2469,6 @@ Each type of knowing involves different cognitive processes and levels of unders
                 gr.HTML("Tree and Branches approach to learning = familiarity with keywords/headings/summaries before reading the whole text <hr> Productivity/Work revolves around repitition which can be found looking for plurals and grouping terms eg. Headings and Hyper/Hyponyms Analysis")        
                 gr.HTML("Sentence to PyDot graph")
                 gr.HTML("Currently a bug that locks all buttons in the space when you use this above example - Reload to fix")
-            with gr.Tab("Random Ideas"):
-                gr.HTML("<hr>(Part to be formatted as System prompt for model used as the help admin for the app) Objective - Learn vocab from video/music and have record of how far you got using as overengineered solution (to keep upto date with SOTA AI models and use cases) <br>Current Workflow = One Youtube video as focus for a week or until learned (i.e. instant recognition recall of vocab in random order exposure) <br>Timeline Brainstorm = Know Nothing (Just need Exposure - Random 10% suggesed as starting point) --- Know a little (Remove known) --- Know half (UNNWFWO) <hr> ")
-                gr.HTML("""<p>Spaces Test - Still Undercontruction   --> Next Milestone is Turning this interface handsfree | Knowledge is a Language but productive knowledge is find replace as well | LingQ is good option for per word state management</p> <p> Arrows app json creator for easy knowledge graphing and spacy POS graph? --> Questions? -->  
-                <p> ChatGPT Turns Learning into a read only what you dont know ask only what you dont know feedback loop --> All you have to do is keep track of what prompts you have asked in the past</p> """)
-                gr.HTML("<p>Target 0: Mnemonics as title of images --> Comprehensible input <br>  Target 1: Dual audio at word Level while using repitition to train random recall --> Word level Time <br> Target 2: Video --> Split by sentence --> each word repeated (60) + each phrase (10) + each sentence (10) --> TTS file for practice --> State Management/Known word Tracker <br>-----------------------<br> The trick is minimum one minute of focus on a new word --> Listening is hard because there are new word within seconds and you need repeated focus on each to learn </p> <p>Audio = best long form attention mechanism AS it is ANTICIPATION (Awareness of something before it happens like knowing song Lyrics) FOCUSED - Attention (Focused Repitition) + Exposure (Random Repitition) </p> <p>Listening is hard due to different word order and word combinations (collocations more important than single words)</p> <hr>")
-                gr.HTML("Predictable to identify the parts of picture being described --> The description moves in one direction from one side of the image to the other side is easiest <hr>")
-                gr.HTML("Image = instant comprehension like Stable Diffusion --> Audiovisual experience is the most optimal reading experience <br> Manga with summary descriptions for the chapters = Most aligned visual to audio experience")
-            with gr.Tab("AI Tools, Prompts and games"):
-                gr.HTML("TODO = Llama-cpp-python with falcon 7b / openllama 7b intergrated into each of the interfaces in this space aka --> interfaces as tools for open source llm <br><br> <b>Test using gradio space/interfaces through the api as function calls for gpt3.5 and 4</b>")
-                with gr.Accordion('Command Based Tools - Instant verification of ability to describe'):
-                    gr.HTML("Roblox - <a href='https://blog.roblox.com/2023/09/revolutionizing-creation-roblox/'> -- Roblox Assistant -- </a> | <br>  ")
             #with gr.Tab("Gradio Client Tests"):
             #    gr.HTML("How to return componets here in gradio (as each client interface needs different inputs) like in react")
             with gr.Tab("Current Ideas to edit old sections"):
@@ -2385,8 +2477,13 @@ Each type of knowing involves different cognitive processes and levels of unders
                 gr.HTML("Parts that are not done - Visualisation (of acronyms / duo word sets / nouns and verbs) - The image placeholder creator script, Tracking (private = database, public = textfile export), calendar based scheduling aka alert based  ")
                 gr.HTML("React Version of the app can combine all of these use cases into one component - so far tracking, placeholder and partially scheduling have been done")
                 gr.Label('True speed simultaneous - which is a boolean state = practice at simulataneous to get simultaneous  |||| Another way to be fast is to practice simultaneously with the varios SOVs i.e. when you read a noun the verb must appear immediately and vice versa |||| Simultaneous Spelling is the other way to practice |||| The main goal of all reading is that next time you read you take less time this time: |||| Spped = ability to anticipate the next word |||| Anticipation of a sentence = POV ||||  ')
-            with gr.Tab("Text to image for only nouns "):
-                gr.Label("Placeholder for the transformers code Generator that can be used by anyone with gpu to turn all nouns in their text to pictures (The lambda labs code)")
+                with gr.Accordion("Random Ideas"):
+                    gr.HTML("<hr>(Part to be formatted as System prompt for model used as the help admin for the app) Objective - Learn vocab from video/music and have record of how far you got using as overengineered solution (to keep upto date with SOTA AI models and use cases) <br>Current Workflow = One Youtube video as focus for a week or until learned (i.e. instant recognition recall of vocab in random order exposure) <br>Timeline Brainstorm = Know Nothing (Just need Exposure - Random 10% suggesed as starting point) --- Know a little (Remove known) --- Know half (UNNWFWO) <hr> ")
+                    gr.HTML("""<p>Spaces Test - Still Undercontruction   --> Next Milestone is Turning this interface handsfree | Knowledge is a Language but productive knowledge is find replace as well | LingQ is good option for per word state management</p> <p> Arrows app json creator for easy knowledge graphing and spacy POS graph? --> Questions? -->  
+                    <p> ChatGPT Turns Learning into a read only what you dont know ask only what you dont know feedback loop --> All you have to do is keep track of what prompts you have asked in the past</p> """)
+                    gr.HTML("<p>Target 0: Mnemonics as title of images --> Comprehensible input <br>  Target 1: Dual audio at word Level while using repitition to train random recall --> Word level Time <br> Target 2: Video --> Split by sentence --> each word repeated (60) + each phrase (10) + each sentence (10) --> TTS file for practice --> State Management/Known word Tracker <br>-----------------------<br> The trick is minimum one minute of focus on a new word --> Listening is hard because there are new word within seconds and you need repeated focus on each to learn </p> <p>Audio = best long form attention mechanism AS it is ANTICIPATION (Awareness of something before it happens like knowing song Lyrics) FOCUSED - Attention (Focused Repitition) + Exposure (Random Repitition) </p> <p>Listening is hard due to different word order and word combinations (collocations more important than single words)</p> <hr>")
+                    gr.HTML("Predictable to identify the parts of picture being described --> The description moves in one direction from one side of the image to the other side is easiest <hr>")
+                    gr.HTML("Image = instant comprehension like Stable Diffusion --> Audiovisual experience is the most optimal reading experience <br> Manga with summary descriptions for the chapters = Most aligned visual to audio experience")
             with gr.Tab("Simultanoues Practice Zone"):
                 gr.Label("Audio based space where you must look at the corresponding text for the audio thats playing as simultaneous practice")
                 gr.DataFrame(None, headers=["text", "audio"], label="Add text pairs to practice", interactive=True)
@@ -2399,8 +2496,6 @@ Each type of knowing involves different cognitive processes and levels of unders
                 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=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():
@@ -2426,4 +2521,4 @@ Each type of knowing involves different cognitive processes and levels of unders
                         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(share=True) #share=true) #docker #(inbrowser="true") #colab