Time first

app.py

@@ -783,8 +783,71 @@ with gr.Blocks() as demo:
     with gr.Accordion("Config and Asset Assistance - Click to open", open=False):
         gr.HTML("Jonas Tyroller - This problem changes your perspective on game dev - minimise the cost of exploration so you can explore more (17:00) | dont make the same game again but worse (:) <br>https://youtu.be/o5K0uqhxgsE")
         with gr.Accordion("Leaveraging Huggingface chat"):
-            gr.HTML("https://huggingface.co/chat -  Huggingface chat supports - State Management (Threads), Image Generation and editing, Websearch, Document parsing (PDF?), Assistants and larger models than zero gpu can support in July 2024 (Unquantised 30B and above)")
-            gr.HTML("Existing Assistants to use and planning custom assistants placeholder")
+            with gr.Tab("Hugging Chat"):
+                gr.HTML("https://huggingface.co/chat -  Huggingface chat supports - State Management (Threads), Image Generation and editing, Websearch, Document parsing (PDF?), Assistants and larger models than zero gpu can support in July 2024 (Unquantised 30B and above)")
+                gr.HTML("Existing Assistants to use and planning custom assistants placeholder")
+            with gr.Tab("ZeroGPU"):
+                gr.HTML("Copy paste any old config to llm and ask to remix is the easiest <br>To bake 'Moral of the story' in you have to be very deliberate")
+                gr.HTML("UI can be media and all items can have media")
+                with gr.Tab("Any Request to Qwen2-0.5B"):
+                    gr.HTML("Placeholder for https://huggingface.co/h2oai/h2o-danube3-500m-chat-GGUF and https://huggingface.co/OuteAI/Lite-Mistral-150M-v2-Instruct as alternative")
+                    gr.HTML("https://huggingface.co/spaces/HuggingFaceTB/SmolLM-135M-Instruct-WebGPU 125 mdeol to be tested as alternative (and all up to 1.5b - how to delte a model in your code?) - Need to go over the dataset to see how to prompt it - https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus ")
+                    gr.HTML("Placeholder for qwen 2 72b as alternative use checkbox and gradio client api call")
+                    gr.Markdown("# Qwen-0.5B-Instruct Language Model")
+                    gr.Markdown("This demo uses the Qwen-0.5B-Instruct model to generate responses based on your input.")
+                    gr.HTML("Example prompts: <br>I am writing a story about a chef. please write dishes to appear on the menu. <br>What are the most common decisions that a chef story would include? <br>What are the kinds problems that a chef story would include? <br>What are the kinds of out of reach goals that a chef story would include? <br>Continue this config - Paste any complete block of the config")
+                    
+                    with gr.Row():
+                        with gr.Column():
+                            llmguide_prompt = gr.Textbox(lines=2, placeholder="Enter your prompt here...")
+                            llmguide_stream_checkbox = gr.Checkbox(label="Enable streaming")
+                            llmguide_submit_button = gr.Button("Generate")
+                        
+                        with gr.Column():
+                            llmguide_output = gr.Textbox(lines=10, label="Generated Response")
+                            llmguide_tokens_per_second = gr.Textbox(label="Tokens per Second")
+                    
+                    llmguide_submit_button.click(
+                        llmguide_generate_response,
+                        inputs=[llmguide_prompt, llmguide_stream_checkbox],
+                        outputs=[llmguide_output, llmguide_tokens_per_second],
+                    )
+                with gr.Tab("General RAG (Pathfinder?) Attempt"):
+                    gr.HTML("https://huggingface.co/spaces/mteb/leaderboard - Source for SOTA - current using all-MiniLM-L6-v2")
+                    gr.HTML("Placeholder for weak RAG Type Charcter interaction test aka input for JSON 'Knowledge Base' Input")
+                    gr.Interface(
+                        fn=process_query,
+                        inputs=[
+                            gr.Textbox(lines=2, placeholder="Enter your question here..."),
+                            gr.Checkbox(label="Use RAG"),
+                            gr.Checkbox(label="Stream output")
+                        ],
+                        outputs=[
+                            gr.Textbox(label="Generated Response"),
+                            gr.Textbox(label="Tokens per second"),
+                            gr.Textbox(label="RAM Usage"),
+                            gr.Textbox(label="Referenced Documents")
+                        ],
+                        title="RAG/Non-RAG Q&A System",
+                        description="Ask a question with or without using RAG. The response is generated using a GPU-accelerated model. RAM usage and referenced document IDs (for RAG) are logged."
+                    )
+                with gr.Tab("General FAQ Attempt"):
+                    with gr.Tab("Front end as FAQ"):
+                        FAQMainOutput = gr.TextArea(placeholder='Output will show here', value='')
+                        FAQCustomButtonInput = gr.TextArea(lines=1, placeholder='Prompt goes here')
+
+                        for category_name, category_prompts in FAQAllprompts.items():
+                            with gr.Accordion(f"General {category_name} Pattern based", open=False):
+                                with gr.Group():
+                                    for index, (prompt, _) in enumerate(category_prompts):
+                                        button = gr.Button(prompt)
+                                        button.click(llmguide_generate_response, inputs=[FAQCustomButtonInput, gr.State(index), gr.State(category_name)], outputs=FAQMainOutput)
+                    with gr.Tab("Function Call as FAQ"):
+                        gr.HTML("Placeholder for media task query routing as dual purpose in workflow and for user queries as psuedo RAG engine")
+                        gr.HTML("https://llama.meta.com/docs/model-cards-and-prompt-formats/llama3_1/#built-in-tooling - The three built-in tools (brave_search, wolfram_alpha, and code interpreter) can be turned on using the system prompt")
+            with gr.Tab("Embedded Spaces"):
+                gr.HTML("In Asset Generation Tab under Text")
+        gr.Markdown("# Current Workflow = Mermaid Diagram to Story to JSON (through LLM and fix JSON by hand) to Media prompts to Asset Gneration")
         with gr.Tab("Main problem to solve - Concept combination / integration and non-linear progression planning"):
             gr.HTML("The story and the gameplay dont have to occur at the same time - eg. ")
             gr.Markdown("## Prompts / Mermaid diagrams to be made from the ideas for workflow")
@@ -809,85 +872,12 @@ with gr.Blocks() as demo:
                     for key, item in examplemermaidconceptblendingstrutures.items():
                         gr.Code(item, label=key)
         with gr.Tab("Guidance / Themes to consider before you attempt config (Currently Qwen 0.5B)"):
-            gr.HTML("Copy paste any old config to llm and ask to remix is the easiest <br>To bake 'Moral of the story' in you have to be very deliberate")
-            gr.HTML("UI can be media and all items can have media")
-            with gr.Accordion("Old Ideas to merge", open=False):
-                gr.HTML("Random Scenario / Song to 'full game' manual or auto is end goal ")
-                gr.HTML("Componets (outside Code Support for Config): Decisions (and context explanation), Nested Sections, Media (Especially to affect decisions), Replayability (GTA and Tekken type mechanics in text form), Theme integration (Modified Varibles that affect UI or config order)") 
-                gr.HTML("Existing Games eg. GTA Heists - Same Map with overlapping branching narratives, Battlefront - Elites amongst Commoners, Tekken Casino (one mistake = 1/2 or 1/3 of your Resources) and Turn based: 'Tactics' type nintendo games, Chess (and any other tile based game) ")
-                gr.HTML("Existing Game Rules for text - Cyberpunk RED, ")
-                gr.HTML("Community playthrough = Tally of players choices, Random item placed in a random location - first person to get it wins, Survival by location or characters met")
-                gr.HTML("Some Kinds of game skeletons ideas - Timelines, Graph as State machine paths, Economy ecosystem")
-                gr.HTML("One prompt to be used to test models - <br>Please make 10 python lists for the types of media files and their purposes in a game and then use those lists to random generate a timeline of 20 items when the function is called <br>Great next suggest ways to improve this function to create better timelines")
-                with gr.Tab("Main areas of considerations"):
-                    gr.HTML("")
-                    with gr.Tab("Structural Inspirations"):
-                        gr.HTML("GTA Heists - Replayability and stakes, Tekken - 2/3 mistakes = lost round ")
-                        gr.HTML("Sports Scores, ")
-                    with gr.Tab("Themes"):
-                        gr.HTML("")
-            with gr.Tab("General FAQ Attempt"):
-                with gr.Tab("Front end as FAQ"):
-                    FAQMainOutput = gr.TextArea(placeholder='Output will show here', value='')
-                    FAQCustomButtonInput = gr.TextArea(lines=1, placeholder='Prompt goes here')
-
-                    for category_name, category_prompts in FAQAllprompts.items():
-                        with gr.Accordion(f"General {category_name} Pattern based", open=False):
-                            with gr.Group():
-                                for index, (prompt, _) in enumerate(category_prompts):
-                                    button = gr.Button(prompt)
-                                    button.click(llmguide_generate_response, inputs=[FAQCustomButtonInput, gr.State(index), gr.State(category_name)], outputs=FAQMainOutput)
-                with gr.Tab("Function Call as FAQ"):
-                    gr.HTML("Placeholder for media task query routing as dual purpose in workflow and for user queries as psuedo RAG engine")
-                    gr.HTML("https://llama.meta.com/docs/model-cards-and-prompt-formats/llama3_1/#built-in-tooling - The three built-in tools (brave_search, wolfram_alpha, and code interpreter) can be turned on using the system prompt")
-
-            with gr.Tab("General RAG (Pathfinder?) Attempt"):
-                gr.HTML("https://huggingface.co/spaces/mteb/leaderboard - Source for SOTA - current using all-MiniLM-L6-v2")
-                gr.HTML("Placeholder for weak RAG Type Charcter interaction test aka input for JSON 'Knowledge Base' Input")
-                gr.Interface(
-                    fn=process_query,
-                    inputs=[
-                        gr.Textbox(lines=2, placeholder="Enter your question here..."),
-                        gr.Checkbox(label="Use RAG"),
-                        gr.Checkbox(label="Stream output")
-                    ],
-                    outputs=[
-                        gr.Textbox(label="Generated Response"),
-                        gr.Textbox(label="Tokens per second"),
-                        gr.Textbox(label="RAM Usage"),
-                        gr.Textbox(label="Referenced Documents")
-                    ],
-                    title="RAG/Non-RAG Q&A System",
-                    description="Ask a question with or without using RAG. The response is generated using a GPU-accelerated model. RAM usage and referenced document IDs (for RAG) are logged."
-                )
-
-            with gr.Tab("Any Request to Qwen2-0.5B"):
-                gr.HTML("Placeholder for https://huggingface.co/h2oai/h2o-danube3-500m-chat-GGUF and https://huggingface.co/OuteAI/Lite-Mistral-150M-v2-Instruct as alternative")
-                gr.HTML("https://huggingface.co/spaces/HuggingFaceTB/SmolLM-135M-Instruct-WebGPU 125 mdeol to be tested as alternative (and all up to 1.5b - how to delte a model in your code?) - Need to go over the dataset to see how to prompt it - https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus ")
-                gr.HTML("Placeholder for qwen 2 72b as alternative use checkbox and gradio client api call")
-                gr.Markdown("# Qwen-0.5B-Instruct Language Model")
-                gr.Markdown("This demo uses the Qwen-0.5B-Instruct model to generate responses based on your input.")
-                gr.HTML("Example prompts: <br>I am writing a story about a chef. please write dishes to appear on the menu. <br>What are the most common decisions that a chef story would include? <br>What are the kinds problems that a chef story would include? <br>What are the kinds of out of reach goals that a chef story would include? <br>Continue this config - Paste any complete block of the config")
-                
-                with gr.Row():
-                    with gr.Column():
-                        llmguide_prompt = gr.Textbox(lines=2, placeholder="Enter your prompt here...")
-                        llmguide_stream_checkbox = gr.Checkbox(label="Enable streaming")
-                        llmguide_submit_button = gr.Button("Generate")
-                    
-                    with gr.Column():
-                        llmguide_output = gr.Textbox(lines=10, label="Generated Response")
-                        llmguide_tokens_per_second = gr.Textbox(label="Tokens per Second")
-                
-                llmguide_submit_button.click(
-                    llmguide_generate_response,
-                    inputs=[llmguide_prompt, llmguide_stream_checkbox],
-                    outputs=[llmguide_output, llmguide_tokens_per_second],
-                )
+            
             with gr.Tab("Themes and Topics"):
                 gr.HTML("https://en.wikipedia.org/wiki/History#Periods")
 
-        with gr.Tab("New Config Proto Assist - Trying to abstract the process into one worflow is beyond me so multiple paths to goal (config) is the aim now"):
+        with gr.Tab("New Config Proto Assist"):
+            gr.HTML("Trying to abstract the process into one worflow is beyond me so multiple paths to goal (config) is the aim now")
             with gr.Tab("Linear - Player List to Empty Config with Edit support"):
                 with gr.Accordion("Can copy in the Test Example State Machine tab - only linear path for now", open=False):
                     gr.Markdown("# Story and Timeline Generator")
@@ -974,13 +964,16 @@ with gr.Blocks() as demo:
                 mermaideditoriframebtn.click(fn=lambda x: "<iframe src='https://mermaid.live/' width='100%' height='1000px'></iframe>", outputs=mermaideditoriframe)
                 with gr.Accordion("Mermaid Structures - click to open", open=False):
                     for key, item in mermaidstorystructures.items():
-                        gr.Code(item, label=key)
+                        with gr.Accordion(key, open=False):
+                            gr.Code(item, label=key)
 
             with gr.Tab("Branching - Network analysis to Game config"):
                 gr.HTML("Placeholder for analysing multiple stories for their network structures and creating general rules for a strucutre generator based of named entity recognition and bias to locations or people - The extreme long way")
 
+            with gr.Tab("Linear - Chess PNG to Game config"):
+                gr.HTML("Any Chess match can serve as end of game final battle")
 
-        with gr.Tab("Existing Config Crafting Progression - click to open"):
+        with gr.Tab("Existing Config Crafting Progression"):
             with gr.Accordion("Test for config to gradio components order - ignore for now", open=False ):
                     gr.HTML("Placeholder for changing the render below to the one above for new config but with the ability to upload files aka the media field should be file uploader / dropdowns for all files that have been uploaded")
                     gr.Markdown("Asset Generation")
@@ -1029,6 +1022,21 @@ Creating more diverse paths through the game""")
                         """ + display_tipsupdatedconfigatbeinningofthisspace + """
                     </div>
                 </div>""")
+        with gr.Tab("Old Ideas to merge"):
+            gr.HTML("Random Scenario / Song to 'full game' manual or auto is end goal ")
+            gr.HTML("Componets (outside Code Support for Config): Decisions (and context explanation), Nested Sections, Media (Especially to affect decisions), Replayability (GTA and Tekken type mechanics in text form), Theme integration (Modified Varibles that affect UI or config order)") 
+            gr.HTML("Existing Games eg. GTA Heists - Same Map with overlapping branching narratives, Battlefront - Elites amongst Commoners, Tekken Casino (one mistake = 1/2 or 1/3 of your Resources) and Turn based: 'Tactics' type nintendo games, Chess (and any other tile based game) ")
+            gr.HTML("Existing Game Rules for text - Cyberpunk RED, ")
+            gr.HTML("Community playthrough = Tally of players choices, Random item placed in a random location - first person to get it wins, Survival by location or characters met")
+            gr.HTML("Some Kinds of game skeletons ideas - Timelines, Graph as State machine paths, Economy ecosystem")
+            gr.HTML("One prompt to be used to test models - <br>Please make 10 python lists for the types of media files and their purposes in a game and then use those lists to random generate a timeline of 20 items when the function is called <br>Great next suggest ways to improve this function to create better timelines")
+            with gr.Tab("Main areas of considerations"):
+                gr.HTML("")
+                with gr.Tab("Structural Inspirations"):
+                    gr.HTML("GTA Heists - Replayability and stakes, Tekken - 2/3 mistakes = lost round ")
+                    gr.HTML("Sports Scores, ")
+                with gr.Tab("Themes"):
+                    gr.HTML("")
     
     with gr.Row():
         with gr.Column(scale=1):