gradio-consilium-roundtable 0.0.6

The roundtable for artificial minds

---

tags:

• gradio-custom-component
• custom-component-track
• roundtable
• consilium title: gradio_consilium_roundtable short_description: The roundtable for artificial minds colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py emoji: 🏆

---

gradio_consilium_roundtable

The roundtable for artificial minds

Installation

pip install gradio_consilium_roundtable

Usage

import gradio as gr
from gradio_consilium_roundtable import consilium_roundtable
import json

def simulate_discussion():
    """Simulate a live AI discussion with custom avatar images"""
    
    # Define avatar images (you can replace these URLs with actual image URLs)
    avatar_images = {
        "QwQ-32B": "https://cdn-avatars.huggingface.co/v1/production/uploads/620760a26e3b7210c2ff1943/-s1gyJfvbE1RgO5iBeNOi.png",
        "DeepSeek-R1": "https://logosandtypes.com/wp-content/uploads/2025/02/deepseek.svg",
        "Mistral Large": "https://logosandtypes.com/wp-content/uploads/2025/02/mistral-ai.svg",
        "Claude": "https://claude.ai/favicon.ico",
        # Web Search Agent will use emoji fallback (no image provided)
    }
    
    # Initial state - everyone ready
    initial_state = {
        "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
        "messages": [],
        "currentSpeaker": None,
        "thinking": [],
        "showBubbles": [],
        "avatarImages": avatar_images
    }

    states = [
        # 1. QwQ-32B starts thinking
        {
            "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
            "messages": [],
            "currentSpeaker": None,
            "thinking": ["QwQ-32B"],
            "showBubbles": [],
            "avatarImages": avatar_images
        },
        
        # 2. DeepSeek-R1 and Search start thinking - QwQ-32B's bubble should stay visible
        {
            "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
            "messages": [
                {"speaker": "QwQ-32B", "text": "This is a very long response that should demonstrate the scrolling functionality. I'm going to explain multiple points in detail.\n\n**Key Analysis Points:**\n- First consideration: market dynamics\n- Second factor: technical feasibility\n- Third aspect: resource allocation\n\nWe need to evaluate each of these systematically."}
            ],
            "currentSpeaker": None,
            "thinking": ["DeepSeek-R1", "Web Search Agent"],
            "showBubbles": ["QwQ-32B"],
            "avatarImages": avatar_images
        },
        
        # 3. DeepSeek-R1 responds - both QwQ-32B and DeepSeek-R1 bubbles visible
        {
            "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
            "messages": [
                {"speaker": "QwQ-32B", "text": "Here's my detailed analysis:\n\n**Key Points:**\n- Market dynamics are shifting rapidly\n- Technical feasibility looks promising\n- Resource allocation needs careful planning\n\n`Implementation roadmap` should include phased rollout."},
                {"speaker": "DeepSeek-R1", "text": "Excellent foundation, QwQ-32B! I'd like to add some **quantitative analysis** to your reasoning:\n\n> Statistical models suggest a 73% success probability\n\nLet me run some deeper calculations..."}
            ],
            "currentSpeaker": "DeepSeek-R1",
            "thinking": [],
            "showBubbles": ["QwQ-32B"],
            "avatarImages": avatar_images
        },
        
        # 4. Multiple models thinking - previous responses stay visible
        {
            "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
            "messages": [
                {"speaker": "QwQ-32B", "text": "Here's my detailed analysis with key considerations for our strategic approach."},
                {"speaker": "DeepSeek-R1", "text": "Excellent foundation! Statistical models suggest a 73% success probability based on current market conditions."}
            ],
            "currentSpeaker": None,
            "thinking": ["Mistral Large", "Claude"],
            "showBubbles": ["QwQ-32B", "DeepSeek-R1"],
            "avatarImages": avatar_images
        },
        
        # 5. Search agent responds with data - all previous responses visible
        {
            "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
            "messages": [
                {"speaker": "QwQ-32B", "text": "Here's my detailed analysis with key considerations for our strategic approach."},
                {"speaker": "DeepSeek-R1", "text": "Excellent foundation! Statistical models suggest a 73% success probability based on current market conditions."},
                {"speaker": "Web Search Agent", "text": "📊 **Recent Market Data:**\n\n- Industry growth: +23% YoY\n- Competition analysis: 5 major players\n- Consumer sentiment: 87% positive\n\nSources: MarketWatch, TechCrunch, Industry Reports"}
            ],
            "currentSpeaker": "Web Search Agent",
            "thinking": [],
            "showBubbles": ["QwQ-32B", "DeepSeek-R1"],
            "avatarImages": avatar_images
        },
        
        # 6. Claude joins the discussion
        {
            "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
            "messages": [
                {"speaker": "QwQ-32B", "text": "Here's my detailed analysis with key considerations for our strategic approach."},
                {"speaker": "DeepSeek-R1", "text": "Statistical models suggest a 73% success probability based on current market conditions."},
                {"speaker": "Web Search Agent", "text": "📊 Industry growth: +23% YoY, Competition: 5 major players, Consumer sentiment: 87% positive"},
                {"speaker": "Claude", "text": "Great insights everyone! Let me synthesize this information:\n\n🎯 **Strategic Recommendation:**\nBased on the quantitative analysis and market data, I suggest a **phased approach** with risk mitigation strategies built in."}
            ],
            "currentSpeaker": "Claude",
            "thinking": [],
            "showBubbles": ["QwQ-32B", "DeepSeek-R1", "Web Search Agent"],
            "avatarImages": avatar_images
        },
        
        # 7. Final consensus with Mistral Large
        {
            "participants": ["QwQ-32B", "DeepSeek-R1", "Mistral Large", "Claude", "Web Search Agent"],
            "messages": [
                {"speaker": "QwQ-32B", "text": "Strategic analysis complete with key considerations outlined."},
                {"speaker": "DeepSeek-R1", "text": "Statistical validation: 73% success probability confirmed."},
                {"speaker": "Web Search Agent", "text": "Market data supports positive outlook: +23% growth, 87% sentiment."},
                {"speaker": "Claude", "text": "Phased approach recommended with integrated risk mitigation."},
                {"speaker": "Mistral Large", "text": "🏆 **CONSENSUS ACHIEVED**\n\nAll analyses converge on a **GO decision** with the following framework:\n\n✅ Phased implementation\n✅ 73% success probability\n✅ Strong market fundamentals\n✅ Risk mitigation protocols"}
            ],
            "currentSpeaker": "Mistral Large",
            "thinking": [],
            "showBubbles": ["QwQ-32B", "DeepSeek-R1", "Web Search Agent", "Claude"],
            "avatarImages": avatar_images
        }
    ]
    
    return initial_state, states

def update_discussion_state(state_index, states):
    """Get the next state in the discussion"""
    if state_index >= len(states):
        state_index = 0
    return states[state_index], state_index + 1

# Initialize the discussion
initial_state, discussion_states = simulate_discussion()

with gr.Blocks() as demo:
    gr.Markdown("# 🎭 Consilium Roundtable Demo")
    gr.Markdown("**Watch the AI discussion unfold!** Click 'Next State' to see different phases of the discussion. 📼 Demo Video: https://youtu.be/oyYlf1BfuU8")
    
    # State management
    state_counter = gr.State(0)
    
    # The roundtable component
    roundtable = consilium_roundtable(
        label="AI Discussion Roundtable",
        show_label=True,
        label_icon="https://huggingface.co/front/assets/huggingface_logo-noborder.svg",
        value=initial_state
    )
    
    with gr.Row():
        next_btn = gr.Button("▶️ Next Discussion State", variant="primary")
        reset_btn = gr.Button("🔄 Reset Discussion", variant="secondary")
    
    # Status display
    with gr.Row():
        status_display = gr.Markdown("**Status:** Discussion ready to begin")
    
    def next_state(current_counter):
        new_state, new_counter = update_discussion_state(current_counter, discussion_states)
        
        # Convert to proper JSON string
        json_state = json.dumps(new_state)
        
        # Create status message
        thinking_list = new_state.get("thinking", [])
        current_speaker = new_state.get("currentSpeaker")
        
        if thinking_list:
            status = f"**Status:** {', '.join(thinking_list)} {'is' if len(thinking_list) == 1 else 'are'} thinking..."
        elif current_speaker:
            status = f"**Status:** {current_speaker} is responding..."
        else:
            status = "**Status:** Discussion in progress..."
            
        return json_state, new_counter, status

    def reset_discussion():
        json_state = json.dumps(initial_state)
        return json_state, 0, "**Status:** Discussion reset - ready to begin"
    
    next_btn.click(
        next_state,
        inputs=[state_counter],
        outputs=[roundtable, state_counter, status_display]
    )
    
    reset_btn.click(
        reset_discussion,
        outputs=[roundtable, state_counter, status_display]
    )

if __name__ == "__main__":
    demo.launch()

consilium_roundtable

Initialization

name	type	default	description
value	str | Callable | None	None	JSON string containing the discussion state with participants, messages, current speaker, thinking states, and avatar images. If a function is provided, it will be called each time the app loads to set the initial value.
placeholder	str | None	None	Not used in this component (roundtable displays participants instead).
label	str | I18nData | None	None	The label for this component, displayed above the roundtable.
label_icon	str | None	"🎭"	Icon displayed next to the label. Can be an emoji (default: "🎭") or a URL to an image. Set to None to disable.
every	Timer | float | None	None	Continuously calls `value` to recalculate it if `value` is a function (useful for live discussion updates).
inputs	Component | Sequence[Component] | set[Component] | None	None	Components that are used as inputs to calculate `value` if `value` is a function.
show_label	bool | None	None	If True, will display the label above the roundtable.
scale	int | None	None	Relative size compared to adjacent components in a Row or Blocks layout.
min_width	int	600	Minimum pixel width for the component (default 600px for proper roundtable display).
visible	bool	True	If False, component will be hidden.
rtl	bool	False	Not used in this component.
elem_id	str | None	None	An optional string assigned as the id of this component in the HTML DOM.
elem_classes	list[str] | str | None	None	Optional list of CSS classes assigned to this component.
render	bool	True	If False, component will not be rendered in the Blocks context initially.
key	int | str | tuple[int | str, ...] | None	None	For gr.render() - components with the same key are treated as the same component across re-renders.
preserved_by_key	list[str] | str | None	"value"	Parameters preserved across re-renders when using keys.

Events

name	description
change	Triggered when the value of the consilium_roundtable changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See .input() for a listener that is only triggered by user input.
input	This listener is triggered when the user changes the value of the consilium_roundtable.
submit	This listener is triggered when the user presses the Enter key while the consilium_roundtable is focused.

User function

The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).

• When used as an Input, the component only impacts the input signature of the user function.
• When used as an output, the component only impacts the return signature of the user function.

The code snippet below is accurate in cases where the component is used as both an input and an output.

• As output: Is passed, passes the JSON string value for processing.
• As input: Should return, discussion state as dict or JSON string containing:.

def predict(
    value: str | None
) -> Any:
    return value