gradio-aicontext 0.0.5

Custom gradio component to visualize your ai context by colours and tokens' size.

---

title: Gradio AI Context sdk: gradio sdk_version: 5.49.0 app_file: app.py pinned: false

gradio_aicontext

Custom gradio component to visualize your ai context by colours and tokens' size.

Installation

pip install gradio_aicontext

Usage

import gradio as gr
from gradio_aicontext import AIContext
import json
import tiktoken


def count_tokens(message: dict) -> int:
    encoding = tiktoken.encoding_for_model("gpt-4")
    return encoding.encode(json.dumps([message])).__len__()


initial_messages = [
    {
        "role": "system",
        "content": "You are a helpful AI assistant skilled in Python programming and data analysis.",
    },
    {
        "role": "user",
        "content": "Can you help me write a function to calculate the factorial of a number?",
    },
    {
        "role": "assistant",
        "content": "I'll help you create a factorial function. Here are two approaches:\n\n```python\n# Recursive approach\ndef factorial_recursive(n):\n    if n <= 1:\n        return 1\n    return n * factorial_recursive(n - 1)\n\n# Iterative approach  \ndef factorial_iterative(n):\n    result = 1\n    for i in range(1, n + 1):\n        result *= i\n    return result\n\n# Example usage\nprint(factorial_recursive(5))  # 120\nprint(factorial_iterative(5))  # 120\n```\n\nBoth functions work well, but the iterative version is more memory efficient for large numbers.",
    },
    {"role": "user", "content": "What about using math.factorial()?"},
    {
        "role": "assistant",
        "content": "Great point! Python's built-in `math.factorial()` is the most efficient option:\n\n```python\nimport math\n\nresult = math.factorial(5)  # 120\n```\n\nIt's optimized, handles edge cases, and is the recommended approach for production code. Use custom implementations mainly for learning or when you need specific behavior.",
    },
    {"role": "user", "content": "What's the weather like in New York today?"},
    {
        "type": "function_call",
        "name": "get_weather",
        "call_id": "call_weather_123",
        "arguments": '{"location": "New York, NY", "units": "fahrenheit"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_weather_123",
        "output": '{"location": "New York, NY", "temperature": 72, "condition": "Partly Cloudy", "humidity": 65, "wind_speed": 8, "visibility": 10, "uv_index": 6, "feels_like": 75}',
    },
    {
        "role": "assistant",
        "content": "The weather in New York today is quite pleasant! Here are the details:\n\n🌤️ **Partly Cloudy** - 72°F (feels like 75°F)\n💨 Wind: 8 mph\n💧 Humidity: 65%\n👁️ Visibility: 10 miles\n☀️ UV Index: 6 (moderate)\n\nIt's a nice day to be outside!",
    },
    {
        "role": "user",
        "content": "Can you also check the forecast for tomorrow and send me an email reminder?",
    },
    {
        "type": "function_call",
        "name": "get_weather_forecast",
        "call_id": "call_forecast_456",
        "arguments": '{"location": "New York, NY", "days": 1}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_forecast_456",
        "output": '{"location": "New York, NY", "forecast": [{"date": "2024-10-17", "high": 68, "low": 58, "condition": "Light Rain", "precipitation_chance": 80, "wind_speed": 12}]}',
    },
    {
        "type": "function_call",
        "name": "send_email",
        "call_id": "call_email_789",
        "arguments": '{"to": "[e-mail]", "subject": "Weather Reminder: Bring an Umbrella Tomorrow!", "body": "Tomorrow\'s forecast for New York: Light rain expected with 80% chance of precipitation. High: 68°F, Low: 58°F. Don\'t forget your umbrella!"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_email_789",
        "output": '{"status": "sent", "message_id": "msg_12345", "delivered_at": "2024-10-16T20:45:30Z"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_forecast_456",
        "output": '{"location": "New York, NY", "forecast": [{"date": "2024-10-17", "high": 68, "low": 58, "condition": "Light Rain", "precipitation_chance": 80, "wind_speed": 12}]}',
    },
    {
        "type": "function_call",
        "name": "send_email",
        "call_id": "call_email_789",
        "arguments": '{"to": "[e-mail]", "subject": "Weather Reminder: Bring an Umbrella Tomorrow!", "body": "Tomorrow\'s forecast for New York: Light rain expected with 80% chance of precipitation. High: 68°F, Low: 58°F. Don\'t forget your umbrella!"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_email_789",
        "output": '{"status": "sent", "message_id": "msg_12345", "delivered_at": "2024-10-16T20:45:30Z"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_forecast_456",
        "output": '{"location": "New York, NY", "forecast": [{"date": "2024-10-17", "high": 68, "low": 58, "condition": "Light Rain", "precipitation_chance": 80, "wind_speed": 12}]}',
    },
    {
        "type": "function_call",
        "name": "send_email",
        "call_id": "call_email_789",
        "arguments": '{"to": "[e-mail]", "subject": "Weather Reminder: Bring an Umbrella Tomorrow!", "body": "Tomorrow\'s forecast for New York: Light rain expected with 80% chance of precipitation. High: 68°F, Low: 58°F. Don\'t forget your umbrella!"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_email_789",
        "output": '{"status": "sent", "message_id": "msg_12345", "delivered_at": "2024-10-16T20:45:30Z"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_forecast_456",
        "output": '{"location": "New York, NY", "forecast": [{"date": "2024-10-17", "high": 68, "low": 58, "condition": "Light Rain", "precipitation_chance": 80, "wind_speed": 12}]}',
    },
    {
        "type": "function_call",
        "name": "send_email",
        "call_id": "call_email_789",
        "arguments": '{"to": "[e-mail]", "subject": "Weather Reminder: Bring an Umbrella Tomorrow!", "body": "Tomorrow\'s forecast for New York: Light rain expected with 80% chance of precipitation. High: 68°F, Low: 58°F. Don\'t forget your umbrella!"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_email_789",
        "output": '{"status": "sent", "message_id": "msg_12345", "delivered_at": "2024-10-16T20:45:30Z"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_forecast_456",
        "output": '{"location": "New York, NY", "forecast": [{"date": "2024-10-17", "high": 68, "low": 58, "condition": "Light Rain", "precipitation_chance": 80, "wind_speed": 12}]}',
    },
    {
        "type": "function_call",
        "name": "send_email",
        "call_id": "call_email_789",
        "arguments": '{"to": "[e-mail]", "subject": "Weather Reminder: Bring an Umbrella Tomorrow!", "body": "Tomorrow\'s forecast for New York: Light rain expected with 80% chance of precipitation. High: 68°F, Low: 58°F. Don\'t forget your umbrella!"}',
    },
    {
        "type": "function_call_output",
        "call_id": "call_email_789",
        "output": '{"status": "sent", "message_id": "msg_12345", "delivered_at": "2024-10-16T20:45:30Z"}',
    },
]

with gr.Blocks(
    title="AI Context Visualization Demo",
    fill_height=True,
    css="""
    .h-full { height: 100% !important; }
    .flex { display: flex; }
    .min-h-0 { min-height: 0; }
    
    #context-column {
        height: calc(100vh - 140px);
        max-height: calc(100vh - 140px);
        overflow: hidden;
    }
    """,
) as demo:
    gr.Markdown("# AI Context Component Demo")
    gr.Markdown("Shows token visualization for OpenAI-style conversation messages")

    with gr.Row():
        with gr.Column(scale=2):
            json_editor = gr.JSON(
                value=initial_messages, label="Raw Messages (Editable)", show_label=True
            )

        with gr.Column(scale=1, elem_id="context-column"):
            context_viz = AIContext(
                value=initial_messages,
                count_tokens_fn=count_tokens,
                elem_classes="h-full flex min-h-0",
            )

    json_editor.change(fn=lambda x: x, inputs=[json_editor], outputs=[context_viz])


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

AIContext

Initialization

name	type	default	description
value	list | dict | Callable | None	None	list of messages or dict containing messages. If a function is provided, the function will be called each time the app loads to set the initial value of this component.
count_tokens_fn	Callable[[Any], int] | None	None	function to count tokens in a message. If None, uses character count / 4 heuristic.
label	str | I18nData | None	"AI Context"	the label for this component, displayed above the component if `show_label` is `True`.
every	Timer | float | None	None	Continously calls `value` to recalculate it if `value` is a function (has no effect otherwise).
inputs	Component | Sequence[Component] | set[Component] | None	None	Components that are used as inputs to calculate `value` if `value` is a function (has no effect otherwise).
scale	int | None	None	relative size compared to adjacent Components.
min_width	int	160	minimum pixel width.
interactive	bool | None	False	if True, will be rendered as interactive; if False, will be read-only.
visible	bool | Literal["hidden"]	True	If False, component will be hidden.
elem_id	str | None	None	An optional string that is assigned as the id of this component in the HTML DOM.
elem_classes	list[str] | str | None	None	An optional list of strings that are assigned as the classes of this component in the HTML DOM.
render	bool	True	If False, component will not render be rendered in the Blocks context.
key	int | str | tuple[int | str, ...] | None	None	in a gr.render, Components with the same key across re-renders are treated as the same component.

Events

name	description
change	Triggered when the value of the AIContext 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.

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 data through unchanged.
• As input: Should return, messages list or dict containing messages.

def predict(
    value: typing.Any
) -> typing.Any:
    return value