Chat

The chat UI element provides an interactive chatbot interface for conversations. It can be customized with different models, including built-in AI models or custom functions.

class marimo.ui.chat(model: Callable[[List[ChatMessage], ChatModelConfig], object], *, prompts: List[str] | None = None, on_message: Callable[[List[ChatMessage]], None] | None = None, show_configuration_controls: bool = False, config: ChatModelConfigDict | None = None)

A chatbot UI element for interactive conversations.

Example - Using a custom model.

You can define a custom chat model Callable that takes in the history of messages and configuration.

The response can be an object, a marimo UI element, or plain text.

def my_rag_model(messages, config):
    question = messages[-1].content
    docs = find_docs(question)
    prompt = template(question, docs, messages)
    response = query(prompt)
    if is_dataset(response):
        return dataset_to_chart(response)
    return response


chat = mo.ui.chat(my_rag_model)

Example - Using a built-in model.

You can use a built-in model from the mo.ai module.

chat = mo.ui.chat(
    mo.ai.openai(
        "gpt-4o",
        system_message="You are a helpful assistant.",
    ),
)

Attributes.

• value: the current chat history

Initialization Args.

• model: (Callable[[List[ChatMessage], ChatModelConfig], object]) a callable that takes in the chat history and returns a response

• prompts: optional list of prompts to start the conversation

• on_message: optional callback function to handle new messages

• show_configuration_controls: whether to show the configuration controls

• config: optional ChatModelConfigDict to override the default configuration keys include:

  • max_tokens

  • temperature

  • top_p

  • top_k

  • frequency_penalty

  • presence_penalty

Public methods

Inherited from UIElement

form([label, bordered, loading, ...])	Create a submittable form out of this UIElement.
send_message(message, buffers)	Send a message to the element rendered on the frontend from the backend.

Inherited from Html

batch(**elements)	Convert an HTML object with templated text into a UI element.
center()	Center an item.
right()	Right-justify.
left()	Left-justify.
callout([kind])	Create a callout containing this HTML element.
style([style])	Wrap an object in a styled container.

Public Data Attributes:

Inherited from UIElement

value

The element’s current value.

Inherited from Html

text	A string of HTML representing this element.

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Basic Usage

Here’s a simple example using a custom echo model:

import marimo as mo

def echo_model(messages, config):
    return f"Echo: {messages[-1].content}"

chat = mo.ui.chat(echo_model, prompts=["Hello", "How are you?"])
chat

Using a Built-in AI Model

You can use marimo’s built-in AI models, such as OpenAI’s GPT:

import marimo as mo

chat = mo.ui.chat(
    mo.ai.openai(
        "gpt-4",
        system_message="You are a helpful assistant.",
    ),
    show_configuration_controls=True
)
chat

Accessing Chat History

You can access the chat history using the value attribute:

chat.value

This returns a list of ChatMessage objects, each containing role and content attributes.

Custom Model with Additional Context

Here’s an example of a custom model that uses additional context:

import marimo as mo

def rag_model(messages, config):
    question = messages[-1].content
    docs = find_relevant_docs(question)
    context = "\n".join(docs)
    prompt = f"Context: {context}\n\nQuestion: {question}\n\nAnswer:"
    response = query_llm(prompt, config)
    return response

mo.ui.chat(rag_model)

This example demonstrates how you can implement a Retrieval-Augmented Generation (RAG) model within the chat interface.

Built-in Models

marimo provides several built-in AI models that you can use with the chat UI element.

import marimo as mo

mo.ui.chat(
    mo.ai.openai(
        "gpt-4",
        system_message="You are a helpful assistant.",
        api_key="sk-...",
    ),
    show_configuration_controls=True
)

mo.ui.chat(
    mo.ai.anthropic(
        "claude-3-5-sonnet-20240602",
        system_message="You are a helpful assistant.",
        api_key="sk-...",
    ),
    show_configuration_controls=True
)

class marimo.ai.models.openai(model: str, *, system_message: str = 'You are a helpful assistant specializing in data science.', api_key: str | None = None, base_url: str | None = None)

OpenAI ChatModel

Args:

• model (str): The model to use. Can be found on the OpenAI models page

• system_message (str): The system message to use

• api_key (Optional[str]): The API key to use. If not provided, the API key will be retrieved from the OPENAI_API_KEY environment variable or the user’s config.

• base_url (Optional[str]): The base URL to use

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class marimo.ai.models.anthropic(model: str, *, system_message: str = 'You are a helpful assistant specializing in data science.', api_key: str | None = None, base_url: str | None = None)

Anthropic ChatModel

Args:

• model (str): The model to use.

• system_message (str): The system message to use

• api_key (Optional[str]): The API key to use. If not provided, the API key will be retrieved from the ANTHROPIC_API_KEY environment variable or the user’s config.

• base_url (Optional[str]): The base URL to use

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