add examples

Dockerfile

@@ -30,6 +30,9 @@ RUN --mount=type=secret,id=MARIMO_PASSWORD \
 # Set working directory
 WORKDIR /data
 
+# Copy examples
+COPY --chown=user:user ./examples ./examples
+
 # Set user
 USER user
 

app.py

@@ -1,470 +0,0 @@
-import marimo
-
-__generated_with = "0.9.2"
-app = marimo.App()
-
-
-@app.cell
-def __():
-    import marimo as mo
-
-    mo.md("# Welcome to marimo! 🌊🍃")
-    return (mo,)
-
-
-@app.cell
-def __(mo):
-    slider = mo.ui.slider(1, 22)
-    return (slider,)
-
-
-@app.cell
-def __(mo, slider):
-    mo.md(
-        f"""
-        marimo is a **reactive** Python notebook.
-
-        This means that unlike traditional notebooks, marimo notebooks **run
-        automatically** when you modify them or
-        interact with UI elements, like this slider: {slider}.
-
-        {"##" + "🍃" * slider.value}
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: disabling automatic execution": mo.md(
-                rf"""
-            marimo lets you disable automatic execution: just go into the
-            notebook settings and set
-
-            "Runtime > On Cell Change" to "lazy".
-
-            When the runtime is lazy, after running a cell, marimo marks its
-            descendants as stale instead of automatically running them. The
-            lazy runtime puts you in control over when cells are run, while
-            still giving guarantees about the notebook state.
-            """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        Tip: This is a tutorial notebook. You can create your own notebooks
-        by entering `marimo edit` at the command line.
-        """
-    ).callout()
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 1. Reactive execution
-
-        A marimo notebook is made up of small blocks of Python code called
-        cells.
-
-        marimo reads your cells and models the dependencies among them: whenever
-        a cell that defines a global variable  is run, marimo
-        **automatically runs** all cells that reference that variable.
-
-        Reactivity keeps your program state and outputs in sync with your code,
-        making for a dynamic programming environment that prevents bugs before they
-        happen.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(changed, mo):
-    (
-        mo.md(
-            f"""
-            **✨ Nice!** The value of `changed` is now {changed}.
-
-            When you updated the value of the variable `changed`, marimo
-            **reacted** by running this cell automatically, because this cell
-            references the global variable `changed`.
-
-            Reactivity ensures that your notebook state is always
-            consistent, which is crucial for doing good science; it's also what
-            enables marimo notebooks to double as tools and  apps.
-            """
-        )
-        if changed
-        else mo.md(
-            """
-            **🌊 See it in action.** In the next cell, change the value of the
-            variable  `changed` to `True`, then click the run button.
-            """
-        )
-    )
-    return
-
-
-@app.cell
-def __():
-    changed = False
-    return (changed,)
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: execution order": (
-                """
-                The order of cells on the page has no bearing on
-                the order in which cells are executed: marimo knows that a cell
-                reading a variable must run after the cell that  defines it. This
-                frees you to organize your code in the way that makes the most
-                sense for you.
-                """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        **Global names must be unique.** To enable reactivity, marimo imposes a
-        constraint on how names appear in cells: no two cells may define the same
-        variable.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: encapsulation": (
-                """
-                By encapsulating logic in functions, classes, or Python modules,
-                you can minimize the number of global variables in your notebook.
-                """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: private variables": (
-                """
-                Variables prefixed with an underscore are "private" to a cell, so
-                they can be defined by multiple cells.
-                """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 2. UI elements
-
-        Cells can output interactive UI elements. Interacting with a UI
-        element **automatically triggers notebook execution**: when
-        you interact with a UI element, its value is sent back to Python, and
-        every cell that references that element is re-run.
-
-        marimo provides a library of UI elements to choose from under
-        `marimo.ui`.
-        """
-    )
-    return
-
-
-@app.cell
-def __(mo):
-    mo.md("""**🌊 Some UI elements.** Try interacting with the below elements.""")
-    return
-
-
-@app.cell
-def __(mo):
-    icon = mo.ui.dropdown(["🍃", "🌊", "✨"], value="🍃")
-    return (icon,)
-
-
-@app.cell
-def __(icon, mo):
-    repetitions = mo.ui.slider(1, 16, label=f"number of {icon.value}: ")
-    return (repetitions,)
-
-
-@app.cell
-def __(icon, repetitions):
-    icon, repetitions
-    return
-
-
-@app.cell
-def __(icon, mo, repetitions):
-    mo.md("# " + icon.value * repetitions.value)
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 3. marimo is just Python
-
-        marimo cells parse Python (and only Python), and marimo notebooks are
-        stored as pure Python files — outputs are _not_ included. There's no
-        magical syntax.
-
-        The Python files generated by marimo are:
-
-        - easily versioned with git, yielding minimal diffs
-        - legible for both humans and machines
-        - formattable using your tool of choice,
-        - usable as Python  scripts, with UI  elements taking their default
-        values, and
-        - importable by other modules (more on that in the future).
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 4. Running notebooks as apps
-
-        marimo notebooks can double as apps. Click the app window icon in the
-        bottom-right to see this notebook in "app view."
-
-        Serve a notebook as an app with `marimo run` at the command-line.
-        Of course, you can use marimo just to level-up your
-        notebooking, without ever making apps.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 5. The `marimo` command-line tool
-
-        **Creating and editing notebooks.** Use
-
-        ```
-        marimo edit
-        ```
-
-        in a terminal to start the marimo notebook server. From here
-        you can create a new notebook or edit existing ones.
-
-
-        **Running as apps.** Use
-
-        ```
-        marimo run notebook.py
-        ```
-
-        to start a webserver that serves your notebook as an app in read-only mode,
-        with code cells hidden.
-
-        **Convert a Jupyter notebook.** Convert a Jupyter notebook to a marimo
-        notebook using `marimo convert`:
-
-        ```
-        marimo convert your_notebook.ipynb > your_app.py
-        ```
-
-        **Tutorials.** marimo comes packaged with tutorials:
-
-        - `dataflow`: more on marimo's automatic execution
-        - `ui`: how to use UI elements
-        - `markdown`: how to write markdown, with interpolated values and
-           LaTeX
-        - `plots`: how plotting works in marimo
-        - `sql`: how to use SQL
-        - `layout`: layout elements in marimo
-        - `fileformat`: how marimo's file format works
-        - `markdown-format`: for using `.md` files in marimo
-        - `for-jupyter-users`: if you are coming from Jupyter
-
-        Start a tutorial with `marimo tutorial`; for example,
-
-        ```
-        marimo tutorial dataflow
-        ```
-
-        In addition to tutorials, we have examples in our
-        [our GitHub repo](https://www.github.com/marimo-team/marimo/tree/main/examples).
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 6. The marimo editor
-
-        Here are some tips to help you get started with the marimo editor.
-        """
-    )
-    return
-
-
-@app.cell
-def __(mo, tips):
-    mo.accordion(tips)
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md("""## Finally, a fun fact""")
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        The name "marimo" is a reference to a type of algae that, under
-        the right conditions, clumps together to form a small sphere
-        called a "marimo moss ball". Made of just strands of algae, these
-        beloved assemblages are greater than the sum of their parts.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __():
-    tips = {
-        "Saving": (
-            """
-            **Saving**
-
-            - _Name_ your app using the box at the top of the screen, or
-              with `Ctrl/Cmd+s`. You can also create a named app at the
-              command line, e.g., `marimo edit app_name.py`.
-
-            - _Save_ by clicking the save icon on the bottom right, or by
-              inputting `Ctrl/Cmd+s`. By default marimo is configured
-              to autosave.
-            """
-        ),
-        "Running": (
-            """
-            1. _Run a cell_ by clicking the play ( ▷ ) button on the top
-            right of a cell, or by inputting `Ctrl/Cmd+Enter`.
-
-            2. _Run a stale cell_  by clicking the yellow run button on the
-            right of the cell, or by inputting `Ctrl/Cmd+Enter`. A cell is
-            stale when its code has been modified but not run.
-
-            3. _Run all stale cells_ by clicking the play ( ▷ ) button on
-            the bottom right of the screen, or input `Ctrl/Cmd+Shift+r`.
-            """
-        ),
-        "Console Output": (
-            """
-            Console output (e.g., `print()` statements) is shown below a
-            cell.
-            """
-        ),
-        "Creating, Moving, and Deleting Cells": (
-            """
-            1. _Create_ a new cell above or below a given one by clicking
-                the plus button to the left of the cell, which appears on
-                mouse hover.
-
-            2. _Move_ a cell up or down by dragging on the handle to the 
-                right of the cell, which appears on mouse hover.
-
-            3. _Delete_ a cell by clicking the trash bin icon. Bring it
-                back by clicking the undo button on the bottom right of the
-                screen, or with `Ctrl/Cmd+Shift+z`.
-            """
-        ),
-        "Disabling Automatic Execution": (
-            """
-            Via the notebook settings (gear icon) or footer panel, you
-            can disable automatic execution. This is helpful when
-            working with expensive notebooks or notebooks that have
-            side-effects like database transactions.
-            """
-        ),
-        "Disabling Cells": (
-            """
-            You can disable a cell via the cell context menu.
-            marimo will never run a disabled cell or any cells that depend on it.
-            This can help prevent accidental execution of expensive computations
-            when editing a notebook.
-            """
-        ),
-        "Code Folding": (
-            """
-            You can collapse or fold the code in a cell by clicking the arrow
-            icons in the line number column to the left, or by using keyboard
-            shortcuts.
-
-            Use the command palette (`Ctrl/Cmd+k`) or a keyboard shortcut to
-            quickly fold or unfold all cells.
-            """
-        ),
-        "Code Formatting": (
-            """
-            If you have [ruff](https://github.com/astral-sh/ruff) installed,
-            you can format a cell with the keyboard shortcut `Ctrl/Cmd+b`.
-            """
-        ),
-        "Command Palette": (
-            """
-            Use `Ctrl/Cmd+k` to open the command palette.
-            """
-        ),
-        "Keyboard Shortcuts": (
-            """
-            Open the notebook menu (top-right) or input `Ctrl/Cmd+Shift+h` to
-            view a list of all keyboard shortcuts.
-            """
-        ),
-        "Configuration": (
-            """
-           Configure the editor by clicking the gears icon near the top-right
-           of the screen.
-           """
-        ),
-    }
-    return (tips,)
-
-
-if __name__ == "__main__":
-    app.run()

examples/chatbot.py

@@ -0,0 +1,152 @@
+import marimo
+
+__generated_with = "0.9.14"
+app = marimo.App(width="medium")
+
+
+@app.cell
+def __():
+    import marimo as mo
+    import os
+    from huggingface_hub import InferenceClient
+    return InferenceClient, mo, os
+
+
+@app.cell
+def __():
+    MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+    return (MODEL_NAME,)
+
+
+@app.cell(hide_code=True)
+def __(MODEL_NAME, mo):
+    mo.md(f"""
+    # Chat with **{MODEL_NAME}**
+    """)
+    return
+
+
+@app.cell
+def __(max_tokens, mo, system_message, temperature, top_p):
+    mo.hstack(
+        [
+            system_message,
+            mo.vstack([temperature, top_p, max_tokens], align="end"),
+        ],
+    )
+    return
+
+
+@app.cell
+def __(mo, respond):
+    chat = mo.ui.chat(
+        model=respond,
+        prompts=["Tell me a joke.", "What is the square root of {{number}}?"],
+    )
+    chat
+    return (chat,)
+
+
+@app.cell
+def __(InferenceClient, MODEL_NAME, os):
+    """
+    For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.26.2/en/guides/inference
+    """
+
+    hf_token = os.environ.get("HF_TOKEN")
+    if not hf_token:
+        print("HF_TOKEN not set, may have limited access.")
+
+    client = InferenceClient(
+        MODEL_NAME,
+        token=hf_token,
+    )
+    return client, hf_token
+
+
+@app.cell
+def __(client, mo):
+    # Create UI controls
+    system_message = mo.ui.text_area(
+        value="You are a friendly Chatbot.",
+        label="System message",
+    )
+    max_tokens = mo.ui.slider(
+        start=1,
+        stop=2048,
+        value=512,
+        step=1,
+        label="Max new tokens",
+        show_value=True,
+    )
+    temperature = mo.ui.slider(
+        start=0.1,
+        stop=4.0,
+        value=0.7,
+        step=0.1,
+        label="Temperature",
+        show_value=True,
+    )
+    top_p = mo.ui.slider(
+        start=0.1,
+        stop=1.0,
+        value=0.95,
+        step=0.05,
+        label="Top-p (nucleus sampling)",
+        show_value=True,
+    )
+
+    # Add more configuration options if needed.
+
+
+    # Create chat callback
+    def respond(messages: list[mo.ai.ChatMessage], config):
+        chat_messages = [{"role": "system", "content": system_message.value}]
+
+        for message in messages:
+            parts = []
+            # Add text
+            parts.append({"type": "text", "text": message.content})
+
+            # Add attachments
+            if message.attachments:
+                for attachment in message.attachments:
+                    content_type = attachment.content_type or ""
+                    # This example only supports image attachments
+                    if content_type.startswith("image"):
+                        parts.append(
+                            {
+                                "type": "image_url",
+                                "image_url": {"url": attachment.url},
+                            }
+                        )
+                    else:
+                        raise ValueError(
+                            f"Unsupported content type {content_type}"
+                        )
+
+            chat_messages.append({"role": message.role, "content": parts})
+
+        response = client.chat_completion(
+            chat_messages,
+            max_tokens=max_tokens.value,
+            temperature=temperature.value,
+            top_p=top_p.value,
+            stream=False,
+        )
+
+        # You can return strings, markdown, charts, tables, dataframes, and more.
+        return response.choices[0].message.content
+    return max_tokens, respond, system_message, temperature, top_p
+
+
+@app.cell
+def __():
+    # If you need to do anything _reactively_ to the chat messages,
+    # you can access the chat messages using the `chat.value` attribute.
+    # chat.value
+    return
+
+
+if __name__ == "__main__":
+    app.run()

examples/dataset_explorer.py

@@ -0,0 +1,108 @@
+import marimo
+
+__generated_with = "0.9.18"
+app = marimo.App(width="full")
+
+
+@app.cell
+def __():
+    datasets = [
+        # Add your own HF datasets
+        "scikit-learn/iris/Iris.csv",
+        "scikit-learn/adult-census-income/adult.csv",
+        "scikit-learn/auto-mpg/auto-mpg.csv",
+        "scikit-learn/credit-card-clients/UCI_Credit_Card.csv",
+        "scikit-learn/Fish/Fish.csv",
+        "scikit-learn/tips/tips.csv",
+    ]
+    return (datasets,)
+
+
+@app.cell(hide_code=True)
+def __(mo):
+    mo.md(r"""## Select a dataset""")
+    return
+
+
+@app.cell(hide_code=True)
+def __(datasets, mo):
+    dataset = mo.ui.dropdown(datasets, value=datasets[0], label="Select a dataset")
+    no_limit = mo.ui.switch(label="Limit 1000", value=True)
+    mo.hstack([dataset, no_limit])
+    return dataset, no_limit
+
+
+@app.cell
+def __(dataset, mo, no_limit):
+    explore = mo.sql(
+        f"""
+        CREATE OR REPLACE TEMP TABLE explore
+        AS (FROM 'hf://datasets/{dataset.value}')
+        {'LIMIT 1000' if no_limit.value else ''};
+
+        FROM explore;
+        """
+    )
+    return (explore,)
+
+
+@app.cell(hide_code=True)
+def __(mo):
+    mo.md(r"""## Summary""")
+    return
+
+
+@app.cell(hide_code=True)
+def __(explore, mo):
+    _schema = mo.accordion({"Schema": explore.schema})
+
+    mo.md(f"""
+    * Total rows: **{len(explore):,}**
+    * Total columns: **{len(explore.columns)}**
+
+    {_schema}
+    """)
+    return
+
+
+@app.cell
+def __(explore):
+    explore.describe()
+    return
+
+
+@app.cell(hide_code=True)
+def __(mo):
+    mo.md("""## Manipulate the data""")
+    return
+
+
+@app.cell
+def __(explore, mo):
+    transformed = mo.ui.dataframe(explore)
+    transformed
+    return (transformed,)
+
+
+@app.cell(hide_code=True)
+def __(mo):
+    mo.md(r"""## Explore the data""")
+    return
+
+
+@app.cell
+def __(mo, transformed):
+    mo.ui.data_explorer(transformed.value)
+    return
+
+
+@app.cell(hide_code=True)
+def __():
+    # Imports
+    import marimo as mo
+    import polars
+    return mo, polars
+
+
+if __name__ == "__main__":
+    app.run()

requirements.txt

@@ -1,6 +1,9 @@
+huggingface-hub==0.26.2
 marimo[sql]
 polars
 altair
+openai
+pyarrow
 # Or a specific version
 # marimo>=0.9.0