update app

README.md

@@ -1,12 +1,12 @@
 ---
-title: marimo app template
-emoji: 🍃
-colorFrom: indigo
-colorTo: purple
+title: marimo generative ui
+emoji: 📊
+colorFrom: green
+colorTo: yellow
 sdk: docker
-pinned: true
+pinned: false
 license: mit
-short_description: Template for deploying a marimo application to HF
+short_description: marimo chatbot that can response with charts and tables
 ---
 
 Check out marimo at <https://github.com/marimo-team/marimo>

app.py

@@ -1,469 +1,150 @@
+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "ell-ai==0.0.14",
+#     "marimo",
+#     "openai==1.53.0",
+#     "polars==1.12.0",
+# ]
+# ///
+
 import marimo
 
-__generated_with = "0.9.2"
-app = marimo.App()
+__generated_with = "0.9.20"
+app = marimo.App(width="medium")
 
 
 @app.cell
-def __():
-    import marimo as mo
-
-    mo.md("# Welcome to marimo! 🌊🍃")
-    return (mo,)
+def __(mo):
+    mo.md(r"""# Generative UI Chatbot""")
+    return
 
 
 @app.cell
 def __(mo):
-    slider = mo.ui.slider(1, 22)
-    return (slider,)
+    _default_dataset = "hf://datasets/scikit-learn/Fish/Fish.csv"
+    dataset_input = mo.ui.text(value=_default_dataset, full_width=True)
+    return (dataset_input,)
 
 
 @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}
-        """
-    )
+def __(dataset_input, mo):
+    mo.md(f"""
+    This chatbot can answer questions about the following dataset: {dataset_input}
+    """)
     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.
-            """
+@app.cell
+def __(dataset_input, mo, pl):
+    # Grab a dataset
+    try:
+        df = pl.read_csv(dataset_input.value)
+        mo.output.replace(
+            mo.md(
+                f"Loaded dataset with {len(df)} rows and {len(df.columns)} columns."
             )
-        }
-    )
-    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.
-            """
+    except Exception as e:
+        df = pl.DataFrame()
+        mo.output.replace(
+            mo.md(f"""**Error loading dataset**:\n\n{e}""").callout(kind="danger")
         )
-    )
-    return
+    return (df,)
 
 
 @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
+    import os
+    import marimo as mo
+    import polars as pl
+    return mo, os, pl
 
-        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`.
-        """
+@app.cell
+def __(mo, os):
+    api_key_input = mo.ui.text(
+        label="OpenAI API Key",
+        kind="password",
+        value=os.environ.get("OPENAI_API_KEY") or "",
     )
-    return
+    return (api_key_input,)
 
 
 @app.cell
-def __(mo):
-    mo.md("""**🌊 Some UI elements.** Try interacting with the below elements.""")
+def __(api_key_input):
+    api_key_input
     return
 
 
 @app.cell
-def __(mo):
-    icon = mo.ui.dropdown(["🍃", "🌊", "✨"], value="🍃")
-    return (icon,)
+def __(api_key_input, mo):
+    from openai import Client
 
+    mo.stop(not api_key_input.value, mo.md("_Missing API key_"))
 
-@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
+    client = Client(api_key=api_key_input.value)
+    return Client, client
 
 
 @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
+def __(df, mo):
+    import ell
 
-        ```
-        marimo edit
-        ```
 
-        in a terminal to start the marimo notebook server. From here
-        you can create a new notebook or edit existing ones.
+    @ell.tool()
+    def chart_data(x_encoding: str, y_encoding: str, color: str):
+        """Generate an altair chart"""
+        import altair as alt
 
-
-        **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
+        return (
+            alt.Chart(df)
+            .mark_circle()
+            .encode(x=x_encoding, y=y_encoding, color=color)
+            .properties(width=500)
+        )
 
 
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
+    @ell.tool()
+    def filter_dataset(sql_query: str):
         """
-        ## 6. The marimo editor
-
-        Here are some tips to help you get started with the marimo editor.
+        Filter a polars dataframe using SQL. Please only use fields from the schema.
+        When referring to the table in SQL, call it 'data'.
         """
-    )
-    return
+        filtered = df.sql(sql_query, table_name="data")
+        return mo.ui.table(
+            filtered,
+            label=f"```sql\n{sql_query}\n```",
+            selection=None,
+            show_column_summaries=False,
+        )
+    return chart_data, ell, filter_dataset
 
 
 @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.
-        """
+def __(chart_data, client, df, ell, filter_dataset, mo):
+    @ell.complex(model="gpt-4o", tools=[chart_data, filter_dataset], client=client)
+    def analyze_dataset(prompt: str) -> str:
+        """You are a data scientist that can analyze a dataset"""
+        return f"I have a dataset with schema: {df.schema}. \n{prompt}"
+
+
+    def my_model(messages):
+        response = analyze_dataset(messages)
+        if response.tool_calls:
+            return response.tool_calls[0]()
+        return response.text
+
+
+    mo.ui.chat(
+        my_model,
+        prompts=[
+            "Can you chart two columns of your choosing?",
+            "Can you find the min, max of all numeric fields?",
+            "What is the sum of {{column}}?",
+        ],
     )
-    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,)
+    return analyze_dataset, my_model
 
 
 if __name__ == "__main__":

requirements.txt

@@ -1,4 +1,7 @@
 marimo
+ell-ai==0.0.14
+openai==1.53.0
+polars==1.12.0
 # Or a specific version
 # marimo>=0.9.0