update app
Browse files- README.md +6 -6
- app.py +111 -426
- requirements.txt +2 -0
README.md
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---
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title: marimo
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emoji:
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colorFrom:
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colorTo:
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sdk: docker
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pinned:
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license: mit
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short_description:
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---
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Check out marimo at <https://github.com/marimo-team/marimo>
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---
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title: marimo code interpreter
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emoji: π»
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colorFrom: purple
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colorTo: green
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sdk: docker
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pinned: false
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license: mit
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short_description: A marimo chatbot that can run Python code
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---
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Check out marimo at <https://github.com/marimo-team/marimo>
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app.py
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import marimo as mo
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mo.md("# Welcome to marimo! ππ")
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return (mo,)
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@app.cell
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def __(mo):
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slider = mo.ui.slider(1, 22)
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return (slider,)
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mo.md(
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f"""
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marimo is a **reactive** Python notebook.
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This means that unlike traditional notebooks, marimo notebooks **run
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automatically** when you modify them or
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interact with UI elements, like this slider: {slider}.
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{"##" + "π" * slider.value}
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"""
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)
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return
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@app.cell(hide_code=True)
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def __(
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{
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"Tip: disabling automatic execution": mo.md(
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rf"""
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marimo lets you disable automatic execution: just go into the
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notebook settings and set
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"Runtime > On Cell Change" to "lazy".
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When the runtime is lazy, after running a cell, marimo marks its
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descendants as stale instead of automatically running them. The
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lazy runtime puts you in control over when cells are run, while
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still giving guarantees about the notebook state.
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"""
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)
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}
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)
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return
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by entering `marimo edit` at the command line.
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"""
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).callout()
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return
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@app.cell(hide_code=True)
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def __(mo):
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mo.md(
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"""
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A marimo notebook is made up of small blocks of Python code called
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cells.
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a cell that defines a global variable is run, marimo
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**automatically runs** all cells that reference that variable.
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Reactivity keeps your program state and outputs in sync with your code,
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making for a dynamic programming environment that prevents bugs before they
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happen.
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"""
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)
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return
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@app.cell(hide_code=True)
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def __(
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(
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When you updated the value of the variable `changed`, marimo
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**reacted** by running this cell automatically, because this cell
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references the global variable `changed`.
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Reactivity ensures that your notebook state is always
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consistent, which is crucial for doing good science; it's also what
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enables marimo notebooks to double as tools and apps.
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"""
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)
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if changed
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else mo.md(
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"""
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**π See it in action.** In the next cell, change the value of the
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variable `changed` to `True`, then click the run button.
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"""
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)
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)
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return
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@app.cell
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def __():
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changed = False
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return (changed,)
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@app.cell(hide_code=True)
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def __(mo):
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mo.accordion(
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{
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"Tip: execution order": (
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"""
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The order of cells on the page has no bearing on
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the order in which cells are executed: marimo knows that a cell
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reading a variable must run after the cell that defines it. This
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frees you to organize your code in the way that makes the most
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sense for you.
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"""
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)
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}
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)
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return
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@app.cell(hide_code=True)
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def __(mo):
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mo.md(
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"""
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**Global names must be unique.** To enable reactivity, marimo imposes a
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constraint on how names appear in cells: no two cells may define the same
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variable.
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"""
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)
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@app.cell(hide_code=True)
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def __(
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"""
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By encapsulating logic in functions, classes, or Python modules,
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you can minimize the number of global variables in your notebook.
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"""
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)
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}
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)
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return
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@app.cell(hide_code=True)
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def __(
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)
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@app.cell(hide_code=True)
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def __(mo):
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mo.md(
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"""
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## 2. UI elements
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Cells can output interactive UI elements. Interacting with a UI
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element **automatically triggers notebook execution**: when
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you interact with a UI element, its value is sent back to Python, and
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every cell that references that element is re-run.
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marimo provides a library of UI elements to choose from under
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`marimo.ui`.
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"""
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)
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return
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@app.cell
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def __(mo):
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mo.md("""**π Some UI elements.** Try interacting with the below elements.""")
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return
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@app.cell
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def __(mo):
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icon = mo.ui.dropdown(["π", "π", "β¨"], value="π")
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return (icon,)
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@app.cell
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def __(icon, mo):
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repetitions = mo.ui.slider(1, 16, label=f"number of {icon.value}: ")
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return (repetitions,)
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@app.cell
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def __(
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@app.cell
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def __(icon, mo, repetitions):
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mo.md("# " + icon.value * repetitions.value)
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return
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@app.cell(hide_code=True)
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def __(mo):
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mo.md(
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"""
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## 3. marimo is just Python
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marimo cells parse Python (and only Python), and marimo notebooks are
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stored as pure Python files β outputs are _not_ included. There's no
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magical syntax.
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The Python files generated by marimo are:
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- easily versioned with git, yielding minimal diffs
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- legible for both humans and machines
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- formattable using your tool of choice,
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- usable as Python scripts, with UI elements taking their default
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values, and
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- importable by other modules (more on that in the future).
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"""
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)
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return
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@app.cell(hide_code=True)
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def __(mo):
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mo.md(
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"""
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## 4. Running notebooks as apps
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marimo notebooks can double as apps. Click the app window icon in the
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bottom-right to see this notebook in "app view."
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Serve a notebook as an app with `marimo run` at the command-line.
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Of course, you can use marimo just to level-up your
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notebooking, without ever making apps.
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"""
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)
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return
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@app.cell(hide_code=True)
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def __(mo):
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mo.md(
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"""
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## 5. The `marimo` command-line tool
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**Creating and editing notebooks.** Use
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```
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marimo edit
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```
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in a terminal to start the marimo notebook server. From here
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you can create a new notebook or edit existing ones.
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**Running as apps.** Use
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```
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to start a webserver that serves your notebook as an app in read-only mode,
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with code cells hidden.
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**Convert a Jupyter notebook.** Convert a Jupyter notebook to a marimo
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notebook using `marimo convert`:
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```
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marimo convert your_notebook.ipynb > your_app.py
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```
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**Tutorials.** marimo comes packaged with tutorials:
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- `dataflow`: more on marimo's automatic execution
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- `ui`: how to use UI elements
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- `markdown`: how to write markdown, with interpolated values and
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LaTeX
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- `plots`: how plotting works in marimo
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- `sql`: how to use SQL
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- `layout`: layout elements in marimo
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- `fileformat`: how marimo's file format works
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- `markdown-format`: for using `.md` files in marimo
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- `for-jupyter-users`: if you are coming from Jupyter
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Start a tutorial with `marimo tutorial`; for example,
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```
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marimo tutorial dataflow
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```
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In addition to tutorials, we have examples in our
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[our GitHub repo](https://www.github.com/marimo-team/marimo/tree/main/examples).
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"""
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)
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return
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@app.cell(hide_code=True)
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def __(mo):
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mo.md(
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"""
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Here are some tips to help you get started with the marimo editor.
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"""
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@app.cell
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def __(mo,
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@app.cell
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def __(mo):
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The name "marimo" is a reference to a type of algae that, under
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the right conditions, clumps together to form a small sphere
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called a "marimo moss ball". Made of just strands of algae, these
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beloved assemblages are greater than the sum of their parts.
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"""
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return
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@app.cell(hide_code=True)
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def __():
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tips = {
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"Saving": (
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"""
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**Saving**
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- _Name_ your app using the box at the top of the screen, or
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with `Ctrl/Cmd+s`. You can also create a named app at the
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command line, e.g., `marimo edit app_name.py`.
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- _Save_ by clicking the save icon on the bottom right, or by
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inputting `Ctrl/Cmd+s`. By default marimo is configured
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to autosave.
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"""
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),
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"Running": (
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"""
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1. _Run a cell_ by clicking the play ( β· ) button on the top
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right of a cell, or by inputting `Ctrl/Cmd+Enter`.
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2. _Run a stale cell_ by clicking the yellow run button on the
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right of the cell, or by inputting `Ctrl/Cmd+Enter`. A cell is
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stale when its code has been modified but not run.
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3. _Run all stale cells_ by clicking the play ( β· ) button on
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the bottom right of the screen, or input `Ctrl/Cmd+Shift+r`.
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"""
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),
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"Console Output": (
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"""
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Console output (e.g., `print()` statements) is shown below a
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cell.
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"""
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),
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"Creating, Moving, and Deleting Cells": (
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"""
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1. _Create_ a new cell above or below a given one by clicking
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the plus button to the left of the cell, which appears on
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mouse hover.
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2. _Move_ a cell up or down by dragging on the handle to the
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right of the cell, which appears on mouse hover.
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3. _Delete_ a cell by clicking the trash bin icon. Bring it
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back by clicking the undo button on the bottom right of the
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screen, or with `Ctrl/Cmd+Shift+z`.
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),
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"Disabling Automatic Execution": (
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"""
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Via the notebook settings (gear icon) or footer panel, you
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can disable automatic execution. This is helpful when
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working with expensive notebooks or notebooks that have
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side-effects like database transactions.
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"""
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),
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"Disabling Cells": (
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"""
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You can disable a cell via the cell context menu.
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marimo will never run a disabled cell or any cells that depend on it.
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This can help prevent accidental execution of expensive computations
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when editing a notebook.
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"""
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),
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"Code Folding": (
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"""
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You can collapse or fold the code in a cell by clicking the arrow
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icons in the line number column to the left, or by using keyboard
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shortcuts.
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Use the command palette (`Ctrl/Cmd+k`) or a keyboard shortcut to
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quickly fold or unfold all cells.
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"""
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),
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"Code Formatting": (
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"""
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If you have [ruff](https://github.com/astral-sh/ruff) installed,
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you can format a cell with the keyboard shortcut `Ctrl/Cmd+b`.
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"""
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),
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"Command Palette": (
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"""
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Use `Ctrl/Cmd+k` to open the command palette.
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),
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"Keyboard Shortcuts": (
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"""
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Open the notebook menu (top-right) or input `Ctrl/Cmd+Shift+h` to
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view a list of all keyboard shortcuts.
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"""
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),
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"Configuration": (
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"""
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Configure the editor by clicking the gears icon near the top-right
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of the screen.
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-
"""
|
464 |
-
),
|
465 |
-
}
|
466 |
-
return (tips,)
|
467 |
|
468 |
|
469 |
if __name__ == "__main__":
|
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|
1 |
+
# /// script
|
2 |
+
# requires-python = ">=3.12"
|
3 |
+
# dependencies = [
|
4 |
+
# "ell-ai==0.0.13",
|
5 |
+
# "marimo",
|
6 |
+
# "openai==1.51.0",
|
7 |
+
# ]
|
8 |
+
# ///
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|
9 |
|
10 |
+
import marimo
|
11 |
|
12 |
+
__generated_with = "0.9.20"
|
13 |
+
app = marimo.App(width="medium")
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14 |
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15 |
|
16 |
@app.cell(hide_code=True)
|
17 |
+
def __():
|
18 |
+
import textwrap
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19 |
|
20 |
+
import ell
|
21 |
+
import os
|
22 |
+
import openai
|
23 |
+
import marimo as mo
|
24 |
+
return ell, mo, openai, os, textwrap
|
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25 |
|
26 |
|
27 |
@app.cell(hide_code=True)
|
28 |
def __(mo):
|
29 |
mo.md(
|
30 |
"""
|
31 |
+
# Creating a code interpreter
|
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|
32 |
|
33 |
+
This example shows how to create a code-interpreter in a few lines of code.
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|
34 |
"""
|
35 |
)
|
36 |
return
|
37 |
|
38 |
|
39 |
@app.cell(hide_code=True)
|
40 |
+
def __(mo, os):
|
41 |
+
api_key = mo.ui.text(
|
42 |
+
label="OpenAI API key",
|
43 |
+
kind="password",
|
44 |
+
value=os.environ.get("OPENAI_API_KEY", ""),
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|
45 |
)
|
46 |
+
api_key
|
47 |
+
return (api_key,)
|
48 |
|
49 |
|
50 |
@app.cell(hide_code=True)
|
51 |
+
def __(api_key, openai):
|
52 |
+
client = openai.Client(api_key=api_key.value)
|
53 |
+
model = "gpt-4-turbo"
|
54 |
+
return client, model
|
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|
55 |
|
56 |
|
57 |
@app.cell(hide_code=True)
|
58 |
+
def __():
|
59 |
+
# https://stackoverflow.com/questions/33908794/get-value-of-last-expression-in-exec-call
|
60 |
+
def exec_with_result(script, globals=None, locals=None):
|
61 |
+
"""Execute a script and return the value of the last expression"""
|
62 |
+
import ast
|
63 |
+
|
64 |
+
stmts = list(ast.iter_child_nodes(ast.parse(script)))
|
65 |
+
if not stmts:
|
66 |
+
return None
|
67 |
+
if isinstance(stmts[-1], ast.Expr):
|
68 |
+
# the last one is an expression and we will try to return the results
|
69 |
+
# so we first execute the previous statements
|
70 |
+
if len(stmts) > 1:
|
71 |
+
exec(
|
72 |
+
compile(
|
73 |
+
ast.Module(body=stmts[:-1]), filename="<ast>", mode="exec"
|
74 |
+
),
|
75 |
+
globals,
|
76 |
+
locals,
|
77 |
+
)
|
78 |
+
# then we eval the last one
|
79 |
+
return eval(
|
80 |
+
compile(
|
81 |
+
ast.Expression(body=stmts[-1].value),
|
82 |
+
filename="<ast>",
|
83 |
+
mode="eval",
|
84 |
+
),
|
85 |
+
globals,
|
86 |
+
locals,
|
87 |
)
|
88 |
+
else:
|
89 |
+
# otherwise we just execute the entire code
|
90 |
+
return exec(script, globals, locals)
|
91 |
+
return (exec_with_result,)
|
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|
92 |
|
93 |
|
94 |
@app.cell
|
95 |
+
def __(ell, exec_with_result, mo):
|
96 |
+
def code_fence(code):
|
97 |
+
return f"```python\n\n{code}\n\n```"
|
|
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|
|
|
|
98 |
|
|
|
99 |
|
100 |
+
@ell.tool()
|
101 |
+
def execute_code(code: str):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
102 |
"""
|
103 |
+
Execute python. The last line should be the result, don't use print().
|
104 |
+
Please make sure it is safe before executing.
|
|
|
105 |
"""
|
106 |
+
with mo.capture_stdout() as out:
|
107 |
+
result = exec_with_result(code)
|
108 |
+
output = out.getvalue()
|
109 |
+
results = [
|
110 |
+
"**Code**",
|
111 |
+
code_fence(code),
|
112 |
+
"**Result**",
|
113 |
+
code_fence(result if result is not None else output),
|
114 |
+
]
|
115 |
+
return mo.md("\n\n".join(results))
|
116 |
+
return code_fence, execute_code
|
117 |
|
118 |
|
119 |
@app.cell
|
120 |
+
def __(client, ell, execute_code, mo, model):
|
121 |
+
@ell.complex(model=model, tools=[execute_code], client=client)
|
122 |
+
def custom_chatbot(messages, config) -> str:
|
123 |
+
"""You are data scientist with access to writing python code."""
|
124 |
+
return [
|
125 |
+
ell.user(message.content)
|
126 |
+
if message.role == "user"
|
127 |
+
else ell.assistant(message.content)
|
128 |
+
for message in messages
|
129 |
+
]
|
130 |
+
|
131 |
+
|
132 |
+
def my_model(messages, config):
|
133 |
+
response = custom_chatbot(messages, config)
|
134 |
+
if response.tool_calls:
|
135 |
+
return response.tool_calls[0]()
|
136 |
+
return mo.md(response.text)
|
137 |
+
return custom_chatbot, my_model
|
138 |
|
139 |
|
140 |
+
@app.cell
|
141 |
+
def __(mo, my_model):
|
142 |
+
numbers = [x for x in range(1, 10)]
|
143 |
+
|
144 |
+
mo.ui.chat(
|
145 |
+
my_model,
|
146 |
+
prompts=[
|
147 |
+
"What is the square root of {{number}}?",
|
148 |
+
f"Can you sum this list using python: {numbers}",
|
149 |
+
],
|
|
|
|
|
|
|
|
|
|
|
150 |
)
|
151 |
+
return (numbers,)
|
|
|
|
|
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|
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|
|
152 |
|
153 |
|
154 |
if __name__ == "__main__":
|
requirements.txt
CHANGED
@@ -1,4 +1,6 @@
|
|
1 |
marimo
|
|
|
|
|
2 |
# Or a specific version
|
3 |
# marimo>=0.9.0
|
4 |
|
|
|
1 |
marimo
|
2 |
+
ell-ai==0.0.14
|
3 |
+
openai==1.53.0
|
4 |
# Or a specific version
|
5 |
# marimo>=0.9.0
|
6 |
|