pip install transformers torch transformers serve transformers chat localhost:8000 --model-name-or-path openai/gpt-oss-20b

app.py

@@ -1,52 +1,162 @@
-from shiny import App, ui, render, reactive
-import subprocess
-
-app_ui = ui.page_sidebar(
-    ui.sidebar(
-        ui.input_action_button("install_ollama", "Install Ollama"),
-        ui.input_action_button("run_ollama", "Run GPT-OSS:20B"),
-    ),
-    ui.panel_main(
-        ui.input_text_area("user_message", "Type your message here...", height="100px"),
-        ui.input_action_button("send", "Send"),
-        ui.output_text_verbatim("chat_history"),
+import faicons as fa
+import plotly.express as px
+
+# Load data and compute static values
+from shared import app_dir, tips
+from shinywidgets import render_plotly
+
+from shiny import reactive, render
+from shiny.express import input, ui
+
+bill_rng = (min(tips.total_bill), max(tips.total_bill))
+
+# Add page title and sidebar
+ui.page_opts(title="Restaurant tipping", fillable=True)
+
+with ui.sidebar(open="desktop"):
+    ui.input_slider(
+        "total_bill",
+        "Bill amount",
+        min=bill_rng[0],
+        max=bill_rng[1],
+        value=bill_rng,
+        pre="$",
+    )
+    ui.input_checkbox_group(
+        "time",
+        "Food service",
+        ["Lunch", "Dinner"],
+        selected=["Lunch", "Dinner"],
+        inline=True,
     )
-)
-
-def server(input, output, session):
-    chat_history = reactive.Value("")
-
-    @output
-    @render.text
-    def chat_history():
-        return chat_history()
-
-    @reactive.Effect
-    @reactive.event(input.install_ollama)
-    def install_ollama():
-        try:
-            subprocess.run(["curl", "-fsSL", "https://ollama.com/install.sh", "|", "sh"], check=True, shell=True)
-            chat_history.set(chat_history() + "\nOllama installed successfully.")
-        except subprocess.CalledProcessError as e:
-            chat_history.set(chat_history() + f"\nError installing Ollama: {e}")
-
-    @reactive.Effect
-    @reactive.event(input.run_ollama)
-    def run_ollama_model():
-        try:
-            subprocess.Popen(["ollama", "run", "gpt-oss:20b"])
-            chat_history.set(chat_history() + "\nRunning GPT-OSS:20B model.")
-        except Exception as e:
-            chat_history.set(chat_history() + f"\nError running model: {e}")
-
-    @reactive.Effect
-    @reactive.event(input.send)
-    def send_message():
-        user_message = input.user_message()
-        if user_message:
-            chat_history.set(chat_history() + f"\nYou: {user_message}")
-            # Here you would typically send the message to the chat server and get a response
-            # For now, we'll just echo the message
-            chat_history.set(chat_history() + f"\nBot: {user_message}")
-
-app = App(app_ui, server)
+    ui.input_action_button("reset", "Reset filter")
+
+# Add main content
+ICONS = {
+    "user": fa.icon_svg("user", "regular"),
+    "wallet": fa.icon_svg("wallet"),
+    "currency-dollar": fa.icon_svg("dollar-sign"),
+    "ellipsis": fa.icon_svg("ellipsis"),
+}
+
+with ui.layout_columns(fill=False):
+    with ui.value_box(showcase=ICONS["user"]):
+        "Total tippers"
+
+        @render.express
+        def total_tippers():
+            tips_data().shape[0]
+
+    with ui.value_box(showcase=ICONS["wallet"]):
+        "Average tip"
+
+        @render.express
+        def average_tip():
+            d = tips_data()
+            if d.shape[0] > 0:
+                perc = d.tip / d.total_bill
+                f"{perc.mean():.1%}"
+
+    with ui.value_box(showcase=ICONS["currency-dollar"]):
+        "Average bill"
+
+        @render.express
+        def average_bill():
+            d = tips_data()
+            if d.shape[0] > 0:
+                bill = d.total_bill.mean()
+                f"${bill:.2f}"
+
+
+with ui.layout_columns(col_widths=[6, 6, 12]):
+    with ui.card(full_screen=True):
+        ui.card_header("Tips data")
+
+        @render.data_frame
+        def table():
+            return render.DataGrid(tips_data())
+
+    with ui.card(full_screen=True):
+        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
+            "Total bill vs tip"
+            with ui.popover(title="Add a color variable", placement="top"):
+                ICONS["ellipsis"]
+                ui.input_radio_buttons(
+                    "scatter_color",
+                    None,
+                    ["none", "sex", "smoker", "day", "time"],
+                    inline=True,
+                )
+
+        @render_plotly
+        def scatterplot():
+            color = input.scatter_color()
+            return px.scatter(
+                tips_data(),
+                x="total_bill",
+                y="tip",
+                color=None if color == "none" else color,
+                trendline="lowess",
+            )
+
+    with ui.card(full_screen=True):
+        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
+            "Tip percentages"
+            with ui.popover(title="Add a color variable"):
+                ICONS["ellipsis"]
+                ui.input_radio_buttons(
+                    "tip_perc_y",
+                    "Split by:",
+                    ["sex", "smoker", "day", "time"],
+                    selected="day",
+                    inline=True,
+                )
+
+        @render_plotly
+        def tip_perc():
+            from ridgeplot import ridgeplot
+
+            dat = tips_data()
+            dat["percent"] = dat.tip / dat.total_bill
+            yvar = input.tip_perc_y()
+            uvals = dat[yvar].unique()
+
+            samples = [[dat.percent[dat[yvar] == val]] for val in uvals]
+
+            plt = ridgeplot(
+                samples=samples,
+                labels=uvals,
+                bandwidth=0.01,
+                colorscale="viridis",
+                colormode="row-index",
+            )
+
+            plt.update_layout(
+                legend=dict(
+                    orientation="h", yanchor="bottom", y=1.02, xanchor="center", x=0.5
+                )
+            )
+
+            return plt
+
+
+ui.include_css(app_dir / "styles.css")
+
+# --------------------------------------------------------
+# Reactive calculations and effects
+# --------------------------------------------------------
+
+
+@reactive.calc
+def tips_data():
+    bill = input.total_bill()
+    idx1 = tips.total_bill.between(bill[0], bill[1])
+    idx2 = tips.time.isin(input.time())
+    return tips[idx1 & idx2]
+
+
+@reactive.effect
+@reactive.event(input.reset)
+def _():
+    ui.update_slider("total_bill", value=bill_rng)
+    ui.update_checkbox_group("time", selected=["Lunch", "Dinner"])