UX improvements

Signed-off-by: András Schmelczer <andras@schmelczer.dev>

good_ai/src/good_ai/good_ai/helper/__init__.py

@@ -1,2 +1,3 @@
 from .get_args import get_args
 from .snake_case_to_text import snake_case_to_text
+from .text_to_hex_color import text_to_hex_color

good_ai/src/good_ai/good_ai/helper/text_to_hex_color.py

@@ -0,0 +1,13 @@
+import colorsys
+from hashlib import md5
+
+
+def text_to_hex_color(text: str) -> str:
+    ascii_bytes = text.encode("ascii")
+    digest = md5(
+        ascii_bytes
+    ).hexdigest()  # the built-in hash function is salted differently in each process
+    integer = int(digest, 16)
+    hue = integer % 6311 / 6311.0
+    rgb = colorsys.hsv_to_rgb(hue, 0.75, 0.6)
+    return "#" + "".join("%02X" % round(i * 255) for i in rgb)

good_ai/src/good_ai/good_ai/metrics/assets/index.css

@@ -1,3 +1,112 @@
-body {
-    background-color: hotpink;
+:root {
+  --accent-color: #47c2d0;
+  --error-color: #a30808;
+  --background-color: #edf5f6;
+  --small-padding: 10px;
+  --medium-padding: 20px;
+  --large-padding: 40px;
+  --border-radius: 10px;
+  --shadow: 0 4px 6px -1px rgb(0 0 0 / 10%), 0 2px 4px -1px rgb(0 0 0 / 6%);
+}
+
+* {
+  margin: 0;
+  box-sizing: border-box;
+}
+
+body {
+  background-color: var(--background-color);
+  font-family: Arial, Helvetica, sans-serif;
+}
+
+h1,
+h2,
+h3,
+h4,
+h5,
+h6 {
+  margin: var(--medium-padding) 0 var(--small-padding) 0;
+}
+
+.glance,
+.table-container,
+.parallel-coords {
+  padding: var(--large-padding);
+  margin: var(--large-padding);
+  border-radius: var(--border-radius);
+  box-shadow: var(--shadow);
+  background-color: white;
+  overflow: hidden;
+}
+
+.glance {
+  display: flex;
+}
+
+.glance .description {
+  width: 350px;
+  display: flex;
+  flex-direction: column;
+  justify-content: center;
+}
+
+.glance .dash-graph {
+  flex: 1;
+}
+
+.table-container {
+  padding: 0;
+}
+
+.table-container h2 {
+  padding: var(--small-padding);
+  margin: 0;
+}
+
+.table-container h2,
+footer.watermark {
+  opacity: 0.35;
+}
+
+.dash-spreadsheet {
+  overflow: auto;
+}
+
+th,
+td {
+  max-width: 350px;
+}
+
+.parallel-coords {
+  padding: 0;
+}
+
+footer.watermark {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  padding: var(--large-padding);
+  background-color: #ddd;
+  position: relative;
+}
+
+footer.watermark div {
+  display: flex;
+  flex-direction: column;
+}
+
+h6 {
+  font-size: 3rem;
+  margin-top: 0;
+}
+
+a img {
+  width: 64px;
+  height: 64px;
+  cursor: pointer;
+  transition: transform 300ms;
+}
+
+a img:hover {
+  transform: scale(1.1);
 }

good_ai/src/good_ai/good_ai/metrics/create_dash_app.py

@@ -10,13 +10,16 @@ from flask import Flask
 from good_ai.utilities.unique import unique
 
 from ..context import get_context
-from ..helper import snake_case_to_text
+from ..helper import snake_case_to_text, text_to_hex_color
 from ..views import SortBy
 from .get_description import get_description
 from .get_filter_from_datatable import get_filter_from_datatable
+from .get_footer import get_footer
 
 
 def create_dash_app(function_name: str) -> Flask:
+    accent_color = text_to_hex_color(function_name)
+
     flask_app = Flask(__name__)
     app = Dash(
         function_name,
@@ -32,24 +35,37 @@ def create_dash_app(function_name: str) -> Flask:
     documents = get_context().persistence.get_documents()
     df = pd.DataFrame(documents)
 
+    execution_time_histogram = dcc.Graph(config={"displaylogo": False})
+    table = dash_table.DataTable(
+        columns=[{"name": i, "id": i} for i in df.columns],
+        page_current=0,
+        page_size=20,
+        page_action="custom",
+        filter_action="custom",
+        filter_query="",
+        sort_action="custom",
+        sort_mode="multi",
+        sort_by=[
+            {"column_id": "created", "direction": "desc"},
+        ],
+    )
+
     app.layout = html.Div(
         [
-            get_description(function_name),
             html.Div(
-                table := dash_table.DataTable(
-                    columns=[{"name": i, "id": i} for i in df.columns],
-                    page_current=0,
-                    page_size=20,
-                    page_action="custom",
-                    filter_action="custom",
-                    filter_query="",
-                    sort_action="custom",
-                    sort_mode="multi",
-                    sort_by=[],
-                ),
+                [
+                    get_description(
+                        function_name=function_name, accent_color=accent_color
+                    ),
+                    execution_time_histogram,
+                ],
+                className="glance",
             ),
-            execution_time_histogram := dcc.Graph(),
-            parallel_coords := dcc.Graph(),
+            html.Div([html.H2("Latest traces"), table], className="table-container"),
+            parallel_coords := dcc.Graph(
+                className="parallel-coords", config={"displaylogo": False}
+            ),
+            get_footer(),
             interval := dcc.Interval(
                 interval=4 * 1000,  # in milliseconds
                 n_intervals=0,
@@ -100,15 +116,23 @@ def create_dash_app(function_name: str) -> Flask:
         )
         df = pd.DataFrame(rows)
 
-        return px.histogram(
+        fig = px.histogram(
             df,
             x="execution_time_ms",
             labels={"execution_time_ms": "Execution time (ms)"},
             nbins=20,
-            title="Execution times",
+            height=400,
             log_y=True,
+            color_discrete_sequence=[accent_color],
         )
 
+        fig.update_layout(
+            autosize=True,
+            margin=dict(l=0, r=0, b=0, t=0, pad=0),
+        )
+
+        return fig
+
     @app.callback(
         Output(parallel_coords, "figure"),
         Input(table, "filter_query"),
@@ -131,7 +155,8 @@ def create_dash_app(function_name: str) -> Flask:
                     get_dimension_descriptor(df, c)
                     for c in df.columns
                     if not c.startswith("arg:") and c not in {"id", "created"}
-                ]
+                ],
+                line_color=accent_color,
             )
         )
 

good_ai/src/good_ai/good_ai/metrics/get_description.py

@@ -1,12 +1,11 @@
-from dash.dcc import Markdown
+from dash import dcc, html
 
 from ..helper import snake_case_to_text
 
 
-def get_description(function_name: str) -> Markdown:
+def get_description(function_name: str, accent_color: str) -> html.Div:
     markdown_text = f"""
-    # {snake_case_to_text(function_name)} - metrics
-    > A human-friendly framework for robust end-to-end AI deployments
+    View the live data of your deployments here.
 
     ## Using the API
 
@@ -14,7 +13,15 @@ def get_description(function_name: str) -> Markdown:
 
     ## Metrics
 
-    The recent traces and aggregated metrics are presented below.
+    Recent traces and aggregated metrics are presented below. Try filtering the table.
     """
 
-    return Markdown(markdown_text)
+    return html.Div(
+        [
+            html.H1(
+                f"{snake_case_to_text(function_name)} - metrics",
+                style={"color": accent_color},
+            ),
+            dcc.Markdown(markdown_text, className="description"),
+        ]
+    )

good_ai/src/good_ai/good_ai/metrics/get_footer.py

@@ -0,0 +1,22 @@
+from dash import html
+
+
+def get_footer() -> html.Footer:
+    return html.Footer(
+        [
+            html.Div(
+                [
+                    html.H6("GoodAI"),
+                    html.P(
+                        "A human-friendly framework for robust end-to-end AI deployments."
+                    ),
+                ]
+            ),
+            html.A(
+                html.Img(src="/assets/github.png"),
+                href="https://github.com/ScoutinScience/good-ai",
+                target="_blank",
+            ),
+        ],
+        className="watermark",
+    )

good_ai/src/good_ai/good_ai/views/query.py

@@ -11,3 +11,17 @@ class Query(BaseModel):
     sort: List[SortBy] = []
     skip: int = 0
     take: int = 100
+
+    class Config:
+        schema_extra = {
+            "example": {
+                "filter": [
+                    {"property": "execution_time_ms", "operator": ">", "value": 100}
+                ],
+                "sort": [
+                    {"column_id": "execution_time_ms", "direction": "asc"},
+                    {"column_id": "id", "direction": "desc"},
+                ],
+                "take": 10,
+            }
+        }