Fix charts

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

good_ai/src/good_ai/good_ai/deploy/create_fastapi_app.py

@@ -1,9 +1,11 @@
+from pathlib import Path
 from typing import Any, Dict, List
 
 from fastapi import FastAPI, status
 from fastapi.middleware.wsgi import WSGIMiddleware
 from fastapi.openapi.docs import get_swagger_ui_html
 from fastapi.responses import RedirectResponse
+from fastapi.staticfiles import StaticFiles
 from starlette.responses import HTMLResponse
 
 from ..context import get_context
@@ -11,6 +13,8 @@ from ..helper import snake_case_to_text
 from ..metrics import create_dash_app
 from ..views import HealthCheckResponse, Query
 
+PATH = Path(__file__).parent.resolve()
+
 
 def create_fastapi_app(
     function_name: str, disable_docs: bool, disable_metrics: bool
@@ -40,6 +44,10 @@ def create_fastapi_app(
         def redirect_to_entrypoint() -> RedirectResponse:
             return RedirectResponse("/metrics")
 
+        app.mount(
+            "/assets", StaticFiles(directory=PATH / "../metrics/assets"), name="static"
+        )
+
         @app.post("/query", status_code=status.HTTP_200_OK)
         def query_metrics(query: Query) -> List[Dict[str, Any]]:
             return get_context().persistence.query(

good_ai/src/good_ai/good_ai/deploy/serve.py

@@ -2,6 +2,7 @@ from typing import Any, Callable
 
 import uvicorn
 from fastapi import FastAPI, status
+from uvicorn.config import LOGGING_CONFIG
 
 from ..tracing import TracingContext
 from ..views import Trace
@@ -32,8 +33,7 @@ def serve(
         host="0.0.0.0",
         port=5050,
         log_config={
-            "version": 1,
+            **LOGGING_CONFIG,
-            "disable_existing_loggers": False,
             "formatters": {
                 "default": {
                     "()": "good_ai.logger.CustomFormatter",
@@ -44,26 +44,5 @@ def serve(
                     "fmt": "%(asctime)s | %(levelname)8s | %(message)s",  # noqa: E501
                 },
             },
-            "handlers": {
-                "default": {
-                    "formatter": "default",
-                    "class": "logging.StreamHandler",
-                    "stream": "ext://sys.stderr",
-                },
-                "access": {
-                    "formatter": "access",
-                    "class": "logging.StreamHandler",
-                    "stream": "ext://sys.stdout",
-                },
-            },
-            "loggers": {
-                "uvicorn": {"handlers": ["default"], "level": "INFO"},
-                "uvicorn.error": {"level": "INFO"},
-                "uvicorn.access": {
-                    "handlers": ["access"],
-                    "level": "INFO",
-                    "propagate": False,
-                },
-            },
         },
     )

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

@@ -0,0 +1,3 @@
+body {
+    background-color: hotpink;
+}

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

@@ -7,6 +7,8 @@ from dash import Dash, dash_table, dcc, html
 from dash.dependencies import Input, Output
 from flask import Flask
 
+from good_ai.utilities.unique import unique
+
 from ..context import get_context
 from ..helper import snake_case_to_text
 from ..views import SortBy
@@ -15,10 +17,16 @@ from .get_filter_from_datatable import get_filter_from_datatable
 
 
 def create_dash_app(function_name: str) -> Flask:
+    flask_app = Flask(__name__)
     app = Dash(
         function_name,
         requests_pathname_prefix=get_context().metrics_path + "/",
+        server=flask_app,
         title=snake_case_to_text(function_name),
+        update_title=None,
+        external_stylesheets=[
+            "/assets/index.css",
+        ],
     )
 
     documents = get_context().persistence.get_documents()
@@ -117,8 +125,34 @@ def create_dash_app(function_name: str) -> Flask:
         )
 
         df = pd.DataFrame(rows)
-        return px.parallel_coordinates(
+        return go.Figure(
-            df, labels={c: snake_case_to_text(c) for c in df.columns}
+            go.Parcoords(
+                dimensions=[
+                    get_dimension_descriptor(df, c)
+                    for c in df.columns
+                    if not c.startswith("arg:") and c not in {"id", "created"}
+                ]
+            )
         )
 
-    return app.server
+    return flask_app
+
+
+def get_dimension_descriptor(df: pd.DataFrame, column: str) -> Dict[str, Any]:
+    dimension: Dict[str, Any] = {
+        "label": snake_case_to_text(column),
+    }
+
+    values = df[column]
+
+    try:
+        dimension["values"] = [float(v) for v in values]
+    except (TypeError, ValueError):
+        unique_values = unique(values)
+        value_mapping = {str(v): i for i, v in enumerate(unique_values)}
+
+        dimension["values"] = [value_mapping[str(v)] for v in values]
+        dimension["tickvals"] = list(value_mapping.values())
+        dimension["ticktext"] = list(value_mapping.keys())
+
+    return dimension

good_ai/src/good_ai/good_ai/views/sort_by.py

@@ -1,4 +1,5 @@
 from typing import Literal
+
 from typing_extensions import TypedDict