chore: address docs review feedback

Signed-off-by: Andre Manoel <amanoel@nvidia.com>

Author: andreatgretel

.github/workflows/docs-preview.yml

@@ -5,8 +5,10 @@ on:
     types: [opened, synchronize, reopened]
     paths:
       - "fern/**"
+      - "docs/assets/recipes/**"
       - "docs/notebook_source/**"
       - "docs/colab_notebooks/**"
+      - "docs/scripts/**"
       - "packages/data-designer-config/src/data_designer/config/**"
       - "packages/data-designer/src/data_designer/interface/**"
       - "packages/data-designer-engine/src/data_designer/engine/column_generators/generators/base.py"

docs/colab_notebooks/7-nemotron-personas.ipynb

@@ -26,7 +26,7 @@
     "If this is your first time using Data Designer, we recommend starting with the [first notebook](https://docs.nvidia.com/nemo/datadesigner/tutorials/the-basics) in this tutorial series.\n",
     "\n",
     "<div align=\"center\">\n",
-    "  <img src=\"https://raw.githubusercontent.com/NVIDIA-NeMo/DataDesigner/main/docs/devnotes/posts/assets/nemotron-personas/nemotron_persona_via_ndd.png\" alt=\"Nemotron Personas pipeline overview\" width=\"600\" />\n",
+    "  <img src=\"https://raw.githubusercontent.com/NVIDIA-NeMo/DataDesigner/main/fern/assets/nemotron-personas/nemotron_persona_via_ndd.png\" alt=\"Nemotron Personas pipeline overview\" width=\"600\" />\n",
     "</div>"
    ]
   },
@@ -95,7 +95,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from __future__ import annotations\n",
+                "from __future__ import annotations  # noqa: F404\n",
     "\n",
     "import json\n",
     "from pathlib import Path\n",
@@ -389,7 +389,7 @@
     "We are focusing just on the part in the diagram below and seeding persona attributes with PGM + OCEAN details:\n",
     "\n",
     "<div align=\"center\">\n",
-    "  <img src=\"https://raw.githubusercontent.com/NVIDIA-NeMo/DataDesigner/main/docs/devnotes/posts/assets/nemotron-personas/nemotron_persona_via_ndd_step_2.png\" alt=\"Stage 3: Persona attributes via structured outputs\" width=\"600\" />\n",
+    "  <img src=\"https://raw.githubusercontent.com/NVIDIA-NeMo/DataDesigner/main/fern/assets/nemotron-personas/nemotron_persona_via_ndd_step_2.png\" alt=\"Stage 3: Persona attributes via structured outputs\" width=\"600\" />\n",
     "</div>"
    ]
   },
@@ -728,7 +728,7 @@
     "Now, let's focus on the second part shown in the diagram below:\n",
     "\n",
     "<div align=\"center\">\n",
-    "  <img src=\"https://raw.githubusercontent.com/NVIDIA-NeMo/DataDesigner/main/docs/devnotes/posts/assets/nemotron-personas/nemotron_persona_via_ndd_step_3.png\" alt=\"Stage 4: Persona prose synthesis\" width=\"600\" />\n",
+    "  <img src=\"https://raw.githubusercontent.com/NVIDIA-NeMo/DataDesigner/main/fern/assets/nemotron-personas/nemotron_persona_via_ndd_step_3.png\" alt=\"Stage 4: Persona prose synthesis\" width=\"600\" />\n",
     "</div>"
    ]
   },

docs/scripts/generate_top_models_figure.py

@@ -10,11 +10,10 @@
 
 Renders the ranked input-vs-output token breakdown shown in the README's
 "Top models (YTD)" section, styled to match the Data Designer devnote charts
-(near-black canvas, NVIDIA-green duotone). The same PNG is written to both
-tracked copies so the README and Fern docs site stay in sync:
+(near-black canvas, NVIDIA-green duotone). The PNG is written to the Fern image
+path rendered by the README and docs site:
 
-    docs/images/top-models.png    (rendered by the README)
-    fern/images/top-models.png    (Fern's /images/* mirror)
+    fern/images/top-models.png
 
 The source telemetry export lives at docs/scripts/top-model-usage.csv with
 columns: model name, input (context) tokens, output (generated) tokens, plus a
@@ -35,7 +34,6 @@
 
 import argparse
 import csv
-import shutil
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -45,13 +43,8 @@
 # Repo root is two levels up from docs/scripts/.
 REPO_ROOT = Path(__file__).resolve().parents[2]
 DEFAULT_CSV = REPO_ROOT / "docs" / "scripts" / "top-model-usage.csv"
-# Tracked copies of the figure; first entry is the canonical render target.
-# docs/images/ is what the README renders; fern/images/ is Fern's mirror for
-# /images/* references.
-TARGETS = (
-    REPO_ROOT / "docs" / "images" / "top-models.png",
-    REPO_ROOT / "fern" / "images" / "top-models.png",
-)
+# Tracked figure path rendered by the README and Fern docs site.
+TARGETS = (REPO_ROOT / "fern" / "images" / "top-models.png",)
 
 # ---------------------------------------------------------------- palette ----
 BG = "#0E0E0E"  # near-black canvas (matches DD devnote charts)
@@ -270,11 +263,8 @@ def main() -> None:
     configure_matplotlib()
     rows = load_rows(args.csv)
 
-    primary, *mirrors = TARGETS
+    (primary,) = TARGETS
     render(rows, primary)
-    for mirror in mirrors:
-        mirror.parent.mkdir(parents=True, exist_ok=True)
-        shutil.copyfile(primary, mirror)
 
     for target in TARGETS:
         print(f"wrote {target.relative_to(REPO_ROOT)}")