Add Colab CLI automation and CPU validation

.github/workflows/ci.yml

@@ -0,0 +1,50 @@
+name: CPU validation
+
+on:
+  push:
+    branches: [main, agent/schema-2-diversity-refactor]
+  pull_request:
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+concurrency:
+  group: cpu-validation-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  tests:
+    runs-on: ubuntu-latest
+    timeout-minutes: 20
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python 3.12
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+          cache: pip
+
+      - name: Install project and test dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
+          python -m pip install --editable ".[test]"
+
+      - name: Run deterministic test suite
+        run: |
+          python -m pytest -q tests -m "not gpu" \
+            --cov=biasauditfw \
+            --cov-report=term-missing \
+            --cov-report=xml
+
+      - name: Upload coverage report
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-python-3.12
+          path: coverage.xml
+          if-no-files-found: error

.gitignore

@@ -219,3 +219,7 @@ __marimo__/
 
 # Local PDF review renders
 Texto_Latex/.preview/
+
+# Local Colab CLI execution artifacts and credentials
+execucao/colab/
+.colab-cli/

Framework_Auditoria_Viés_IA_Generativa.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "83776683",
+   "id": "d2e70da5cf87",
    "metadata": {},
    "source": [
     "# BiasAuditFW 2.0 — notebook oficial para Google Colab T4\n",
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bbc9085f",
+   "id": "1ca43532b6e5",
    "metadata": {},
    "source": [
     "## 1. Preparação\n",
@@ -33,16 +33,19 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a7af3e4d",
+   "id": "3f89a0bb8250",
    "metadata": {},
    "outputs": [],
    "source": [
     "from pathlib import Path\n",
+    "import os\n",
     "import subprocess\n",
     "import sys\n",
     "\n",
     "REPOSITORY_URL = \"https://github.com/Kauandugi/bias-audit-framework.git\"\n",
-    "REPOSITORY_REF = \"agent/schema-2-diversity-refactor\"\n",
+    "REPOSITORY_REF = os.getenv(\n",
+    "    \"BIASAUDIT_REPOSITORY_REF\", \"agent/schema-2-diversity-refactor\"\n",
+    ")\n",
     "REPO_DIR = Path(\"/content/bias-audit-framework\")\n",
     "\n",
     "if REPO_DIR.exists() and not (REPO_DIR / \".git\").is_dir():\n",
@@ -100,7 +103,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "510db36a",
+   "id": "d19bb8a58de0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -111,7 +114,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "46c5d394",
+   "id": "b532ba955966",
    "metadata": {},
    "source": [
     "## 2. Configuração da execução\n",
@@ -124,26 +127,51 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6d09a7ca",
+   "id": "6addcac4205b",
    "metadata": {},
    "outputs": [],
    "source": [
+    "import os\n",
     "from pathlib import Path\n",
     "\n",
-    "DATASET_ROOT = Path(\"/content/drive/MyDrive/Estudo UNAL/Images Generated by IA\")\n",
-    "OUTPUT_ROOT = Path(\"/content/drive/MyDrive/Estudo UNAL/BiasAuditFW outputs schema 2\")\n",
+    "\n",
+    "def env_flag(name: str, default: bool = False) -> bool:\n",
+    "    value = os.getenv(name)\n",
+    "    if value is None:\n",
+    "        return default\n",
+    "    return value.strip().lower() in {\"1\", \"true\", \"yes\", \"on\"}\n",
+    "\n",
+    "DATASET_ROOT = Path(\n",
+    "    os.getenv(\n",
+    "        \"BIASAUDIT_DATASET_ROOT\",\n",
+    "        \"/content/drive/MyDrive/Estudo UNAL/Images Generated by IA\",\n",
+    "    )\n",
+    ")\n",
+    "OUTPUT_ROOT = Path(\n",
+    "    os.getenv(\n",
+    "        \"BIASAUDIT_OUTPUT_ROOT\",\n",
+    "        \"/content/drive/MyDrive/Estudo UNAL/BiasAuditFW outputs schema 2\",\n",
+    "    )\n",
+    ")\n",
     "DATASET_ID = \"original-64\"\n",
     "MANIFEST_PATH = REPO_DIR / \"data\" / \"original_64_manifest.csv\"\n",
     "EXPECTED_IMAGES = 64\n",
     "\n",
-    "RUN_FULL = False\n",
-    "RUN_GROUND_TRUTH = False\n",
-    "RUN_HUMAN_BASELINE = False\n",
-    "RUN_FAIRFACE = False\n",
-    "DOWNLOAD_FAIRFACE_WEIGHTS = False\n",
+    "RUN_FULL = env_flag(\"BIASAUDIT_RUN_FULL\")\n",
+    "RUN_GROUND_TRUTH = env_flag(\"BIASAUDIT_RUN_GROUND_TRUTH\")\n",
+    "RUN_HUMAN_BASELINE = env_flag(\"BIASAUDIT_RUN_HUMAN_BASELINE\")\n",
+    "RUN_FAIRFACE = env_flag(\"BIASAUDIT_RUN_FAIRFACE\")\n",
+    "DOWNLOAD_FAIRFACE_WEIGHTS = env_flag(\"BIASAUDIT_DOWNLOAD_FAIRFACE_WEIGHTS\")\n",
     "\n",
-    "GROUND_TRUTH_COCO = Path(\"/content/drive/MyDrive/Estudo UNAL/ground_truth_consenso.json\")\n",
-    "FAIRFACE_WEIGHTS = Path(\"/content/fairface_alldata_20191111.pt\")\n",
+    "GROUND_TRUTH_COCO = Path(\n",
+    "    os.getenv(\n",
+    "        \"BIASAUDIT_GROUND_TRUTH_COCO\",\n",
+    "        \"/content/drive/MyDrive/Estudo UNAL/ground_truth_consenso.json\",\n",
+    "    )\n",
+    ")\n",
+    "FAIRFACE_WEIGHTS = Path(\n",
+    "    os.getenv(\"BIASAUDIT_FAIRFACE_WEIGHTS\", \"/content/fairface_alldata_20191111.pt\")\n",
+    ")\n",
     "HUMAN_BASELINE_URL = (\n",
     "    \"https://raw.githubusercontent.com/Kauandugi/\"\n",
     "    \"Bias-ai-university-visuals/main/data/metadada/\"\n",
@@ -154,7 +182,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "23ea24d1",
+   "id": "f3f04f228cf3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -187,7 +215,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a36e309b",
+   "id": "b8d568b5420a",
    "metadata": {},
    "source": [
     "## 3. Preflight de ingestão\n",
@@ -200,7 +228,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "edc05fc7",
+   "id": "0f1007864400",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -215,7 +243,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98f74bad",
+   "id": "927db5f91750",
    "metadata": {},
    "source": [
     "## 4. Testes determinísticos\n",
@@ -227,7 +255,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "61f348c9",
+   "id": "898d25313da2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -250,7 +278,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8210cfba",
+   "id": "edbb51d8b675",
    "metadata": {},
    "source": [
     "## 5. Carregamento único dos modelos\n",
@@ -263,7 +291,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5810e4ee",
+   "id": "0c0204f5988f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -286,7 +314,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c16e1de5",
+   "id": "1d3b5dfe776f",
    "metadata": {},
    "source": [
     "## 6. Smoke test ou corpus completo\n",
@@ -298,7 +326,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "21b1fc25",
+   "id": "b9195c788e2a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -363,7 +391,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "81256a42",
+   "id": "25a3ea5a01e9",
    "metadata": {},
    "source": [
     "## 7. Estatística no nível da imagem\n",
@@ -376,7 +404,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c7a98d52",
+   "id": "d777fe6d633d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -395,7 +423,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a3a24004",
+   "id": "644f5744bca0",
    "metadata": {},
    "source": [
     "## 8. Gráficos exploratórios"
@@ -404,7 +432,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "28571d07",
+   "id": "bb4c2ec4a5b3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -448,7 +476,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "561a14aa",
+   "id": "2395ddc88640",
    "metadata": {},
    "source": [
     "## 9. Ground Truth da detecção facial\n",
@@ -461,7 +489,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0496b012",
+   "id": "cfc7a6c0cf18",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -491,7 +519,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "16a8f822",
+   "id": "1369f0899375",
    "metadata": {},
    "source": [
     "## 10. Baseline humana\n",
@@ -504,7 +532,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b852577b",
+   "id": "d69a60bc8410",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -529,7 +557,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b8f2e956",
+   "id": "e0b7b84bc5a0",
    "metadata": {},
    "source": [
     "## 11. FairFace como pseudo-oráculo\n",
@@ -541,7 +569,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d462f231",
+   "id": "f11107867cc6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -589,7 +617,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "323036e8",
+   "id": "5423b9dfda8d",
    "metadata": {},
    "source": [
     "## 12. Validação independente dos outputs\n",
@@ -601,7 +629,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "637fe862",
+   "id": "d7046b1e31d4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -621,7 +649,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cda43b96",
+   "id": "7dd45e520f55",
    "metadata": {},
    "source": [
     "## Checklist final\n",
@@ -654,4 +682,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}