Add Truth-Zeeker AI Demo Colab notebook

Download.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "M8NNCivsv-38"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -q huggingface-hub joblib pandas scikit-learn matplotlib seaborn"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from huggingface_hub import hf_hub_download\n",
+        "import joblib, os, pandas as pd\n",
+        "\n",
+        "REPO_ID = \"dr-rakshith-truth-zeeker/truth-zeeker-ai-demo\"\n",
+        "FNAME = \"model.joblib\"\n",
+        "\n",
+        "path = hf_hub_download(repo_id=REPO_ID, filename=FNAME)\n",
+        "print(\"✅ Downloaded model from Hugging Face:\", path)\n",
+        "\n",
+        "model = joblib.load(path)\n",
+        "print(\"Model loaded successfully:\", type(model))"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "4cRLizbOwmYH",
+        "outputId": "e8c03cc1-4573-4d17-95aa-73955dbafc76"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "✅ Downloaded model from Hugging Face: /root/.cache/huggingface/hub/models--dr-rakshith-truth-zeeker--truth-zeeker-ai-demo/snapshots/c53c401c56ba50cac5bb805104dfe5ecf380d022/model.joblib\n",
+            "Model loaded successfully: <class 'tuple'>\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "csv_url = \"https://raw.githubusercontent.com/dr-rakshith-truth-zeeker/Truth-Zeeker-AI/refs/heads/release/demo_data/sample_features.csv?token=GHSAT0AAAAAADNHI2OE4ZDLAJ26R6E2CJZY2HP242Q\"\n",
+        "\n",
+        "df = pd.read_csv(csv_url)\n",
+        "print(\"Loaded demo data shape:\", df.shape)\n",
+        "print(\"\\nFirst 10 rows:\\n\")\n",
+        "print(df.head(10).to_string(index=False))\n",
+        "\n",
+        "# Run inference (handle tuple (scaler, model) or plain model)\n",
+        "if isinstance(model, tuple) and len(model) == 2:\n",
+        "    scaler, clf = model\n",
+        "    Xs = scaler.transform(df[['duration','orig_bytes','resp_bytes']])\n",
+        "    preds = clf.predict(Xs)\n",
+        "else:\n",
+        "    clf = model\n",
+        "    preds = clf.predict(df[['duration','orig_bytes','resp_bytes']])\n",
+        "\n",
+        "df['anomaly_flag'] = preds\n",
+        "print(\"\\nResults with anomaly_flag:\\n\")\n",
+        "print(df.to_string(index=False))"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "4NqEdftzx-dN",
+        "outputId": "dcff4174-28dc-4ea5-b900-18575399a712"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Loaded demo data shape: (10, 3)\n",
+            "\n",
+            "First 10 rows:\n",
+            "\n",
+            " duration  orig_bytes  resp_bytes\n",
+            "     0.12         456         789\n",
+            "     0.08         123          80\n",
+            "     0.30        2000         150\n",
+            "     0.05          60           0\n",
+            "     0.90        4000        1200\n",
+            "     0.02          50          10\n",
+            "     0.20         300         400\n",
+            "     0.25        1500        1200\n",
+            "     0.15         800         200\n",
+            "     0.07          90          70\n",
+            "\n",
+            "Results with anomaly_flag:\n",
+            "\n",
+            " duration  orig_bytes  resp_bytes  anomaly_flag\n",
+            "     0.12         456         789             1\n",
+            "     0.08         123          80             1\n",
+            "     0.30        2000         150             1\n",
+            "     0.05          60           0             1\n",
+            "     0.90        4000        1200            -1\n",
+            "     0.02          50          10             1\n",
+            "     0.20         300         400             1\n",
+            "     0.25        1500        1200            -1\n",
+            "     0.15         800         200             1\n",
+            "     0.07          90          70             1\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.12/dist-packages/sklearn/utils/validation.py:2732: UserWarning: X has feature names, but StandardScaler was fitted without feature names\n",
+            "  warnings.warn(\n"
+          ]
+        }
+      ]
+    }
+  ]
+}