adding best batches and updated automatic link recommendation ui logic (small bug fixes)

Author: martech-engineer

initial_thoughts/automatic_led/best_batches/240_best_updated_link_graph_edges_1.csv

@@ -2,77 +2,22 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "TYL7OLjWanv_",
-    "outputId": "8e8b2e7e-37e1-4ece-a219-b34cdb6bcc79"
+    "id": "TYL7OLjWanv_"
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m63.1/63.1 kB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.8/13.8 MB\u001b[0m \u001b[31m27.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.6/24.6 MB\u001b[0m \u001b[31m32.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m883.7/883.7 kB\u001b[0m \u001b[31m20.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m2.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m12.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m7.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m81.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m62.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[?25h"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "!pip install -q torch torch-geometric pandas duckdb pyarrow networkx gradio -q"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 669
-    },
-    "id": "cAanZXMGaSGF",
-    "outputId": "7e27d6cc-6554-47ce-e675-4e40a365c9e7"
+    "id": "cAanZXMGaSGF"
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Mounted at /content/drive\n",
-      "It looks like you are running Gradio on a hosted a Jupyter notebook. For the Gradio app to work, sharing must be enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
-      "\n",
-      "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
-      "* Running on public URL: https://b69dd71c31c2a5f22c.gradio.live\n",
-      "\n",
-      "This share link expires in 1 week. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div><iframe src=\"https://b69dd71c31c2a5f22c.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import gradio as gr\n",
     "import pandas as pd\n",
@@ -93,7 +38,7 @@
     "# Add the project root to the Python path\n",
     "project_root = \"/content/drive/My Drive/WebKnoGraph\"\n",
     "if project_root not in sys.path:\n",
-    "    sys.sys.path.insert(0, project_root)\n",
+    "    sys.path.insert(0, project_root)  # Corrected: removed extra 'sys.'\n",
     "\n",
     "# --- Import Real Classes from WebKnoGraph Project ---\n",
     "try:\n",
@@ -156,9 +101,9 @@
     "            )\n",
     "            self.node_mapping_path = os.path.join(base_path, \"model_metadata.json\")\n",
     "            self.edge_index_path = os.path.join(base_path, \"edge_index.pt\")\n",
-    "            self.link_graph_edges_path = os.path.join(\n",
+    "            self.edge_csv_path = os.path.join(\n",
     "                base_path, \"link_graph_edges.csv\"\n",
-    "            )  # Dummy path\n",
+    "            )  # Corrected dummy path\n",
     "\n",
     "    # Dummy ILogger for fallback scenario\n",
     "    class ILogger:\n",
@@ -529,7 +474,7 @@
     "        results = []\n",
     "        successful_recommendations_count = 0\n",
     "\n",
-    "        # --- Generate Original Graph Edges CSV by loading from config.link_graph_edges_path ---\n",
+    "        # --- Generate Original Graph Edges CSV by loading from config.edge_csv_path ---\n",
     "        try:\n",
     "            df_original_edges = pd.read_csv(\n",
     "                config.edge_csv_path\n",