From 03fb3fa0e2f328912619794e111e9f7fff2ab024 Mon Sep 17 00:00:00 2001
From: MasterPhooey <106418429+MasterPhooey@users.noreply.github.com>
Date: Sun, 5 Jan 2025 18:30:22 -0600
Subject: [PATCH] Update advanced_training_notebook.ipynb

---
 advanced_training_notebook.ipynb | 62 ++++++++++----------------------
 1 file changed, 19 insertions(+), 43 deletions(-)

diff --git a/advanced_training_notebook.ipynb b/advanced_training_notebook.ipynb
index f314237..12e37ee 100644
--- a/advanced_training_notebook.ipynb
+++ b/advanced_training_notebook.ipynb
@@ -640,73 +640,49 @@
     "id": "ex_UIWvwtjAN"
    },
    "outputs": [],
-   "source": [
+    "source": [
     "import shutil\n",
     "import json\n",
-    "from http.server import HTTPServer, SimpleHTTPRequestHandler\n",
-    "import threading\n",
-    "from pathlib import Path\n",
+    "from IPython.display import FileLink\n",
     "\n",
-    "# Copy the TFLite model file to the working directory\n",
+    "# Define the source path and desired download location for the TFLite file\n",
     "source_path = \"trained_models/wakeword/tflite_stream_state_internal_quant/stream_state_internal_quant.tflite\"\n",
     "destination_path = \"./stream_state_internal_quant.tflite\"\n",
+    "\n",
+    "# Copy the TFLite file to the current working directory\n",
     "shutil.copy(source_path, destination_path)\n",
     "\n",
-    "# Define the JSON metadata for the model\n",
+    "# Define the JSON file content\n",
     "json_data = {\n",
     "    \"type\": \"micro\",\n",
-    "    \"wake_word\": \"hey_norman\",  # Adjust based on your target wake word\n",
+    "    \"wake_word\": \"khum_puter\",  # Adjust this if the target_word changes dynamically\n",
     "    \"author\": \"master phooey\",\n",
     "    \"website\": \"https://github.com/MasterPhooey/MicroWakeWord-Trainer-Docker\",\n",
     "    \"model\": \"stream_state_internal_quant.tflite\",\n",
     "    \"trained_languages\": [\"en\"],\n",
     "    \"version\": 2,\n",
     "    \"micro\": {\n",
-    "        \"probability_cutoff\": 0.97,  # Threshold for wake word detection\n",
-    "        \"sliding_window_size\": 5,  # Frames averaged for predictions\n",
+    "        \"probability_cutoff\": 0.97,\n",
+    "        \"sliding_window_size\": 5,\n",
     "        \"feature_step_size\": 10,\n",
-    "        \"tensor_arena_size\": 30000,  # Memory allocation for TensorFlow Lite model\n",
+    "        \"tensor_arena_size\": 30000,\n",
     "        \"minimum_esphome_version\": \"2024.7.0\"\n",
     "    }\n",
     "}\n",
     "\n",
-    "# Write the metadata to a JSON file\n",
+    "# Define the JSON file path\n",
     "json_path = \"./stream_state_internal_quant.json\"\n",
+    "\n",
+    "# Write the JSON file\n",
     "with open(json_path, \"w\") as json_file:\n",
     "    json.dump(json_data, json_file, indent=2)\n",
     "\n",
-    "# Custom HTTPRequestHandler to set the Content-Disposition header\n",
-    "class CustomHTTPRequestHandler(SimpleHTTPRequestHandler):\n",
-    "    def end_headers(self):\n",
-    "        if self.path.endswith(\".json\"):\n",
-    "            self.send_header(\"Content-Disposition\", \"attachment\")\n",
-    "        super().end_headers()\n",
-    "\n",
-    "# Start an HTTP server in a separate thread\n",
-    "def start_server():\n",
-    "    server = HTTPServer((\"0.0.0.0\", 8000), CustomHTTPRequestHandler)\n",
-    "    print(\"Serving files on http://localhost:8000\")\n",
-    "    server.serve_forever()\n",
-    "\n",
-    "thread = threading.Thread(target=start_server, daemon=True)\n",
-    "thread.start()\n",
-    "\n",
-    "# Generate download links with styled HTML\n",
-    "html_content = f\"\"\"\n",
-    "<div align=\\\"center\\\">,\n",
-    "<img src=\\\"https://raw.githubusercontent.com/MasterPhooey/MicroWakeWord-Trainer-Docker/refs/heads/main/mmw.png\\\" alt=\\\"MicroWakeWord Trainer Logo\\\" width=\\\"100\\\" />\\n\"\n",
-    "<h1>MicroWakeWord Trainer Docker</h1>\n",
-    "</div>\\n\n",
-    "<h3 style=\"color:orange;\">Your files are ready for download:</h3>\n",
-    "<ul>\n",
-    "    <li><b><a href=\"http://localhost:8000/stream_state_internal_quant.tflite\" target=\"_blank\" style=\"color:orange;\">TFLite Model: stream_state_internal_quant.tflite</a></b></li>\n",
-    "    <li><b><a href=\"http://localhost:8000/stream_state_internal_quant.json\" target=\"_blank\" style=\"color:orange;\">JSON Metadata: stream_state_internal_quant.json</a></b></li>\n",
-    "</ul>\n",
-    "<p style=\"font-size:12px; color:gray;\">Click the links to download the files. Ensure the files are moved to the correct directory for deployment.</p>\n",
-    "\"\"\"\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "display(HTML(html_content))"
+    "# Generate download links for both files\n",
+    "print(\"Download your files:\")\n",
+    "print(\"TFLite Model:\")\n",
+    "display(FileLink(destination_path))\n",
+    "print(\"\\nJSON Metadata:\")\n",
+    "display(FileLink(json_path))"
    ]
   }
  ],