Simplify by replacing generation code with flat data file

Author: zackproser

learn/assistant/pinecone-assistant-getting-started.ipynb

@@ -89,7 +89,7 @@
         "assistant = pc.assistant.create_assistant(\n",
         "    assistant_name=assistant_name,\n",
         "    metadata=metadata,\n",
-        "    timeout=30 # Wait 30 seconds for model creation to complete.\n",
+        "    timeout=30 # Wait 30 seconds for assistant creation to complete.\n",
         ")"
       ],
       "metadata": {
@@ -112,57 +112,17 @@
       "outputs": []
     },
     {
-      "cell_type": "code",
+      "cell_type": "markdown",
       "source": [
-        "import random\n",
-        "\n",
-        "# Function to generate a random toy title\n",
-        "def generate_toy_title():\n",
-        "    adjectives = [\"Amazing\", \"Super\", \"Fantastic\", \"Incredible\", \"Awesome\", \"Magical\", \"Ultimate\", \"Deluxe\"]\n",
-        "    nouns = [\"Robot\", \"Doll\", \"Blocks\", \"Puzzle\", \"Car\", \"Train\", \"Spaceship\", \"Dinosaur\", \"Unicorn\", \"Dragon\"]\n",
-        "    return f\"{random.choice(adjectives)} {random.choice(nouns)}\"\n",
-        "\n",
-        "# Function to generate a random toy description\n",
-        "def generate_toy_description():\n",
-        "    features = [\n",
-        "        \"Made from high-quality materials\",\n",
-        "        \"Encourages imaginative play\",\n",
-        "        \"Develops problem-solving skills\",\n",
-        "        \"Suitable for ages 3 and up\",\n",
-        "        \"Battery-operated with flashing lights\",\n",
-        "        \"Includes multiple accessories\",\n",
-        "        \"Educational and fun\",\n",
-        "        \"Easy to clean and store\",\n",
-        "        \"Durable and long-lasting\",\n",
-        "        \"Promotes hand-eye coordination\"\n",
-        "    ]\n",
-        "    return \"\\n\".join(random.sample(features, 4))\n",
-        "\n",
-        "# Generate 75 toy entries\n",
-        "toy_entries = []\n",
-        "for i in range(75):\n",
-        "    title = generate_toy_title()\n",
-        "    description = generate_toy_description()\n",
-        "    entry = f\"{title}\\n\\n{description}\\n\\n{'='*30}\\n\\n\"\n",
-        "    toy_entries.append(entry)\n",
-        "\n",
-        "# Write to a local file in Colab\n",
-        "file_path = \"/content/toy_descriptions.txt\"\n",
-        "\n",
-        "with open(file_path, 'w') as f:\n",
-        "    f.writelines(toy_entries)\n",
+        "Upload the toys.txt file from the repository to Google Colab:\n",
         "\n",
-        "print(f\"Created toy descriptions file at {file_path}\")\n",
-        "\n",
-        "# Display the first few entries as a sample\n",
-        "with open(file_path, 'r') as f:\n",
-        "    print(f.read().split('='*30)[:3])"
+        "1. Click the folder icon in Google Colab's left rail <--\n",
+        "2. Click the upload button and use the file picker to select `toys.txt` from the subdirectory of https://github.com/pinecone-io/examples that contains this notebook\n",
+        "3. Run the next cell to upload the toys.txt file to your Pinecone assistant\n"
       ],
       "metadata": {
-        "id": "uqOICQmhNZiY"
-      },
-      "execution_count": null,
-      "outputs": []
+        "id": "nIyz6gYqAbHn"
+      }
     },
     {
       "cell_type": "code",
@@ -174,6 +134,8 @@
         "    assistant_name=assistant_name,\n",
         ")\n",
         "\n",
+        "file_path = '/content/toys.txt'\n",
+        "\n",
         "# Upload the file\n",
         "if os.path.exists(file_path):\n",
         "    response = assistant.upload_file(\n",
@@ -210,7 +172,7 @@
         "# Chat with your Pinecone assistant, which automatically references\n",
         "# your uploaded documents in its responses\n",
         "from pinecone_plugins.assistant.models.chat import Message\n",
-        "chat_context = [Message(content='Which toys include Unicorn in their name?')]\n",
+        "chat_context = [Message(content='Which toys teach STEM skills?')]\n",
         "response = assistant.chat_completions(messages=chat_context)\n",
         "print(response)"
       ],