examples/python/diagnose-alert-anthropic.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "# AI Dev Explainer - AI is stateless\n",
    "\n",
    "This is a notebook for https://www.aiexplainer.dev/stateless\n",
    "\n",
    "View all notebooks at https://github.com/chroma-core/ai_explainer"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "## Get an API Key from Anthropic\n",
    "1. Create an account - https://console.anthropic.com/\n",
    "2. Create an API key - https://console.anthropic.com/settings/keys\n",
    "3. Replace `<your_api_key>` below"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the code\n",
    "In Colab - you can click, \"Runtime -> \"Run All\" in the topbar\n",
    "\n",
    "In VS Code - you can click \"Run All\" in the topbar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# install dependencies\n",
    "! pip install anthropic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import os\n",
    "import anthropic\n",
    "\n",
    "# Initialize the Anthropic client\n",
    "# Replace '<your_api_key>' with your actual Anthropic API key\n",
    "client = anthropic.Client(api_key='<your_api_key>')\n",
    "\n",
    "alert = \"Slow query performance detected on database-01. Average query time: 2.5 seconds\"\n",
    "\n",
    "messages = [\n",
    "    {\n",
    "        \"role\": \"user\",\n",
    "        \"content\": alert\n",
    "    }\n",
    "]\n",
    "\n",
    "response = client.messages.create(\n",
    "    system=\"You are an AI assistant monitoring database performance. When you receive an alert, gather diagnostic information and generate commands to optimize the database. Send only 1 command that I shoud run and send only the command with no comments before or after.\",\n",
    "    model=\"claude-3-5-sonnet-20240620\",\n",
    "    max_tokens=1024,\n",
    "    messages=messages\n",
    ")\n",
    "\n",
    "print(\"Diagnostic command:\")\n",
    "print(response.content[0].text)\n",
    "\n",
    "# Let's assume it asks the users to run\n",
    "# #!/bin/bash\n",
    "# # Get top CPU-consuming processes\n",
    "# ssh admin@web-server-01 \"top -b -n 1 -o %CPU | head -n 5\"\n",
    "# # Check system load average\n",
    "# ssh admin@web-server-01 \"uptime\"\n",
    "\n",
    "# Simulate running the diagnostic commands\n",
    "diagnostic_results = \"\"\"\n",
    "Top 5 slow queries:\n",
    "1. SELECT * FROM orders WHERE date > '2023-01-01' (avg time: 3.2s)\n",
    "2. SELECT customers.*, orders.* FROM customers JOIN orders ON customers.id = orders.customer_id (avg time: 2.8s)\n",
    "3. UPDATE inventory SET stock = stock - 1 WHERE product_id IN (SELECT product_id FROM order_items WHERE order_id = 12345) (avg time: 2.5s)\n",
    "4. SELECT COUNT(*) FROM log_entries WHERE timestamp > NOW() - INTERVAL 1 DAY (avg time: 2.3s)\n",
    "5. DELETE FROM expired_sessions WHERE last_activity < NOW() - INTERVAL 30 DAY (avg time: 2.1s)\n",
    "\n",
    "Current database stats:\n",
    "- Buffer pool hit ratio: 85%\n",
    "- Index usage: 70%\n",
    "- Table scans: 25% of queries\n",
    "- Temporary tables created on disk: 15% of queries\n",
    "\"\"\"\n",
    "\n",
    "# Add the diagnostic results to the messages\n",
    "messages.append({\n",
    "    \"role\": \"assistant\",\n",
    "    \"content\": response.content[0].text\n",
    "})\n",
    "messages.append({\n",
    "    \"role\": \"user\",\n",
    "    \"content\": diagnostic_results\n",
    "})\n",
    "\n",
    "# Get optimization commands from the LLM\n",
    "response = client.messages.create(\n",
    "    model=\"claude-3-5-sonnet-20240620\",\n",
    "    max_tokens=1024,\n",
    "    messages=messages\n",
    ")\n",
    "\n",
    "print(\"\\nOptimization commands:\")\n",
    "print(response.content[0].text)"
   ]
  }
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