After testing on AWS SageMaker Studio

Author: hammerhead

topic/chatbot/table-augmented-generation/aws/cratedb_tag_inline_agent.ipynb

@@ -232,7 +232,7 @@
     "# --- Configuration ---\n",
     "num_machines = 10  # Number of machines to simulate\n",
     "days = 30  # Number of days to simulate\n",
-    "freq_minutes = 10  # Frequency of readings (in minutes)\n",
+    "freq_minutes = 15  # Frequency of readings (in minutes)\n",
     "\n",
     "\n",
     "# --- Data Generation ---\n",
@@ -548,7 +548,7 @@
     "question = \"What was the average rotation for machine 3 the last week?\"\n",
     "# question = \"When was the last recorded anomaly?\"\n",
     "# question = \"How many readings had a vibration greater than 1.5?\"\n",
-    "# question = \"What was the number of anomalies per machine in last 48 hours?\"\n",
+    "# question = \"What was the number of anomalies per machine in the last 48 hours?\"\n",
     "\n",
     "# Convert to SQL\n",
     "sql_query = get_sql_from_llm(question)\n",
@@ -723,7 +723,7 @@
     "    \"\"\"\n",
     "    Due to a technicality, we need to translate between two different types of connection URLs.\n",
     "    pandas was using a SQLAlchemy-style connection URL (crate://...),\n",
-    "    while the MCP server uses an standard HTTP URL with basic auth.\n",
+    "    while the MCP server uses a standard HTTP URL with basic auth.\n",
     "    \"\"\"\n",
     "\n",
     "    parsed = parse.urlparse(connection_string)\n",
@@ -749,7 +749,7 @@
     "        server_params=StdioServerParameters(\n",
     "            # The MCP server is a Python script that we installed earlier as part of `pip install`.\n",
     "            # It got placed in the `bin` directory of our virtual environment.\n",
-    "            command=f\"{os.environ['VIRTUAL_ENV']}/bin/cratedb-mcp\",\n",
+    "            command=\"cratedb-mcp\",\n",
     "            args=[\"serve\"],\n",
     "            env={\n",
     "                \"CRATEDB_CLUSTER_URL\": sqlalchemy_to_http(CONNECTION_STRING),\n",
@@ -759,7 +759,7 @@
     "    )\n",
     "\n",
     "    # The action group containing our MCP server.\n",
-    "    # Other type of actions may be OpenAPI schemas or Python methods.\n",
+    "    # Other types of actions may be OpenAPI schemas or Python methods.\n",
     "    # https://docs.aws.amazon.com/bedrock/latest/userguide/action-define.html\n",
     "    #\n",
     "    # We stick to only CrateDB here for the sake of the workshop,\n",
@@ -772,17 +772,17 @@
     "    return await InlineAgent(\n",
     "        foundation_model=\"eu.amazon.nova-lite-v1:0\",\n",
     "        instruction=f\"\"\"\n",
-    "            You are a friendly assistant that receives information from CrateDB.\n",
+    "            You are a friendly assistant who receives information from CrateDB.\n",
     "            Your task is to translate questions into SQL queries, run them on CrateDB, and return back results.\n",
     "            Try to generate SQL queries based on the known data model and don't ask questions back.\n",
     "\n",
     "            You have the following tools available:\n",
     "            1. `query_sql`: Executes SQL queries on CrateDB\n",
     "            2. `get_cratedb_documentation`: Returns the table of contents for the CrateDB documentation. If in doubt about CrateDB-specific syntax, you can obtain the documentation here.\n",
-    "            3. `fetch_cratedb_docs`: One a specific link within the CrateDB documentation is identified, you can download its content here by providing the link.\n",
+    "            3. `fetch_cratedb_docs`: Once a specific link within the CrateDB documentation is identified, you can download its content here by providing the link.\n",
     "            4. `get_table_metadata`: This returns all metadata for tables in CrateDB.\n",
     "\n",
-    "            Try to reason and give an interpretation about the result.\n",
+    "            Try to reason and give an interpretation of the result.\n",
     "\n",
     "            When asked about manuals, query the `manual` column of the `machine_manuals` table to retrieve the manual. Interpret its content to provide an answer.\n",
     "\n",
@@ -814,7 +814,7 @@
     "# fmt: off\n",
     "question = \"Is any of my machines behaving significantly different compared to others? I'm interested in vibration from motor_readings.\"\n",
     "# question = \"Did the vibration of machine 4 change between today and yesterday? Query the table motor_readings.\"\n",
-    "# question = \"How recent is my data in motor_readings? Is there any machine which lacks behind?\"\n",
+    "# question = \"How recent is my data in motor_readings? Is there any machine that lacks behind?\"\n",
     "# question = \"What was the highest temperature ever observed over all machines? Apply DATE_TRUNC to generate a weekly overview and include the week in your reply. The week is returned as a timestamp in millisecond, format it in a human-readable way.\"\n",
     "# fmt: on\n",
     "\n",
@@ -1017,9 +1017,9 @@
    "outputs": [],
    "source": [
     "# fmt: off\n",
-    "question = \"Show me the maintenance steps for machine 5.\"\n",
+    "question = \"Show me the maintenance schedule for machine 5. Retrieve the manual column from the machine_manuals table and extract the maintenance schedule from its content.\"\n",
     "# question = \"Is machine 4 overheating?\"\n",
-    "# question = \"Give me the max and min vibration observed for machine 6 when rotations > 1600\"\n",
+    "# question = \"Give me the max and min vibration observed for machine 6 when rotations > 1600. Rotations are stored in the rotations column.\"\n",
     "# question = \"What should I do if machine 2 has an anomaly?\"\n",
     "# question = \"What can be a reason for higher than usual values for the column vibration in motor_readings for machine 2?\"\n",
     "# question = \"Is machine 5's most recent temperature still ok according to the manual? Look up the most recent temperature from motor_readings.\"\n",