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1013{
"cells": [
{
"cell_type": "markdown",
"id": "93e325b8",
"metadata": {},
"source": [
"# Evaluating retrieval in a RAG pipeline"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "732d3c4a-ff93-4140-88e9-347bc8cf6af0",
"metadata": {
"collapsed": true,
"execution": {
"iopub.execute_input": "2024-08-04T09:34:07.914423Z",
"iopub.status.busy": "2024-08-04T09:34:07.913986Z",
"iopub.status.idle": "2024-08-04T09:34:08.921591Z",
"shell.execute_reply": "2024-08-04T09:34:08.921207Z",
"shell.execute_reply.started": "2024-08-04T09:34:07.914408Z"
},
"jupyter": {
"outputs_hidden": true
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: ranx in ./.venv/lib/python3.12/site-packages (0.3.20)\n",
"Requirement already satisfied: duckdb in ./.venv/lib/python3.12/site-packages (1.0.0)\n",
"Requirement already satisfied: rich in ./.venv/lib/python3.12/site-packages (13.7.1)\n",
"Requirement already satisfied: numpy in ./.venv/lib/python3.12/site-packages (from ranx) (2.0.1)\n",
"Requirement already satisfied: numba>=0.54.1 in ./.venv/lib/python3.12/site-packages (from ranx) (0.60.0)\n",
"Requirement already satisfied: pandas in ./.venv/lib/python3.12/site-packages (from ranx) (2.2.2)\n",
"Requirement already satisfied: tabulate in ./.venv/lib/python3.12/site-packages (from ranx) (0.9.0)\n",
"Requirement already satisfied: tqdm in ./.venv/lib/python3.12/site-packages (from ranx) (4.66.4)\n",
"Requirement already satisfied: scipy>=1.8.0 in ./.venv/lib/python3.12/site-packages (from ranx) (1.14.0)\n",
"Requirement already satisfied: ir-datasets in ./.venv/lib/python3.12/site-packages (from ranx) (0.5.8)\n",
"Requirement already satisfied: orjson in ./.venv/lib/python3.12/site-packages (from ranx) (3.10.6)\n",
"Requirement already satisfied: lz4 in ./.venv/lib/python3.12/site-packages (from ranx) (4.3.3)\n",
"Requirement already satisfied: cbor2 in ./.venv/lib/python3.12/site-packages (from ranx) (5.6.4)\n",
"Requirement already satisfied: seaborn in ./.venv/lib/python3.12/site-packages (from ranx) (0.13.2)\n",
"Requirement already satisfied: fastparquet in ./.venv/lib/python3.12/site-packages (from ranx) (2024.5.0)\n",
"Requirement already satisfied: markdown-it-py>=2.2.0 in ./.venv/lib/python3.12/site-packages (from rich) (3.0.0)\n",
"Requirement already satisfied: pygments<3.0.0,>=2.13.0 in ./.venv/lib/python3.12/site-packages (from rich) (2.18.0)\n",
"Requirement already satisfied: mdurl~=0.1 in ./.venv/lib/python3.12/site-packages (from markdown-it-py>=2.2.0->rich) (0.1.2)\n",
"Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in ./.venv/lib/python3.12/site-packages (from numba>=0.54.1->ranx) (0.43.0)\n",
"Requirement already satisfied: cramjam>=2.3 in ./.venv/lib/python3.12/site-packages (from fastparquet->ranx) (2.8.3)\n",
"Requirement already satisfied: fsspec in ./.venv/lib/python3.12/site-packages (from fastparquet->ranx) (2024.6.1)\n",
"Requirement already satisfied: packaging in ./.venv/lib/python3.12/site-packages (from fastparquet->ranx) (24.1)\n",
"Requirement already satisfied: python-dateutil>=2.8.2 in ./.venv/lib/python3.12/site-packages (from pandas->ranx) (2.9.0.post0)\n",
"Requirement already satisfied: pytz>=2020.1 in ./.venv/lib/python3.12/site-packages (from pandas->ranx) (2024.1)\n",
"Requirement already satisfied: tzdata>=2022.7 in ./.venv/lib/python3.12/site-packages (from pandas->ranx) (2024.1)\n",
"Requirement already satisfied: beautifulsoup4>=4.4.1 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (4.12.3)\n",
"Requirement already satisfied: inscriptis>=2.2.0 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (2.5.0)\n",
"Requirement already satisfied: lxml>=4.5.2 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (5.2.2)\n",
"Requirement already satisfied: pyyaml>=5.3.1 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (6.0.1)\n",
"Requirement already satisfied: requests>=2.22.0 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (2.32.3)\n",
"Requirement already satisfied: trec-car-tools>=2.5.4 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (2.6)\n",
"Requirement already satisfied: warc3-wet>=0.2.3 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (0.2.5)\n",
"Requirement already satisfied: warc3-wet-clueweb09>=0.2.5 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (0.2.5)\n",
"Requirement already satisfied: zlib-state>=0.1.3 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (0.1.6)\n",
"Requirement already satisfied: ijson>=3.1.3 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (3.3.0)\n",
"Requirement already satisfied: unlzw3>=0.2.1 in ./.venv/lib/python3.12/site-packages (from ir-datasets->ranx) (0.2.2)\n",
"Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in ./.venv/lib/python3.12/site-packages (from seaborn->ranx) (3.9.1)\n",
"Requirement already satisfied: soupsieve>1.2 in ./.venv/lib/python3.12/site-packages (from beautifulsoup4>=4.4.1->ir-datasets->ranx) (2.5)\n",
"Requirement already satisfied: contourpy>=1.0.1 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn->ranx) (1.2.1)\n",
"Requirement already satisfied: cycler>=0.10 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn->ranx) (0.12.1)\n",
"Requirement already satisfied: fonttools>=4.22.0 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn->ranx) (4.53.1)\n",
"Requirement already satisfied: kiwisolver>=1.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn->ranx) (1.4.5)\n",
"Requirement already satisfied: pillow>=8 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn->ranx) (10.4.0)\n",
"Requirement already satisfied: pyparsing>=2.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn->ranx) (3.1.2)\n",
"Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas->ranx) (1.16.0)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in ./.venv/lib/python3.12/site-packages (from requests>=2.22.0->ir-datasets->ranx) (3.3.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in ./.venv/lib/python3.12/site-packages (from requests>=2.22.0->ir-datasets->ranx) (3.7)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in ./.venv/lib/python3.12/site-packages (from requests>=2.22.0->ir-datasets->ranx) (2.2.2)\n",
"Requirement already satisfied: certifi>=2017.4.17 in ./.venv/lib/python3.12/site-packages (from requests>=2.22.0->ir-datasets->ranx) (2024.7.4)\n",
"Requirement already satisfied: cbor>=1.0.0 in ./.venv/lib/python3.12/site-packages (from trec-car-tools>=2.5.4->ir-datasets->ranx) (1.0.0)\n"
]
}
],
"source": [
"!pip install ranx duckdb rich"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "90855bc0",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:33.258028Z",
"iopub.status.busy": "2024-08-04T09:32:33.257316Z",
"iopub.status.idle": "2024-08-04T09:32:35.468073Z",
"shell.execute_reply": "2024-08-04T09:32:35.467649Z",
"shell.execute_reply.started": "2024-08-04T09:32:33.257986Z"
}
},
"outputs": [],
"source": [
"from ranx import Qrels, Run, evaluate, compare"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3a377f4b",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:35.469589Z",
"iopub.status.busy": "2024-08-04T09:32:35.469323Z",
"iopub.status.idle": "2024-08-04T09:32:35.471891Z",
"shell.execute_reply": "2024-08-04T09:32:35.471634Z",
"shell.execute_reply.started": "2024-08-04T09:32:35.469572Z"
}
},
"outputs": [],
"source": [
"qrels_dict = {\n",
" \"q_1\": { \"d_12\": 1 },\n",
" \"q_2\": { \"d_11\": 1 },\n",
" \"q_3\": { \"d_10\": 1 }\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "2e49c4de",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:35.472535Z",
"iopub.status.busy": "2024-08-04T09:32:35.472417Z",
"iopub.status.idle": "2024-08-04T09:32:36.461525Z",
"shell.execute_reply": "2024-08-04T09:32:36.461053Z",
"shell.execute_reply.started": "2024-08-04T09:32:35.472526Z"
}
},
"outputs": [],
"source": [
"qrels = Qrels(qrels_dict)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "9476d750",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:36.462478Z",
"iopub.status.busy": "2024-08-04T09:32:36.462279Z",
"iopub.status.idle": "2024-08-04T09:32:36.465379Z",
"shell.execute_reply": "2024-08-04T09:32:36.464640Z",
"shell.execute_reply.started": "2024-08-04T09:32:36.462463Z"
}
},
"outputs": [],
"source": [
"run1_dict = {\n",
" \"q_1\": { \"d_12\": 0.9, \"d_23\": 0.8, \"d_25\": 0.7 },\n",
" \"q_2\": { \"d_12\": 0.9, \"d_25\": 0.7, \"d_36\": 0.6},\n",
" \"q_3\": { \"d_10\": 1.0}\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "ffda3756",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:36.467313Z",
"iopub.status.busy": "2024-08-04T09:32:36.467106Z",
"iopub.status.idle": "2024-08-04T09:32:36.631047Z",
"shell.execute_reply": "2024-08-04T09:32:36.626035Z",
"shell.execute_reply.started": "2024-08-04T09:32:36.467301Z"
}
},
"outputs": [],
"source": [
"run1 = Run(run1_dict)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e72024ec",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:36.631760Z",
"iopub.status.busy": "2024-08-04T09:32:36.631643Z",
"iopub.status.idle": "2024-08-04T09:32:37.995353Z",
"shell.execute_reply": "2024-08-04T09:32:37.995046Z",
"shell.execute_reply.started": "2024-08-04T09:32:36.631750Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
],
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},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.6666666666666666\u001b[0m\u001b[1m)\u001b[0m"
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"metadata": {},
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}
],
"source": [
"evaluate(qrels, run1, [\"hit_rate\"])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "12e88a4c",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:37.996135Z",
"iopub.status.busy": "2024-08-04T09:32:37.995865Z",
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}
},
"outputs": [],
"source": [
"run2_dict = {\n",
" \"q_1\": { \"d_32\": 0.5, \"d_35\": 0.4},\n",
" \"q_2\": { \"d_12\": 0.9, \"d_11\": 0.8, \"d_35\": 0.4},\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "dd4eca7b",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:37.999422Z",
"iopub.status.busy": "2024-08-04T09:32:37.999257Z",
"iopub.status.idle": "2024-08-04T09:32:38.001872Z",
"shell.execute_reply": "2024-08-04T09:32:38.001512Z",
"shell.execute_reply.started": "2024-08-04T09:32:37.999412Z"
}
},
"outputs": [],
"source": [
"run2 = Run(run2_dict)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "806dedda",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:38.002479Z",
"iopub.status.busy": "2024-08-04T09:32:38.002328Z",
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"shell.execute_reply": "2024-08-04T09:32:38.182004Z",
"shell.execute_reply.started": "2024-08-04T09:32:38.002467Z"
}
},
"outputs": [
{
"ename": "AssertionError",
"evalue": "Qrels and Run query ids do not match. Pass `make_comparable=True` to add empty results for queries missing from the run and remove those not appearing in qrels.",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mqrels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrun2\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mhit_rate\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/projects/learndatawithmark/evaluate-rag/.venv/lib/python3.12/site-packages/ranx/meta/evaluate.py:135\u001b[0m, in \u001b[0;36mevaluate\u001b[0;34m(qrels, run, metrics, return_mean, return_std, threads, save_results_in_run, make_comparable)\u001b[0m\n\u001b[1;32m 132\u001b[0m run \u001b[38;5;241m=\u001b[39m run\u001b[38;5;241m.\u001b[39mmake_comparable(qrels)\n\u001b[1;32m 134\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(qrels) \u001b[38;5;129;01min\u001b[39;00m [Qrels, \u001b[38;5;28mdict\u001b[39m] \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(run) \u001b[38;5;129;01min\u001b[39;00m [Run, \u001b[38;5;28mdict\u001b[39m]:\n\u001b[0;32m--> 135\u001b[0m \u001b[43mcheck_keys\u001b[49m\u001b[43m(\u001b[49m\u001b[43mqrels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrun\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 137\u001b[0m _qrels \u001b[38;5;241m=\u001b[39m convert_qrels(qrels)\n\u001b[1;32m 138\u001b[0m _run \u001b[38;5;241m=\u001b[39m convert_run(run)\n",
"File \u001b[0;32m~/projects/learndatawithmark/evaluate-rag/.venv/lib/python3.12/site-packages/ranx/meta/evaluate.py:60\u001b[0m, in \u001b[0;36mcheck_keys\u001b[0;34m(qrels, run)\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcheck_keys\u001b[39m(qrels, run):\n\u001b[0;32m---> 60\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m (\n\u001b[1;32m 61\u001b[0m qrels\u001b[38;5;241m.\u001b[39mkeys() \u001b[38;5;241m==\u001b[39m run\u001b[38;5;241m.\u001b[39mkeys()\n\u001b[1;32m 62\u001b[0m ), \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mQrels and Run query ids do not match. Pass `make_comparable=True` to add empty results for queries missing from the run and remove those not appearing in qrels.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
"\u001b[0;31mAssertionError\u001b[0m: Qrels and Run query ids do not match. Pass `make_comparable=True` to add empty results for queries missing from the run and remove those not appearing in qrels."
]
}
],
"source": [
"evaluate(qrels, run2, [\"hit_rate\"])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "da436bbe",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:42.783537Z",
"iopub.status.busy": "2024-08-04T09:32:42.782625Z",
"iopub.status.idle": "2024-08-04T09:32:43.047268Z",
"shell.execute_reply": "2024-08-04T09:32:43.046779Z",
"shell.execute_reply.started": "2024-08-04T09:32:42.783511Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
],
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.3333333333333333\u001b[0m\u001b[1m)\u001b[0m"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"evaluate(qrels, run2, [\"hit_rate\"], make_comparable=True)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "cee355db",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:50.864509Z",
"iopub.status.busy": "2024-08-04T09:32:50.864024Z",
"iopub.status.idle": "2024-08-04T09:32:50.890873Z",
"shell.execute_reply": "2024-08-04T09:32:50.890331Z",
"shell.execute_reply.started": "2024-08-04T09:32:50.864487Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
],
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"# Model Hit Rate\n",
"--- ------- ----------\n",
"a run_1 \u001b[1;36m0.667\u001b[0m\n",
"b run_2 \u001b[1;36m0.333\u001b[0m"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"compare(\n",
" qrels,\n",
" runs=[run1, run2],\n",
" metrics=[\"hit_rate\"],\n",
")"
]
},
{
"cell_type": "markdown",
"id": "da9eb04f",
"metadata": {},
"source": [
"## Importing DuckDB database"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "52461f29",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:50.892356Z",
"iopub.status.busy": "2024-08-04T09:32:50.892143Z",
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"shell.execute_reply.started": "2024-08-04T09:32:50.892345Z"
}
},
"outputs": [],
"source": [
"import duckdb"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "53bf996b",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:51.026640Z",
"iopub.status.busy": "2024-08-04T09:32:51.026547Z",
"iopub.status.idle": "2024-08-04T09:32:51.034342Z",
"shell.execute_reply": "2024-08-04T09:32:51.033692Z",
"shell.execute_reply.started": "2024-08-04T09:32:51.026632Z"
}
},
"outputs": [],
"source": [
"con = duckdb.connect(\"evaluate_rag.duckdb\")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "bb037cd8",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:51.035363Z",
"iopub.status.busy": "2024-08-04T09:32:51.035176Z",
"iopub.status.idle": "2024-08-04T09:32:51.084865Z",
"shell.execute_reply": "2024-08-04T09:32:51.084303Z",
"shell.execute_reply.started": "2024-08-04T09:32:51.035350Z"
}
},
"outputs": [],
"source": [
"con.sql(\"INSTALL httpfs\")\n",
"con.sql(\"LOAD httpfs\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "70de973a",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:51.087027Z",
"iopub.status.busy": "2024-08-04T09:32:51.086799Z",
"iopub.status.idle": "2024-08-04T09:32:52.289854Z",
"shell.execute_reply": "2024-08-04T09:32:52.289023Z",
"shell.execute_reply.started": "2024-08-04T09:32:51.087016Z"
}
},
"outputs": [],
"source": [
"con.sql(\"\"\"\n",
"ATTACH IF NOT EXISTS\n",
"'https://raw.githubusercontent.com/mneedham/LearnDataWithMark/main/evaluate-rag/olympics.duckdb' AS olympics\n",
"\"\"\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "c40e9000",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:52.293206Z",
"iopub.status.busy": "2024-08-04T09:32:52.292743Z",
"iopub.status.idle": "2024-08-04T09:32:52.312224Z",
"shell.execute_reply": "2024-08-04T09:32:52.311252Z",
"shell.execute_reply.started": "2024-08-04T09:32:52.293185Z"
}
},
"outputs": [],
"source": [
"con.sql(\"USE olympics\")"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "bd7c3a92",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:52.314278Z",
"iopub.status.busy": "2024-08-04T09:32:52.313892Z",
"iopub.status.idle": "2024-08-04T09:32:52.339608Z",
"shell.execute_reply": "2024-08-04T09:32:52.339260Z",
"shell.execute_reply.started": "2024-08-04T09:32:52.314255Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
],
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"┌─────────────┬─────────────┬─────────┬─────────┬─────────┬─────────┐\n",
"│ column_name │ column_type │ null │ key │ default │ extra │\n",
"│ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │\n",
"├─────────────┼─────────────┼─────────┼─────────┼─────────┼─────────┤\n",
"│ index │ BIGINT │ YES │ NULL │ NULL │ NULL │\n",
"│ embeddings │ FLOAT\u001b[1m[\u001b[0m\u001b[1;36m1024\u001b[0m\u001b[1m]\u001b[0m │ YES │ NULL │ NULL │ NULL │\n",
"│ text │ VARCHAR │ YES │ NULL │ NULL │ NULL │\n",
"│ url │ VARCHAR │ YES │ NULL │ NULL │ NULL │\n",
"│ title │ VARCHAR │ YES │ NULL │ NULL │ NULL │\n",
"└─────────────┴─────────────┴─────────┴─────────┴─────────┴─────────┘"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"con.sql(\"DESCRIBE olympics\")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "1dea5f5d",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:52.340304Z",
"iopub.status.busy": "2024-08-04T09:32:52.340198Z",
"iopub.status.idle": "2024-08-04T09:32:52.407493Z",
"shell.execute_reply": "2024-08-04T09:32:52.407142Z",
"shell.execute_reply.started": "2024-08-04T09:32:52.340294Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
],
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"┌───────┬──────────────────────────────────────────────────────────────────────────────────────────────────────────────┐\n",
"│ index │ text │\n",
"│ int64 │ varchar │\n",
"├───────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
"│ \u001b[1;36m0\u001b[0m │ The \u001b[1;36m2024\u001b[0m Olympics opened in Paris in spectacular style with thousands of athletes sailing along the River … │\n",
"│ \u001b[1;36m1\u001b[0m │ Swapping a stadium for a waterway for the first time to open the \u001b[32m\"greatest show on Earth\"\u001b[0m, the near four-h… │\n",
"│ \u001b[1;36m2\u001b[0m │ Blue, white and red fireworks had raised the Tricolore above Austerlitz Bridge before \u001b[1;36m6\u001b[0m,\u001b[1;36m800\u001b[0m athletes from … │\n",
"│ \u001b[1;36m3\u001b[0m │ There were surprise performances through the ceremony, including a cabaret number from US singer-songwrite… │\n",
"│ \u001b[1;36m4\u001b[0m │ The day had started with major disruption when the French train network was hit by arson attacks and heavy… │\n",
"│ \u001b[1;36m5\u001b[0m │ The lashing rain may have forced athletes to add rain ponchos and umbrellas to their planned outfits but i… │\n",
"│ \u001b[1;36m6\u001b[0m │ The last two boats to parade - first the US as the next hosts for Los Angeles \u001b[1;36m2028\u001b[0m and then France - had t… │\n",
"│ \u001b[1;36m7\u001b[0m │ Rower Helen Glover and diver Tom Daley were Great Britain's flagbearers in Paris, which is hosting the sum… │\n",
"│ \u001b[1;36m8\u001b[0m │ In opening the 33rd summer Olympics, which are taking part against a difficult international and domestic … │\n",
"│ \u001b[1;36m9\u001b[0m │ More than \u001b[1;36m10\u001b[0m,\u001b[1;36m500\u001b[0m athletes will compete across \u001b[1;36m32\u001b[0m sports at the Games, which will close on \u001b[1;36m11\u001b[0m August. │\n",
"├───────┴──────────────────────────────────────────────────────────────────────────────────────────────────────────────┤\n",
"│ \u001b[1;36m10\u001b[0m rows \u001b[1;36m2\u001b[0m columns │\n",
"└──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"con.sql(\"SELECT index, text FROM olympics LIMIT 10\")"
]
},
{
"cell_type": "markdown",
"id": "0461b9b5",
"metadata": {},
"source": [
"## Evaluating against real questions"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "df582978",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:52.408595Z",
"iopub.status.busy": "2024-08-04T09:32:52.408321Z",
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"shell.execute_reply": "2024-08-04T09:32:53.467857Z",
"shell.execute_reply.started": "2024-08-04T09:32:52.408583Z"
}
},
"outputs": [],
"source": [
"qrels = Qrels.from_file(\"data/questions.json\")"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "dcc41ea3",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:53.469612Z",
"iopub.status.busy": "2024-08-04T09:32:53.469452Z",
"iopub.status.idle": "2024-08-04T09:32:53.581670Z",
"shell.execute_reply": "2024-08-04T09:32:53.581144Z",
"shell.execute_reply.started": "2024-08-04T09:32:53.469601Z"
}
},
"outputs": [],
"source": [
"from search import Search\n",
"s = Search(con)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "46af986c",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:53.582813Z",
"iopub.status.busy": "2024-08-04T09:32:53.582484Z",
"iopub.status.idle": "2024-08-04T09:32:53.585705Z",
"shell.execute_reply": "2024-08-04T09:32:53.585028Z",
"shell.execute_reply.started": "2024-08-04T09:32:53.582801Z"
}
},
"outputs": [],
"source": [
"functions = [\n",
" (s.fts, \"Full-Text\"), \n",
" (s.vector_search, \"Vector\"), \n",
" (s.hybrid, \"Hybrid\")\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "dc44ca9a",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:53.586898Z",
"iopub.status.busy": "2024-08-04T09:32:53.586555Z",
"iopub.status.idle": "2024-08-04T09:32:53.589969Z",
"shell.execute_reply": "2024-08-04T09:32:53.589536Z",
"shell.execute_reply.started": "2024-08-04T09:32:53.586887Z"
}
},
"outputs": [],
"source": [
"def create_run(qrels, retrieval_fn, name):\n",
" run_dict = {\n",
" question: {\n",
" str(index): score\n",
" for index, score in (retrieval_fn(question)\n",
" .select(\"index, score\")\n",
" .fetchall()\n",
" )\n",
" }\n",
" for question in qrels.to_dict()\n",
" }\n",
" return Run(run_dict, name=name)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "3cd2f834",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:32:53.590837Z",
"iopub.status.busy": "2024-08-04T09:32:53.590606Z",
"iopub.status.idle": "2024-08-04T09:33:00.896105Z",
"shell.execute_reply": "2024-08-04T09:33:00.891632Z",
"shell.execute_reply.started": "2024-08-04T09:32:53.590826Z"
}
},
"outputs": [],
"source": [
"runs = [\n",
" create_run(qrels, fn, name)\n",
" for fn, name in functions\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "78e78548",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:33:00.898793Z",
"iopub.status.busy": "2024-08-04T09:33:00.898603Z",
"iopub.status.idle": "2024-08-04T09:33:01.278889Z",
"shell.execute_reply": "2024-08-04T09:33:01.278569Z",
"shell.execute_reply.started": "2024-08-04T09:33:00.898778Z"
}
},
"outputs": [
{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"# Model Hit Rate\n",
"--- --------- ----------\n",
"a Full-Text \u001b[1;36m0.7\u001b[0m\n",
"b Vector \u001b[1;36m0.75\u001b[0m\n",
"c Hybrid \u001b[1;36m0.9\u001b[0m"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"compare(\n",
" qrels,\n",
" runs=runs,\n",
" metrics=[\"hit_rate\"],\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "ac0094eb",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:33:01.279434Z",
"iopub.status.busy": "2024-08-04T09:33:01.279349Z",
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"shell.execute_reply": "2024-08-04T09:33:01.281121Z",
"shell.execute_reply.started": "2024-08-04T09:33:01.279425Z"
}
},
"outputs": [],
"source": [
"from rich.table import Table\n",
"from rich.console import Console\n",
"c = Console()"
]
},
{
"cell_type": "markdown",
"id": "cbd83afc",
"metadata": {},
"source": [
"## Which ones did we get wrong?"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "b4179c75",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:33:01.282368Z",
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}
},
"outputs": [],
"source": [
"table = Table(title=\"Comparing Retrieval Techniques\")\n",
"table.add_column(\"Question\")\n",
"for run in runs:\n",
" table.add_column(run.name, justify=\"center\")\n",
"\n",
"cols = [col.header for col in table.columns][1:]\n",
"for question in qrels.to_dict():\n",
" row = [question]\n",
" for col in cols:\n",
" selected_run = [r for r in runs if r.name == col][0]\n",
" score = selected_run.scores['hit_rate'][question]\n",
" row.append(\"✅\" if score == 1.0 else \"❌\")\n",
" table.add_row(*row)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "2b5b380d",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:33:01.287346Z",
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"shell.execute_reply": "2024-08-04T09:33:01.296047Z",
"shell.execute_reply.started": "2024-08-04T09:33:01.287336Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[3m Comparing Retrieval Techniques \u001b[0m\n",
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mQuestion \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mFull-Text\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mVector\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mHybrid\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━┩\n",
"│ How many competitors are there? │ ❌ │ ✅ │ ✅ │\n",
"│ How many medals will be won on Saturday? │ ✅ │ ✅ │ ✅ │\n",
"│ How many times has Paris hosted the Olympic games? │ ✅ │ ✅ │ ✅ │\n",
"│ What colors were the fireworks during the ceremony? │ ✅ │ ✅ │ ✅ │\n",
"│ What started the day of the opening ceremony? │ ✅ │ ❌ │ ❌ │\n",
"│ What things went wrong? │ ❌ │ ❌ │ ❌ │\n",
"│ What was Serena's role? │ ✅ │ ✅ │ ✅ │\n",
"│ What was the weather like? │ ✅ │ ✅ │ ✅ │\n",
"│ What was unique about the location for the ceremony? │ ❌ │ ✅ │ ✅ │\n",
"│ Where are opening ceremonies usually held? │ ✅ │ ✅ │ ✅ │\n",
"│ Where are they playing the tennis? │ ✅ │ ✅ │ ✅ │\n",
"│ Where did the opening ceremony end? │ ✅ │ ❌ │ ✅ │\n",
"│ Where did the opening ceremony take place? │ ✅ │ ✅ │ ✅ │\n",
"│ Where was the last games held? │ ✅ │ ✅ │ ✅ │\n",
"│ Which number Olympics is this? │ ❌ │ ❌ │ ✅ │\n",
"│ Who did Zidane hand the flame to? │ ✅ │ ✅ │ ✅ │\n",
"│ Who is banned from the Olympics? │ ✅ │ ✅ │ ✅ │\n",
"│ Who received significant applause? │ ❌ │ ✅ │ ✅ │\n",
"│ Who was the oldest athlete? │ ❌ │ ❌ │ ✅ │\n",
"│ Why were there concerns about the Seine? │ ✅ │ ✅ │ ✅ │\n",
"└──────────────────────────────────────────────────────┴───────────┴────────┴────────┘\n"
]
},
{
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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},
"metadata": {},
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"source": [
"with c.pager(styles=True):\n",
" c.print(table)"
]
},
{
"cell_type": "markdown",
"id": "d4b023de",
"metadata": {},
"source": [
"## What wrong answers did we return?"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "bc32f40a",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-04T09:33:01.297477Z",
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"shell.execute_reply.started": "2024-08-04T09:33:01.297462Z"
}
},
"outputs": [],
"source": [
"def get_text(ids):\n",
" result = con.sql(\"\"\"SELECT text\n",
" FROM olympics \n",
" WHERE list_contains($ids::BIGINT[], index)\n",
" \"\"\", \n",
" params={\"ids\": ids}\n",
" )\n",
" return [row[0] for row in result.fetchall()]"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "8635c132",
"metadata": {
"execution": {
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}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[1mWhat started the day of the opening ceremony?\u001b[0m\n",
"\u001b[3;32mCorrect Answer\u001b[0m\n",
"\u001b[32mThe day had started with major disruption when the French train network was hit by arson attacks and heavy rain in \u001b[0m\n",
"\u001b[32mthe evening put paid to the original plan by artistic director Thomas Jolly to use the Parisian sun to \u001b[0m\u001b[32m\"make the \u001b[0m\n",
"\u001b[32mwater sparkle\"\u001b[0m\u001b[32m. \u001b[0m\n",
"\u001b[3;33mRun Answer\u001b[0m\n",
"\u001b[33mThe \u001b[0m\u001b[1;36m2024\u001b[0m\u001b[33m Olympics opened in Paris in spectacular style with thousands of athletes sailing along the River Seine \u001b[0m\n",
"\u001b[33mpast lively performers on bridges, banks and rooftops in an ambitious take on an opening ceremony. \u001b[0m\n",
"\u001b[33mGiven the miserable weather after what had been a sunny week in Paris until now, it seemed fitting that the \u001b[0m\n",
"\u001b[33mstoryline at the start of the ceremony was about the arrival of the Olympic flame in Paris not going according to \u001b[0m\n",
"\u001b[33mplan.\u001b[0m\n",
"\u001b[33mThe peace anthem, part of all Olympic opening ceremonies, is aligned with the message of unity and tolerance \u001b[0m\n",
"\u001b[33mconveyed by the Games. \u001b[0m\n",
"\n",
"\u001b[1mWhat things went wrong?\u001b[0m\n",
"\u001b[3;32mCorrect Answer\u001b[0m\n",
"\u001b[32mThe torchbearer did not get the memo about it not being in the Stade de France, and then Zinedine Zidane's metro \u001b[0m\n",
"\u001b[32mtrain broke down while he was transporting the torch.\u001b[0m\n",
"\u001b[3;33mRun Answer\u001b[0m\n",
"\u001b[33mAt times it was bizarre - one moment Lady Gaga surrounded by pink and black feathers was singing in French, the \u001b[0m\n",
"\u001b[33mnext Bangladesh's athletes were being introduced on their boat. \u001b[0m\n",
"\u001b[33mA lot of the time it was brilliantly frenetic and occasionally emotional. \u001b[0m\n",
"\u001b[33mGiven the miserable weather after what had been a sunny week in Paris until now, it seemed fitting that the \u001b[0m\n",
"\u001b[33mstoryline at the start of the ceremony was about the arrival of the Olympic flame in Paris not going according to \u001b[0m\n",
"\u001b[33mplan.\u001b[0m\n",
"\n"
]
},
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"source": [
"run = [r for r in runs if r.name == \"Hybrid\"][0]\n",
"with c.pager(styles=True):\n",
" for question, score in run.scores['hit_rate'].items():\n",
" if score == 0.0:\n",
" c.print(question, style=\"bold\")\n",
"\n",
" correct_ids = list(qrels.to_dict()[question])\n",
" c.print(\"Correct Answer\", style=\"Green italic\")\n",
" c.print(\"\\n\".join(get_text(correct_ids)), style=\"Green\")\n",
"\n",
" answer_ids = list(run.to_dict()[question]) \n",
" c.print(\"Run Answer\", style=\"Yellow italic\")\n",
" c.print(\"\\n\".join(get_text(answer_ids)) or \"None\", style=\"Yellow\")\n",
"\n",
" c.print()"
]
}
],
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