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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import rich\n",
"import weave\n",
"from dotenv import load_dotenv\n",
"\n",
"from medrag_multi_modal.retrieval import BM25sRetriever"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Logged in as Weights & Biases user: geekyrakshit.\n",
"View Weave data at https://wandb.ai/ml-colabs/medrag-multi-modal/weave\n"
]
},
{
"data": {
"text/plain": [
"<weave.trace.weave_client.WeaveClient at 0x31bb4b200>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"load_dotenv()\n",
"weave.init(project_name=\"ml-colabs/medrag-multi-modal\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: 7 of 7 files downloaded. \n"
]
}
],
"source": [
"retriever = BM25sRetriever.from_wandb_artifact(\n",
" index_artifact_address=\"ml-colabs/medrag-multi-modal/grays-anatomy-bm25s:v2\"\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "6247f921c889469283505348967807da",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Split strings: 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "0ccb25cf58c84023846d68561962adc5",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Stem Tokens: 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d2eddb186fac447d8e7dc8f185ce7c86",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"BM25S Retrieve: 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"results = retriever.retrieve(query=\"What are Ribosomes?\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"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\"><span style=\"font-weight: bold\"><</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">class</span><span style=\"color: #000000; text-decoration-color: #000000\"> </span><span style=\"color: #008000; text-decoration-color: #008000\">'dict'</span><span style=\"font-weight: bold\">></span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'dict'\u001b[0m\u001b[1m>\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"rich.print(list(list(results['results'])[0])[0])"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[0.4504720866680145, 0.3982057571411133]"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"results[\"scores\"].flatten().tolist()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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