remove: notebook

test.ipynb

@@ -1,209 +0,0 @@
-{
- "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\">&lt;</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\">&gt;</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
-}