Upload ragwiki_indexing-e5.flex.ipynb

ragwiki_indexing-e5.flex.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# E5 PyTerrier_DR Index for RAG Wikipedia Corpus\n",
+    "\n",
+    "This creates a dense index using [PyTerrier](https://github.com/terrier-org/pyterrier) and [PyTerrier_dr](https://github.com/terrierteam/pyterrier_dr) for the Wikipedia corpus used by Natural Questions and TextbookQuestionAnswering datasets.\n",
+    "\n",
+    "The corpus is downloaded from https://huggingface.co/datasets/RUC-NLPIR/FlashRAG_datasets/resolve/main/retrieval-corpus/wiki18_100w.zip by `\n",
+    "pt.get_dataset('rag:nq_wiki').get_corpus_iter()`.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pyterrier as pt\n",
+    "import pyterrier_rag\n",
+    "\n",
+    "# print pretty progress bars\n",
+    "pt.utils.set_tqdm('notebook')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ensure pyterrier_dr is installed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager, possibly rendering your system unusable.It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv. Use the --root-user-action option if you know what you are doing and want to suppress this warning.\u001b[0m\u001b[33m\n",
+      "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install -q pyterrier_dr\n",
+    "from pyterrier_dr import FlexIndex, E5"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We'll need an E5 model - this will transform the document text into document embeddings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "e5 = E5()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's setup an indexing pipeline. Documents are encoded using `e5` before being stored in the FlexIndex emebdding store. The FlexIndex can be used for retrieval later."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "53fb275a60da417daa05d5e1240ae039",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "indexing: 0dvec [00:00, ?dvec/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "index = \"./nq_tctindex.flex\"\n",
+    "index = FlexIndex(index)\n",
+    "(e5 >> index).index(pt.get_dataset('rag:nq_wiki').get_corpus_iter())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, we upload the index to Huggingface."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "adding docnos.npids [207 B]\n",
+      "adding pt_meta.json [81 B]\n",
+      "adding vecs.f4 [60.1 GB]\n",
+      "starting segment 1\n",
+      "starting segment 2\n",
+      "starting segment 3\n",
+      "starting segment 4\n",
+      "starting segment 5\n",
+      "starting segment 6\n",
+      "starting segment 7\n",
+      "starting segment 8\n",
+      "starting segment 9\n",
+      "starting segment 10\n",
+      "starting segment 11\n",
+      "starting segment 12\n",
+      "starting segment 13\n"
+     ]
+    },
+    {
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+      },
+      "text/plain": [
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+      "text/plain": [
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+     "metadata": {},
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+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Artifact uploaded to https://huggingface.co/datasets/pyterrier/ragwiki-e5.flex/tree/main/\n",
+      "Consider editing the README.md to help explain this artifact to others.\n"
+     ]
+    }
+   ],
+   "source": [
+    "e5_emb_index.to_hf('pyterrier/ragwiki-e5.flex')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:rag]",
+   "language": "python",
+   "name": "conda-env-rag-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}