RAG_Application.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setting up the Environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Requirement already satisfied: tzdata>=2022.7 in /home/codespace/.local/lib/python3.12/site-packages (from pandas->llama-index-legacy<0.10.0,>=0.9.48->llama-index) (2024.1)\n",
      "Requirement already satisfied: packaging>=17.0 in /home/codespace/.local/lib/python3.12/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses-json->llama-index-core<0.12.0,>=0.11.8->llama-index) (24.1)\n",
      "Requirement already satisfied: six>=1.5 in /home/codespace/.local/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas->llama-index-legacy<0.10.0,>=0.9.48->llama-index) (1.16.0)\n"
     ]
    }
   ],
   "source": [
    "! pip install -U llama-index clickhouse-connect llama-index-postprocessor-jinaai-rerank llama-index-vector-stores-myscale"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Establishing a Connection with the Knowledge Base"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import clickhouse_connect\n",
    "\n",
    "client = clickhouse_connect.get_client(\n",
    "    host='msc-735c084e.us-east-1.aws.myscale.com',\n",
    "    port=443,\n",
    "    username='simran_org_default',\n",
    "    password='passwd_Nzofxs2KmPafOe'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Downloading and Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core import VectorStoreIndex, SimpleDirectoryReader\n",
    "import requests\n",
    "\n",
    "url = 'https://niketeam-asset-download.nike.net/catalogs/2024/2024_Nike%20Kids_02_09_24.pdf?cb=09302022'\n",
    "# response = requests.get(url)\n",
    "\n",
    "with open('Nike_Catalog.pdf', 'wb') as f:\n",
    "   f.write(response.content)\n",
    "\n",
    "reader = SimpleDirectoryReader(input_files=[\"Nike_Catalog.pdf\"])\n",
    "documents = reader.load_data()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Categorizing the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def analyze_and_assign_category(text):\n",
    "   if \"football\" in text.lower():\n",
    "       return \"Football\"\n",
    "   elif \"basketball\" in text.lower():\n",
    "       return \"Basketball\"\n",
    "   elif \"running\" in text.lower():\n",
    "       return \"Running\"\n",
    "   else:\n",
    "       return \"Uncategorized\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating an index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Retrying llama_index.embeddings.openai.base.get_embeddings in 0.7657967660909984 seconds as it raised RateLimitError: Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}.\n"
     ]
    },
    {
     "ename": "RateLimitError",
     "evalue": "Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRateLimitError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[13], line 10\u001b[0m\n\u001b[1;32m      8\u001b[0m vector_store \u001b[38;5;241m=\u001b[39m MyScaleVectorStore(myscale_client\u001b[38;5;241m=\u001b[39mclient)\n\u001b[1;32m      9\u001b[0m storage_context \u001b[38;5;241m=\u001b[39m StorageContext\u001b[38;5;241m.\u001b[39mfrom_defaults(vector_store\u001b[38;5;241m=\u001b[39mvector_store)\n\u001b[0;32m---> 10\u001b[0m index \u001b[38;5;241m=\u001b[39m \u001b[43mVectorStoreIndex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_documents\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdocuments\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstorage_context\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_context\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/base.py:119\u001b[0m, in \u001b[0;36mBaseIndex.from_documents\u001b[0;34m(cls, documents, storage_context, show_progress, callback_manager, transformations, **kwargs)\u001b[0m\n\u001b[1;32m    110\u001b[0m     docstore\u001b[38;5;241m.\u001b[39mset_document_hash(doc\u001b[38;5;241m.\u001b[39mget_doc_id(), doc\u001b[38;5;241m.\u001b[39mhash)\n\u001b[1;32m    112\u001b[0m nodes \u001b[38;5;241m=\u001b[39m run_transformations(\n\u001b[1;32m    113\u001b[0m     documents,  \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m    114\u001b[0m     transformations,\n\u001b[1;32m    115\u001b[0m     show_progress\u001b[38;5;241m=\u001b[39mshow_progress,\n\u001b[1;32m    116\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m    117\u001b[0m )\n\u001b[0;32m--> 119\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m    120\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnodes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnodes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    121\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_context\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_context\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    122\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallback_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    123\u001b[0m \u001b[43m    \u001b[49m\u001b[43mshow_progress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mshow_progress\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    124\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtransformations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtransformations\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    125\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    126\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/vector_store/base.py:75\u001b[0m, in \u001b[0;36mVectorStoreIndex.__init__\u001b[0;34m(self, nodes, use_async, store_nodes_override, embed_model, insert_batch_size, objects, index_struct, storage_context, callback_manager, transformations, show_progress, **kwargs)\u001b[0m\n\u001b[1;32m     68\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_embed_model \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m     69\u001b[0m     resolve_embed_model(embed_model, callback_manager\u001b[38;5;241m=\u001b[39mcallback_manager)\n\u001b[1;32m     70\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m embed_model\n\u001b[1;32m     71\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m Settings\u001b[38;5;241m.\u001b[39membed_model\n\u001b[1;32m     72\u001b[0m )\n\u001b[1;32m     74\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_insert_batch_size \u001b[38;5;241m=\u001b[39m insert_batch_size\n\u001b[0;32m---> 75\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m     76\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnodes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnodes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     77\u001b[0m \u001b[43m    \u001b[49m\u001b[43mindex_struct\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindex_struct\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     78\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_context\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_context\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     79\u001b[0m \u001b[43m    \u001b[49m\u001b[43mshow_progress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mshow_progress\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     80\u001b[0m \u001b[43m    \u001b[49m\u001b[43mobjects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mobjects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     81\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallback_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     82\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtransformations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtransformations\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     83\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     84\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/base.py:77\u001b[0m, in \u001b[0;36mBaseIndex.__init__\u001b[0;34m(self, nodes, objects, index_struct, storage_context, callback_manager, transformations, show_progress, **kwargs)\u001b[0m\n\u001b[1;32m     75\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m index_struct \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m     76\u001b[0m     nodes \u001b[38;5;241m=\u001b[39m nodes \u001b[38;5;129;01mor\u001b[39;00m []\n\u001b[0;32m---> 77\u001b[0m     index_struct \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_index_from_nodes\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     78\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnodes\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mobjects\u001b[49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m     79\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m     80\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     81\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_index_struct \u001b[38;5;241m=\u001b[39m index_struct\n\u001b[1;32m     82\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_storage_context\u001b[38;5;241m.\u001b[39mindex_store\u001b[38;5;241m.\u001b[39madd_index_struct(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_index_struct)\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/vector_store/base.py:307\u001b[0m, in \u001b[0;36mVectorStoreIndex.build_index_from_nodes\u001b[0;34m(self, nodes, **insert_kwargs)\u001b[0m\n\u001b[1;32m    299\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28many\u001b[39m(\n\u001b[1;32m    300\u001b[0m     node\u001b[38;5;241m.\u001b[39mget_content(metadata_mode\u001b[38;5;241m=\u001b[39mMetadataMode\u001b[38;5;241m.\u001b[39mEMBED) \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m node \u001b[38;5;129;01min\u001b[39;00m nodes\n\u001b[1;32m    301\u001b[0m ):\n\u001b[1;32m    302\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    303\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot build index from nodes with no content. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    304\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPlease ensure all nodes have content.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    305\u001b[0m     )\n\u001b[0;32m--> 307\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_build_index_from_nodes\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnodes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minsert_kwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/vector_store/base.py:278\u001b[0m, in \u001b[0;36mVectorStoreIndex._build_index_from_nodes\u001b[0;34m(self, nodes, **insert_kwargs)\u001b[0m\n\u001b[1;32m    276\u001b[0m     run_async_tasks(tasks)\n\u001b[1;32m    277\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 278\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_add_nodes_to_index\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    279\u001b[0m \u001b[43m        \u001b[49m\u001b[43mindex_struct\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    280\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnodes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    281\u001b[0m \u001b[43m        \u001b[49m\u001b[43mshow_progress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_show_progress\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    282\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minsert_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    283\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m index_struct\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/vector_store/base.py:231\u001b[0m, in \u001b[0;36mVectorStoreIndex._add_nodes_to_index\u001b[0;34m(self, index_struct, nodes, show_progress, **insert_kwargs)\u001b[0m\n\u001b[1;32m    228\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m    230\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m nodes_batch \u001b[38;5;129;01min\u001b[39;00m iter_batch(nodes, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_insert_batch_size):\n\u001b[0;32m--> 231\u001b[0m     nodes_batch \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_node_with_embedding\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnodes_batch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshow_progress\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    232\u001b[0m     new_ids \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_vector_store\u001b[38;5;241m.\u001b[39madd(nodes_batch, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39minsert_kwargs)\n\u001b[1;32m    234\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_vector_store\u001b[38;5;241m.\u001b[39mstores_text \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_store_nodes_override:\n\u001b[1;32m    235\u001b[0m         \u001b[38;5;66;03m# NOTE: if the vector store doesn't store text,\u001b[39;00m\n\u001b[1;32m    236\u001b[0m         \u001b[38;5;66;03m# we need to add the nodes to the index struct and document store\u001b[39;00m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/vector_store/base.py:138\u001b[0m, in \u001b[0;36mVectorStoreIndex._get_node_with_embedding\u001b[0;34m(self, nodes, show_progress)\u001b[0m\n\u001b[1;32m    126\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_get_node_with_embedding\u001b[39m(\n\u001b[1;32m    127\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    128\u001b[0m     nodes: Sequence[BaseNode],\n\u001b[1;32m    129\u001b[0m     show_progress: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m    130\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m List[BaseNode]:\n\u001b[1;32m    131\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    132\u001b[0m \u001b[38;5;124;03m    Get tuples of id, node, and embedding.\u001b[39;00m\n\u001b[1;32m    133\u001b[0m \n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    136\u001b[0m \n\u001b[1;32m    137\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 138\u001b[0m     id_to_embed_map \u001b[38;5;241m=\u001b[39m \u001b[43membed_nodes\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    139\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnodes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_embed_model\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshow_progress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mshow_progress\u001b[49m\n\u001b[1;32m    140\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    142\u001b[0m     results \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m    143\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m node \u001b[38;5;129;01min\u001b[39;00m nodes:\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/indices/utils.py:138\u001b[0m, in \u001b[0;36membed_nodes\u001b[0;34m(nodes, embed_model, show_progress)\u001b[0m\n\u001b[1;32m    135\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    136\u001b[0m         id_to_embed_map[node\u001b[38;5;241m.\u001b[39mnode_id] \u001b[38;5;241m=\u001b[39m node\u001b[38;5;241m.\u001b[39membedding\n\u001b[0;32m--> 138\u001b[0m new_embeddings \u001b[38;5;241m=\u001b[39m \u001b[43membed_model\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_text_embedding_batch\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    139\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtexts_to_embed\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshow_progress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mshow_progress\u001b[49m\n\u001b[1;32m    140\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    142\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m new_id, text_embedding \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(ids_to_embed, new_embeddings):\n\u001b[1;32m    143\u001b[0m     id_to_embed_map[new_id] \u001b[38;5;241m=\u001b[39m text_embedding\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/instrumentation/dispatcher.py:265\u001b[0m, in \u001b[0;36mDispatcher.span.<locals>.wrapper\u001b[0;34m(func, instance, args, kwargs)\u001b[0m\n\u001b[1;32m    257\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mspan_enter(\n\u001b[1;32m    258\u001b[0m     id_\u001b[38;5;241m=\u001b[39mid_,\n\u001b[1;32m    259\u001b[0m     bound_args\u001b[38;5;241m=\u001b[39mbound_args,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    262\u001b[0m     tags\u001b[38;5;241m=\u001b[39mtags,\n\u001b[1;32m    263\u001b[0m )\n\u001b[1;32m    264\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 265\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    266\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    267\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mevent(SpanDropEvent(span_id\u001b[38;5;241m=\u001b[39mid_, err_str\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mstr\u001b[39m(e)))\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/core/base/embeddings/base.py:335\u001b[0m, in \u001b[0;36mBaseEmbedding.get_text_embedding_batch\u001b[0;34m(self, texts, show_progress, **kwargs)\u001b[0m\n\u001b[1;32m    326\u001b[0m dispatcher\u001b[38;5;241m.\u001b[39mevent(\n\u001b[1;32m    327\u001b[0m     EmbeddingStartEvent(\n\u001b[1;32m    328\u001b[0m         model_dict\u001b[38;5;241m=\u001b[39mmodel_dict,\n\u001b[1;32m    329\u001b[0m     )\n\u001b[1;32m    330\u001b[0m )\n\u001b[1;32m    331\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcallback_manager\u001b[38;5;241m.\u001b[39mevent(\n\u001b[1;32m    332\u001b[0m     CBEventType\u001b[38;5;241m.\u001b[39mEMBEDDING,\n\u001b[1;32m    333\u001b[0m     payload\u001b[38;5;241m=\u001b[39m{EventPayload\u001b[38;5;241m.\u001b[39mSERIALIZED: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mto_dict()},\n\u001b[1;32m    334\u001b[0m ) \u001b[38;5;28;01mas\u001b[39;00m event:\n\u001b[0;32m--> 335\u001b[0m     embeddings \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_text_embeddings\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcur_batch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    336\u001b[0m     result_embeddings\u001b[38;5;241m.\u001b[39mextend(embeddings)\n\u001b[1;32m    337\u001b[0m     event\u001b[38;5;241m.\u001b[39mon_end(\n\u001b[1;32m    338\u001b[0m         payload\u001b[38;5;241m=\u001b[39m{\n\u001b[1;32m    339\u001b[0m             EventPayload\u001b[38;5;241m.\u001b[39mCHUNKS: cur_batch,\n\u001b[1;32m    340\u001b[0m             EventPayload\u001b[38;5;241m.\u001b[39mEMBEDDINGS: embeddings,\n\u001b[1;32m    341\u001b[0m         },\n\u001b[1;32m    342\u001b[0m     )\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/embeddings/openai/base.py:434\u001b[0m, in \u001b[0;36mOpenAIEmbedding._get_text_embeddings\u001b[0;34m(self, texts)\u001b[0m\n\u001b[1;32m    427\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Get text embeddings.\u001b[39;00m\n\u001b[1;32m    428\u001b[0m \n\u001b[1;32m    429\u001b[0m \u001b[38;5;124;03mBy default, this is a wrapper around _get_text_embedding.\u001b[39;00m\n\u001b[1;32m    430\u001b[0m \u001b[38;5;124;03mCan be overridden for batch queries.\u001b[39;00m\n\u001b[1;32m    431\u001b[0m \n\u001b[1;32m    432\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    433\u001b[0m client \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_client()\n\u001b[0;32m--> 434\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mget_embeddings\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    435\u001b[0m \u001b[43m    \u001b[49m\u001b[43mclient\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    436\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtexts\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    437\u001b[0m \u001b[43m    \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_text_engine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    438\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madditional_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    439\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/tenacity/__init__.py:336\u001b[0m, in \u001b[0;36mBaseRetrying.wraps.<locals>.wrapped_f\u001b[0;34m(*args, **kw)\u001b[0m\n\u001b[1;32m    334\u001b[0m copy \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcopy()\n\u001b[1;32m    335\u001b[0m wrapped_f\u001b[38;5;241m.\u001b[39mstatistics \u001b[38;5;241m=\u001b[39m copy\u001b[38;5;241m.\u001b[39mstatistics  \u001b[38;5;66;03m# type: ignore[attr-defined]\u001b[39;00m\n\u001b[0;32m--> 336\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcopy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkw\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/tenacity/__init__.py:475\u001b[0m, in \u001b[0;36mRetrying.__call__\u001b[0;34m(self, fn, *args, **kwargs)\u001b[0m\n\u001b[1;32m    473\u001b[0m retry_state \u001b[38;5;241m=\u001b[39m RetryCallState(retry_object\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m, fn\u001b[38;5;241m=\u001b[39mfn, args\u001b[38;5;241m=\u001b[39margs, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[1;32m    474\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m--> 475\u001b[0m     do \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miter\u001b[49m\u001b[43m(\u001b[49m\u001b[43mretry_state\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretry_state\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    476\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(do, DoAttempt):\n\u001b[1;32m    477\u001b[0m         \u001b[38;5;28;01mtry\u001b[39;00m:\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/tenacity/__init__.py:376\u001b[0m, in \u001b[0;36mBaseRetrying.iter\u001b[0;34m(self, retry_state)\u001b[0m\n\u001b[1;32m    374\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    375\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m action \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39miter_state\u001b[38;5;241m.\u001b[39mactions:\n\u001b[0;32m--> 376\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43maction\u001b[49m\u001b[43m(\u001b[49m\u001b[43mretry_state\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    377\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/tenacity/__init__.py:418\u001b[0m, in \u001b[0;36mBaseRetrying._post_stop_check_actions.<locals>.exc_check\u001b[0;34m(rs)\u001b[0m\n\u001b[1;32m    416\u001b[0m retry_exc \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mretry_error_cls(fut)\n\u001b[1;32m    417\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreraise:\n\u001b[0;32m--> 418\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[43mretry_exc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreraise\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    419\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m retry_exc \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfut\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexception\u001b[39;00m()\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/tenacity/__init__.py:185\u001b[0m, in \u001b[0;36mRetryError.reraise\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    183\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mreraise\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m t\u001b[38;5;241m.\u001b[39mNoReturn:\n\u001b[1;32m    184\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlast_attempt\u001b[38;5;241m.\u001b[39mfailed:\n\u001b[0;32m--> 185\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlast_attempt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    186\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/concurrent/futures/_base.py:449\u001b[0m, in \u001b[0;36mFuture.result\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    447\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m CancelledError()\n\u001b[1;32m    448\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_state \u001b[38;5;241m==\u001b[39m FINISHED:\n\u001b[0;32m--> 449\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__get_result\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    451\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_condition\u001b[38;5;241m.\u001b[39mwait(timeout)\n\u001b[1;32m    453\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_state \u001b[38;5;129;01min\u001b[39;00m [CANCELLED, CANCELLED_AND_NOTIFIED]:\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/concurrent/futures/_base.py:401\u001b[0m, in \u001b[0;36mFuture.__get_result\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    399\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception:\n\u001b[1;32m    400\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 401\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception\n\u001b[1;32m    402\u001b[0m     \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m    403\u001b[0m         \u001b[38;5;66;03m# Break a reference cycle with the exception in self._exception\u001b[39;00m\n\u001b[1;32m    404\u001b[0m         \u001b[38;5;28mself\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/tenacity/__init__.py:478\u001b[0m, in \u001b[0;36mRetrying.__call__\u001b[0;34m(self, fn, *args, **kwargs)\u001b[0m\n\u001b[1;32m    476\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(do, DoAttempt):\n\u001b[1;32m    477\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 478\u001b[0m         result \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    479\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m:  \u001b[38;5;66;03m# noqa: B902\u001b[39;00m\n\u001b[1;32m    480\u001b[0m         retry_state\u001b[38;5;241m.\u001b[39mset_exception(sys\u001b[38;5;241m.\u001b[39mexc_info())  \u001b[38;5;66;03m# type: ignore[arg-type]\u001b[39;00m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/llama_index/embeddings/openai/base.py:180\u001b[0m, in \u001b[0;36mget_embeddings\u001b[0;34m(client, list_of_text, engine, **kwargs)\u001b[0m\n\u001b[1;32m    176\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(list_of_text) \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2048\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe batch size should not be larger than 2048.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    178\u001b[0m list_of_text \u001b[38;5;241m=\u001b[39m [text\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m text \u001b[38;5;129;01min\u001b[39;00m list_of_text]\n\u001b[0;32m--> 180\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43membeddings\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlist_of_text\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mdata\n\u001b[1;32m    181\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [d\u001b[38;5;241m.\u001b[39membedding \u001b[38;5;28;01mfor\u001b[39;00m d \u001b[38;5;129;01min\u001b[39;00m data]\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/resources/embeddings.py:114\u001b[0m, in \u001b[0;36mEmbeddings.create\u001b[0;34m(self, input, model, dimensions, encoding_format, user, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m    108\u001b[0m         embedding\u001b[38;5;241m.\u001b[39membedding \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mfrombuffer(  \u001b[38;5;66;03m# type: ignore[no-untyped-call]\u001b[39;00m\n\u001b[1;32m    109\u001b[0m             base64\u001b[38;5;241m.\u001b[39mb64decode(data), dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfloat32\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    110\u001b[0m         )\u001b[38;5;241m.\u001b[39mtolist()\n\u001b[1;32m    112\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m obj\n\u001b[0;32m--> 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_post\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    115\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/embeddings\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    116\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43membedding_create_params\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mEmbeddingCreateParams\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    117\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmake_request_options\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    118\u001b[0m \u001b[43m        \u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_headers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    119\u001b[0m \u001b[43m        \u001b[49m\u001b[43mextra_query\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_query\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    120\u001b[0m \u001b[43m        \u001b[49m\u001b[43mextra_body\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_body\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    121\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    122\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpost_parser\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparser\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    123\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    124\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mCreateEmbeddingResponse\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    125\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1260\u001b[0m, in \u001b[0;36mSyncAPIClient.post\u001b[0;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1246\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(\n\u001b[1;32m   1247\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   1248\u001b[0m     path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1255\u001b[0m     stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1256\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[1;32m   1257\u001b[0m     opts \u001b[38;5;241m=\u001b[39m FinalRequestOptions\u001b[38;5;241m.\u001b[39mconstruct(\n\u001b[1;32m   1258\u001b[0m         method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpost\u001b[39m\u001b[38;5;124m\"\u001b[39m, url\u001b[38;5;241m=\u001b[39mpath, json_data\u001b[38;5;241m=\u001b[39mbody, files\u001b[38;5;241m=\u001b[39mto_httpx_files(files), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions\n\u001b[1;32m   1259\u001b[0m     )\n\u001b[0;32m-> 1260\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:937\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    928\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrequest\u001b[39m(\n\u001b[1;32m    929\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    930\u001b[0m     cast_to: Type[ResponseT],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    935\u001b[0m     stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    936\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[0;32m--> 937\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    938\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    939\u001b[0m \u001b[43m        \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    940\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    941\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    942\u001b[0m \u001b[43m        \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    943\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1026\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1024\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_retry(err\u001b[38;5;241m.\u001b[39mresponse):\n\u001b[1;32m   1025\u001b[0m     err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m-> 1026\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1027\u001b[0m \u001b[43m        \u001b[49m\u001b[43minput_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1028\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1029\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1030\u001b[0m \u001b[43m        \u001b[49m\u001b[43merr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1031\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1032\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1033\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1035\u001b[0m \u001b[38;5;66;03m# If the response is streamed then we need to explicitly read the response\u001b[39;00m\n\u001b[1;32m   1036\u001b[0m \u001b[38;5;66;03m# to completion before attempting to access the response text.\u001b[39;00m\n\u001b[1;32m   1037\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mis_closed:\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1075\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[0;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1071\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[1;32m   1072\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[1;32m   1073\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[0;32m-> 1075\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1076\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1077\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1078\u001b[0m \u001b[43m    \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1079\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1080\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1081\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1026\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1024\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_retry(err\u001b[38;5;241m.\u001b[39mresponse):\n\u001b[1;32m   1025\u001b[0m     err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m-> 1026\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1027\u001b[0m \u001b[43m        \u001b[49m\u001b[43minput_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1028\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1029\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1030\u001b[0m \u001b[43m        \u001b[49m\u001b[43merr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1031\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1032\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1033\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1035\u001b[0m \u001b[38;5;66;03m# If the response is streamed then we need to explicitly read the response\u001b[39;00m\n\u001b[1;32m   1036\u001b[0m \u001b[38;5;66;03m# to completion before attempting to access the response text.\u001b[39;00m\n\u001b[1;32m   1037\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mis_closed:\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1075\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[0;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1071\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[1;32m   1072\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[1;32m   1073\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[0;32m-> 1075\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1076\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1077\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1078\u001b[0m \u001b[43m    \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1079\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1080\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1081\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "    \u001b[0;31m[... skipping similar frames: SyncAPIClient._request at line 1026 (7 times), SyncAPIClient._retry_request at line 1075 (7 times)]\u001b[0m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1026\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1024\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_retry(err\u001b[38;5;241m.\u001b[39mresponse):\n\u001b[1;32m   1025\u001b[0m     err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m-> 1026\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1027\u001b[0m \u001b[43m        \u001b[49m\u001b[43minput_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1028\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1029\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1030\u001b[0m \u001b[43m        \u001b[49m\u001b[43merr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1031\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1032\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1033\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1035\u001b[0m \u001b[38;5;66;03m# If the response is streamed then we need to explicitly read the response\u001b[39;00m\n\u001b[1;32m   1036\u001b[0m \u001b[38;5;66;03m# to completion before attempting to access the response text.\u001b[39;00m\n\u001b[1;32m   1037\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mis_closed:\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1075\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[0;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1071\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[1;32m   1072\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[1;32m   1073\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[0;32m-> 1075\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1076\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1077\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1078\u001b[0m \u001b[43m    \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1079\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1080\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1081\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/usr/local/python/3.12.1/lib/python3.12/site-packages/openai/_base_client.py:1041\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1038\u001b[0m         err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mread()\n\u001b[1;32m   1040\u001b[0m     log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRe-raising status error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 1041\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_status_error_from_response(err\u001b[38;5;241m.\u001b[39mresponse) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1043\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_response(\n\u001b[1;32m   1044\u001b[0m     cast_to\u001b[38;5;241m=\u001b[39mcast_to,\n\u001b[1;32m   1045\u001b[0m     options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1049\u001b[0m     retries_taken\u001b[38;5;241m=\u001b[39moptions\u001b[38;5;241m.\u001b[39mget_max_retries(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_retries) \u001b[38;5;241m-\u001b[39m retries,\n\u001b[1;32m   1050\u001b[0m )\n",
      "\u001b[0;31mRateLimitError\u001b[0m: Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}"
     ]
    }
   ],
   "source": [
    "from llama_index.vector_stores.myscale import MyScaleVectorStore\n",
    "from llama_index.core import StorageContext\n",
    "\n",
    "for document in documents:\n",
    "   category = analyze_and_assign_category(document.text)\n",
    "   document.metadata = {\"Category\": category}\n",
    "\n",
    "vector_store = MyScaleVectorStore(myscale_client=client)\n",
    "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n",
    "index = VectorStoreIndex.from_documents(documents, storage_context=storage_context)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'index' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m query_engine \u001b[38;5;241m=\u001b[39m \u001b[43mindex\u001b[49m\u001b[38;5;241m.\u001b[39mas_query_engine()\n\u001b[1;32m      2\u001b[0m response \u001b[38;5;241m=\u001b[39m query_engine\u001b[38;5;241m.\u001b[39mquery(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mI want a few running shoes\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28mprint\u001b[39m(response\u001b[38;5;241m.\u001b[39msource_nodes[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mtext)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'index' is not defined"
     ]
    }
   ],
   "source": [
    "query_engine = index.as_query_engine()\n",
    "response = query_engine.query(\"I want a few running shoes\")\n",
    "print(response.source_nodes[0].text)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Filtered query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core.vector_stores import ExactMatchFilter, MetadataFilters\n",
    "\n",
    "query_engine = index.as_query_engine(\n",
    "   filters=MetadataFilters(\n",
    "       filters=[ExactMatchFilter(key=\"Category\", value=\"Running\")]\n",
    "   ),\n",
    "   similarity_top_k=2,\n",
    "   vector_store_query_mode=\"hybrid\",\n",
    ")\n",
    "response = query_engine.query(\"I want a few running shoes?\")\n",
    "print(response.source_nodes[0].text)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding a Reranker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.postprocessor.jinaai_rerank import JinaRerank\n",
    "from llama_index.llms.openai import OpenAI\n",
    "\n",
    "jina_rerank = JinaRerank(api_key=\"api-key-here\", top_n=2)\n",
    "llm = OpenAI(model=\"gpt-4\", temperature=0)\n",
    "\n",
    "query_engine = index.as_query_engine(\n",
    "   similarity_top_k=10, llm=llm, node_postprocessors=[jina_rerank]\n",
    ")\n",
    "response = query_engine.query(\"I want a few running shoes?\")\n",
    "print(response.source_nodes[0].text)\n"
   ]
  }
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