{ "cells": [ { "cell_type": "code", "execution_count": 5, "id": "9eb87f74", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import json\n", "from typing import List\n", "from unstructured.partition.pdf import partition_pdf\n", "from unstructured.chunking.title import chunk_by_title\n", "from langchain_core.documents import Document\n", "from langchain_groq import ChatGroq\n", "from langchain_classic.vectorstores import FAISS\n", "from langchain_core.messages import HumanMessage\n", "from dotenv import load_dotenv\n", "\n", "load_dotenv()" ] }, { "cell_type": "code", "execution_count": 6, "id": "be7c2d32", "metadata": {}, "outputs": [], "source": [ "from langchain_huggingface import HuggingFaceEmbeddings\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "9c5a5679", "metadata": {}, "outputs": [], "source": [ "def partition_document(file_path: str):\n", " \"\"\"Extract elements from PDF using unstructured\"\"\"\n", " print(f\"📄 Partitioning document: {file_path}\")\n", " \n", " elements = partition_pdf(\n", " filename=file_path, # Path to your PDF file\n", " strategy=\"hi_res\", # Use the most accurate (but slower) processing method of extraction\n", " infer_table_structure=True, # Keep tables as structured HTML, not jumbled text\n", " extract_image_block_types=[\"Image\"], # Grab images found in the PDF\n", " extract_image_block_to_payload=True # Store images as base64 data you can actually use\n", " )\n", " \n", " print(f\"✅ Extracted {len(elements)} elements\")\n", " return elements" ] }, { "cell_type": "code", "execution_count": 11, "id": "2694ce04", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "📄 Partitioning document: ../docs/attention_is_all_you_need.pdf\n", "Warning: No languages specified, defaulting to English.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Loading weights: 100%|██████████| 367/367 [00:00<00:00, 8059.72it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Extracted 232 elements\n" ] } ], "source": [ "file_path = \"../docs/attention_is_all_you_need.pdf\" # Change this to your PDF path\n", "elements = partition_document(file_path)" ] }, { "cell_type": "code", "execution_count": 12, "id": "8563532a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " 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,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "elements" ] }, { "cell_type": "code", "execution_count": 13, "id": "030ce66a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{\"\",\n", " \"\",\n", " \"\",\n", " \"\",\n", " \"\",\n", " \"\",\n", " \"\",\n", " \"\",\n", " \"\",\n", " \"\"}" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "set(str(type(el)) for el in elements)" ] }, { "cell_type": "code", "execution_count": 14, "id": "d4bfa3c1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'type': 'NarrativeText',\n", " 'element_id': 'f79000cfdbeb125e8a343def1e0cd745',\n", " 'text': '31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA.',\n", " 'metadata': {'detection_class_prob': 0.8697707653045654,\n", " 'is_extracted': 'true',\n", " 'coordinates': {'points': ((np.float64(525.0),\n", " np.float64(3562.4523588888887)),\n", " (np.float64(525.0), np.float64(3606.0390255555553)),\n", " (np.float64(2236.7791600000005), np.float64(3606.0390255555553)),\n", " (np.float64(2236.7791600000005), np.float64(3562.4523588888887))),\n", " 'system': 'PixelSpace',\n", " 'layout_width': 2975,\n", " 'layout_height': 3850},\n", " 'last_modified': '2026-05-26T11:16:29',\n", " 'filetype': 'application/pdf',\n", " 'languages': ['eng'],\n", " 'page_number': 1,\n", " 'file_directory': '../docs',\n", " 'filename': 'attention_is_all_you_need.pdf',\n", " 'parent_id': '02a986bbe49a3b2497a9ae242a1b70bb'}}" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "elements[36].to_dict()" ] }, { "cell_type": "code", "execution_count": 16, "id": "bfd5acc1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "images = [el for el in elements if el.category == \"Image\"]\n", "images" ] }, { "cell_type": "code", "execution_count": 18, "id": "5771b4fc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'type': 'Image',\n", " 'element_id': '6bc97160173466e30b52c337618dff7d',\n", " 'text': 'Output Probabilities Add & Norm Feed Forward Add & Norm Multi-Head Attention a, Add & Norm Nx Add & Norm Feed Forward Nx | —-Casda Nom] Add & Norm VWEeea Multi-Head Multi-Head Attention Attention Se a, SE a, Positional CY Encoding or, Positional @ g Encoding Input Embedding Inputs Outputs (shifted right) Output Embedding',\n", " 'metadata': {'coordinates': {'points': ((np.float64(955.4951388888888),\n", " np.float64(350.00972222222197)),\n", " (np.float64(955.4951388888888), np.float64(1917.309722222222)),\n", " (np.float64(2019.4951388888885), np.float64(1917.309722222222)),\n", " (np.float64(2019.4951388888885), np.float64(350.00972222222197))),\n", " 'system': 'PixelSpace',\n", " 'layout_width': 2975,\n", " 'layout_height': 3850},\n", " 'last_modified': '2026-05-26T11:16:29',\n", " 'filetype': 'application/pdf',\n", " 'languages': ['eng'],\n", " 'page_number': 3,\n", " 'image_base64': 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WVyIyu7GzRXlfxR8V6Ks+kaeNSiF3Zavby3MQzmNBySeOmCK6LVPiD4Uk8O3U8et25jlSWCNhu+aQJnb06/MPzpezdk+4c6u0dlRXnPwo8U6LceFNI0RNRifVEhbdb87hgknt6V1uveKtF8MxI+rX0cBkz5cfLO+PRRyaTg1LlGpJq5s0VzGhfEDw14iuxaWGoD7SfuwzI0TN9AwGfwrb1DVbHShAb65SAXEqwxbs/M56KKTi07NDunqXKK5DU/id4T0q+a0n1IySoxV/IiaVUI6glQQK2rfxLo13oT63BqEMmnRqWedTkKB1z3GPShxkugcy7mrVWfUrK2vbeymuoo7m5z5MTNhpMdcDvivK9A8eeGbX4ieKL+41qBLO6W3FvId219qkNjjtXearFoUnizQ5b2Z11RRJ9hUE4YEfNnt0qnCzsyVO60OioqnqmrWGi2Ml7qV3FbWyfeeRsD6D1PtXL2vxV8H3d0LcaoYiTtEk8Lxof+BEYqVGT1SKcktztKKhnu7e2s5LyWVVt44zI8mcgKBkn6Yrn9T+IPhjSbS3ubjVEZbmMSwpCrSO6Ho20DOPrQot7A2ludNRWF4e8Y6F4o8xdKv1lljGXhZSkij1KnnFbtJprRgmnsFFFFAwooooAK8Q/aI/49tB/wB+b+S17fXiH7RH/HtoP+/N/Ja1ofxEZ1fgZ2vwN/5JhZ/9d5f/AEKvR684+Bv/ACTCz/67y/8AoVej16BxhRRRQAUUUUAFfJHhH/kttl/2F3/9Davrevkjwj/yW2y/7C7/APobUAfW9FFFAHhX7R//AB7aB/vzfyWvQPgj/wAki0T63H/o+SvP/wBo/wD49tA/35v5LXoHwR/5JFon1uP/AEfJQB6DRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGX4m/5FTWP+vGb/0A18xfAX/kpaf9ecv9K+nfE3/Iqax/14zf+gGvmL4C/wDJS0/685f6UAfUtFFFAHyb8a/+Soaj/uRf+gCvqy0/484P+ua/yr5T+Nf/ACVDUf8Aci/9AFfVlp/x5wf9c1/lQBNRRRQAUUUUAFFFFAHmHx7/AOSav/1+Rf1rkv2fP+Qdrv8A11h/k1db8e/+Sav/ANfkX9a5L9nz/kHa7/11h/k1XT+IyrfAz2eiiiuk4gooooAKKKKACiiigAooooA87+H/APyOvjf/AK/l/ka9ErL0zw/p+kX+oXtnGyz6hIJbglyQzD0B6VqUoqyKk7u55n8SrSwg8UeGNZ1i2jn0lJHtbkSoGRd4+UsD2zn8q6hfA3g94xInh7SmQjIYW6EEevStvUNPtNVsZbK+t0ntpV2vG4yCK43/AIVVpSjyYta8QRWPT7CmoEQ49MYzj8aVtSlK6SvYi0GHQ9Yl8TafoGhWdlbRRtZf2hbhQJ3KnIAC9FPfJrK+GmheFdY8Lx219oenvq9izQXiTQKZAwJwT65HevSNK0mx0TTorDTrdILaMYVF/mT3PvWFrfgDR9Z1FtSSW903UGGHutOnMLsPfgg/lS5XuPnWqMbxVpng7w3DaJH4T0u8v7ydYbe0ESIz5PJztOAB7UniGWLw98UtB1q6VYbG6sm01pScLG+dyg1uaF4D0nQ7/wDtHzb3UNQC7Rd6hOZpFHseAPwFberaRYa5p8lhqVslxbSdUcdD6j0PvT5WLmSZbZ0SMyMwCAZLE8AeteYeDNWh1r4u+Jb22y1s1rGkUnaRVO3cPUZB5rZj+F2lKfLl1fXp7EcCxl1BjAB6bQM4/GuisPDelaZqbahZWwhma3S2whwojXoAvQUWbaBOKTNaiiiqMwooooAKKKKACiiigAooooA+VPHn/JWNT/6/l/8AZa+vYf8AUR/7o/lXyF48/wCSsan/ANfy/wDstfXsP+oj/wB0fyrkluehH4UPrM8Sf8itq/8A15Tf+gGtOszxJ/yK2r/9eU3/AKAaRR86fs+f8lMP/XjL/Na+qq+Vf2fP+SmH/rxl/mtfVVABRRRQB8g/G3/krOs/SH/0UlfX1fIPxt/5KzrP0h/9FJX19QAUUUUAfMf7R3/I9ad/2D1/9GPXt/gP/kn/AIe/7B0H/oArxD9o7/ketO/7B6/+jHr2/wAB/wDJP/D3/YOg/wDQBQB0NFFFAHx78MP+Sn6J/wBfDf8AoLV9a18lfDD/AJKfon/Xw3/oLV9a1xYn4kdVD4QooornNgooooAK5nx/4hHhnwZqF+GCzlPJg/66Nwv5dfwrpq838SIni74naX4cdFm0/Sojf3qMAyM54RCDwevQ9iauCu9SZuy0LPg7xB4P8O+ErDS28SaUZEi3TE3SfNI3LE8+pNZfwx1ewtPFHiHwxY3sF1ZCY3ti8MgZdjY3KCPQkfrXc/8ACHeF/wDoW9H/APAGL/4muI8eaVZeDdR0PxdpFhb2cVnciG9S1iWMNFJwSQoGcf1FWmpNruQ01Z9i58UrGz8rw/N9lg82XWrZZH8sZcZPBPcV1mr6Tpq6DfKNPtAqwSMAIVwDtPPTrwK5b4q3EUej+H71nAto9YtpXk7BOTn6V1tzf2eq6Dfvp13Bdp5EiboJA43bemQevIpa8sR6XZznwrsrRPh9o10LWBbgwtmURjf949+tcZ4c8Z+EB4p1vX/EmpRrqTXTQ2kckEj+RAnA24UgE96634T6xps/gPSLCO/tmvEjZWt/NHmDDHPy5zWZ4HubHw54i1rwlqyRQ3BvHubF5gMTxPzwT3Hp/hVdZE9IlHx3418A+IvD85t9Yj/ta3XzrKZLeVZFlXkANtGM9OuKf44vJfE3gHwddCUxTX19bEyLwVZgQSPxrrvGfiTTvDGkM1vBaXGqzER2dpsDNLIeB8o5x61jePvtP9j+EPtqQpdf2tamVYQQitzkKCTxmnB7WCXU7nTdIsdJ06Ows7aOK3RQu0L973Pqa4PwbY2+nfEnxrokEMY07FvOLfblAzpluOmOa9Krz7w5/wAln8af9e9n/wCixWcW7SLktUQeGtL0+T4o+MIXsLVoo0tdiGFSFypzgY4q34o/5Kl4N+lx/wCg1T0fVdP0r4s+LV1G9t7QzRWzRmeQIGAXnBP1q54oOfil4NI9Lj/0Gr+18v0I+z8/1KT2sfjL4uXttqCibTfD0Mey3cZRppBncR3wB39K73UdIsNW06SwvrSKa1ddpjZeAPb0/CuBuLuPwV8WLu+1AiHSvEEMa/aW+5HNGMAMe2R6+tdzqevaXo+mPqN7fQxWyru3lwd3sPU/SonfSxUba3PO/D01zZ+CPGnhm5leUaKk8MEjnJMTIzKD9K3PhVoVrp3gnTb7asl7dwLJJOw+bbj5VB7ADAxWH4etru58DeM/Et5E8La0k88UTjDLEI2C5/Cux+Hv/JPPD/8A14xf+g1dR6O3cmC1Rzni60h034o+DtStI1iuLyWW3uGQY8xAo6+vWvSK8+8ef8j14C/6/pv/AEFa9BrOXwouO7CiiioLCiiigArxD9oj/j20H/fm/kte314h+0R/x7aD/vzfyWtaH8RGdX4Gdr8Df+SYWf8A13l/9Cr0evOPgb/yTCz/AOu8v/oVej16BxhRRRQAUUUUAFfJHhH/AJLbZf8AYXf/ANDavrevkjwj/wAltsv+wu//AKG1AH1vRRRQB4V+0f8A8e2gf7838lr0D4I/8ki0T63H/o+SvP8A9o//AI9tA/35v5LXoHwR/wCSRaJ9bj/0fJQB6DRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGX4m/5FTWP+vGb/ANANfMXwF/5KWn/XnL/Svp3xN/yKmsf9eM3/AKAa+YvgL/yUtP8Arzl/pQB9S0UUUAfJvxr/AOSoaj/uRf8AoAr6stP+POD/AK5r/KvlP41/8lQ1H/ci/wDQBX1Zaf8AHnB/1zX+VAE1FFFABRRRQAUUUUAeYfHv/kmr/wDX5F/WuS/Z8/5B2u/9dYf5NXW/Hv8A5Jq//X5F/WuS/Z8/5B2u/wDXWH+TVdP4jKt8DPZ6KKK6TiCiiigAooooAKKr39ybLTrm6CbzDE0m3OM4GcV5/pHjrxnrumQ6jp3giGa1mBKP/aka5wcdCAe1JtIpRb1PSKK4ZfEfj8sA3gOEDPJ/taLiu3QsUUsu1iORnODTTuJqw6iiigQUUUUAFFFFABRRRQAUUUUAFFFFABRXPX/iZrLxrpXh4Wodb6GSUz78FNvbGOc/WuhouNqwUUUUCCiiigAooooA+VPHn/JWNT/6/l/9lr69h/1Ef+6P5V8hePP+Ssan/wBfy/8AstfXsP8AqI/90fyrkluehH4UPrM8Sf8AIrav/wBeU3/oBrTrM8Sf8itq/wD15Tf+gGkUfOn7Pn/JTD/14y/zWvqqvlX9nz/kph/68Zf5rX1VQAUUUUAfIPxt/wCSs6z9If8A0UlfX1fIPxt/5KzrP0h/9FJX19QAUUUUAfMf7R3/ACPWnf8AYPX/ANGPXt/gP/kn/h7/ALB0H/oArxD9o7/ketO/7B6/+jHr2/wH/wAk/wDD3/YOg/8AQBQB0NFFFAHx78MP+Sn6J/18N/6C1fWtfIdjLL4D+JMb3cTE6bekSL3ZMkEj6qcivpqz8eeFb61S4h12xCOMgPKEYfUHkVyYiLbTR0UZJKx0VFYn/CY+Gv8AoPad/wCBC/40f8Jj4a/6D2nf+BC/41zcsuxvzLubdFYn/CY+Gv8AoPad/wCBC/40f8Jj4a/6D2nf+BC/40csuwcy7m3VO20mws725vba0iiurogzyquGkx0ye9UP+Ex8Nf8AQe07/wACF/xo/wCEx8Nf9B7Tv/Ahf8afLLsK8TbqvfWFpqdnJZ31vHcW0ow8Ui5Vh7isz/hMfDX/AEHtO/8AAhf8aP8AhMfDX/Qe07/wIX/Glyy7D5kX5dKsJ9NGnTWcMlkFCCB0BTaOgwaZpWiaZoVs9vpVjBZwu+9khTaC2AM/kBVP/hMfDX/Qe07/AMCF/wAaP+Ex8Nf9B7Tv/Ahf8adpCvEltfC+hWOqHU7TSbSC9OczxxBW568ijXPDOi+JIFh1jTobtVztLghlz6MOR+BqL/hMfDX/AEHtO/8AAhf8aP8AhMfDX/Qe07/wIX/Gi073C8dirofgDwt4cuftOlaPDDOM4lZmkZfoXJI/Ctu902y1IQi9tYpxBIJovMXOxx0Ye9Z3/CY+Gv8AoPad/wCBC/40f8Jj4a/6D2nf+BC/40NTbu7heK0NuqkOmWNvqNzqENrEl5chVmmVfmkCjC5PfArP/wCEx8Nf9B7Tv/Ahf8aP+Ex8Nf8AQe07/wACF/xo5Zdh3RLqvhjQtclWXVNJtLuRRhXmiDED0zVubTLG4vba8mtYnubYEQSsuWjzwcHtWf8A8Jj4a/6D2nf+BC/40f8ACY+Gv+g9p3/gQv8AjRaQrxNHUNOstVspLO/torm3kGGjlXINc1Z/C7wVYXn2uDQYPNzuHmO8ig+ysxA/KtT/AITHw1/0HtO/8CF/xo/4THw1/wBB7Tv/AAIX/GmudbXB8r3Nae3hubaS2miV4JEKPGw4ZSMEY9MUlpaW9haRWlrCkNvCoSONBhVUdABWV/wmPhr/AKD2nf8AgQv+NH/CY+Gv+g9p3/gQv+NLll2C6NC60yxvbq1ubq1ilntGLwSOuTGx6kelW6xP+Ex8Nf8AQe07/wACF/xo/wCEx8Nf9B7Tv/Ahf8aOWXYd0bdFYn/CY+Gv+g9p3/gQv+NH/CY+Gv8AoPad/wCBC/40uWXYOZdzborE/wCEx8Nf9B7Tv/Ahf8aP+Ex8Nf8AQe07/wACF/xo5Zdg5l3NuvEP2iP+PbQf9+b+S16p/wAJj4aA/wCQ9p3/AIEL/jXg3xo8aaZ4n1OxstKlFxBZBi86/dZ2xwPUDHWtqEXzp2M6slynrXwN/wCSYWf/AF3l/wDQq9Hrhfg/ps+l/DPS47lSkk2+faeoVmJX9MH8a7qu45AooooAKKKKACvkjwj/AMltsv8AsLv/AOhtX1vXyR4R/wCS22X/AGF3/wDQ2oA+t6KKKAPCv2j/APj20D/fm/ktegfBH/kkWifW4/8AR8lef/tH/wDHtoH+/N/Ja9A+CP8AySLRPrcf+j5KAPQaKKKACiiuD+JfxJ/4V3Hpsh0r7eL13U4uPK2bdv8AsnP3vbpQB3lFUtH1ay13SbbVNPmE1pcoHjcenofQjoRV2gAork9G8anV/H2u+GP7P8r+ykjf7T527zdwB+7tGOvqa6ygAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAMvxN/yKmsf9eM3/oBr5i+Av8AyUtP+vOX+lfTvib/AJFTWP8Arxm/9ANfMXwF/wCSlp/15y/0oA+paKKKAPk341/8lQ1H/ci/9AFfVlp/x5wf9c1/lXyn8a/+Soaj/uRf+gCvqy0/484P+ua/yoAmooooAKKKKACiiigDzD49/wDJNX/6/Iv61yX7Pn/IO13/AK6w/wAmrrfj3/yTV/8Ar8i/rXJfs+f8g7Xf+usP8mq6fxGVb4Gez0UUV0nEFFFFABRRRQBn67/yL+pf9esn/oJrlfhVd20fw40lXuIlYK+QzgH75rqtd/5F/Uv+vWT/ANBNeafDv4eeFNa8DadqGo6Qk91KrF5DLIM4YjoGAqXfm0NI25Hc9VW7tnYKlxEzHoA4JNYPivxYnh1bW1trV77Vr1ilpZxnBcjqSeyjuai074ceEtK1CC/sdHSG6gbfHIJpDtPrgtise2AuvjletcDJtNLQW2f4Qx+Yj8zQ2xJRuSNefEy1iN7NYaDcxAbjZQSSCbHoGPyk1vaB4ptfEnh2TU7NGjkjDLLBKPmikUcqwrfrznQVS2+IHj21t2/cNFDMyDosjI2fxPWjZjVpJ6Eei+OPEvijSraPQ9Os5b7Zm8u5yyW0LEnCADJLYwSPeug0jxJqD+L7nw3q9vbpcRWcdzFNAW2zZwHwD6N09qp/Ce3it/h5YGNAplaSRz6sXPP6CovHK/2R4l8NeJl+VIbn7HdN/wBMpeAT9D/Okr2uN2cnGxp+O/FcvhLRI7q1tBd3c0wiigJPzcEk8c8AVs6JqketaJZalFgJcwrJgHOCRyPwNctfquu/FWwtCA9to9m9xKDyDLL8qg/8Byao+FdVXwx4R8R2FwSD4fmnCA9TGQXj/POKd9fIXKuXzN3SPF/9paj4jMsMcWl6PJ5QudxJkZQS/HoMfrWRa67458T241HQLHSbDTZCfIOpmQySr2bCdAak8L2VhoPwt8/Xwnk3MTXd/wCYMhjIc4I78ECrGl65r95YWw0PwnFa6aFUQPfXYiPl9iI1ViBj1IpX7jstbIl8NeKdTuNeuPDviGwitdVhiE8b27Fop484yueR9Kp6145u9I8ZXWjR2YvGNrE1nbxDEksrEg5OcBQBknHFZVqurD42WD6xJaGd9LkKpaqwRFz0y3JNaVtbxSfHC9ndAZItIj2E9stg0Xdh2V/kXT4i1nw7oN7q/i9LCNRt+zW1iWZyx/gJbgsTjpVSC++JOoRpfwafodnbuNy2d1JIZsdskDANN+IK+f4l8FWky7rWTUy75PBZQCoI79TXfU7XdiW0le255LDrz658XPDoubOSxv7W3uIrm1kOSjYyCD3UjkGvWq851qCFPjj4dmRQJZLGYOQOSAGxn8zXo1EeoT6WCiiiqMwooooAKKKKAPlTx5/yVjU/+v5f/Za+vYf9RH/uj+VfIXjz/krGp/8AX8v/ALLX17D/AKiP/dH8q5JbnoR+FD6zPEn/ACK2r/8AXlN/6Aa06zPEn/Irav8A9eU3/oBpFHzp+z5/yUw/9eMv81r6qr5V/Z8/5KYf+vGX+a19VUAFFFFAHyD8bf8AkrOs/SH/ANFJX19XyD8bf+Ss6z9If/RSV9fUAFFFFAHzH+0d/wAj1p3/AGD1/wDRj17f4D/5J/4e/wCwdB/6AK8Q/aO/5HrTv+wev/ox69v8B/8AJP8Aw9/2DoP/AEAUAdDRRRQB558Q/hRp3jhvt0M32LVlUKJ9uVkA6Bx/WvJX/Z+8Xq7KtxpbqDwwmYZ/8dr6dooA+YP+Gf8Axj/z10z/AL/t/wDE0f8ADP8A4x/566Z/3/b/AOJr6fpskiQxPLIwVEUszHoAKAPlUfBbxGdabRxe6V9uWAXBi+0NkITjP3fWrv8Awz/4x/566Z/3/b/4mqlv8RpF+M7eJ3kIs3uDAQTwLb7o/TDfWvqlWDKGUggjII70AfMP/DP/AIx/566Z/wB/2/8AiaP+Gf8Axj/z10z/AL/t/wDE19P0UAfMH/DP/jH/AJ66Z/3/AG/+Jo/4Z/8AGP8Az10z/v8At/8AE19P0UAfMH/DP/jH/nrpn/f9v/iaP+Gf/GP/AD10z/v+3/xNfT9FAHzB/wAM/wDjH/nrpn/f9v8A4mj/AIZ/8Y/89dM/7/t/8TX0/RQB8wf8M/8AjH/nrpn/AH/b/wCJo/4Z/wDGP/PXTP8Av+3/AMTX0/XMfEHxGvhbwTqOpBws/lmK3HrI3C/l1/CgD58074JeJdVt3uLK80qaJJXiLLcNjcjFWH3fUVb/AOGf/GP/AD10z/v+3/xNdF+z54ob7XqPh25lJMxN3BuP8XRx/I/ga99oA+YP+Gf/ABj/AM9dM/7/ALf/ABNH/DP/AIx/566Z/wB/2/8Aia+n6KAPmD/hn/xj/wA9dM/7/t/8TR/wz/4x/wCeumf9/wBv/ia+n6KAPmD/AIZ/8Y/89dM/7/t/8TR/wz/4x/566Z/3/b/4mvp+igD5g/4Z/wDGP/PXTP8Av+3/AMTR/wAM/wDjH/nrpn/f9v8A4mvp+igD5g/4Z/8AGP8Az10z/v8At/8AE1S1L4K+I9IS3e+vNKhW4nS3jJnbl2OAPu19WV86fH3xW8/iSy0O0mKrpwE8pU/8tWwV/EDH/fVAGX/wz/4x/wCeumf9/wBv/iaP+Gf/ABj/AM9dM/7/ALf/ABNe/wDgjxCnijwdpuqqR5kkQWYDtIOGH5iugoA+YP8Ahn/xj/z10z/v+3/xNdd4O+AIsr6K98TXkNyIyGW0t8lCR03MQMj2A/GvcaKAEVVRQqgBQMADoBS0UUAFFFFABRRRQAV8keEf+S22X/YXf/0Nq+t6+SPCP/JbbL/sLv8A+htQB9b0UUUAeFftH/8AHtoH+/N/Ja9A+CP/ACSLRPrcf+j5K8//AGj/APj20D/fm/ktegfBH/kkWifW4/8AR8lAHoNFFFABXkfxitYL3xZ4AtbmJZYJtRaORGGQykxgg165XlHxY/5Hf4df9hU/+hR0AUPDk83wn8et4VvpHPhnV5PM0y4fJEMpP3Cf0P8AwE8ZNezVzPjvwfa+NfC9xpk21LgfvLWYjmKUDg/TsfY1gfCvxhdarZ3PhrXcx+IdGPkzq55lQHAf37An6HvQBm+Df+S9eOv+uMH/AKClei3ev6VY6xZ6TdX0UV/eqzW8LnBk29ce/PTvzjpXnXg3/kvXjr/rjB/6Cldv4u8I6f4w0j7HeBop4zvtbuPiS3k7Mp/LI70AdBWdda9pdlrFnpNxfQx394GMEBb5nAGScdvx615gvxL1zwrHL4V13TXv/FSFItOeI/u79WO1JGP8PTn19ua63wV4Lk0aabXNduBqHiW9Gbi6I4iXtHH6KOnHXFAHZ0UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAZfib/kVNY/68Zv/QDXzF8Bf+Slp/15y/0r6d8Tf8iprH/XjN/6Aa+YvgL/AMlLT/rzl/pQB9S0UUUAfJvxr/5KhqP+5F/6AK+rLT/jzg/65r/KvlP41/8AJUNR/wByL/0AV9WWn/HnB/1zX+VAE1FFFABRRRQAUUUUAeYfHv8A5Jq//X5F/WuS/Z8/5B2u/wDXWH+TV1vx7/5Jq/8A1+Rf1rkv2fP+Qdrv/XWH+TVdP4jKt8DPZ6KKK6TiCiiigAooooApaxFJPot9DEpaSS3dVUdyVOBWF8ONNvNJ8CabZX9u8FzErB436r8xNdVRRbW476WCuK8X6Bqia5Y+K/DyJLqVmhimtXbAuYT1XPqO1drRQ1cE7M4J/iHqM8Rt7LwXr39pEYCTwBIVb3kzyPwq54S8L3uj6Rql3qciz63qpaa6ZOgODtQewz+tdjRSt3K5tLJHMfD3TrvSvBGn2d9A0FzGG3xt1GWJq74u0f8At/wpqOnKP3ssJMR9JByp/MCtqii2lhczvc4j4caZq0FrqOq69bNBql9MoZG6rGihV/qfxrG8Z+FdYv8Axoi6fbs2lawsCalIvRBE+c/ivFeoUUuVWsPnd7nNeOvD03iLwRf6PZFUmkRTECcAlGDAfjjFYdj8QNTt7WKyv/Bmvf2miBGEFuGhZgOofOADXoNFNrW6EpaWaPKxYeKrXx/pviu/0qS5W4ge3ktLV1P2NSflBJxn1J9c101rpl6nxUv9Ta3cWUmmxxJN/CXDEkV11FCiNzucz448Nz+I9FiFjKsOp2U63VnI3QSL0B9jWTb/ABA1S3jS01Pwbrp1MDDfZYA8DMO4fdwDXeUUNa3QlLSzPMLDQvEt18SdK8Tava+WHjmRoY2DJaR7cIpPdiSSceten0UUJWCUuYKKKKZIUUUUAFFFFAHyp48/5Kxqf/X8v/stfXsP+oj/AN0fyr5C8ef8lY1P/r+X/wBlr69h/wBRH/uj+Vcktz0I/Ch9ZniT/kVtX/68pv8A0A1p1meJP+RW1f8A68pv/QDSKPnT9nz/AJKYf+vGX+a19VV8q/s+f8lMP/XjL/Na+qqACiiigD5B+Nv/ACVnWfpD/wCikr6+r5R+PumPY/EyW6Odl9bRTKceg2Ef+OfrX0x4Y1qHxF4Y03V4WBW6gVzg5w2MMPwII/CgDWooooA+Y/2jv+R607/sHr/6Mevb/Af/ACT/AMPf9g6D/wBAFeIftHf8j1p3/YPX/wBGPXt/gP8A5J/4e/7B0H/oAoA6GiiigAooooAK87+M/iU6B4Dnt4Xxd6kfs0eDyFP3yPw4/GvRKwde0nRDN/wkOr26TtpsDvEZjlIgOSQOmTgc+1AHxZ5b+YY9jbwcFcc5+lfWnwg8Tf8ACR+ArTzn3Xll/o02Tz8v3T+K4/I14N8ObeTxL8XrK4K5D3cl5Jx0Ay/88D8a+odO8N6VpGp3d/p9qttLdgCdYuEcjo23oDyeR1oA1aKKKACiiigAooooAKKKKACvnb9oPxKbvWLPw7A5Mdmvn3AH99h8oP0Xn/gVfRNeN/F3TNE8L+DdUuo4Q+sa1OEa5lO6Rhu3EA9lAGMDtigDwfwxrk3hvxLYaxDuJtZQzAfxL0YfiMivta1uob20hurdw8MyCRGHQqRkGvA/gL4Xs9Y0rXrjVLGK5s5mS3CyrkEgFjj0xlefevc9F0i30LSYNNtGkNtACsQkbcVXOQue4HSgC/RRRQAUUUUAFFFFABRRRQBS1fUoNG0e81K5bbDaxNK59gM4r4o1nUrnWdYu9Uu8mW7laUk+56D6dK+09a0ax1/TmsNSRpLRmV5IwxUPg5wcds44r5T+IF5B4l+IslnosMa2kbpY2ccKgKcccAerE0Ad9+z14jaG7v8Aw1cMQJR9rtw3rgBgPqMH8DXv9c3beCtHiTRpzaol/pcUccN1F8r4Vdu0nuCMjBrpKACiiigAooooAKKKKACiiigAr5I8I/8AJbbL/sLv/wChtX1vXyR4R/5LbZf9hd//AENqAPreiiigDwr9o/8A49tA/wB+b+S16B8Ef+SRaJ9bj/0fJXn/AO0f/wAe2gf7838lr0D4I/8AJItE+tx/6PkoA9BooooAK8o+LH/I7/Dr/sKn/wBCjr1esXW/Cul+INQ0q+v45Gn0ubz7YrIVCvkHkd/uigDaryv4p+Hr/Tb61+IPhxMarpY/0uJQcXEHQ5A64BOfb6CvVKRlV1KsAykYIIyCKAPE/hRr9t4o+K/i3WrRJEgu7aBlWQYZSAoIP4g16D428aJ4Ygt7Kxtmv9evyUsLFBku395vRB3P/wBciXw18P8Aw94R1O9v9GtXglvBiRTIWUDOcKD0FdE1tA9xHcPDG08QKxyFQWUHGQD1GcD8qAPNbX4RQapo93c+J7yW58TXzCZ9QiYg2jjlVi9FX9fbjF7wh4t1Kz1f/hDvGIWPW41za3gGIr+MdGU/38dRXoNRPbQSTxTyQxtNFny5GUFkzwcHtmgCWiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDL8Tf8AIqax/wBeM3/oBr5i+Av/ACUtP+vOX+lfTvib/kVNY/68Zv8A0A18xfAX/kpaf9ecv9KAPqWiiigD5N+Nf/JUNR/3Iv8A0AV9WWn/AB5wf9c1/lXyn8a/+Soaj/uRf+gCvqy0/wCPOD/rmv8AKgCaiiigAooooAKKKKAOG+LuiT678OdQgtULzwFblUUZLbDkgfhmvC/hP48s/B2oXdtqYcWN7tJlVdxiZc4JA5IOf5V9WkZGDXknjD4E6Tr19Lf6RdnTLiUlpI/L3xMx7gZBX8OKadndClFSVma3/C0vBf8A0HYP++W/wo/4Wl4L/wCg7B/3y3+Fee/8M46p/wBDBZ/9+G/xo/4Zx1T/AKGCz/78N/jWntWY+wiehf8AC0vBf/Qdg/75b/Cj/haXgv8A6DsH/fLf4V57/wAM46p/0MFn/wB+G/xo/wCGcdU/6GCz/wC/Df40e1Yewiehf8LS8F/9B2D/AL5b/Cj/AIWl4L/6DsH/AHy3+Fee/wDDOOqf9DBZ/wDfhv8AGj/hnHVP+hgs/wDvw3+NHtWHsInoX/C0vBf/AEHYP++W/wAKP+FpeC/+g7B/3y3+Fee/8M46p/0MFn/34b/Gj/hnHVP+hgs/+/Df40e1Yewiehf8LS8F/wDQdg/75b/Cj/haXgv/AKDsH/fLf4V57/wzjqn/AEMFn/34b/Gj/hnHVP8AoYLP/vw3+NHtWHsInoX/AAtLwX/0HYP++W/wo/4Wl4L/AOg7B/3y3+Fee/8ADOOqf9DBZ/8Afhv8aP8AhnHVP+hgs/8Avw3+NHtWHsInoX/C0vBf/Qdg/wC+W/wo/wCFpeC/+g7B/wB8t/hXnv8Awzjqn/QwWf8A34b/ABo/4Zx1T/oYLP8A78N/jR7Vh7CJ6F/wtLwX/wBB2D/vlv8ACj/haXgv/oOwf98t/hXlXiD4HTeGtGn1XUfEloltDtDEQNnkgDHPqa0k/Z01KRFdPEVkysMgiFiCPzo9qw9hE9D/AOFpeC/+g7B/3y3+FH/C0vBf/Qdg/wC+W/wrz3/hnHVP+hgs/wDvw3+NH/DOOqf9DBZ/9+G/xo9qw9hE9C/4Wl4L/wCg7B/3y3+FH/C0vBf/AEHYP++W/wAK89/4Zx1T/oYLP/vw3+NH/DOOqf8AQwWf/fhv8aPasPYRPQv+FpeC/wDoOwf98t/hR/wtLwX/ANB2D/vlv8K89/4Zx1T/AKGCz/78N/jR/wAM46p/0MFn/wB+G/xo9qw9hE9C/wCFpeC/+g7B/wB8t/hR/wALS8F/9B2D/vlv8K89/wCGcdU/6GCz/wC/Df40f8M46p/0MFn/AN+G/wAaPasPYRPQv+FpeC/+g7B/3y3+FH/C0vBf/Qdg/wC+W/wrz3/hnHVP+hgs/wDvw3+NH/DOOqf9DBZ/9+G/xo9qw9hE9C/4Wl4L/wCg7B/3y3+FH/C0vBf/AEHYP++W/wAK89/4Zx1T/oYLP/vw3+NH/DOOqf8AQwWf/fhv8aPasPYRPQv+FpeC/wDoOwf98t/hVe9+Lfg2ztJJk1UXDqPlihjYsx9Bxj864X/hnHVP+hgs/wDvw3+NPj/Zx1AyL5viG1CZ+YrbsTj25o9qw9hE8+09Lzx/8TYpI4dsl/eiV1XkRoDkk/RRX2IqhVCjoBiuR8D/AA60bwNbP9iVp72UAS3Uv3mHoB/CPYV19ZG4VmeJP+RW1f8A68pv/QDWnWZ4k/5FbV/+vKb/ANANAHzp+z5/yUw/9eMv81r6qr5V/Z8/5KYf+vGX+a19VUAFFFFAHmPxs8DyeLPCi3tjD5mp6bmSNQOZIz99R6ngEfTHevLvgx8UYvC0x0DWpNulTyboZjk/Z5D1z/sHv6Hnua+n68T+JvwPTW7mbWvDAjgvnJeezY7Umb+8p6Kx9Oh9u4B7TFLHPEksTrJG4DK6HIYHuDT6+OdP8VePvhrN9gEl7YRq3/Hpdw7oz/uhh091611aftH+KAgD6XpLN3ISQf8As9ACftHf8j1p3/YPX/0Y9e3+A/8Akn/h7/sHQf8AoAr5U8ceN7/x5q8Opahb28EsUIhVYAcYBJ7k8811mj/HXX9G0ay0yDTrB4rSBIUZw2SFGATz7UAfUFFfNh/aH8SY40zTvyf/ABqP/hoXxR/z46b/AN8N/wDFUAfS9FfNH/DQvij/AJ8dN/74b/4qkb9oTxSVIFlpoPr5bf8AxVAH0uzBVLMQABkk9q+fPjN8UYNTik8M6FP5lvu/0y5Q/LJj+BT3Geprz7xJ8TfFfimJoL/Uilqwwbe3URofrjk/iTXPaTfRabqcF5LZQ3ixNuEMxOxiOmcdR7UAfQnwI8Ey6RpUviK/iKXN8oW3VhysPXP/AAI/oBXsVfNa/tC+IkUKul6aFAwAA3A/Ol/4aH8R/wDQM078n/xoA+k6K+bP+Gh/Ef8A0DNO/J/8aP8AhofxH/0DNO/J/wDGgD6Tor5s/wCGh/Ef/QM078n/AMaP+Gh/Ef8A0DNO/J/8aAPpOivmz/hofxH/ANAzTvyf/Gj/AIaH8R/9AzTvyf8AxoA+k6K+bP8AhofxH/0DNO/J/wDGoLr9oLxXNEVt7XTrdj/GI2Yj8zigD6M1fWLDQtNl1DUrqO3tohlnc4/Aep9q+VfHPizUPib4xgisYJDBvEFjbd+erH3J59h9KgW28dfE/UkZ1vdROeJHXZDF+gUfhzXvfw3+Fdj4Ii+23Trd6w64aYD5YgeqoP69aAOi8D+GIvCHhKy0lCGlRd87j+KQ8sfpngewFdFTZJI4YmlldUjQZZmOAB6k14z4x+Pllp00ln4atkvpV4N3KcRA/wCyBy314H1oA9oor5Ln+KHxE12Zhb6ld/MeI7KALj2G0Z/Wmf8ACTfFD/n98Rf98Sf4UAfW9FfJH/CTfFD/AJ/fEX/fEn+FH/CTfFD/AJ/fEX/fEn+FAH1vRXyR/wAJN8UP+f3xF/3xJ/hR/wAJN8UP+f3xF/3xJ/hQB9b0yaaK3haWaRI40GWd2AAHqSa+S/8AhJvih/z++Iv++JP8KjOhfEfxfIsVxaa3dpnrdB1jH4tgUAej/FH4y2psp9C8MT+bJKCk98hwqr3VD3Pv+VZvwM+H81zfp4r1KErbQ5+xKw/1j9C/0Hb3+lafgn4BpbTR33iqaOcrytlCTtz/ALbd/oPzr3CKKOCFIokWONAFVFGAoHQAUAPooooAKKKKACiiigAooooAKKKKACvkjwj/AMltsv8AsLv/AOhtX1vXyR4R/wCS22X/AGF3/wDQ2oA+t6KKKAPCv2j/APj20D/fm/ktegfBH/kkWifW4/8AR8lef/tH/wDHtoH+/N/Ja9A+CP8AySLRPrcf+j5KAPQaKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAy/E3/ACKmsf8AXjN/6Aa+YvgL/wAlLT/rzl/pX074m/5FTWP+vGb/ANANfMXwF/5KWn/XnL/SgD6looooA+TfjX/yVDUf9yL/ANAFfVlp/wAecH/XNf5V8p/Gv/kqGo/7kX/oAr6stP8Ajzg/65r/ACoAmooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKiubiKztZrmdgkUKGR2PYAZJoA8J/aG8TZew8NQScD/SrkA9+QgP6n8q7r4N+Jv+Ei8BW0cr7rvTz9mlyeSB90/lj8jXzX4u1W88ReIb7X54pRBd3D+S7KQu0fdUHocLiu0+CGvTaB4yhtblJEsdYTyUdlIVpAflIPQ8gr+NAH1DRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFZniT/AJFbV/8Arym/9ANadZniT/kVtX/68pv/AEA0AfOn7Pn/ACUw/wDXjL/Na+qq+Vf2fP8Akph/68Zf5rX1VQAUUUUAFFFFAEF3ZWt/AYLy2huIj1jmjDqfwNYb/D/wbIxZvC2jZPpZRj+Qro6KAPlT486JpeheMrG30rT7ayhexV2jt4wilt7DOB3wBXr/AIM8DeFbzwTodzc+HdMmnlsYXkke2UszFASSccmvL/2jv+R607/sHr/6Mevb/Af/ACT/AMPf9g6D/wBAFAEZ+Hvg4jH/AAjGlf8AgKn+FM/4Vx4M/wChZ0z/AL8CuoooA5f/AIVx4M/6FnTP+/ApR8OfBgOf+EZ0z8bda6eigDm/+Fe+Dv8AoWNJ/wDAVP8ACj/hXvg7/oWNJ/8AAVP8K6SigDm/+Fe+Dv8AoWNJ/wDAVP8ACj/hXvg7/oWNJ/8AAVP8K6SigDm/+Fe+Dv8AoWNJ/wDAVP8ACj/hXvg7/oWNJ/8AAVP8K6SigDm/+Fe+Dv8AoWNJ/wDAVP8ACj/hXvg7/oWNJ/8AAVP8K6SigDm/+Fe+Dv8AoWNJ/wDAVP8ACj/hXvg7/oWNJ/8AAVP8K6SigDm/+Fe+Dv8AoWNJ/wDAVP8ACpbfwN4TtZBJB4b0pHHRhaJkfTit+igBkUUcEYjijSNB0VBgD8KfRWN4s1c6D4S1XVB9+2tndP8Aexhf1xQB4Z8bPiNNqGoy+F9KnK2Vu227dDjzZB1T/dH6n6VqfDb4JQSWsOseKomdpAHisDwAOxk9T7fnXFfB7w6vir4grcXw82CzBu5g3O98/KD/AMCOfwr6toArWWn2WnQLBZWkFtEowEhjCAfgKs0UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAIzBELHoBk18keBT9u+NGnSQ8q+pPKMf3cs38q94+LfjOHwr4QngilH9pX6GGBAeVBGGf6AfqRXmP7P3hqS78Q3XiCVCLeyjMUTH+KRuuPoP5igD6OooooA8K/aP/49tA/35v5LXoHwR/5JFon1uP8A0fJXn/7R/wDx7aB/vzfyWvQPgj/ySLRPrcf+j5KAPQaKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAy/E3/Iqax/14zf+gGvmL4C/wDJS0/685f6V9O+Jv8AkVNY/wCvGb/0A18xfAX/AJKWn/XnL/SgD6looooA+U/jjbvD8TbxmBAlhidT6jbj+lfT+j3Ud9olhdxMGSa3jkUj0Kg14z+0L4ZkmtrDxJAmRAPs1yQOik5Q/mSPxFa3wL8axar4eHh27lAvrAHyQx5khzxj3XOPpigD12iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAqvfWNvqVjNZXcYlt5l2yRk8MvcH2NWKKAPA/2hrW3srDw5b2sMcMMZlVI41CqowvQCuu+E2j6frHwj0aK/tY5xHLM8ZYfMjCZyGU9QR6iuW/aP/1Ogf703/stdt8E/wDklOk/78//AKOegD0GiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKzPEn/ACK2r/8AXlN/6Aa06zPEn/Irav8A9eU3/oBoA+dP2fP+SmH/AK8Zf5rX1VXyr+z5/wAlMP8A14y/zWvqqgAooooAKKKKACiiigD5j/aO/wCR607/ALB6/wDox69v8B/8k/8AD3/YOg/9AFeIftHf8j1p3/YPX/0Y9e3+A/8Akn/h7/sHQf8AoAoA6GiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK4T4yEj4V6zg4yIgf+/i13dcH8Zf+SWax9Iv/Ri0AeU/AnxFofh6bWZNX1G2sjKsYjMzY3YLZx+le0f8LL8Ff9DLp3/f2vmjwH8O77x616LK9t7b7IFLecCd27PTH0rtP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsf/Cy/BX/Qy6d/39o/4WX4K/6GXTv+/teOf8M6a7/0GtP/AO+X/wAKP+GdNd/6DWn/APfL/wCFAHsTfEzwUqknxLp+B6SZrjfFHx80HToHi0CJ9TuiMLIymOJT6nIyfy/GuPH7OmuZGda08DvhH/wrpND/AGeNKtpVl1rVJ7zbg+TAvlKfqeTj6YoA8q07TPE/xa8WtLI7zSOR51wwxHbp6D09gOtfU/hnw7Y+FdBttI09MQwjlj96Rj1Y+5NWdJ0fTtDsEstMs4rW3Toka4z7n1PuavUAFFFFAHhX7R//AB7aB/vzfyWvQPgj/wAki0T63H/o+SvP/wBo/wD49tA/35v5LXoHwR/5JFon1uP/AEfJQB6DRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGX4m/5FTWP+vGb/0A18xfAX/kpaf9ecv9K+nfE3/Iqax/14zf+gGvmL4C/wDJS0/685f6UAfUtFFFAFXUdOtdW064sL2IS21whSRD3Br5W8ZeCNd+GfiGPULCSf7Gsm+0vox90/3W9D9eDX1nUN1a297bSW11BHPBINrxyqGVh6EGgDxTwn+0DaSW8dt4ntHinUYN3bruV/cr1H4ZrvYPiz4Gnj3r4ht19pEdSPwIrm/EHwC8N6nI82l3Fxpcrc7ExJF/3yeR+Brkpf2cdR8w+T4gtSnbfAwP6GgD1b/hafgf/oZLP/x7/Cj/AIWn4H/6GSz/APHv8K8m/wCGcdV/6D9l/wB+Wo/4Zx1X/oP2X/flqAPWf+Fp+B/+hks//Hv8KP8Ahafgf/oZLP8A8e/wryb/AIZx1X/oP2X/AH5aj/hnHVf+g/Zf9+WoA9Z/4Wn4H/6GSz/8e/wo/wCFp+B/+hks/wDx7/CvJv8AhnHVf+g/Zf8AflqP+GcdV/6D9l/35agD1n/hafgf/oZLP/x7/Cj/AIWn4H/6GSz/APHv8K8m/wCGcdV/6D9l/wB+Wo/4Zx1X/oP2X/flqAPWf+Fp+B/+hks//Hv8KP8Ahafgf/oZLP8A8e/wryb/AIZx1X/oP2X/AH5aj/hnHVf+g/Zf9+WoA9Z/4Wn4H/6GSz/8e/wo/wCFp+B/+hks/wDx7/CvJv8AhnHVf+g/Zf8AflqP+GcdV/6D9l/35agD1n/hafgf/oZLP/x7/Cj/AIWn4H/6GSz/APHv8K8m/wCGcdV/6D9l/wB+Wo/4Zx1X/oP2X/flqAPWf+Fp+B/+hks//Hv8KP8Ahafgf/oZLP8A8e/wryb/AIZx1X/oP2X/AH5aj/hnHVf+g/Zf9+WoA9Z/4Wn4H/6GSz/8e/wo/wCFp+B/+hks/wDx7/CvJv8AhnHVf+g/Zf8AflqP+GcdV/6D9l/35agD1n/hafgf/oZLP/x7/Cj/AIWn4H/6GSz/APHv8K8m/wCGcdV/6D9l/wB+Wo/4Zx1X/oP2X/flqAIPjn4q0LxLFow0bUobwwtL5nl5+XO3Gcj2r074J/8AJKdJ/wB+f/0c9eCeP/hvd+AEsWudQgu/tZcL5SFdu3HXP1r3v4J/8kp0n/fn/wDRz0Aeg0UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABWZ4k/wCRW1f/AK8pv/QDWnWZ4k/5FbV/+vKb/wBANAHzp+z5/wAlMP8A14y/zWvqqvlX9nz/AJKYf+vGX+a19VUAFFFFABRRRQAUUUUAfMf7R3/I9ad/2D1/9GPXt/gP/kn/AIe/7B0H/oArxD9o7/ketO/7B6/+jHr2/wAB/wDJP/D3/YOg/wDQBQB0NFFFABRXH+N/iRongaJFvWee9kXdHaw/eI9SegFeWy/tH3nmt5PhyAR9t9yc/otAH0FRXz1/w0fqP/Qu2v8A4EN/hR/w0fqP/Qu2v/gQ3+FAH0LRXz1/w0fqP/Qu2v8A4EN/hR/w0fqP/Qu2v/gQ3+FAH0LRXz1/w0fqP/Qu2v8A4EN/hR/w0fqP/Qu2v/gQ3+FAH0LRXz1/w0fqP/Qu2v8A4EN/hR/w0fqP/Qu2v/gQ3+FAH0LRXz1/w0fqP/Qu2v8A4EN/hR/w0fqP/Qu2v/gQ3+FAH0LRXz1/w0fqP/Qu2v8A4EN/hR/w0fqP/Qu2v/gQ3+FAH0LXB/GX/klmsfSL/wBGLXm3/DR+o/8AQu2v/gQ3+FYni7413vizwzd6LLotvbpcbcypMWK4YN0x7UAdJ+zh/rNf+kP/ALNXvlfIXw++I1x4Aa+Nvp0V59rCA+ZIV27c+g967j/ho/Uf+hdtf/Ahv8KAPoWivnr/AIaP1H/oXbX/AMCG/wAKP+Gj9R/6F21/8CG/woA+haK+ev8Aho/Uf+hdtf8AwIb/AAo/4aP1H/oXbX/wIb/CgD6For56/wCGj9R/6F21/wDAhv8ACj/ho/Uf+hdtf/Ahv8KAPoWivnr/AIaP1H/oXbX/AMCG/wAKP+Gj9R/6F21/8CG/woA+haK+ev8Aho/Uf+hdtf8AwIb/AAo/4aP1H/oXbX/wIb/CgD6For56/wCGj9R/6F21/wDAhv8ACj/ho/Uf+hdtf/Ahv8KAPoWivnr/AIaP1HPPh21/8CG/wrtfBnxt0TxNex6ffQNpl7KQse990bt6BuMH6igD1CiiigAooooAKKKKACiiigAooooA8K/aP/49tA/35v5LXoHwR/5JFon1uP8A0fJXn/7R/wDx7aB/vzfyWvQPgj/ySLRPrcf+j5KAPQaKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAy/E3/Iqax/14zf+gGvmL4C/wDJS0/685f6V9O+Jv8AkVNY/wCvGb/0A18xfAX/AJKWn/XnL/SgD6looooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA8I/aP/1Ogf703/stdt8E/wDklOk/78//AKOeuJ/aP/1Ogf703/stdt8E/wDklOk/78//AKOegD0GiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKzPEn/ACK2r/8AXlN/6Aa06zPEn/Irav8A9eU3/oBoA+dP2fP+SmH/AK8Zf5rX1VXyr+z5/wAlMP8A14y/zWvqqgAooooAKKKKACiiigD5j/aO/wCR607/ALB6/wDox69v8B/8k/8AD3/YOg/9AFeIftHf8j1p3/YPX/0Y9e3+A/8Akn/h7/sHQf8AoAoA6GkdgiMx6AZNLUdx/wAe0v8AuH+VAHx5DHe/Ej4jhJZSsuo3Ry558uP/AOsor3+2+CXgWG3SOXS5Z3UYaV7qUFj64VgPyFeHfCH/AJKjpX+9J/6Aa+tK5MROSaSY0cD/AMKX8Bf9ARv/AAMm/wDi6P8AhS/gL/oCN/4GTf8Axdd9RXP7SfcZwP8AwpfwF/0BG/8AAyb/AOLo/wCFL+Av+gI3/gZN/wDF1ueOdfPhrwff6hHn7Rt8q3UDJMr/ACrj8Tn8K5X4b32taVr2p+EvEl/Pe3scUd5bzTyF2ZGADAEk8A8fnVpzcea4F7/hS/gL/oCN/wCBk3/xdH/Cl/AX/QEb/wADJv8A4uu+oqPaT7gcD/wpfwF/0BG/8DJv/i6P+FL+Av8AoCN/4GTf/F0/4r6je6Z4XtJrC7ntZW1GBC8MhQlSTkZHY13S/cX6U3KaSdwOC/4Uv4C/6Ajf+Bk3/wAXR/wpfwF/0BG/8DJv/i676uDutRvV+N9jpy3c4sW0dpWtxIfLL7yNxXpn3ojKb6gN/wCFL+Av+gI3/gZN/wDF0f8ACl/AX/QEb/wMm/8Ai676snxPrB8P+GNS1YR+Y1pA0qp6kDj9aSnNu1wOX/4Uv4C/6Ajf+Bk3/wAXR/wpfwF/0BG/8DJv/i6y9N8MeKNZ8PW/iN/G+pw6nc24uYoIiBaoGG4IY+h4OCa63wD4in8U+C9P1a6jVLiUMkoX7pZWKkj2OM/jVyc0rqQGN/wpfwF/0BG/8DJv/i6P+FL+Av8AoCN/4GTf/F131ef/ABj1DUNO8CmbTL2e0uWuokEsEpjbBPTI5xUxlOTtcB3/AApfwF/0BG/8DJv/AIuj/hS/gL/oCN/4GTf/ABdT/DjxXc61p82kayPL17SyIbpGPMg7SD1z6/412F6zJYXDKSGETEEdQcGiUpp2bA4j/hS/gL/oCN/4GTf/ABdH/Cl/AX/QEb/wMm/+Lqb4R6heap8ObC7v7ue6uXeUNLPIXY4cgZJ5ruKJTnF2uBwP/Cl/AX/QEb/wMm/+Lo/4Uv4C/wCgI3/gZN/8XXfUUvaT7gcD/wAKX8Bf9ARv/Ayb/wCLo/4Uv4C/6Ajf+Bk3/wAXXfUUe0n3A4H/AIUv4C/6Ajf+Bk3/AMXR/wAKX8Bf9ARv/Ayb/wCLrvqKPaT7gcD/AMKX8Bf9ARv/AAMm/wDi6P8AhS/gL/oCN/4GTf8Axdd9RR7SfcDgf+FL+Av+gI3/AIFzf/F14h8VvAcHgbXLY6dJI1hdqXiDnLRsDyue/UYr6trwj9ozpoP/AG1/9lrWhUk52bBnp/wz1yfxD8PdJv7pi1x5ZilY/wATIxXP4gA11tee/BL/AJJbp3/XSb/0M16FXcSFFFFABRRRQAUUUUAFFFFAHhX7R/8Ax7aB/vzfyWvQPgj/AMki0T63H/o+SvP/ANo//j20D/fm/ktegfBH/kkWifW4/wDR8lAHoNFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAZfib/kVNY/68Zv/AEA18xfAX/kpaf8AXnL/AEr6d8Tf8iprH/XjN/6Aa+YvgL/yUtP+vOX+lAH1LRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB4R+0f/AKnQP96b/wBlrtvgn/ySnSf9+f8A9HPXE/tH/wCp0D/em/8AZa7b4J/8kp0n/fn/APRz0Aeg0UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABWZ4k/5FbV/wDrym/9ANadZniT/kVtX/68pv8A0A0AfOn7Pn/JTD/14y/zWvqqvlX9nz/kph/68Zf5rX1VQAUUUUAFFFFABRRRQB8x/tHf8j1p3/YPX/0Y9e3+A/8Akn/h7/sHQf8AoArxD9o7/ketO/7B6/8Aox69v8B/8k/8Pf8AYOg/9AFAHQ1Hcf8AHtL/ALh/lUlR3H/HtL/uH+VAHyV8If8AkqOlf70n/oBr60r5L+EP/JUdK/3pP/QDX1pXFifiRSCiioL28h0+xuLy4cJDBG0jseygZNcwzg/EBHif4oaPoI+ey0hP7RvO4MnSNT79/wAai+JSvoOt+HvGcIO2yuBbXuO8EnBP4c/nWJ4Q8G6h4rt7zxdL4h1fSbjV7h5RHZShAYgcJnjJ4rZ1T4UXOpaZPaXHjXxFcxyIf3M9wGRiORkY6ZxXR7sZJX2Edrr2uQaH4ZvdafEkNvAZQAfv+g/EkVwmh/D8eLtMh1vxrdXd7d3iiaO1Wd4orZDyqqqkc4NY/wBuu/EPwA1nTJd/9paSv2W4UHLfunVufqq/oa9U8N30Gp+GtMvLZg0UttGVx2+UZH4dKlpwjpvcDyD4kaDf+FdPsLK1vbi70K6v4SkVzIZHtZFbOFY8lWBPB6YrvfH+vajp9ppmjaI4j1bV5hBDKRkQrjLP+ArH+Nd9bw6DpFm7r59xqUTRr3IU8n9R+dWPG7rYfEDwRqlwxW1WaW3Zj91XdQFzVL3lFvzAmh+EOgCNZrm71SfVMfNqBvXEu71GDgfTFc5oEWrWnxzt9P1e4N1JaaVJFDdEYaeLdlWb/a5wfpXsdeXm+t7v9omKKF1ZrbSGilx2bdux+TCphOUr37AeoVn65LpsOiXjavLFHp5iZZ2lOF2kYNaFeb+NFTVfid4U0LUT/wASp45bkwsfkuJl+6pHfGAce9ZwV2Bxeg63rcsUPgm2u3sNFvZJE0/Vr2Fkkkt/+eaA8FjngnHH4V7bo2lWegaRaaVYrst7dNkak8n1J9ycn8apeKfC9l4p0NtOuP3TIQ9vOgw0Eg+6y/SvNfButar4h+JtrYaxcQi68P2s0Mrxygi6ctgMAPbGf6Vq/wB4rrSwHs1ec/Gv/kRE/wCv6D/0KvRq85+Nf/IiJ/1/Qf8AoVZ0vjQMZ470a80qey8daDGTf6fGBeQL/wAvNvjkEdyB/niuxs9Zs/EHhX+1LCTfb3FuzKe44OQfcHitOJQ1qisAQUAIPfivJ2J+F/ie606QlfC2thzbMfu2twR9z6H/AA9DVL31bqgNT4SXsOnfB62vZziG3E8rn2DsTVPQfDE/xJs/+Ei8WXN21ndEmy0yGZooo4s/KWxgljjr/kVvBVlNqP7O9zZ24JmmtrpUA7nc3Fdp8NtQt9R+HuivbsD5VqkDgfwug2kH8R+tVN25mt7gcnrej3Hwt+z67oF3dPoaSrHf6bPKZFWNiBvjJ5BH1qX4j316PFHgufRtr3U7zrbluVBeMKGPsN2fwra+Ld9Da/DrUoHAaa8C20Efd3ZhjH6n8KytXt3tfFnw2tpR+8iWVG+ohANODvaT31/IDe0TwLZaDPJq0t5fX+sNC6SXdzOxznkgL0AyOK4vwF4fuvHXhhJfEuoX02nQyyxQWyXDL5x3ks8jA5brgDOBivXrj/j2l/3D/KuK+EX/ACTqy/67T/8AoxqhTfK31A5LVtI1PwJ4w0vR/CeoTxWGuK0BguHaUWzAjMiZ7gc10Wo/CTRHs5rm3vNUj1hYyyag17I0m8c5POMewFSeL/8Akp3gn/rpcf8AoFd5cf8AHtL/ALh/lTlOSSaA5f4ba5deIfA1je3z+ZdLuhlkxjeyMVz9Tiusrz74Mf8AJPIv+vu4/wDQzXoNRUVpMArwj9ozpoP/AG1/9lr3evCP2jOmg/8AbX/2WrofxEDO5+CX/JLdO/66Tf8AoZrb8SfEPwx4WVl1HU4jOBn7PCfMk/IdPxxXlvhLwn4k8S/CLTk0TxNJp6bpg1rs2rL856uvzD6civK/EvgXxN4YldtW02dY8/8AHyn7yNvfcP616BJ7bofxZ1Lxz4sh0rQ7OPTtNX95c3VyQ0gjHUAfdBJ4HXrXrX2y1/5+Yf8Av4K+K/DnhjU/FeoNYaTHHLcqhfy3lVCQOuM9a6r/AIUl47/6BcX/AIEx/wCNAH1WLy2JwLiHP++KlBDDIII9RXyc3wV8eRrvXSkLLyAt1Hn8PmqoNR+IPw8uk82TU9PGeEmy8T/nlTQB9e0V5P8ADz40WXiWWPS9bSOx1NsLHID+6nPoM/db2/8A1V6xQAUUUUAeFftH/wDHtoH+/N/Ja9A+CP8AySLRPrcf+j5K8/8A2j/+PbQP9+b+S16B8Ef+SRaJ9bj/ANHyUAeg0UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAfMj+INf8MfFXxP4ktBNdaVYai0N/BvJAikcgcdByOD2OPWvpHTtRtdW0231CxmWa1uIxJHIvQg15X8O7O31Dx78TLO7iWa3nvRHJG4yGUtICKh8HXlx8MfG8ngXVZnbRb9/N0a6kIwpY8xk+pJx9ecfNQB6F4+do/h54jdGKsum3BDA4IPlmqHwqkeX4YaA8js7tb8sxyT8xq78Qf8AknPiT/sGXH/os1n/AAoz/wAKq0DaQD9mOCRn+JqAO0orgvDfjPULfxFL4U8YRxW2rlmayuYxthvo8kjZ6MBxj+tbfjDxhY+ENMWedWuL2dvLs7KLmS4kPRVHp6nt+QoA6KisXwq2vvoEMviUW66lIWd47dcLEpOVQnPJA4z/AD6naoAKKKKAMvxN/wAiprH/AF4zf+gGvmL4C/8AJS0/685f6V9O+Jv+RU1j/rxm/wDQDXzF8Bf+Slp/15y/0oA+paKKKACiiigAooooAKKKKACiiigArn/EPjbw74VAGsapDBIRkRDLuR/ujJpnjvxJ/wAIn4O1DV1AM0abIQehkbhf1Ofwr5f8K+E9b+JniK6Iuvn/ANbd3k+W25zjjuTg4HtSbSV2B73/AMLz8Df8/wBdf+Ar/wCFH/C8/A3/AD/XX/gK/wDhXEf8M4Sf9DSn/gAf/jlH/DOEn/Q0p/4AH/45Wft6fcdjt/8Ahefgb/n+uv8AwFf/AAo/4Xn4G/5/rr/wFf8AwriP+GcJP+hpT/wAP/xyj/hnCT/oaU/8AD/8co9vT7hY7f8A4Xn4G/5/rr/wFf8Awo/4Xn4G/wCf66/8BX/wriP+GcJP+hpT/wAAD/8AHKP+GcJP+hpT/wAAD/8AHKPb0+4WO3/4Xn4G/wCf66/8BX/wo/4Xn4G/5/rr/wABX/wriP8AhnCT/oaU/wDAA/8Axyj/AIZwk/6GlP8AwAP/AMco9vT7hY7f/hefgb/n+uv/AAFf/Cj/AIXn4G/5/rr/AMBX/wAK4j/hnCT/AKGlP/AA/wDxyj/hnCT/AKGlP/AA/wDxyj29PuFjt/8Ahefgb/n+uv8AwFf/AAo/4Xn4G/5/rr/wFf8AwriP+GcJP+hpT/wAP/xyj/hnCT/oaU/8AD/8co9vT7hY7f8A4Xn4G/5/rr/wFf8Awo/4Xn4G/wCf66/8BX/wriP+GcJP+hpT/wAAD/8AHKP+GcJP+hpT/wAAD/8AHKPb0+4WMP4y+O9C8Zx6SNGnllNsZDJ5kRTGduOv0NdN8M/ir4V8M+AtP0nU7qeO7haUuqQMwG6RmHI9iKq/8M4Sf9DSn/gAf/jlH/DOEn/Q0p/4AH/45R7en3Cx2/8AwvPwN/z/AF1/4Cv/AIUf8Lz8Df8AP9df+Ar/AOFcR/wzhJ/0NKf+AB/+OUf8M4Sf9DSn/gAf/jlHt6fcLHb/APC8/A3/AD/XX/gK/wDhR/wvPwN/z/XX/gK/+FcR/wAM4Sf9DSn/AIAH/wCOUf8ADOEn/Q0p/wCAB/8AjlHt6fcLHb/8Lz8Df8/11/4Cv/hR/wALz8Df8/11/wCAr/4VxH/DOEn/AENKf+AB/wDjlH/DOEn/AENKf+AB/wDjlHt6fcLHb/8AC8/A3/P9df8AgK/+FH/C8/A3/P8AXX/gK/8AhXEf8M4Sf9DSn/gAf/jlH/DOEn/Q0p/4AH/45R7en3Cx2/8AwvPwN/z/AF1/4Cv/AIUf8Lz8Df8AP9df+Ar/AOFcR/wzhJ/0NKf+AB/+OUf8M4Sf9DSn/gAf/jlHt6fcLHb/APC8/A3/AD/XX/gK/wDhR/wvPwN/z/XX/gK/+FcR/wAM4Sf9DSn/AIAH/wCOUf8ADOEn/Q0p/wCAB/8AjlHt6fcLHb/8Lz8Df8/11/4Cv/hUkHxu8CzSrH/aU0ef4pLZwPzxXCf8M4Sf9DSn/gAf/jlQXn7Ol7FayPaeIoZ51GVje1MYY+m7ecflR7en3Cx73puqWOr2SXmnXcN1bv8AdkiYMDVuvkv4c+JtR8B+O0sbovHbS3Atb23Y8A527vqDX1p1rUQVmeJP+RW1f/rym/8AQDWnWZ4k/wCRW1f/AK8pv/QDQB86fs+f8lMP/XjL/Na+qq+Vf2fP+SmH/rxl/mtfVVABRRRQAUUUUAFFFFAHzH+0d/yPWnf9g9f/AEY9e3+A/wDkn/h7/sHQf+gCvEP2jv8AketO/wCwev8A6Mevb/Af/JP/AA9/2DoP/QBQB0NRzgm3kAGSVP8AKpKKAPkL4UTx23xQ0hpnCBpWQE+pUgD86+uK+Zfip8N9S8Na/PrelQSy6ZPL5yvCCTbOTkg46DPINZtr8a/G9rbRwf2hDLsGA8tupY/U45rnrUXN3Q0z6srF8V6C/ifw7c6OL57NLnCySIm5imckDkdelfOf/C8vG/8Az92n/gKtH/C8vG//AD92n/gKtZLDzTuh3Pp6wsodN062sbdQsFvEsUYHZVGB/KrFfLP/AAvLxv8A8/dp/wCAq0f8Ly8b/wDP3af+Aq0vq0wufQOmeD4NL8U6zrEN0zQasq+fZNGNm8DG7Oe/PGO9YMfw/wBc8PyzJ4P8THT7GVy/2O6gE6Rk9dhPQe1eOf8AC8vG/wDz92n/AICrR/wvLxv/AM/dp/4CrV+xqd0K6PZLr4XDVYJJ9Y1y5vdWkkjb7W8Y2xKjbtkaDhQe9dZ4h8Oaf4n0SXStSjZ4HwQynDIw6Mp7EV83/wDC8vG//P3af+Aq0f8AC8vG/wDz92n/AICrSdGq+oXR7ND4R8b2yLYw+OSdPUbQ8lmrThf989/er2ifDqw0HxBZ6va3c7yw20kMvnfM9w7tuaR29fwrwv8A4Xl43/5+7T/wFWj/AIXl43/5+7T/AMBVpulV7oLo+pq53xd4PsvF1lBHPNNa3dq/m2t3bnEkL+o9uBkV89/8Ly8b/wDP3af+Aq0f8Ly8b/8AP3af+Aq1Kw9RO6Y7nsp8IeOLqI2N745P2Ajaz29mqTsv+/2OM81Ym+F+kQWumf2LLJpl/p0nmRXqAPJJn7wk6bwfevEv+F5eN/8An7tP/AVaP+F5eN/+fu0/8BVqvZVe6FdH1IgYRqHYM4A3EDAJ+lYPjHwtH4v0RdMlumtlE6Tb1TcflOcYyK+ef+F5eN/+fu0/8BVo/wCF5eN/+fu0/wDAValYead0x3PqRF2Rquc7QBWT4n8OWPivQbnSb9T5Uo+VwPmjYdGHuK+cf+F5eN/+fu0/8BVo/wCF5eN/+fu0/wDAVaFh5p3TC59EeDvDMfhDw1b6LHctcpCznzWTaTuYnpk+tYF18P8AUNN1O51Dwfrz6Qbpi89pJEJYGcnlgp+6a8W/4Xl43/5+7T/wFWj/AIXl43/5+7T/AMBVpqjUve6FdHtuneAbq41q21nxXrT6zd2p3W0IiEcETf3gg6mt3VvDceq+ItF1drlo20t5HWMJkSb128nPGK+df+F5eN/+fu0/8BVo/wCF5eN/+fu0/wDAVaHRqXvcLo+pJE8yNkzjcCM1j+FPDqeFvD8Okx3DXCxO7eYy7SdzFun4185/8Ly8b/8AP3af+Aq0f8Ly8b/8/dp/4CrS+rzta47n0Tq3hmPVfEmjay1y0baY0hWIJkSbhjk54rbkXfGyZxuBGa+W/wDheXjf/n7tP/AVaP8AheXjf/n7tP8AwFWh4eb6hc+iPB/hmPwjoC6VFdNcqssknmMm0/M2cYzW9Xyz/wALy8b/APP3af8AgKtH/C8vG/8Az92n/gKtDw827thc+pq8E/aLuIjcaHbhwZVWVyvcAkAH9DXJ/wDC8vG+P+Pu0/8AAVaytK0TxT8UfEvnSGe5kkIE97KuI4lH04GOyirpUJRldibPoD4JqV+FumEgjLyke/7xq790SRCkiqykYKsMg1R0LSLfQNDstJtAfItYhGpPU46k/U5NaFdQjj7j4a+Hv7ct9a02BtL1K3kEiy2eEVvUMnQg9D0rsKKKACq99YWmpWklpe20VxbyDDxyqGUj6GrFFAHy98WPhifBtyusaRvOkTPjaTlrdzyBn+76H8K9Y+DnjmTxb4bezv5N+p6fhJGJ5lQ/db68YP0967XxHo8HiDw7f6VcqDHcwsnP8JxwfwODXzN8G9Qm0X4pWlo5Ki58y0lA9cEj/wAeUUAfVtFFFAHhX7R//HtoH+/N/Ja9A+CP/JItE+tx/wCj5K8//aP/AOPbQP8Afm/ktegfBH/kkWifW4/9HyUAeg0UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAeT/C//kpXxG/7CC/+hSV1nxC8Fw+NfDUlmGEWoQHzrK46GOUdORzg9D+faue+HOl6hY/EDx7c3dhdW9vdXyvbyywsiyruflSRhhyOnrXptAHjun+M5vEfwi8VaVqwaLxBpOnXFvexvwzYRgH98459/qK6/wCE3/JLPD//AF7n/wBCauM+MvgPU52fxR4Xhma/kha01C3tkLPcRONuQoGWODg+2D2rufhnZ3dh8NdEtbu3ltrqO3IeKeMoyHceqnkUAZPxfk0D/hFVg1SOSTU5XxpKW3/Hz9o4wYz1AzjPt74rlfh4J7Lx60XxC88+LJLdBpst0ytF5OOVjI4Emc57nnuTntfC/gi6t9euPFHii5i1DX5SUhMYPk2kXICxg+o6nrz9Sdnxd4R07xjo5sL8MkiN5lvcx8SQSDoyn+negDforF8KW2u2fh+C28RXdvd6hEWQzwggSID8pOf4iMZraoAKKKKAMvxN/wAiprH/AF4zf+gGvmL4C/8AJS0/685f6V9O+Jv+RU1j/rxm/wDQDXzF8Bf+Slp/15y/0oA+paKKKACiiigAorN1TxBo+iR79U1S0sx28+ZVJ+gJya5p/i74FRyv9vwnHGVjcj+VAHb0Vw//AAt/wL/0HY/+/T//ABNH/C3/AAL/ANB2P/v0/wD8TQB3FFfNuu/FK88M+LJZvCmuJqWiXH737JcKzLEx+8o3AEDPIwe9dx4Z+Pfh/VNkGswy6XcHgyH54ifqOR+I/GgC58ej/wAW0f3vIv61zP7OQH9na+e/mw/yetz426hZan8LDc2F3BdQNdwkSQyB1PXuKw/2cv8AkHa//wBdof5NWNf+Gxrc9vooorzygri/iH4w1DwvZ2cOi2cN5qt3I3lwSgkeWilnbAI6YHfvXaV534dA8U/EvWtfbEljpif2ZZ9wW6yt+fH0NXBLd7IR1nhbXYvEvhmw1iLAFzEGZR/C/Rh+BBrYrzfwA58O+L/EXg6XKwpL9usM94n+8B9Dj9a6Xxn4qXwrpMc0ds13f3Uot7O1XrLIen4DvRKHvWQHR1ykvie8j+KEHhgQwfY5NMN4ZCD5m/eVxnOMYHpWVFpfxOlRb2TxJpUMxG7+z/sIaIH+6ZPvfjXP6BrN1rPxxtzf2Zs9QtdGe3uoc5USCQnKnupBBH1qow36gewUVxHiXxVq8niSPwr4Wggk1Mxia6urgExWkZ6EgdSfT6VVlT4h+G4G1G41Sz8Q20fzz2i2gglCd/LK8Egc4PWpUH3A1vA3ie88T2+sSXkMEZstSms4/JBGUTGCck8811deafBi5jvdG8QXUJJim1qeRCRjKkKR/OvS6KitJoDmvGPiz/hGLS1S3s2vdSvphBZ2qtt3v6k9gK5+Txj4s8N3VpJ4v0jTU0y6mWH7Tp0rMbdmPG8N1HuKtfE7TZzpdj4ismjF7oU4u1WVtqyJ/GufXHSsW51l/i2lhp+j2s8WixTxz6jeTDaMr83lJ6nPU9quEVyp206geqg5GRRSABQAOg4paxGeaeOPiddeDfG+nabJZwy6VLCstzIFYyoCxXIIOMDjqK9HgniureO4gkWSKVQ6OpyGBGQRXmOv2Ntqfxz0+xu4hLbz6LLHIjdCCWqXwTfXPg3xHL4D1eUtAczaRcuf9ZGT/q8+o54/+tW0oJxVt7COi+IPie88J+HotQsoYJZXuooCs4JXaxwTwRzXUo26NWPUgGvO/jT/AMiVbf8AYRg/ma6nxL4ltPCfhp9Vu1ZwgVY4k+9K5+6o+tTy3irbgbtFed21l8TdYhXUJNc07Rd/zpp62Qm2jsHZuQfXFX/Cvi3Up9dufDHia1ittagTzY5Ic+VdR/3kzz+FJwfRgdrRXmD+MvEs/jLXvDmkpFdXiToLXz0CxWsWzLO5UZPJAArQ1/WPEfgjwNNqWp6na6jei7jBkFr5aJGzAFQoPOBnBNP2b0QXO/orz8R/EHxFAupWWrWWhW0g329o9oJpGQ8gyM33SfQdKzdF8beLNenuPDMNla23iGxkZL68kUtbxoOjKvUs3YdOM0ezfcLnqVFeY6lq3jXwHPZ3+u6raa3o01wsNwyWogkg3HAIxwR9a9OqZRtqAUUUVIz5G8f8fF3Vccf6ev8A7LX13D/qY/8AdH8q+RPiB/yV3Vf+v9f/AGWvruH/AFEf+6P5V6kfhRA+szxJ/wAitq//AF5Tf+gGtOszxJ/yK2r/APXlN/6AaoD50/Z8/wCSmH/rxl/mtfVVfKv7Pn/JTD/14y/zWvqqgAooooAKKKKACiiigD5j/aO/5HrTv+wev/ox69v8B/8AJP8Aw9/2DoP/AEAV4h+0d/yPWnf9g9f/AEY9e3+A/wDkn/h7/sHQf+gCgDoaKKKAEIDAhgCD1BrNk8N6FM5eTRdOdz1ZrVCT+leefE34wR+ErptI0eKK51QLmV3OY4M9AQOre1eRN8Y/H8zs66wwBPRLWPA9vu0AfTv/AAi/h/8A6AWmf+Akf+FH/CL+H/8AoBaZ/wCAkf8AhXzD/wALe+IX/QYl/wDAWP8A+Jo/4W98Qv8AoMS/+Asf/wATQB9Pf8Iv4f8A+gFpn/gJH/hR/wAIv4f/AOgFpn/gJH/hXzD/AMLe+IX/AEGJf/AWP/4mj/hb3xC/6DEv/gLH/wDE0AfT3/CL+H/+gFpn/gJH/hR/wi/h/wD6AWmf+Akf+FfMP/C3viF/0GJf/AWP/wCJo/4W98Qv+gxL/wCAsf8A8TQB9Pf8Iv4f/wCgFpn/AICR/wCFH/CL+H/+gFpn/gJH/hXzD/wt74hf9BiX/wABY/8A4mj/AIW98Qv+gxL/AOAsf/xNAH09/wAIv4f/AOgFpn/gJH/hR/wi/h//AKAWmf8AgJH/AIV8w/8AC3viF/0GJf8AwFj/APiaP+FvfEL/AKDEv/gLH/8AE0AfT3/CL+H/APoBaZ/4CR/4Uf8ACL+H/wDoBaZ/4CR/4V8w/wDC3viF/wBBiX/wFj/+Jo/4W98Qv+gxL/4Cx/8AxNAH09/wi/h//oBaZ/4CR/4VxPxc0HR7L4Z6tPa6TYQTL5e2SK2RWH7xehAzXi//AAt74hf9BiX/AMBY/wD4mqGs/EXxnr+lzabqeoyT2k2N8f2dFzggjkKD1AoA739n3S9P1KTXBfWNtdbBFt8+FX2/e6ZHFe4f8Iv4f/6AWmf+Akf+FfIfhzxX4j8Jm4OiXMlqbjHmYhVt2M4+8D6mt7/hb3xC/wCgxL/4Cx//ABNAH09/wi/h/wD6AWmf+Akf+FH/AAi/h/8A6AWmf+Akf+FfMP8Awt74hf8AQYl/8BY//iaP+FvfEL/oMS/+Asf/AMTQB9Pf8Iv4f/6AWmf+Akf+FH/CL+H/APoBaZ/4CR/4V8w/8Le+IX/QYl/8BY//AImj/hb3xC/6DEv/AICx/wDxNAH09/wi/h//AKAWmf8AgJH/AIUf8Iv4f/6AWmf+Akf+FfMP/C3viF/0GJf/AAFj/wDiaP8Ahb3xC/6DEv8A4Cx//E0AfT3/AAi/h/8A6AWmf+Akf+FH/CL+H/8AoBaZ/wCAkf8AhXzD/wALe+IX/QYl/wDAWP8A+Jo/4W98Qv8AoMS/+Asf/wATQB9Pf8Iv4f8A+gFpn/gJH/hR/wAIv4f/AOgFpn/gJH/hXzD/AMLe+IX/AEGJf/AWP/4mj/hb3xC/6DEv/gLH/wDE0AfT3/CL+H/+gFpn/gJH/hR/wi/h/wD6AWmf+Akf+FfMP/C3viF/0GJf/AWP/wCJo/4W98Qv+gxL/wCAsf8A8TQB9Pjwv4fByNC0zP8A16R/4VowW8NtEIreGOKMdEjUKB+Ar5P/AOFvfEH/AKDEn/gLH/8AE11Xg3496nBfxWvihY7m0chTdRxhJI/cgcEfgDQB9FUVHBPFcwRzwSLJFIodHU5DA8gipKACiiigAooooAK+SPCPHxtssf8AQXf/ANDavrevkjwj/wAltsv+wu//AKG1AH1vRRRQB4V+0f8A8e2gf7838lr0D4I/8ki0T63H/o+SvP8A9o//AI9tA/35v5LXoHwR/wCSRaJ9bj/0fJQB6DRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGX4m/5FTWP+vGb/ANANfMXwF/5KWn/XnL/Svp3xN/yKmsf9eM3/AKAa+YvgL/yUtP8Arzl/pQB9S0UUUAFeF/Ev41va3E2i+FpV3oSk1+OcHuE+n978q6b42eMpPDXhVbCykKX2pExqynBSMfeI9+QPxrzr4L/DeHxDOfEOsQ+Zp9vJtt4WHE0g6k+qj9T9KAOc0H4ceM/Hkn9pOkghlOTe30hG/wCmfmb8sV2kX7OF4Y1MviKBXxyFtiQPxyK+gVVUUKqhVAwABgCloA8A/wCGcLn/AKGSL/wFP/xVH/DOFz/0MkX/AICn/wCKr3+igD428W+DD4d8Uf8ACP2F42rXiqPMWCAjax6LjJycY/Oup8M/ArxLrOybVCmk2zc/vfnlI/3AePxIr6Q07Q9M0qSaWysoYppnLyyhcu7E5JLHk1oUAeA/Eb4caN4H+Gcr2D3M1zJdRLJNNIfmHP8ACPlHT0zVr9nL/kHa/wD9dof5NXS/Hr/kmr/9fkX9a5r9nL/kHa//ANdYf5PWNf8Ahsa3Pb6KKK88o53x14hHhjwdqGpqf3ypsgA6mRvlXH4nP4VxHhTS/iV4Z8PW+nWWmeHmjGZGeeeXzGZjklscZ5/Suk8XeHdS8S+KfD8JhX+wrKU3V07OMvIB8ihep5/nXa1pzKMbCPEvEsvjLRPE+i+NNfstKt7eykFtcPYSOxaKQ4O8N2GTj3NdR4tZJvij4HMmxrVvPdCehfaNtdh4l0WLxF4b1DSZQNtzCUBPZuqn8CAa4r/hC9d1n4e6RaX0iWPiTR3D2lxvDjKcLkjPBGM/SrUk7N+gHpVeaOsS/tERGMDe2hkyY9d/+GKtw+KvHaItnP4I8y+AwblLxRbk+vqB7VU8O+Ctf0/4jReJNVmiuZbmykF5LG2EjlLDbGinnaFAGamMeW930An8DAN8RvHbzBftP2qJffy9p216J1rgvEXh3XNN8WDxb4WSGe4liEN/YStsFwg6FT2YCo5tY8c+JLZ9Ps/Dn9g+b8kt9d3CuY1PUoqjlsdKJLmd0wK3wZWJdI8QrBjyhrU4THTbhcfpXpVcV8NfCl14Q0vVLC4TbE+oSS253hi0W1QCcd+K7WpqNObaBHmVhaj4jeMNXm1YmTRNEujaW9hn5JZl+88g7+w6U7W7Kb4c66/ifSYC2gXJC6rYxDAh7CZB/MD/APU+80XxN4Q8V6jrXhuzi1TTNTYS3Vg0uyRJe7ITxz/Wi/m8b+N7ZtLXRx4c06YFLu4uZhJMyHqsYXoSO5rW+u+gGv4A8RXnihNa1GSXzNOGoPFp7bAuYV7/AIk967GuD8IeGtY8E6xNpFtuvfDE2ZYJHkHmWrnqpBxlT7ev1rvKyqW5tNgPNdQ/5OC0j/sESfzat7x94S/4SnRFNo/k6tZP9osbgcFZBzjPof8ACq154d1Kb4uaf4gSJTp0OnvA8m8ZDknA29e9drTlKzi12A8P8WeLR4q+Ftu1ynk6rZ6nBBfW54McgYjOPQ4zXT/En5tV8ERzgGybVE80H7pbA25/Ws34k/DHUNZ1uDWPDoUSTyJ/aFuZAiybSCr88EjkV3Xi3wtD4s8NNpk0hgmUrJBOvWKVejCtOaK5WvMDoa878X+WnxZ8DNESLpjcq23qY9nOfbr+tFt4k8faTCthqPhD+07lPkF7Z3SrHJ6MQRke9WvC/hjWJ/Es3i3xS0K6k8Xk2lpC25LWI9Rnux7/AI1EVy3bYEHg2KP/AIWX43m2jzPOgXd3xszipPjAofwE6sMq15bgg9x5grR8N6Ff6d4x8UajcxqttfyxNbsHBLBVwcjtzTviHod94h8LGx06NZLj7TDJtZwo2q4J5PtTuvaJ+gHTxACFABgBRXAeCEUfEfx6+0bzc24z3x5Zr0BAQig9QBXKeGNBv9M8YeK9RuolW21GeJ7dg4JYKmDkdufWoi9GBj/G/wD5Jfff9dof/QxXoo6CuO+KHh/UfE/ga60vS4llu5JI2VWcKMBgTyfauxHShv3EvUAoooqBnyN8QP8Akruq/wDX+v8A7LX13D/qI/8AdH8q+RPiB/yV3Vf+v9f/AGWvruH/AFEf+6P5V6kfhRA+szxJ/wAitq//AF5Tf+gGtOszxJ/yK2r/APXlN/6AaoD50/Z8/wCSmH/rxl/mtfVVfKv7Pn/JTD/14y/zWvqqgAooooAKKKKACiiigD5j/aO/5HrTv+wev/ox69v8B/8AJP8Aw9/2DoP/AEAV4h+0d/yPWnf9g9f/AEY9e3+A/wDkn/h7/sHQf+gCgDoaKKKAPjXQLYeMviTax6gzFdQvS83PJGSxGfoMV9YWmj6bY2yW9rYW0MKDCokQAAr5X+GH/JT9E/6+G/8AQWr61rjxLfMkdNBKzZB9jtf+faH/AL9ij7Ha/wDPtD/37FT0VzXN7EH2O1/59of+/Yo+x2v/AD7Q/wDfsVPRRcLEH2O1/wCfaH/v2KPsdr/z7Q/9+xU9FFwsQfY7X/n2h/79ij7Ha/8APtD/AN+xXl3xws5dStvDlhC+yS5vzEpz3K4Fdb8Odak1vwZZvcE/bLTNpcg9RJHwc++MH8a0cGoKVyFJc3KdJ9jtf+faH/v2KPsdr/z7Q/8AfsU+eeO2t5Z5WCxxIXdj2AGTXhPg2e91T4w6f4gunYR6st3Lbxn+GJQyr/KlCLkm77BKSTSPc/sdr/z7Q/8AfsUfY7X/AJ9of+/Yp808NtEZZ5UijXq7sFA/E1Tsdd0jU5DHYarY3bjqsFwkhH4A1OpWhZ+x2v8Az7Q/9+xR9jtf+faH/v2KnrOk1/RobsWkur2CXJOBC1ygc/8AAc5o1DQtfY7X/n2h/wC/Yo+x2v8Az7Q/9+xUWqkHRb0g5Bt5CCP901zvwvJPw20QkknyDyf9407PluK+tjp/sdr/AM+0P/fsUfY7X/n2h/79inS3NvA6JNPFGz8IruAW+metOlljhjMksixovJZjgD8anUehH9jtf+faH/v2KPsdr/z7Q/8AfsVXstb0nUpGjsdUsrp1+8sFwjkfUA1fp6oNCD7Ha/8APtD/AN+xR9jtf+faH/v2Kr3et6Tp86w3uqWVtK/CpNcIjH6AmuK+IcofxB4IeNwyNqgwVOQRgU4pt2E2kjvfsdr/AM+0P/fsUfY7X/n2h/79ip6Km5ViD7Ha/wDPtD/37FH2O1/59of+/Yqeii4WIPsdr/z7Q/8AfsUfY7X/AJ9of+/Yqeii4WIPsVr/AM+0P/fsV8/fHXwxpuj6jp+pafbpbteB1mjjXapZcfNjsea+iK8Q/aI/49tB/wB+b+S1tQb50ZVUuU734MXk158MNMM7lzC0kSk9doY4H4Dj8K7+vOPgb/yTCz/67y/+hV6PXecgUUUUAFFFFABXyR4R/wCS22X/AGF3/wDQ2r63r5I8I/8AJbbL/sLv/wChtQB9b0UUUAeFftH/APHtoH+/N/Ja9A+CP/JItE+tx/6Pkrz/APaP/wCPbQP9+b+S16B8Ef8AkkWifW4/9HyUAeg0UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQBl+Jv+RU1j/rxm/wDQDXzF8Bf+Slp/15y/0r6d8Tf8iprH/XjN/wCgGvmL4C/8lLT/AK85f6UAfUtFFFAHy78etQe7+In2Yk+XaWscajPc5Y/z/SvofwfpMeh+D9J06NQohtk3Y7sRlj+ZNfNHxr/5KhqP+5F/6AK+rLT/AI84P+ua/wAqAJqKKKACiiigAooooA5f4heG38V+CdQ0qHH2hlEkGe7qcgfjjH4180eCfGuqfDbXroPZmSOQiO7s5DsOVzjnBwRk9u9fX9cr4m+HPhjxbJ52p6ev2nGPtEJ8uQ/Ujr+OaTSaswPOv+Gi9M/6F+7/AO/6/wCFH/DRemf9C/d/9/1/wrc/4UB4N/56an/4EL/8TR/woDwb/wA9NT/8CF/+JrL2FPsO5h/8NF6Z/wBC/d/9/wBf8KP+Gi9M/wChfu/+/wCv+Fbn/CgPBv8Az01P/wACF/8AiaP+FAeDf+emp/8AgQv/AMTR7Cn2C5h/8NF6Z/0L93/3/X/Cj/hovTP+hfu/+/6/4Vuf8KA8G/8APTU//Ahf/iaP+FAeDf8Anpqf/gQv/wATR7Cn2C5h/wDDRemf9C/d/wDf9f8ACj/hovTP+hfu/wDv+v8AhW5/woDwb/z01P8A8CF/+Jo/4UB4N/56an/4EL/8TR7Cn2C5h/8ADRemf9C/d/8Af9f8KP8AhovTP+hfu/8Av+v+Fbn/AAoDwb/z01P/AMCF/wDiaP8AhQHg3/npqf8A4EL/APE0ewp9guYf/DRemf8AQv3f/f8AX/Cj/hovTP8AoX7v/v8Ar/hW5/woDwb/AM9NT/8AAhf/AImj/hQHg3/npqf/AIEL/wDE0ewp9guYf/DRemf9C/d/9/1/wo/4aL0z/oX7v/v+v+Fbn/CgPBv/AD01P/wIX/4mj/hQHg3/AJ6an/4EL/8AE0ewp9guYf8Aw0Xpn/Qv3f8A3/X/AAo/4aL0z/oX7v8A7/r/AIVxvxe+H2i+B49LbSWuiboyCTz5A33cYxgD1ro/hx8IvDXirwNY6xqL3wup2lDiKYKvyyMowNp7AUewp9guX/8AhovTP+hfu/8Av+v+FH/DRemf9C/d/wDf9f8ACtz/AIUB4N/56an/AOBC/wDxNH/CgPBv/PTU/wDwIX/4mj2FPsFzD/4aL0z/AKF+7/7/AK/4Uf8ADRemf9C/d/8Af9f8K3P+FAeDf+emp/8AgQv/AMTR/wAKA8G/89NT/wDAhf8A4mj2FPsFzD/4aL0z/oX7v/v+v+FH/DRemf8AQv3f/f8AX/Ctz/hQHg3/AJ6an/4EL/8AE0f8KA8G/wDPTU//AAIX/wCJo9hT7Bcw/wDhovTP+hfu/wDv+v8AhR/w0Xpn/Qv3f/f9f8K3P+FAeDf+emp/+BC//E0f8KA8G/8APTU//Ahf/iaPYU+wXMP/AIaL0z/oX7v/AL/r/hR/w0Xpn/Qv3f8A3/X/AArc/wCFAeDf+emp/wDgQv8A8TR/woDwb/z01P8A8CF/+Jo9hT7Bcw/+Gi9M/wChfu/+/wCv+FH/AA0Xpn/Qv3f/AH/X/Ctz/hQHg3/npqf/AIEL/wDE0f8ACgPBv/PTU/8AwIX/AOJo9hT7Bcw/+Gi9M/6F+7/7/r/hVe9/aLtzZyCx0CUXJGEM042qfU4GT9K6T/hQHg3/AJ6an/4EL/8AE0+L4B+C45A7DUZQP4XuBg/koNHsKfYLni/gTQdS+IHxBjurgNJGLgXV9ORwBnOPqeg/+tX1wBgYFZ2jaFpfh6wWy0myitYBztjXG4+pPUn3NaNbCCszxJ/yK2r/APXlN/6Aa06zPEn/ACK2r/8AXlN/6AaAPnT9nz/kph/68Zf5rX1VXyr+z5/yUw/9eMv81r6qoAKKKKACiiigAooooA+Y/wBo7/ketO/7B6/+jHr2/wAB/wDJP/D3/YOg/wDQBXiH7R3/ACPWnf8AYPX/ANGPXt/gP/kn/h7/ALB0H/oAoA6GiiigD49+GH/JT9E/6+G/9BavrWvkr4Yf8lP0T/r4b/0Fq+ta4sT8SOqh8IUUUVzmwUUUUAFFFFAHm3xU/wCQv4K/7C6f0qfSf+KY+LGo6V92y12H7dB6ecvDge5HP5VB8VP+Qv4K/wCwun9KvfFG0mh0ey8R2Sk3mi3K3PHVoujr+X8q3XwqPe5i92+w74o6hMvh+30KyYi+1u4WyjA6hCfnP0xx+NZk+nw6V8WvBun26hYbbSpokA9FUinaFdReNvidPrcLebpejWyw2rdmmkGWI+g4/KrOt/8AJb/DH/YPuP5NQtPd8mD197zLWq+E7nxP42aTXY/N8PWkC/ZbbzPllmP3mdRzx0GawviL4Z8J6L4WudT06Cy0rVrMCS0ltSIn3hhxgdc5xVmxhPjvxp4httWvblbDSplt4dOhmMaPkcu+Dlv5Uz4h6D4W8M+ANTe30y0gupYjFA+zdIWY84JyemSfaiLaklcHqmy3431fVJfg8mp2LSJcXNrbyTPF95EcKXI/A1Pongz4eatocS6fp+n30LxjM2d0pyOpb7wNSDxLB4X+Hfhm7urRp7WeC0tpWBAEQeMfM2eoq3ffDfwrqMhuYrAWczfMJ7CQwnPqNvH6Ur2Vth2u77kHh/RdV8PeGdb0y/n8+yhMv9nOz7nEBU4VvpXN6D440/wf8KdAEhWfUbiHbbWgcKXYsQCx/hXPUmr/AIZvr63m8W+GrnUZdSt9Mizb3UzbpArIfkdu5GP51R+HngDQtS+G0Ut3bme51O2KyTyHc8YycBD/AAgYBqtEnzd0LXTlOm8N+Ergaj/wkfiSdL7W5B+6AH7qzQ/wRj+bd65/U2svGnxBvdM1i+ji0LRlQG0acILmc85bkZAHGK0fAetXmnX0/gnXpM6jYLm0nP8Ay9QdiCepA6//AFqwLDw14du/iv4k0vxDYQ3FxdFLyyMxI3IR8wXBGef5H0pK6bbDorG1rng7wZPpzyaPLpulanApe1urOZY2Vx0zg8j61BP4+vW+D8GuQbTq05WzUrgjzy2wt+hOK1NR+H3gHStOuL+70K0jgt4zI7FmGAPxrmPENta3HwdsdU0bRWsLW1vItRS0DEnYGILfiDmiNpWvrqDurnVaL8MfDtlpyrqlhDqmoSDdc3d2vmPI564J6D6Vxnibw4fDPjrwna2Er/2NPqIlitnYt9nkGAQpP8JBBx2xXr+n39tqdhBfWcqy286B0dTkEGvNviHqtvN8QfB2lRNvmgvlmm287M8KD6E4Jx7UqcpOWo5xio6HqVFFFYmoUUUUAFFFFABXiH7RH/HtoP8AvzfyWvb68Q/aI/49tB/35v5LWtD+IjOr8DO1+Bv/ACTCz/67y/8AoVej15x8Df8AkmFn/wBd5f8A0KvR69A4wooooAKKKKACvkjwj/yW2y/7C7/+htX1vXyR4R/5LbZf9hd//Q2oA+t6KKKAPCv2j/8Aj20D/fm/ktegfBH/AJJFon1uP/R8lef/ALR//HtoH+/N/Ja9A+CP/JItE+tx/wCj5KAPQaKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAy/E3/Iqax/14zf+gGvmL4C/8lLT/rzl/pX074m/5FTWP+vGb/0A18xfAX/kpaf9ecv9KAPqWiiigD5N+Nf/ACVDUf8Aci/9AFfVlp/x5wf9c1/lXyn8a/8AkqGo/wC5F/6AK+rLT/jzg/65r/KgCaiiigAooooAKKKKAEJABJOAOpNeK+NPj1Dpl/Lp/hy0ivHiYq93MT5ZI/ugdfrXdfFPU7jSfhxrFzauUlaIRBwcFQxCkj8Ca8H+DfgzT/Feu3k+qR+da2CI3kE8SMxOM+w2mplJRV2OKu7Is/8AC/8Axn/c0z/wHb/4qk/4X94z/uaZ/wCA7f8AxVe7DwR4TAA/4RnRuPWxj/8AiaX/AIQnwp/0LOjf+AMX/wATWH1ldjb2D7nhH/C/vGf9zTP/AAHb/wCKo/4X94z/ALmmf+A7f/FV7v8A8IT4U/6FnRv/AABi/wDiaP8AhCfCn/Qs6N/4Axf/ABNH1ldg9g+54R/wv7xn/c0z/wAB2/8AiqP+F/eM/wC5pn/gO3/xVe7/APCE+FP+hZ0b/wAAYv8A4mj/AIQnwp/0LOjf+AMX/wATR9ZXYPYPueEf8L+8Z/3NM/8AAdv/AIqj/hf3jP8AuaZ/4Dt/8VXu/wDwhPhT/oWdG/8AAGL/AOJo/wCEJ8Kf9Czo3/gDF/8AE0fWV2D2D7nhH/C/vGf9zTP/AAHb/wCKo/4X94z/ALmmf+A7f/FV7v8A8IT4U/6FnRv/AABi/wDiaP8AhCfCn/Qs6N/4Axf/ABNH1ldg9g+54R/wv7xn/c0z/wAB2/8AiqP+F/eM/wC5pn/gO3/xVe7/APCE+FP+hZ0b/wAAYv8A4mj/AIQnwp/0LOjf+AMX/wATR9ZXYPYPueEf8L+8Z/3NM/8AAdv/AIqj/hf3jP8AuaZ/4Dt/8VXu/wDwhPhT/oWdG/8AAGL/AOJo/wCEJ8Kf9Czo3/gDF/8AE0fWV2D2D7nzB4x+IOteOFtF1ZbUC1LGPyIyv3sZzkn0rS8NfF3xL4V0KDR9OWxNrAWKebCWb5mLHJ3DuTX0b/whPhT/AKFnRv8AwBi/+Jo/4Qnwp/0LOjf+AMX/AMTR9ZXYPYPueEf8L+8Z/wBzTP8AwHb/AOKo/wCF/eM/7mmf+A7f/FV7v/whPhT/AKFnRv8AwBi/+Jo/4Qnwp/0LOjf+AMX/AMTR9ZXYPYPueEf8L+8Z/wBzTP8AwHb/AOKo/wCF/eM/7mmf+A7f/FV7v/whPhT/AKFnRv8AwBi/+Jo/4Qnwp/0LOjf+AMX/AMTR9ZXYPYPueEf8L+8Z/wBzTP8AwHb/AOKo/wCF/eM/7mmf+A7f/FV7v/whPhT/AKFnRv8AwBi/+Jo/4Qnwp/0LOjf+AMX/AMTR9ZXYPYPueEf8L+8Z/wBzTP8AwHb/AOKo/wCF/eM/7mmf+A7f/FV7v/whPhT/AKFnRv8AwBi/+Jo/4Qnwp/0LOjf+AMX/AMTR9ZXYPYPueEf8L+8Z/wBzTP8AwHb/AOKo/wCF/eM/7mmf+A7f/FV7v/whPhT/AKFnRv8AwBi/+Jo/4Qnwp/0LOjf+AMX/AMTR9ZXYPYPueEf8L+8Z/wBzTP8AwHb/AOKo/wCF/eM/7mmf+A7f/FV7v/whPhT/AKFnRv8AwBi/+Jo/4Qnwp/0LOjf+AMX/AMTR9ZXYPYPueEf8L+8Z/wBzTP8AwHb/AOKp8f7QHjBZFMkOmOoPK+Qwz+O6vdP+EJ8Kf9Czo3/gDF/8TUNz4B8I3Vu8L+G9LRXGN0VqkbD6MoBFH1ldg9g+5kfDz4t6d41m/s+6hFjqoXIiLZSX12H19jXo9fG+v2T+AfiRPBYzPnTrlJIXz820gOAfwOK+xIJPOt4pcY3oGx9RXQndXRg1bQkrM8Sf8itq/wD15Tf+gGtOszxJ/wAitq//AF5Tf+gGmB86fs+f8lMP/XjL/Na+qq+Vf2fP+SmH/rxl/mtfVVABRRRQAUUUUAFFFFAHzH+0d/yPWnf9g9f/AEY9e3+A/wDkn/h7/sHQf+gCvEP2jv8AketO/wCwev8A6Mevb/Af/JP/AA9/2DoP/QBQB0NFFFAHx78MP+Sn6J/18N/6C1fWtfJXww/5Kfon/Xw3/oLV9a1xYn4kdVD4QooornNgooooAKKKKAMbXPDNh4huNNmvTMH0+4FxD5bADePXjkcVp3drDfWc1pcIHhmRo5FPdSMGpqKLsVkYvhfwtpvhHSf7N0tZBCXMjNK25mY+pwKkufDtjdeJrLX5DL9ts4nhiAb5NrZzkY681rUU+Z3uFlschrvw+stW1ltZstQvtJ1R1CSXFlJt8wDpuHQ0ll8OtMjE8mq3d9rF1NC0BnvZixRGGGCgcLn1612FFPnla1xciOe07wbpVh4al8PyG4vdOkJzHeS7yq4ACg8YAxx6VhR/DFrVRb2Pi3XrXTxwLVLjIA9ASM131FCnJdQ5UYeieEtJ8P6PPpthE6x3G4zyu5aSViMFmY96uaHo1r4f0a20qyMht7ZdieY2WxnPJ/GtCik5N7jSSMTW/Cuna9faffXBmivLCTzLe4gcK6+oOQcg+lReJvB2leKVga9WWK6tm3QXdu+yWM+xHb2roKKFJoHFM4NPhjDdSx/254h1jWLaNgy2tzNiMkf3gOvau3NtC1qbYxIYCnl+WR8u3GMY9MVLRQ5N7gopbHB/8Kxgs5WGh+INY0i0dyzWltP+7567c9O/51oWvw60G0FoyLcGe3uheNcPLukmlAxl2PUewxXWUU/aS7i5I9goooqSgooooAKKKKACvEP2iP8Aj20H/fm/kte314h+0R/x7aD/AL838lrWh/ERnV+Bna/A3/kmFn/13l/9Cr0evOPgb/yTCz/67y/+hV6PXoHGFFFFABRRRQAV8keEf+S22X/YXf8A9Davrevkjwj/AMltsv8AsLv/AOhtQB9b0UUUAeFftH/8e2gf7838lr0D4I/8ki0T63H/AKPkrz/9o/8A49tA/wB+b+S16B8Ef+SRaJ9bj/0fJQB6DRRRQAUUUUA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" 'image_mime_type': 'image/jpeg',\n", " 'file_directory': '../docs',\n", " 'filename': 'attention_is_all_you_need.pdf'}}" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "images[0].to_dict()" ] }, { "cell_type": "code", "execution_count": 19, "id": "dece78cb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 4 tables\n" ] }, { "data": { "text/plain": [ "{'type': 'Table',\n", " 'element_id': '100107765e33787fba57326569aded5c',\n", " 'text': 'Layer Type Complexity per Layer Sequential Maximum Path Length Operations Self-Attention O(n2 · d) O(1) O(1) Recurrent O(n · d2) O(n) O(n) Convolutional O(k · n · d2) O(1) O(logk(n)) Self-Attention (restricted) O(r · n · d) O(1) O(n/r)',\n", " 'metadata': {'detection_class_prob': 0.9282485246658325,\n", " 'is_extracted': 'true',\n", " 'coordinates': {'points': ((np.float64(561.3704223632812),\n", " np.float64(550.455078125)),\n", " (np.float64(561.3704223632812), np.float64(908.8231201171875)),\n", " (np.float64(2395.106201171875), np.float64(908.8231201171875)),\n", " (np.float64(2395.106201171875), np.float64(550.455078125))),\n", " 'system': 'PixelSpace',\n", " 'layout_width': 2975,\n", " 'layout_height': 3850},\n", " 'last_modified': '2026-05-26T11:16:29',\n", " 'text_as_html': '
Layer TypeComplexity per LayerSequential OperationsMaximum Path Length
Self-AttentionO(n? - d)O(1)O(1)
RecurrentO(n - d?)O(n)O(n)
ConvolutionalO(k-n-d?)O(1)O(log, (n))
Self-Attention (restricted)O(r-n-d)O(1)O(n/r)
',\n", " 'filetype': 'application/pdf',\n", " 'languages': ['eng'],\n", " 'page_number': 6,\n", " 'file_directory': '../docs',\n", " 'filename': 'attention_is_all_you_need.pdf'}}" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tables = [element for element in elements if element.category == 'Table']\n", "print(f\"Found {len(tables)} tables\")\n", "\n", "tables[0].to_dict()" ] }, { "cell_type": "code", "execution_count": 20, "id": "2ae5f550", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "🔨 Creating smart chunks...\n", "✅ Created 25 chunks\n" ] } ], "source": [ "def create_chunks_by_title(elements):\n", " \"\"\"Create intelligent chunks using title-based strategy\"\"\"\n", " print(\"🔨 Creating smart chunks...\")\n", " \n", " chunks = chunk_by_title(\n", " elements, # The parsed PDF elements from previous step\n", " max_characters=3000, # Hard limit - never exceed 3000 characters per chunk\n", " new_after_n_chars=2400, # Try to start a new chunk after 2400 characters\n", " combine_text_under_n_chars=500 # Merge tiny chunks under 500 chars with neighbors\n", " )\n", " \n", " print(f\"✅ Created {len(chunks)} chunks\")\n", " return chunks\n", "\n", "# Create chunks\n", "chunks = create_chunks_by_title(elements)" ] }, { "cell_type": "code", "execution_count": 21, "id": "cf0c86bb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ,\n", " ]" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "chunks" ] }, { "cell_type": "code", "execution_count": 22, "id": "0a3cc400", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{\"\"}" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "set([str(type(chunk)) for chunk in chunks])" ] }, { "cell_type": "code", "execution_count": 26, "id": "08c6d4a9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[,\n", " ,\n", " ,\n", " ,\n", " ]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "chunks[11].metadata.orig_elements" ] }, { "cell_type": "code", "execution_count": 23, "id": "dae7f951", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'type': 'Table',\n", " 'element_id': '100107765e33787fba57326569aded5c',\n", " 'text': 'Layer Type Complexity per Layer Sequential Maximum Path Length Operations Self-Attention O(n2 · d) O(1) O(1) Recurrent O(n · d2) O(n) O(n) Convolutional O(k · n · d2) O(1) O(logk(n)) Self-Attention (restricted) O(r · n · d) O(1) O(n/r)',\n", " 'metadata': {'detection_class_prob': 0.9282485246658325,\n", " 'is_extracted': 'true',\n", " 'coordinates': {'points': ((np.float64(561.3704223632812),\n", " np.float64(550.455078125)),\n", " (np.float64(561.3704223632812), np.float64(908.8231201171875)),\n", " (np.float64(2395.106201171875), np.float64(908.8231201171875)),\n", " (np.float64(2395.106201171875), np.float64(550.455078125))),\n", " 'system': 'PixelSpace',\n", " 'layout_width': 2975,\n", " 'layout_height': 3850},\n", " 'last_modified': '2026-05-26T11:16:29',\n", " 'text_as_html': '
Layer TypeComplexity per LayerSequential OperationsMaximum Path Length
Self-AttentionO(n? - d)O(1)O(1)
RecurrentO(n - d?)O(n)O(n)
ConvolutionalO(k-n-d?)O(1)O(log, (n))
Self-Attention (restricted)O(r-n-d)O(1)O(n/r)
',\n", " 'filetype': 'application/pdf',\n", " 'languages': ['eng'],\n", " 'page_number': 6,\n", " 'file_directory': '../docs',\n", " 'filename': 'attention_is_all_you_need.pdf'}}" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "chunks[11].metadata.orig_elements[-1].to_dict()" ] }, { "cell_type": "code", "execution_count": 27, "id": "a1038b5b", "metadata": {}, "outputs": [], "source": [ "def separate_content_types(chunk):\n", " \"\"\"Analyze what types of content are in a chunk\"\"\"\n", " content_data = {\n", " 'text': chunk.text,\n", " 'tables': [],\n", " 'images': [],\n", " 'types': ['text']\n", " }\n", " \n", " # Check for tables and images in original elements\n", " if hasattr(chunk, 'metadata') and hasattr(chunk.metadata, 'orig_elements'):\n", " for element in chunk.metadata.orig_elements:\n", " element_type = type(element).__name__\n", " \n", " # Handle tables\n", " if element_type == 'Table':\n", " content_data['types'].append('table')\n", " table_html = getattr(element.metadata, 'text_as_html', element.text)\n", " content_data['tables'].append(table_html)\n", " \n", " # Handle images\n", " elif element_type == 'Image':\n", " if hasattr(element, 'metadata') and hasattr(element.metadata, 'image_base64'):\n", " content_data['types'].append('image')\n", " content_data['images'].append(element.metadata.image_base64)\n", " \n", " content_data['types'] = list(set(content_data['types']))\n", " return content_data" ] }, { "cell_type": "code", "execution_count": 38, "id": "f1db5deb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AIMessage(content='The image presents a detailed diagram of the Transformer architecture, a type of neural network model introduced in the paper \"Attention Is All You Need\" by Vaswani et al. in 2017. The diagram illustrates the Encoder and Decoder components of the Transformer model.\\n\\n**Encoder:**\\n\\n* The Encoder takes in a sequence of tokens (e.g., words or characters) and outputs a sequence of vectors.\\n* The Encoder consists of a stack of identical layers, each comprising two sub-layers:\\n * **Multi-Head Attention:** This sub-layer applies self-attention to the input sequence, allowing the model to attend to different parts of the input sequence simultaneously and weigh their importance.\\n * **Feed Forward Network (FFN):** This sub-layer applies a fully connected feed-forward network to the output of the multi-head attention sub-layer.\\n\\n**Decoder:**\\n\\n* The Decoder takes in a sequence of tokens (e.g., words or characters) and outputs a sequence of tokens.\\n* The Decoder consists of a stack of identical layers, each comprising three sub-layers:\\n * **Masked Multi-Head Attention:** This sub-layer applies self-attention to the input sequence, but with a mask to prevent the model from attending to future tokens in the output sequence.\\n * **Multi-Head Attention:** This sub-layer applies self-attention to the output of the Encoder.\\n * **Feed Forward Network (FFN):** This sub-layer applies a fully connected feed-forward network to the output of the multi-head attention sub-layer.\\n\\n**Common Components:**\\n\\n* **Positional Encoding:** Both the Encoder and Decoder use positional encoding to add information about the position of each token in the sequence.\\n* **Add & Norm:** Both the Encoder and Decoder use an \"Add & Norm\" component, which adds the output of each sub-layer to the input of the sub-layer and applies layer normalization.\\n\\n**Output:**\\n\\n* The final output of the Decoder is passed through a linear layer and a softmax function to produce a probability distribution over the possible output tokens.\\n\\nOverall, the Transformer architecture is designed to handle sequential data, such as text or speech, and is particularly well-suited for tasks like machine translation, text summarization, and text generation.', additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 456, 'prompt_tokens': 2339, 'total_tokens': 2795, 'completion_time': 1.0334433650000001, 'completion_tokens_details': None, 'prompt_time': 0.138003678, 'prompt_tokens_details': None, 'queue_time': 0.219886211, 'total_time': 1.171447043}, 'model_name': 'meta-llama/llama-4-scout-17b-16e-instruct', 'system_fingerprint': 'fp_37da608fc1', 'service_tier': 'on_demand', 'finish_reason': 'stop', 'logprobs': None, 'model_provider': 'groq'}, id='lc_run--019e630d-9aa9-7b60-b8a4-18f6312f0597-0', tool_calls=[], invalid_tool_calls=[], usage_metadata={'input_tokens': 2339, 'output_tokens': 456, 'total_tokens': 2795})" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model = ChatGroq(model=\"meta-llama/llama-4-scout-17b-16e-instruct\")\n", "image_base64 = images[0].metadata.image_base64\n", "message = HumanMessage(\n", " content=[\n", " {\"type\": \"text\", \"text\": \"what is this image about\"},\n", " {\n", " \"type\": \"image_url\",\n", " \"image_url\": {\"url\": f\"data:image/jpeg;base64,{image_base64}\"},\n", " },\n", " ]\n", ")\n", "model.invoke([message])" ] }, { "cell_type": "code", "execution_count": null, "id": "0f8dfa59", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "aiagents (3.12.3)", "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": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }