118 lines
3.3 KiB
Text
118 lines
3.3 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c4d5a399",
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"metadata": {},
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"outputs": [],
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"source": [
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"from os import listdir, path\n",
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"from uuid import uuid5, UUID\n",
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"from cognee import add\n",
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"\n",
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"data_path = path.abspath(\".data\")\n",
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"\n",
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"results = await add(data_path, \"izmene\")\n",
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"for result in results:\n",
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" print(result)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "47edce91",
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"metadata": {},
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"outputs": [],
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"source": [
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"import duckdb\n",
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"from cognee.root_dir import get_absolute_path\n",
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"\n",
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"dataset_name = \"pdf_files\"\n",
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"\n",
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"db_path = get_absolute_path(\"./data/cognee\")\n",
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"db_location = db_path + \"/cognee.duckdb\"\n",
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"print(db_location)\n",
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"\n",
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"db = duckdb.connect(db_location)\n",
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"\n",
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"tables = db.sql(\"SELECT DISTINCT schema_name FROM duckdb_tables();\").df()\n",
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"print(list(filter(lambda table_name: table_name.endswith('staging') is False, tables.to_dict()[\"schema_name\"].values())))\n",
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"\n",
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"# izmene = db.sql(f\"SELECT * FROM izmene.file_metadata;\")\n",
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"\n",
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"# print(izmene)\n",
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"\n",
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"# pravilnik = db.sql(f\"SELECT * FROM pravilnik.file_metadata;\")\n",
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"\n",
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"# print(pravilnik)\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "607bf624",
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"metadata": {},
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"outputs": [],
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"source": [
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"from os import path, listdir\n",
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"from cognee import cognify, list_datasets\n",
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"from cognee.utils import render_graph\n",
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"\n",
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"print(list_datasets())\n",
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"\n",
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"graph = await cognify(\"izmene\")\n",
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"\n",
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"graph_url = await render_graph(graph, graph_type = \"networkx\")\n",
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"print(graph_url)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6edb9cac",
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"metadata": {},
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"outputs": [],
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"source": [
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"from cognee.infrastructure.databases.graph.get_graph_client import get_graph_client\n",
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"from cognee.shared.data_models import GraphDBType\n",
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"from cognee import search, SearchType\n",
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"\n",
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"graph_client = get_graph_client(GraphDBType.NETWORKX)\n",
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"await graph_client.load_graph_from_file()\n",
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"\n",
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"graph = graph_client.graph\n",
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"\n",
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"query_params = {\n",
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" SearchType.SIMILARITY: {'query': 'nacin vrsenja kontrole tehnicke dokumentacije'}\n",
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"}\n",
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"\n",
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"results = await search(graph, query_params)\n",
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"print(results)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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