diff --git a/notebooks/cognee_demo.ipynb b/notebooks/cognee_demo.ipynb
index f95a082cd..312ca0e65 100644
--- a/notebooks/cognee_demo.ipynb
+++ b/notebooks/cognee_demo.ipynb
@@ -794,14 +794,7 @@
"from cognee.shared.utils import render_graph\n",
"from cognee.infrastructure.databases.graph import get_graph_engine\n",
"import graphistry\n",
- "from dotenv import load_dotenv \n",
- "\n",
- "load_dotenv()\n",
- "os.environ[\"GRAPHISTRY_USERNAME\"] = \"vasilije\"\n",
- "os.environ[\"GRAPHISTRY_PASSWORD\"] = \"wV!4yzNGjDLCpwV\"\n",
- "\n",
- "\n",
- "\n",
+ "# from dotenv import load_dotenv \n",
"graphistry.login(username=os.getenv(\"GRAPHISTRY_USERNAME\"), password=os.getenv(\"GRAPHISTRY_PASSWORD\"))\n",
"\n",
"graph_engine = await get_graph_engine()\n",
@@ -821,683 +814,6 @@
],
"execution_count": 12
},
- {
- "metadata": {
- "ExecuteTime": {
- "end_time": "2024-12-29T17:27:20.635684Z",
- "start_time": "2024-12-29T17:27:18.253572Z"
- }
- },
- "cell_type": "code",
- "source": "!pip install cairosvg",
- "id": "1995cab3f32a393b",
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Collecting cairosvg\r\n",
- " Obtaining dependency information for cairosvg from https://files.pythonhosted.org/packages/01/a5/1866b42151f50453f1a0d28fc4c39f5be5f412a2e914f33449c42daafdf1/CairoSVG-2.7.1-py3-none-any.whl.metadata\r\n",
- " Downloading CairoSVG-2.7.1-py3-none-any.whl.metadata (2.7 kB)\r\n",
- "Collecting cairocffi (from cairosvg)\r\n",
- " Obtaining dependency information for cairocffi from https://files.pythonhosted.org/packages/93/d8/ba13451aa6b745c49536e87b6bf8f629b950e84bd0e8308f7dc6883b67e2/cairocffi-1.7.1-py3-none-any.whl.metadata\r\n",
- " Downloading cairocffi-1.7.1-py3-none-any.whl.metadata (3.3 kB)\r\n",
- "Collecting cssselect2 (from cairosvg)\r\n",
- " Obtaining dependency information for cssselect2 from https://files.pythonhosted.org/packages/9d/3a/e39436efe51894243ff145a37c4f9a030839b97779ebcc4f13b3ba21c54e/cssselect2-0.7.0-py3-none-any.whl.metadata\r\n",
- " Downloading cssselect2-0.7.0-py3-none-any.whl.metadata (2.9 kB)\r\n",
- "Requirement already satisfied: defusedxml in /Users/vasilije/cognee/.venv/lib/python3.11/site-packages (from cairosvg) (0.7.1)\r\n",
- "Requirement already satisfied: pillow in /Users/vasilije/cognee/.venv/lib/python3.11/site-packages (from cairosvg) (11.0.0)\r\n",
- "Requirement already satisfied: tinycss2 in /Users/vasilije/cognee/.venv/lib/python3.11/site-packages (from cairosvg) (1.4.0)\r\n",
- "Requirement already satisfied: cffi>=1.1.0 in /Users/vasilije/cognee/.venv/lib/python3.11/site-packages (from cairocffi->cairosvg) (1.17.1)\r\n",
- "Requirement already satisfied: webencodings in /Users/vasilije/cognee/.venv/lib/python3.11/site-packages (from cssselect2->cairosvg) (0.5.1)\r\n",
- "Requirement already satisfied: pycparser in /Users/vasilije/cognee/.venv/lib/python3.11/site-packages (from cffi>=1.1.0->cairocffi->cairosvg) (2.22)\r\n",
- "Downloading CairoSVG-2.7.1-py3-none-any.whl (43 kB)\r\n",
- "\u001B[2K \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m43.2/43.2 kB\u001B[0m \u001B[31m1.6 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\r\n",
- "\u001B[?25hDownloading cairocffi-1.7.1-py3-none-any.whl (75 kB)\r\n",
- "\u001B[2K \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m75.6/75.6 kB\u001B[0m \u001B[31m4.3 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\r\n",
- "\u001B[?25hDownloading cssselect2-0.7.0-py3-none-any.whl (15 kB)\r\n",
- "Installing collected packages: cssselect2, cairocffi, cairosvg\r\n",
- "Successfully installed cairocffi-1.7.1 cairosvg-2.7.1 cssselect2-0.7.0\r\n",
- "\r\n",
- "\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m A new release of pip is available: \u001B[0m\u001B[31;49m23.2.1\u001B[0m\u001B[39;49m -> \u001B[0m\u001B[32;49m24.3.1\u001B[0m\r\n",
- "\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m To update, run: \u001B[0m\u001B[32;49mpip install --upgrade pip\u001B[0m\r\n"
- ]
- }
- ],
- "execution_count": 25
- },
- {
- "metadata": {
- "ExecuteTime": {
- "end_time": "2024-12-29T22:05:06.689621Z",
- "start_time": "2024-12-29T22:05:06.688268Z"
- }
- },
- "cell_type": "code",
- "source": "\n",
- "id": "7014c8acf720b50",
- "outputs": [],
- "execution_count": 70
- },
- {
- "metadata": {
- "ExecuteTime": {
- "end_time": "2024-12-29T22:27:10.842044Z",
- "start_time": "2024-12-29T22:27:10.826453Z"
- }
- },
- "cell_type": "code",
- "source": [
- "from PIL import Image\n",
- "import potrace\n",
- "\n",
- "def png_to_svg(png_path, threshold=128):\n",
- " \"\"\"\n",
- " Converts a PNG image to an SVG string using potrace and prints the output.\n",
- "\n",
- " :param png_path: Path to the input PNG file.\n",
- " :param threshold: Grayscale threshold for converting to black-and-white (default: 128).\n",
- " :return: The SVG content as a string.\n",
- " \"\"\"\n",
- " # Load the PNG image and convert to grayscale\n",
- " img = Image.open(png_path).convert(\"L\")\n",
- "\n",
- " # Convert image to black-and-white\n",
- " img = img.point(lambda p: p > threshold and 255)\n",
- "\n",
- " # Convert the image to a bitmap for potrace\n",
- " bitmap = potrace.Bitmap(img)\n",
- "\n",
- " # Trace the bitmap into a path\n",
- " path = bitmap.trace()\n",
- "\n",
- " # Generate SVG output\n",
- " svg_content = '\\n'\n",
- " svg_content += '\\n'\n",
- "\n",
- " # Print the SVG content\n",
- " print(svg_content)\n",
- "\n",
- " # Return the SVG content as a string\n",
- " return svg_content\n"
- ],
- "id": "494ff0eafc9892db",
- "outputs": [
- {
- "ename": "ModuleNotFoundError",
- "evalue": "No module named 'potrace'",
- "output_type": "error",
- "traceback": [
- "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
- "\u001B[0;31mModuleNotFoundError\u001B[0m Traceback (most recent call last)",
- "Cell \u001B[0;32mIn[87], line 2\u001B[0m\n\u001B[1;32m 1\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mPIL\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m Image\n\u001B[0;32m----> 2\u001B[0m \u001B[38;5;28;01mimport\u001B[39;00m \u001B[38;5;21;01mpotrace\u001B[39;00m\n\u001B[1;32m 4\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mpng_to_svg\u001B[39m(png_path, threshold\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m128\u001B[39m):\n\u001B[1;32m 5\u001B[0m \u001B[38;5;250m \u001B[39m\u001B[38;5;124;03m\"\"\"\u001B[39;00m\n\u001B[1;32m 6\u001B[0m \u001B[38;5;124;03m Converts a PNG image to an SVG string using potrace and prints the output.\u001B[39;00m\n\u001B[1;32m 7\u001B[0m \n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 10\u001B[0m \u001B[38;5;124;03m :return: The SVG content as a string.\u001B[39;00m\n\u001B[1;32m 11\u001B[0m \u001B[38;5;124;03m \"\"\"\u001B[39;00m\n",
- "\u001B[0;31mModuleNotFoundError\u001B[0m: No module named 'potrace'"
- ]
- }
- ],
- "execution_count": 87
- },
- {
- "metadata": {
- "ExecuteTime": {
- "end_time": "2024-12-29T22:27:11.546173Z",
- "start_time": "2024-12-29T22:27:11.533929Z"
- }
- },
- "cell_type": "code",
- "source": [
- "import os\n",
- "from typing import BinaryIO, Union\n",
- "\n",
- "import requests\n",
- "import hashlib\n",
- "from datetime import datetime, timezone\n",
- "import graphistry\n",
- "import networkx as nx\n",
- "import numpy as np\n",
- "import pandas as pd\n",
- "import matplotlib.pyplot as plt\n",
- "import tiktoken\n",
- "import nltk\n",
- "import base64\n",
- "import networkx as nx\n",
- "from bokeh.io import output_file, save\n",
- "from bokeh.plotting import figure, from_networkx\n",
- "from bokeh.models import Circle, MultiLine, HoverTool, ColumnDataSource, Range1d\n",
- "\n",
- "\n",
- "from cognee.base_config import get_base_config\n",
- "from cognee.infrastructure.databases.graph import get_graph_engine\n",
- "\n",
- "from uuid import uuid4\n",
- "import pathlib\n",
- "\n",
- "from cognee.shared.exceptions import IngestionError\n",
- "\n",
- "\n",
- "async def create_cognee_style_network_with_logo(\n",
- " G,\n",
- " output_filename: str = \"cognee_network_with_logo.html\",\n",
- " title: str = \"Cognee-Style Network\",\n",
- " node_attribute: str = \"group\",\n",
- " layout_func=nx.spring_layout,\n",
- " layout_scale: float = 3.0,\n",
- " logo_alpha: float = 0.1, # Transparency of the logo\n",
- "):\n",
- " \"\"\"\n",
- " Create a Cognee-inspired network visualization with an embedded logo as a watermark.\n",
- "\n",
- " :param G: Graph data.\n",
- " :param output_filename: The HTML file where the visualization will be saved.\n",
- " :param title: Title of the visualization.\n",
- " :param node_attribute: Node attribute used to color the nodes.\n",
- " :param layout_func: Layout function from NetworkX (e.g., nx.spring_layout).\n",
- " :param layout_scale: Scale of the layout.\n",
- " :param logo_alpha: Transparency of the logo (0 = fully transparent, 1 = fully opaque).\n",
- " \"\"\"\n",
- "\n",
- " # Ensure every node has the specified attribute; otherwise \"Unknown\"\n",
- " \n",
- " (nodes, edges) = G\n",
- " networkx_graph = nx.MultiDiGraph()\n",
- "\n",
- " networkx_graph.add_nodes_from(nodes)\n",
- " networkx_graph.add_edges_from(edges)\n",
- "\n",
- " G = networkx_graph\n",
- " new_G = nx.MultiDiGraph() if isinstance(G, nx.MultiDiGraph) else nx.Graph()\n",
- " \n",
- " # Convert nodes and their attributes\n",
- " for node, data in G.nodes(data=True):\n",
- " print(data.items())\n",
- " import uuid\n",
- " serializable_data = {k: str(v) if isinstance(v, uuid.UUID) else v for k, v in data.items()}\n",
- " new_G.add_node(str(node), **serializable_data)\n",
- " \n",
- " # Convert edges and their attributes\n",
- " for u, v, data in G.edges(data=True):\n",
- " import uuid\n",
- " serializable_data = {k: str(v) if isinstance(v, uuid.UUID) else v for k, v in data.items()}\n",
- " new_G.add_edge(str(u), str(v), **serializable_data)\n",
- " \n",
- " G = new_G # Use the new graph\n",
- "\n",
- " # Prepare Bokeh output\n",
- " output_file(output_filename)\n",
- "\n",
- " # Create a figure with light gray background\n",
- " p = figure(\n",
- " title=title,\n",
- " tools=\"pan,wheel_zoom,save,reset,hover\",\n",
- " active_scroll=\"wheel_zoom\",\n",
- " width=1200,\n",
- " height=900,\n",
- " background_fill_color=\"#F4F4F4\", # Light Gray\n",
- " toolbar_location=\"below\",\n",
- " x_range=Range1d(-layout_scale, layout_scale),\n",
- " y_range=Range1d(-layout_scale, layout_scale),\n",
- " )\n",
- " p.toolbar.logo = None\n",
- " p.axis.visible = False\n",
- " p.grid.visible = False\n",
- " p.outline_line_color = None\n",
- "\n",
- " import cairosvg\n",
- " \n",
- " svg_logo =\"\"\"\"\"\"\n",
- "\n",
- "\n",
- " png_data = cairosvg.svg2png(bytestring=svg_logo.encode(\"utf-8\"))\n",
- " logo_base64 = base64.b64encode(png_data).decode(\"utf-8\")\n",
- " logo_url = f\"data:image/png;base64,{logo_base64}\"\n",
- "\n",
- " # Add the logo as an image at the center of the graph\n",
- " # Position the logo behind the graph using CSS layering\n",
- " p.image_url(\n",
- " url=[logo_url],\n",
- " x=-layout_scale * 0.5, # Adjusted position to center\n",
- " y=layout_scale * 0.5, # Adjusted position to center\n",
- " w=layout_scale * 1.2, # Width of the logo\n",
- " h=layout_scale * 1.2, # Height of the logo\n",
- " anchor=\"center\",\n",
- " global_alpha=logo_alpha, # Transparency for watermark effect\n",
- " )\n",
- " p.image_url(\n",
- " url=[logo_url],\n",
- " x=-layout_scale * -0.5, # Adjusted position to center\n",
- " y=layout_scale * -0.5, # Adjusted position to center\n",
- " w=layout_scale * 1.2, # Width of the logo\n",
- " h=layout_scale * 1.2, # Height of the logo\n",
- " anchor=\"center\",\n",
- " global_alpha=logo_alpha, # Transparency for watermark effect\n",
- " )\n",
- "\n",
- " # Generate graph layout\n",
- " layout_positions = {str(node): position for node, position in layout_func(G).items()}\n",
- "\n",
- " graph_renderer = from_networkx(\n",
- " G,\n",
- " layout_positions,\n",
- " scale=layout_scale,\n",
- " center=(0, 0),\n",
- " )\n",
- "\n",
- " # Compute node sizes based on centrality\n",
- " centrality = nx.degree_centrality(G)\n",
- " node_radii = [0.02 + 0.1 * centrality[node] for node in G.nodes()]\n",
- " graph_renderer.node_renderer.data_source.data[\"radius\"] = node_radii\n",
- "\n",
- " # Apply Cognee-inspired colors for nodes\n",
- " cognee_colors = [\"#6510F4\", \"#0DFF00\", \"#FFFFFF\"] # Violet, Green, White\n",
- " unique_attrs = list({\n",
- " G.nodes[node].get(node_attribute, G.nodes[node].get('id', 'Unknown')) \n",
- " for node in G.nodes()\n",
- " })\n",
- " color_map = {attr: cognee_colors[i % len(cognee_colors)] for i, attr in enumerate(unique_attrs)}\n",
- " node_colors = [\n",
- " color_map[G.nodes[node].get(node_attribute, G.nodes[node].get('id', 'Unknown'))] \n",
- " for node in G.nodes()\n",
- "]\n",
- "\n",
- " graph_renderer.node_renderer.data_source.data[\"fill_color\"] = node_colors\n",
- "\n",
- " # Style nodes\n",
- " graph_renderer.node_renderer.glyph = Circle(\n",
- " radius=\"radius\",\n",
- " fill_color=\"fill_color\",\n",
- " fill_alpha=0.9,\n",
- " line_color=\"#000000\", # Abyss Black outline\n",
- " line_width=1.5,\n",
- " )\n",
- " graph_renderer.node_renderer.hover_glyph = Circle(\n",
- " radius=\"radius\",\n",
- " fill_color=\"#FFFFFF\", # White fill on hover\n",
- " fill_alpha=1.0,\n",
- " line_color=\"#6510F4\", # Violet outline on hover\n",
- " line_width=2.5,\n",
- " )\n",
- "\n",
- " # Style edges\n",
- " graph_renderer.edge_renderer.glyph = MultiLine(\n",
- " line_color=\"#000000\", # Abyss Black edges\n",
- " line_alpha=0.3,\n",
- " line_width=1.5,\n",
- " )\n",
- " graph_renderer.edge_renderer.hover_glyph = MultiLine(\n",
- " line_color=\"#0DFF00\", # Green on hover\n",
- " line_alpha=0.8,\n",
- " line_width=2.0,\n",
- " )\n",
- "\n",
- " # Hover tool for node tooltips\n",
- " graph_renderer.node_renderer.data_source.data[node_attribute] = [\n",
- " G.nodes[node].get(node_attribute, G.nodes[node].get('id', 'Unknown')) \n",
- " for node in G.nodes()\n",
- " ]\n",
- " hover_tool = HoverTool(\n",
- " tooltips=[\n",
- " (\"Node\", \"@index\"),\n",
- " (node_attribute.capitalize(), f\"@{node_attribute}\"),\n",
- " (\"Centrality\", \"@radius{0.00}\"),\n",
- " ],\n",
- " renderers=[graph_renderer],\n",
- " )\n",
- " p.add_tools(hover_tool)\n",
- "\n",
- " # Add the graph to the plot\n",
- " p.renderers.append(graph_renderer)\n",
- " from bokeh.io import output_notebook, show\n",
- "\n",
- " # Save the result\n",
- " output_notebook()\n",
- "\n",
- " # Display the plot in the notebook\n",
- " show(p)\n",
- " print(f\"Cognee-style network with logo saved to '{output_filename}'\")\n",
- " from bokeh.embed import file_html\n",
- " from bokeh.resources import CDN\n",
- " \n",
- " html_content = file_html(p, CDN, title=\"Cognee-style Network\")\n",
- "\n",
- " # Save HTML to file if needed\n",
- " with open(output_filename, \"w\") as f:\n",
- " f.write(html_content)\n",
- " print(f\"HTML plot saved to '{output_filename}'\")\n",
- "\n",
- " # Return the HTML content as a string\n",
- " return html_content\n"
- ],
- "id": "296c8298f25d53d8",
- "outputs": [],
- "execution_count": 88
- },
- {
- "metadata": {
- "ExecuteTime": {
- "end_time": "2024-12-30T09:50:38.625634Z",
- "start_time": "2024-12-30T09:50:38.614895Z"
- }
- },
- "cell_type": "code",
- "source": [
- "import networkx as nx\n",
- "from bokeh.plotting import figure, output_file, show\n",
- "from bokeh.models import Circle, MultiLine, HoverTool, Range1d\n",
- "from bokeh.io import output_notebook\n",
- "from bokeh.embed import file_html\n",
- "from bokeh.resources import CDN\n",
- "from bokeh.plotting import figure, from_networkx\n",
- "import base64\n",
- "import cairosvg\n",
- "import logging\n",
- "\n",
- "logging.basicConfig(level=logging.INFO)\n",
- "\n",
- "def convert_to_serializable_graph(G):\n",
- " \"\"\"\n",
- " Convert a graph into a serializable format with stringified node and edge attributes.\n",
- " \"\"\"\n",
- " (nodes, edges) = G\n",
- " networkx_graph = nx.MultiDiGraph()\n",
- "\n",
- " networkx_graph.add_nodes_from(nodes)\n",
- " networkx_graph.add_edges_from(edges)\n",
- " G = networkx_graph\n",
- " new_G = nx.MultiDiGraph() if isinstance(G, nx.MultiDiGraph) else nx.Graph()\n",
- " for node, data in G.nodes(data=True):\n",
- " serializable_data = {k: str(v) for k, v in data.items()}\n",
- " new_G.add_node(str(node), **serializable_data)\n",
- " for u, v, data in G.edges(data=True):\n",
- " serializable_data = {k: str(v) for k, v in data.items()}\n",
- " new_G.add_edge(str(u), str(v), **serializable_data)\n",
- " return new_G\n",
- "\n",
- "def generate_layout_positions(G, layout_func, layout_scale):\n",
- " \"\"\"\n",
- " Generate layout positions for the graph using the specified layout function.\n",
- " \"\"\"\n",
- " positions = layout_func(G)\n",
- " return {str(node): (x * layout_scale, y * layout_scale) for node, (x, y) in positions.items()}\n",
- "\n",
- "def assign_node_colors(G, node_attribute, palette):\n",
- " \"\"\"\n",
- " Assign colors to nodes based on a specified attribute and a given palette.\n",
- " \"\"\"\n",
- " unique_attrs = set(G.nodes[node].get(node_attribute, \"Unknown\") for node in G.nodes)\n",
- " color_map = {attr: palette[i % len(palette)] for i, attr in enumerate(unique_attrs)}\n",
- " return [color_map[G.nodes[node].get(node_attribute, \"Unknown\")] for node in G.nodes], color_map\n",
- "\n",
- "def embed_logo(p, layout_scale, logo_alpha):\n",
- " \"\"\"\n",
- " Embed a logo into the graph visualization as a watermark.\n",
- " \"\"\"\n",
- " svg_logo=\"\"\"\"\"\" # Add your SVG content here\n",
- " png_data = cairosvg.svg2png(bytestring=svg_logo.encode(\"utf-8\"))\n",
- " logo_base64 = base64.b64encode(png_data).decode(\"utf-8\")\n",
- " logo_url = f\"data:image/png;base64,{logo_base64}\"\n",
- " p.image_url(\n",
- " url=[logo_url],\n",
- " x=-layout_scale * 0.5,\n",
- " y=layout_scale * 0.5,\n",
- " w=layout_scale,\n",
- " h=layout_scale,\n",
- " anchor=\"center\",\n",
- " global_alpha=logo_alpha,\n",
- " )\n",
- "\n",
- "def style_and_render_graph(p, G, layout_positions, node_attribute, node_colors, centrality):\n",
- " \"\"\"\n",
- " Apply styling and render the graph into the plot.\n",
- " \"\"\"\n",
- " graph_renderer = from_networkx(G, layout_positions)\n",
- " node_radii = [0.02 + 0.1 * centrality[node] for node in G.nodes()]\n",
- " graph_renderer.node_renderer.data_source.data[\"radius\"] = node_radii\n",
- " graph_renderer.node_renderer.data_source.data[\"fill_color\"] = node_colors\n",
- " graph_renderer.node_renderer.glyph = Circle(\n",
- " radius=\"radius\",\n",
- " fill_color=\"fill_color\",\n",
- " fill_alpha=0.9,\n",
- " line_color=\"#000000\",\n",
- " line_width=1.5,\n",
- " )\n",
- " graph_renderer.edge_renderer.glyph = MultiLine(\n",
- " line_color=\"#000000\",\n",
- " line_alpha=0.3,\n",
- " line_width=1.5,\n",
- " )\n",
- " p.renderers.append(graph_renderer)\n",
- " return graph_renderer\n",
- "\n",
- "def create_cognee_style_network_with_logo(\n",
- " G,\n",
- " output_filename=\"cognee_netwdzsfsdfsdgo.html\",\n",
- " title=\"Cognee-Style Network\",\n",
- " node_attribute=\"group\",\n",
- " layout_func=nx.spring_layout,\n",
- " layout_scale=3.0,\n",
- " logo_alpha=0.1,\n",
- "):\n",
- " \"\"\"\n",
- " Create a Cognee-inspired network visualization with an embedded logo.\n",
- " \"\"\"\n",
- " logging.info(\"Converting graph to serializable format...\")\n",
- " G = convert_to_serializable_graph(G)\n",
- "\n",
- " logging.info(\"Generating layout positions...\")\n",
- " layout_positions = generate_layout_positions(G, layout_func, layout_scale)\n",
- "\n",
- " logging.info(\"Assigning node colors...\")\n",
- " palette = [\"#6510F4\", \"#0DFF00\", \"#FFFFFF\"]\n",
- " node_colors, color_map = assign_node_colors(G, node_attribute, palette)\n",
- "\n",
- " logging.info(\"Calculating centrality...\")\n",
- " centrality = nx.degree_centrality(G)\n",
- "\n",
- " logging.info(\"Preparing Bokeh output...\")\n",
- " output_file(output_filename)\n",
- " p = figure(\n",
- " title=title,\n",
- " tools=\"pan,wheel_zoom,save,reset,hover\",\n",
- " active_scroll=\"wheel_zoom\",\n",
- " width=1200,\n",
- " height=900,\n",
- " background_fill_color=\"#F4F4F4\",\n",
- " x_range=Range1d(-layout_scale, layout_scale),\n",
- " y_range=Range1d(-layout_scale, layout_scale),\n",
- " )\n",
- " p.toolbar.logo = None\n",
- " p.axis.visible = False\n",
- " p.grid.visible = False\n",
- "\n",
- " logging.info(\"Embedding logo into visualization...\")\n",
- " embed_logo(p, layout_scale, logo_alpha)\n",
- "\n",
- " logging.info(\"Styling and rendering graph...\")\n",
- " style_and_render_graph(p, G, layout_positions, node_attribute, node_colors, centrality)\n",
- "\n",
- " logging.info(\"Adding hover tool...\")\n",
- " hover_tool = HoverTool(\n",
- " tooltips=[\n",
- " (\"Node\", \"@index\"),\n",
- " (node_attribute.capitalize(), f\"@{node_attribute}\"),\n",
- " (\"Centrality\", \"@radius{0.00}\"),\n",
- " ],\n",
- " )\n",
- " p.add_tools(hover_tool)\n",
- " # from bokeh.io import output_notebook, show\n",
- " # \n",
- " # # Save the result\n",
- " # output_notebook()\n",
- " # \n",
- " # # Display the plot in the notebook\n",
- " # show(p)\n",
- "\n",
- " logging.info(f\"Saving visualization to {output_filename}...\")\n",
- " html_content = file_html(p, CDN, title)\n",
- " with open(output_filename, \"w\") as f:\n",
- " f.write(html_content)\n",
- " # \n",
- " # logging.info(\"Visualization complete.\")\n",
- " print(html_content)\n",
- "\n",
- " # return html_content\n",
- "\n",
- "\n",
- "def graph_to_tuple(graph):\n",
- " \"\"\"\n",
- " Converts a networkx graph to a tuple of (nodes, edges).\n",
- "\n",
- " :param graph: A networkx graph.\n",
- " :return: A tuple (nodes, edges).\n",
- " \"\"\"\n",
- " nodes = list(graph.nodes(data=True)) # Get nodes with attributes\n",
- " edges = list(graph.edges(data=True)) # Get edges with attributes\n",
- " return (nodes, edges)"
- ],
- "id": "bf001eeda0f4f450",
- "outputs": [],
- "execution_count": 110
- },
- {
- "metadata": {
- "ExecuteTime": {
- "end_time": "2024-12-30T09:50:39.237084Z",
- "start_time": "2024-12-30T09:50:39.184107Z"
- }
- },
- "cell_type": "code",
- "source": [
- "\n",
- "import networkx as nx\n",
- "\n",
- "# graph_data = await graph_engine.get_graph_data()\n",
- "# \n",
- "# print(graph_data)\n",
- "G = nx.random_geometric_graph(50, 0.3)\n",
- "# Assign random group attributes for coloring\n",
- "for i, node in enumerate(G.nodes()):\n",
- " G.nodes[node][\"group\"] = f\"Group {i % 3 + 1}\"\n",
- "def graph_to_tuple(graph):\n",
- " \"\"\"\n",
- " Converts a networkx graph to a tuple of (nodes, edges).\n",
- " \n",
- " :param graph: A networkx graph.\n",
- " :return: A tuple (nodes, edges).\n",
- " \"\"\"\n",
- " nodes = list(graph.nodes(data=True)) # Get nodes with attributes\n",
- " edges = list(graph.edges(data=True)) # Get edges with attributes\n",
- " return (nodes, edges)\n",
- "\n",
- "G= graph_to_tuple(G)\n",
- " \n",
- "print(G)\n",
- "\n",
- "create_cognee_style_network_with_logo(\n",
- " G,\n",
- " output_filename=\"cognee_style_network_with_logo.html\",\n",
- " title=\"Cognee-Graph Network\",\n",
- " node_attribute=\"group\",\n",
- " layout_func=nx.spring_layout,\n",
- " layout_scale=3.0, \n",
- ")"
- ],
- "id": "75ff7ff88fd5894e",
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "INFO:root:Converting graph to serializable format...INFO:root:Generating layout positions...INFO:root:Assigning node colors...INFO:root:Calculating centrality...INFO:root:Preparing Bokeh output...INFO:bokeh.io.state:Session output file 'cognee_style_network_with_logo.html' already exists, will be overwritten.INFO:root:Embedding logo into visualization...INFO:root:Styling and rendering graph...INFO:root:Adding hover tool...INFO:root:Saving visualization to cognee_style_network_with_logo.html..."
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
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- "\n",
- "\n",
- " \n",
- " \n",
- " Cognee-Graph Network\n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- "\n"
- ]
- }
- ],
- "execution_count": 111
- },
{
"metadata": {
"ExecuteTime": {
@@ -2142,7 +1458,7 @@
"cell_type": "code",
"outputs": [],
"execution_count": null,
- "source": " 0.0667",
+ "source": "",
"id": "d042efe5d38144fa"
},
{
@@ -2150,7 +1466,7 @@
"cell_type": "code",
"outputs": [],
"execution_count": null,
- "source": "0.085",
+ "source": "",
"id": "9436af97520e0ae"
}
],