Spaces:
Sleeping
Sleeping
File size: 1,970 Bytes
5a5be73 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
{
"cells": [
{
"cell_type": "markdown",
"id": "dfad5f6b",
"metadata": {},
"source": [
"# Demo: AI-Powered Scientific Research Companion\n",
"This notebook demonstrates how to use the `Dispatcher` to search for papers, retrieve reproducible notebook cells, and fetch a knowledge graph."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "307d78b9",
"metadata": {},
"outputs": [],
"source": [
"from orchestrator.dispatcher import Dispatcher\n",
"\n",
"# Initialize dispatcher\n",
"dispatcher = Dispatcher()\n",
"\n",
"# Example query\n",
"query = \"CRISPR delivery\"\n",
"\n",
"# 1. Search for papers\n",
"papers = dispatcher.search_papers(query, limit=3)\n",
"print(\"Papers found:\")\n",
"for p in papers:\n",
" print(f\"- {p['title']} (ID: {p['id']})\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8db389c8",
"metadata": {},
"outputs": [],
"source": [
"# 2. Retrieve notebook cells for the first paper\n",
"if papers:\n",
" first_id = papers[0]['id']\n",
" cells = dispatcher.get_notebook_cells(first_id)\n",
" print(f\"Notebook cells for paper {first_id}:\")\n",
" for i, cell in enumerate(cells, 1):\n",
" print(f\"Cell {i}:\")\n",
" print(cell)\n",
" print(\"------\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "52666e2a",
"metadata": {},
"outputs": [],
"source": [
"# 3. Fetch knowledge graph for the first paper\n",
"if papers:\n",
" graph = dispatcher.get_graph(first_id)\n",
" print(\"Graph nodes:\")\n",
" for node in graph.get(\"nodes\", []):\n",
" print(node)\n",
" print(\"Graph edges:\")\n",
" for edge in graph.get(\"edges\", []):\n",
" print(edge)\n"
]
}
],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 5
}
|