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chore: import upstream snapshot with attribution
2026-07-13 12:26:52 +08:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "87854970",
"metadata": {},
"source": [
"<a href=\"https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/customization/streaming/SimpleIndexDemo-streaming.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "9c48213d-6e6a-4c10-838a-2a7c710c3a05",
"metadata": {},
"source": [
"# Streaming"
]
},
{
"cell_type": "markdown",
"id": "8a660477",
"metadata": {},
"source": [
"If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d3dc5ada",
"metadata": {},
"outputs": [],
"source": [
"!pip install llama-index"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "690a6918-7c75-4f95-9ccc-d2c4a1fe00d7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:numexpr.utils:Note: NumExpr detected 12 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n",
"Note: NumExpr detected 12 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n",
"INFO:numexpr.utils:NumExpr defaulting to 8 threads.\n",
"NumExpr defaulting to 8 threads.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/suo/miniconda3/envs/llama/lib/python3.9/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.6.7) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.\n",
" warnings.warn(\n"
]
}
],
"source": [
"import logging\n",
"import sys\n",
"\n",
"logging.basicConfig(stream=sys.stdout, level=logging.INFO)\n",
"logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))\n",
"\n",
"from llama_index.core import VectorStoreIndex, SimpleDirectoryReader"
]
},
{
"cell_type": "markdown",
"id": "738c7284",
"metadata": {},
"source": [
"#### Download Data"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5eb5ecc0",
"metadata": {},
"outputs": [],
"source": [
"!mkdir -p 'data/paul_graham/'\n",
"!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "50d3b817-b70e-4667-be4f-d3a0fe4bd119",
"metadata": {},
"source": [
"#### Load documents, build the VectorStoreIndex"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "03d1691e-544b-454f-825b-5ee12f7faa8a",
"metadata": {},
"outputs": [],
"source": [
"# load documents\n",
"documents = SimpleDirectoryReader(\"./data/paul_graham\").load_data()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ad144ee7-96da-4dd6-be00-fd6cf0c78e58",
"metadata": {},
"outputs": [],
"source": [
"index = VectorStoreIndex.from_documents(documents)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "b6caf93b-6345-4c65-a346-a95b0f1746c4",
"metadata": {},
"source": [
"#### Query Index"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "85466fdf-93f3-4cb1-a5f9-0056a8245a6f",
"metadata": {},
"outputs": [],
"source": [
"# set Logging to DEBUG for more detailed outputs\n",
"query_engine = index.as_query_engine(streaming=True, similarity_top_k=1)\n",
"response_stream = query_engine.query(\n",
" \"What did the author do growing up?\",\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "29ed26f2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"The author grew up writing short stories and programming on an IBM 1401. He also nagged his father to buy him a TRS-80 microcomputer, on which he wrote simple games, a program to predict how high his model rockets would fly, and a word processor. He eventually went to college to study philosophy, but found it boring and switched to AI."
]
}
],
"source": [
"response_stream.print_response_stream()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "llama",
"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"
}
},
"nbformat": 4,
"nbformat_minor": 5
}