139 lines
3.4 KiB
Plaintext
139 lines
3.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Quick Start \n",
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"\n",
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"**Home GitHub Repository:** [LEANN on GitHub](https://github.com/yichuan-w/LEANN)\n",
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"\n",
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"**Important for Colab users:** Set your runtime type to T4 GPU for optimal performance. Go to Runtime → Change runtime type → Hardware accelerator → T4 GPU."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# install this if you are using colab\n",
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"! uv pip install leann-core leann-backend-hnsw --no-deps\n",
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"! uv pip install leann --no-deps\n",
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"# For Colab environment, we need to set some environment variables\n",
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"import os\n",
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"\n",
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"os.environ[\"LEANN_LOG_LEVEL\"] = \"INFO\" # Enable more detailed logging"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from pathlib import Path\n",
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"\n",
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"INDEX_DIR = Path(\"./\").resolve()\n",
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"INDEX_PATH = str(INDEX_DIR / \"demo.leann\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Build the index"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from leann.api import LeannBuilder\n",
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"\n",
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"builder = LeannBuilder(backend_name=\"hnsw\")\n",
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"builder.add_text(\"C# is a powerful programming language and it is good at game development\")\n",
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"builder.add_text(\n",
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" \"Python is a powerful programming language and it is good at machine learning tasks\"\n",
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")\n",
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"builder.add_text(\"Machine learning transforms industries\")\n",
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"builder.add_text(\"Neural networks process complex data\")\n",
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"builder.add_text(\"Leann is a great storage saving engine for RAG on your MacBook\")\n",
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"builder.build_index(INDEX_PATH)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Search with real-time embeddings"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from leann.api import LeannSearcher\n",
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"\n",
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"searcher = LeannSearcher(INDEX_PATH)\n",
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"results = searcher.search(\"programming languages\", top_k=2)\n",
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"results"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Chat with LEANN using retrieved results"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from leann.api import LeannChat\n",
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"\n",
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"llm_config = {\n",
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" \"type\": \"hf\",\n",
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" \"model\": \"Qwen/Qwen3-0.6B\",\n",
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"}\n",
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"\n",
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"chat = LeannChat(index_path=INDEX_PATH, llm_config=llm_config)\n",
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"response = chat.ask(\n",
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" \"Compare the two retrieved programming languages and tell me their advantages.\",\n",
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" top_k=2,\n",
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" llm_kwargs={\"max_tokens\": 128},\n",
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")\n",
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"response"
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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": ".venv",
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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": "3.11.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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