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docs: Register langchain-singlestore integration (#30841)
I created and published `langchain-singlestoe` integration package that should replace SingleStoreDB community implementation.
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‎docs/docs/integrations/caches/singlestore_semantic_cache.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "e49f1e0d",
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"metadata": {},
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"source": [
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"# SingleStoreSemanticCache\n",
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"\n",
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"This example demonstrates how to get started with the SingleStore semantic cache.\n",
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"\n",
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"### Integration Overview\n",
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"\n",
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"`SingleStoreSemanticCache` leverages `SingleStoreVectorStore` to cache LLM responses directly in a SingleStore database, enabling efficient semantic retrieval and reuse of results.\n",
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"\n",
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"### Integration details\n",
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"\n",
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"\n",
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"\n",
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"| Class | Package | JS support |\n",
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"| :--- | :--- | :---: |\n",
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"| SingleStoreSemanticCache | langchain_singlestore | ❌ | "
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]
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},
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{
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"cell_type": "markdown",
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"id": "0730d6a1-c893-4840-9817-5e5251676d5d",
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"metadata": {},
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"source": [
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"## Installation\n",
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"\n",
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"This cache lives in the `langchain-singlestore` package:"
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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": "652d6238-1f87-422a-b135-f5abbb8652fc",
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install -qU langchain-singlestore"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5c5f2839-4020-424e-9fc9-07777eede442",
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"metadata": {},
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"source": [
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"## Usage"
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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": "51a60dbe-9f2e-4e04-bb62-23968f17164a",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_core.globals import set_llm_cache\n",
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"from langchain_singlestore import SingleStoreSemanticCache\n",
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"\n",
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"set_llm_cache(\n",
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" SingleStoreSemanticCache(\n",
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" embedding=YourEmbeddings(),\n",
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" host=\"root:pass@localhost:3306/db\",\n",
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" )\n",
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")"
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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": "cddda8ef",
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"metadata": {},
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"outputs": [],
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"source": [
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"%%time\n",
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"# The first time, it is not yet in cache, so it should take longer\n",
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"llm.invoke(\"Tell me a joke\")"
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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": "c474168f",
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"metadata": {},
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"outputs": [],
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"source": [
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"%%time\n",
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"# The second time, while not a direct hit, the question is semantically similar to the original question,\n",
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"# so it uses the cached result!\n",
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"llm.invoke(\"Tell me one joke\")"
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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": "langchain-singlestore-BD1RbQ07-py3.11",
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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": "3.11.11"
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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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}

‎docs/docs/integrations/document_loaders/singlestore.ipynb

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{
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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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"---\n",
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"sidebar_label: SingleStore\n",
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"---"
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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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"# SingleStoreLoader\n",
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"\n",
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"The `SingleStoreLoader` allows you to load documents directly from a SingleStore database table. It is part of the `langchain-singlestore` integration package.\n",
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"\n",
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"## Overview\n",
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"\n",
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"### Integration Details\n",
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"\n",
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"| Class | Package | JS Support |\n",
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"| :--- | :--- | :---: |\n",
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"| `SingleStoreLoader` | `langchain_singlestore` | ❌ |\n",
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"\n",
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"### Features\n",
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"- Load documents lazily to handle large datasets efficiently.\n",
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"- Supports native asynchronous operations.\n",
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"- Easily configurable to work with different database schemas.\n",
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"\n",
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"## Setup\n",
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"\n",
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"To use the `SingleStoreLoader`, you need to install the `langchain-singlestore` package. Follow the installation instructions below."
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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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"### Installation\n",
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"\n",
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"Install **langchain_singlestore**."
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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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"%pip install -qU langchain_singlestore"
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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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"## Initialization\n",
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"\n",
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"To initialize `SingleStoreLoader`, you need to provide connection parameters for the SingleStore database and specify the table and fields to load documents from.\n",
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"\n",
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"### Required Parameters:\n",
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"- **host** (`str`): Hostname, IP address, or URL for the database.\n",
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"- **table_name** (`str`): Name of the table to query. Defaults to `embeddings`.\n",
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"- **content_field** (`str`): Field containing document content. Defaults to `content`.\n",
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"- **metadata_field** (`str`): Field containing document metadata. Defaults to `metadata`.\n",
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"\n",
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"### Optional Parameters:\n",
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"- **id_field** (`str`): Field containing document IDs. Defaults to `id`.\n",
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"\n",
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"### Connection Pool Parameters:\n",
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"- **pool_size** (`int`): Number of active connections in the pool. Defaults to `5`.\n",
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"- **max_overflow** (`int`): Maximum connections beyond `pool_size`. Defaults to `10`.\n",
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"- **timeout** (`float`): Connection timeout in seconds. Defaults to `30`.\n",
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"\n",
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"### Additional Options:\n",
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"- **pure_python** (`bool`): Enables pure Python mode.\n",
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"- **local_infile** (`bool`): Allows local file uploads.\n",
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"- **charset** (`str`): Character set for string values.\n",
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"- **ssl_key**, **ssl_cert**, **ssl_ca** (`str`): Paths to SSL files.\n",
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"- **ssl_disabled** (`bool`): Disables SSL.\n",
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"- **ssl_verify_cert** (`bool`): Verifies server's certificate.\n",
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"- **ssl_verify_identity** (`bool`): Verifies server's identity.\n",
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"- **autocommit** (`bool`): Enables autocommits.\n",
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"- **results_type** (`str`): Structure of query results (e.g., `tuples`, `dicts`)."
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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 langchain_singlestore.document_loaders import SingleStoreLoader\n",
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"\n",
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"loader = SingleStoreLoader(\n",
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" host=\"127.0.0.1:3306/db\",\n",
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" table_name=\"documents\",\n",
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" content_field=\"content\",\n",
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" metadata_field=\"metadata\",\n",
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" id_field=\"id\",\n",
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")"
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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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"## Load"
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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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"docs = loader.load()\n",
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"docs[0]"
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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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"print(docs[0].metadata)"
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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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"## Lazy Load"
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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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"page = []\n",
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"for doc in loader.lazy_load():\n",
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" page.append(doc)\n",
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" if len(page) >= 10:\n",
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" # do some paged operation, e.g.\n",
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" # index.upsert(page)\n",
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"\n",
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" page = []"
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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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"## API reference\n",
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"\n",
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"For detailed documentation of all SingleStore Document Loader features and configurations head to the github page: [https://github.com/singlestore-labs/langchain-singlestore/](https://github.com/singlestore-labs/langchain-singlestore/)"
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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": "3.11.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎docs/docs/integrations/llm_caching.ipynb

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"## `SingleStoreDB` semantic cache\n",
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"\n",
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"You can use [SingleStoreDB](https://python.langchain.com/docs/integrations/vectorstores/singlestoredb/) as a semantic cache to cache prompts and responses."
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"You can use [SingleStore](https://python.langchain.com/docs/integrations/vectorstores/singlestore/) as a semantic cache to cache prompts and responses."
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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": "596e15e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install -qU langchain-singlestore"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_community.cache import SingleStoreDBSemanticCache\n",
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"from langchain_openai import OpenAIEmbeddings\n",
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"from langchain_singlestore.cache import SingleStoreSemanticCache\n",
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"\n",
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"set_llm_cache(\n",
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" SingleStoreDBSemanticCache(\n",
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" SingleStoreSemanticCache(\n",
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" embedding=OpenAIEmbeddings(),\n",
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" host=\"root:pass@localhost:3306/db\",\n",
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" )\n",

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