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add Epsilla vectorstore (#9239)
[Epsilla](https://github.com/epsilla-cloud/vectordb) vectordb is an open-source vector database that leverages the advanced academic parallel graph traversal techniques for vector indexing. This PR adds basic integration with [pyepsilla](https://github.com/epsilla-cloud/epsilla-python-client)(Epsilla vectordb python client) as a vectorstore. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
ricki-epsilla
GitHub
23
docs/extras/integrations/providers/epsilla.mdx
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23
docs/extras/integrations/providers/epsilla.mdx
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# Epsilla
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This page covers how to use [Epsilla](https://github.com/epsilla-cloud/vectordb) within LangChain.
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It is broken into two parts: installation and setup, and then references to specific Epsilla wrappers.
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## Installation and Setup
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- Install the Python SDK with `pip/pip3 install pyepsilla`
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## Wrappers
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### VectorStore
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There exists a wrapper around Epsilla vector databases, allowing you to use it as a vectorstore,
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whether for semantic search or example selection.
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To import this vectorstore:
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```python
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from langchain.vectorstores import Epsilla
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```
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For a more detailed walkthrough of the Epsilla wrapper, see [this notebook](/docs/integrations/vectorstores/epsilla.html)
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160
docs/extras/integrations/vectorstores/epsilla.ipynb
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docs/extras/integrations/vectorstores/epsilla.ipynb
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Epsilla\n",
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"\n",
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">[Epsilla](https://www.epsilla.com) is an open-source vector database that leverages the advanced parallel graph traversal techniques for vector indexing. Epsilla is licensed under GPL-3.0.\n",
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"\n",
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"This notebook shows how to use the functionalities related to the `Epsilla` vector database.\n",
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"\n",
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"As a prerequisite, you need to have a running Epsilla vector database (for example, through our docker image), and install the ``pyepsilla`` package. View full docs at [docs](https://epsilla-inc.gitbook.io/epsilladb/quick-start)."
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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/pip3 install pyepsilla"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We want to use OpenAIEmbeddings so we have to get the OpenAI API Key. "
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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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"import os\n",
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"import getpass\n",
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"\n",
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"os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"OpenAI API Key: ········"
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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.embeddings import OpenAIEmbeddings\n",
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"from langchain.vectorstores import Epsilla"
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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.document_loaders import TextLoader\n",
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"from langchain.text_splitter import CharacterTextSplitter\n",
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"\n",
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"loader = TextLoader(\"../../modules/state_of_the_union.txt\")\n",
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"documents = loader.load()\n",
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"\n",
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"documents = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0).split_documents(documents)\n",
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"\n",
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"embeddings = OpenAIEmbeddings()"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Epsilla vectordb is running with default host \"localhost\" and port \"8888\". We have a custom db path, db name and collection name instead of the default ones."
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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 pyepsilla import vectordb\n",
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"\n",
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"client = vectordb.Client()\n",
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"vector_store = Epsilla.from_documents(\n",
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" documents,\n",
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" embeddings,\n",
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" client,\n",
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" db_path=\"/tmp/mypath\",\n",
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" db_name=\"MyDB\",\n",
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" collection_name=\"MyCollection\"\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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"metadata": {},
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"outputs": [],
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"source": [
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"query = \"What did the president say about Ketanji Brown Jackson\"\n",
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"docs = vector_store.similarity_search(query)\n",
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"print(docs[0].page_content)"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections.\n",
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"\n",
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"We cannot let this happen.\n",
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"\n",
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"Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections.\n",
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"\n",
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"Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.\n",
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"\n",
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"One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court.\n",
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"\n",
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"And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence."
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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",
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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": "3.9.17"
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},
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"orig_nbformat": 4
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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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