This release is a pre-release and may not be stable for production use.
Zep: Fast, scalable building blocks for LLM apps
Chat history memory, embedding, vector search, data enrichment, and more.
Quick Start |
Documentation |
LangChain and
LlamaIndex Support |
Discord
www.getzep.com
What is Zep?
Zep is an open source platform for productionizing LLM apps. Zep summarizes, embeds, and enriches chat histories and documents asynchronously, ensuring these operations don't impact your user's chat experience. Data is persisted to database, allowing you to scale out when growth demands. As drop-in replacements for popular LangChain components, you can get to production in minutes without rewriting code.
Zep Python Client
This is the Python client package for the Zep service. For more information about Zep, see https://github.com/getzep/zep.
Zep QuickStart Guide: https://docs.getzep.com/deployment/quickstart
Zep Documentation: https://docs.getzep.com
Installation
pip install zep-python
-- OR --
poetry add zep-python
Zep Cloud Installation
In order to install Zep Python SDK with Zep Cloud support, you will need to install a release candidate version.
pip install --pre zep-python
-- OR --
poetry add zep-python@^2.0.0rc
You will also need to provide a Zep Project API key to your zep client for cloud support. You can find out about Zep Projects in our cloud docs
Using LangChain Zep Classes with zep-python
(Currently only available on release candidate versions)
In the pre-release version zep-python sdk comes with ZepChatMessageHistory and ZepVectorStore
classes that are compatible with LangChain's Python expression language
In order to use these classes in your application, you need to make sure that you have
langchain_core package installed, please refer to Langchain's docs installation section.
We support langchain_core@>=0.1.3<0.2.0
You can import these classes in the following way:
from zep_python.langchain import ZepChatMessageHistory, ZepVectorStore
Running Examples
You will need to set the following environment variables to run examples in the examples directory:
# Please use examples/.env.example as a template for .env file
# Required
ZEP_API_KEY=<zep-project-api-key># Your Zep Project API Key
ZEP_COLLECTION=<zep-collection-name># used in ingestion script and in vector store examples
OPENAI_API_KEY=<openai-api-key># Your OpenAI API Key
# Optional (If you want to use langsmith with LangServe Sample App)
LANGCHAIN_TRACING_V2=true
LANGCHAIN_API_KEY=<your-langchain-api-key>
LANGCHAIN_PROJECT=<your-langchain-project-name># If not specified, defaults to "default"
1 maintainer
Release files for zep-python 2.0.0rc5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| zep_python-2.0.0rc5.tar.gz | 26.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| zep_python-2.0.0rc5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 60.1 kB
Release files / zep_python-2.0.0rc5.tar.gz
| Download URL | zep_python-2.0.0rc5.tar.gz |
|---|---|
| Size | 26.8 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / zep_python-2.0.0rc5-py3-none-any.whl
| Download URL | zep_python-2.0.0rc5-py3-none-any.whl |
|---|---|
| Size | 33.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Yes |
| Uploaded via |
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