Zep stores, summarizes, embeds, indexes, and enriches LLM app / chatbot histories, and exposes them via simple, low-latency APIs. Zep allows developers to focus on developing their AI apps, rather than on building memory persistence, search, and enrichment infrastructure.
Zep's Extractor model is easily extensible, with a simple, clean interface available to build new enrichment functionality, such as summarizers, entity extractors, embedders, and more.
Key Features:
- Fast! Zep's async extractors operate independently of the your chat loop, ensuring a snappy user experience.
- Memory operations like addMemory(), getMemory(), searchMemory(), deleteMemory() with soft & hard deletes
- Long-term memory persistence, with access to historical messages irrespective of your summarization strategy.
- Auto-summarization of memory messages based on a configurable message window. A series of summaries are stored, providing flexibility for future summarization strategies.
- Hybrid Vector search over memories and metadata, with messages automatically embedded on creation.
- Entity Extractor that extracts named entities and intents from messages and stores them in the message metadata.
- Auto-token counting of memories and summaries, allowing finer-grained control over prompt assembly.
- OpenAI & Azure OpenAI Service models for your applications
- Python and JavaScript SDKs.
- Langchain
memoryandretrieversupport.
Read the docs: https://getzep.github.io
- Clone this repo
git clone https://github.com/getzep/zep.git- Add your OpenAI API key to a
.envfile in the root of the repo:
ZEP_OPENAI_API_KEY=<your key here>- Start the Zep server:
docker-compose upThis will start a Zep server on port 8000, and a Postgres database on port 5432.
- Access Zep via the Python or Javascript SDKs:
Python
async with ZepClient(base_url) as client:
role = "user"
content = "who was the first man to go to space?"
message = Message(role=role, content=content)
memory = Memory()
memory.messages = [message]
# Add a memory
result = await client.aadd_memory(session_id, memory)See zep-python for installation and use docs.
Javascript
// Add memory
const role = "user";
const content = "I'm looking to plan a trip to Iceland. Can you help me?"
const message = new Message({ role, content });
const memory = new Memory();
memory.messages = [message];
const result = await client.addMemoryAsync(session_id, memory);
...Server installation and SDK usage documentation is available here: https://getzep.github.io
h/t to the Motorhead and Langchain projects for inspiration.