yujunjun/graphiti
1
0
Fork 0
mirror of https://github.com/getzep/graphiti.git synced 2025-06-27 02:00:02 +00:00
Code Issues Packages Projects Releases Wiki Activity

Neo4j 5.26 (#271)

Browse Source 
5.26
This commit is contained in:
Preston Rasmussen 2025-02-21 13:05:41 -05:00 committed by GitHub
parent 088029a80c
commit 5e57c58037
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 7 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
README.md
View File

@ -47,7 +47,8 @@ recall and state-based reasoning for both assistants and agents.
Graphiti powers the core of [Zep's memory layer](https://www.getzep.com) for LLM-powered Assistants and Agents.
Using Graphiti, we've demonstrated Zep is the [State of the Art in Agent Memory](https://blog.getzep.com/state-of-the-art-agent-memory/).
Using Graphiti, we've demonstrated Zep is
the [State of the Art in Agent Memory](https://blog.getzep.com/state-of-the-art-agent-memory/).
Read our paper: [Zep: A Temporal Knowledge Graph Architecture for Agent Memory](https://arxiv.org/abs/2501.13956).
@ -86,7 +87,7 @@ scale:
Requirements:
- Python 3.10 or higher
- Neo4j 5.21 or higher
- Neo4j 5.26 or higher
- OpenAI API key (for LLM inference and embedding)
Optional:
@ -111,7 +112,8 @@ poetry add graphiti-core
> [!IMPORTANT]
> Graphiti uses OpenAI for LLM inference and embedding. Ensure that an `OPENAI_API_KEY` is set in your environment.
> Support for Anthropic and Groq LLM inferences is available, too. Other LLM providers may be supported via OpenAI compatible APIs.
> Support for Anthropic and Groq LLM inferences is available, too. Other LLM providers may be supported via OpenAI
> compatible APIs.
```python
from graphiti_core import Graphiti
@ -203,8 +205,8 @@ as such this feature is off by default.
Graphiti is under active development. We aim to maintain API stability while working on:
- [ ] Supporting custom graph schemas:
- Allow developers to provide their own defined node and edge classes when ingesting episodes
- Enable more flexible knowledge representation tailored to specific use cases
- Allow developers to provide their own defined node and edge classes when ingesting episodes
- Enable more flexible knowledge representation tailored to specific use cases
- [x] Enhancing retrieval capabilities with more robust and configurable options
- [ ] Expanding test coverage to ensure reliability and catch edge cases