Daniel Chalef 6d52be49f4
Add Apache License 2.0 boilerplate to all Python files (#30)
* Add Apache License 2.0 boilerplate to all Python files

---

For more details, open the [Copilot Workspace session](https://copilot-workspace.githubnext.com/getzep/graphiti?shareId=XXXX-XXXX-XXXX-XXXX).

* format

* format

* chore: Add Ellipsis configuration file
2024-08-23 16:01:33 -04:00
2024-08-22 15:16:15 -07:00
2024-08-13 14:35:43 -04:00
2024-08-22 12:26:13 -07:00
2024-08-23 11:15:44 -04:00
2024-08-22 13:06:42 -07:00
2024-08-22 12:26:13 -07:00

Graphiti (LLM generated readme)

Graphiti is a Python library for building and managing knowledge graphs using Neo4j and OpenAI's language models. It provides a flexible framework for processing episodes of information, extracting semantic nodes and edges, and maintaining a dynamic graph structure.

Features

  • Asynchronous interaction with Neo4j database
  • Integration with OpenAI's GPT models for natural language processing
  • Automatic extraction of semantic nodes and edges from episodic data
  • Temporal tracking of relationships and facts
  • Flexible schema management

Installation

(Add installation instructions here)

Quick Start

from graphiti import Graphiti

# Initialize Graphiti
graphiti = Graphiti("bolt://localhost:7687", "neo4j", "password")

# Process an episode
await graphiti.process_episode(
    name="Example Episode",
    episode_body="Alice met Bob at the coffee shop.",
    source_description="User input",
    reference_time=datetime.now()
)

# Retrieve recent episodes
recent_episodes = await graphiti.retrieve_episodes(last_n=5)

# Close the connection
graphiti.close()

Documentation

(Add link to full documentation when available)

Contributing

(Add contribution guidelines)

License

This project is licensed under the Apache License, Version 2.0. See the LICENSE file for details.

Description
Build Real-Time Knowledge Graphs for AI Agents
Readme Apache-2.0 22 MiB
Languages
Python 99.4%
Dockerfile 0.4%
Makefile 0.2%