No description
| .github | ||
| core | ||
| tests | ||
| .env.example | ||
| .gitignore | ||
| conftest.py | ||
| podcast_runner.py | ||
| podcast_transcript.txt | ||
| poetry.lock | ||
| pyproject.toml | ||
| pytest.ini | ||
| README.md | ||
| runner.py | ||
| SECURITY.md | ||
| transcript_parser.py | ||
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
(Add license information)