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* feat: Initial version of temporal invalidation + tests * fix: dont run int tests on CI * fix: dont run int tests on CI * fix: dont run int tests on CI * fix: time of day issue * fix: running non int tests in ci * fix: running non int tests in ci * fix: running non int tests in ci * fix: running non int tests in ci * fix: running non int tests in ci * fix: running non int tests in ci * fix: running non int tests in ci * revert: Tests structural changes * chore: Remove idea file * chore: Get rid of NodesWithEdges class and define a triplet type instead
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)
Languages
Python
99.4%
Dockerfile
0.4%
Makefile
0.2%