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* Makefile and format * fix podcast stuff * refactor: update import statement for transcript_parser in podcast_runner.py * format and linting * chore: Update import statements and remove unused code in maintenance module
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
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Contributing
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License
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