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Pavlo Paliychuk 40e74a2e97
fix: Address graph disconnect (#7)
* fix: Address graph disconnect

* chore: Remove valid_to and valid_from setting in extract edges step (will be handled during invalidation step)
2024-08-19 09:37:56 -04:00
core fix: Address graph disconnect (#7) 2024-08-19 09:37:56 -04:00
tests Update Maintenance LLM Queries and Partial Schema Retrieval (#6) 2024-08-18 13:22:31 -04:00
.env.example add nodes and edges 2024-08-13 14:35:43 -04:00
.gitignore chore: Add readme, gitignore and poetry files 2024-08-13 14:50:17 -04:00
podcast_runner.py Cleanup maintenance utilities + add podcast runner (#5) 2024-08-16 09:29:57 -04:00
podcast_transcript.txt Cleanup maintenance utilities + add podcast runner (#5) 2024-08-16 09:29:57 -04:00
poetry.lock renaming and add indices (#3) 2024-08-15 11:04:57 -04:00
pyproject.toml renaming and add indices (#3) 2024-08-15 11:04:57 -04:00
README.md chore: Add readme, gitignore and poetry files 2024-08-13 14:50:17 -04:00
runner.py fix: Address graph disconnect (#7) 2024-08-19 09:37:56 -04:00
transcript_parser.py Cleanup maintenance utilities + add podcast runner (#5) 2024-08-16 09:29:57 -04:00

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

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