Pavlo Paliychuk ad552b527e
Cleanup maintenance utilities + add podcast runner (#5)
* chore: Fix minor issues with episodic edge building + cleanup

* feat: Port podcast runner

* feat: Port podcast runner
2024-08-16 09:29:57 -04:00
2024-08-15 11:04:57 -04:00
2024-08-13 14:35:43 -04:00
2024-08-15 11:04:57 -04:00
2024-08-15 11:04:57 -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

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Contributing

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License

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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%