No description
* chore: Add romeo runner * fix: Linter * dedupe fixes * wip * wip dump * allbirds * chore: Update romeo parser * chore: Anthropic model fix * allbirds runner * format * wip * mypy updates * update * remove r * update tests * format * wip * wip * wip * chore: Strategically update the message * chore: Add romeo runner * fix: Linter * wip * wip dump * chore: Update romeo parser * chore: Anthropic model fix * wip * allbirds * allbirds runner * format * wip * wip * mypy updates * update * remove r * update tests * format * wip * chore: Strategically update the message * rebase and fix import issues * Update package imports for graphiti_core in examples and utils * nits * chore: Update OpenAI GPT-4o model to gpt-4o-2024-08-06 * implement groq * improvments & linting * cleanup and nits * Refactor package imports for graphiti_core in examples and utils * Refactor package imports for graphiti_core in examples and utils * chore: Nuke unused examples * chore: Nuke unused examples * chore: Only run type check on graphiti_core * fix unit tests * reformat * unit test * fix: Unit tests * test: Add coverage for extract_date_strings_from_edge * lint * remove commented code --------- Co-authored-by: prestonrasmussen <prasmuss15@gmail.com> Co-authored-by: Daniel Chalef <131175+danielchalef@users.noreply.github.com> |
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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
This project is licensed under the Apache License, Version 2.0. See the LICENSE file for details.