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Lettria's Text-to-Graph SDK 🚀

In today's world, a vast amount of valuable information is locked away in unstructured text—documents, articles, emails, and more. While AI and analytics tools are incredibly powerful, they struggle to make sense of this chaotic data. They need structured, connected information to reason effectively.

This is where the gap lies:

What Organizations Have	What AI Systems Need
📄 Unstructured Text	🔗 Connected Knowledge
Chaotic, disconnected data	Structured, queryable graphs
Implicit relationships	Explicit entities and relations
Hard to query and analyze	Ready for deep analysis

Without a way to bridge this gap, AI systems can't unlock the full potential of your data. They might miss critical insights, provide incomplete answers, or fail to see the bigger picture.

Lettria's Text-to-Graph SDK is designed to solve this problem. It transforms your raw text into a structured knowledge graph, making it instantly usable for AI applications, from advanced search to complex reasoning. Furthermore, the SDK empowers users to leverage their own ontologies, providing a flexible way to define the desired data schema. This greatly reduces data complexity and ensures the generated knowledge graph is precisely tailored to specific use cases.

🌟 Features

• Asynchronous Client: High-performance, non-blocking API calls using asyncio and aiohttp.
• Simple Interface: Easy-to-use methods for file operations, ontology management, and graph building.
• Data Validation: Robust data modeling with pydantic.
• Neo4j Integration: Directly save your graph data to a Neo4j instance.
• Flexible Configuration: Configure via environment variables or directly in code.

📦 Installation

pip install t2g-sdk==1.0.0-rc.15

🚀 Quick Start

To start using the SDK, you will need an API key from Lettria.

To create an API key, please visit our preview instance here.

Access to the API is managed by whitelisting. If you require access, please contact us at hello@lettria.com to request whitelisting.

Configuration

The SDK can be configured via environment variables. The T2GClient will automatically load them. You can place them in a .env file in your project root.

Variable	Description	Required
LETTRIA_API_KEY	Your unique API key for the Lettria API.	Yes
NEO4J_URI	The URI for your Neo4j database instance.	No
NEO4J_USER	The username for your Neo4j database.	No
NEO4J_PASSWORD	The password for your Neo4j database.	No

Example: Build a Graph

This example shows how to build a graph from a text file.

import asyncio
from t2g_sdk import T2GClient

async def main():
    async with T2GClient() as client:
        try:
            await client.build_graph(
                file_path="path/to/your/document.txt",
            )
            print("🎉 Graph built successfully!")
        except Exception as e:
            print(f"An error occurred: {e}")

if __name__ == "__main__":
    asyncio.run(main())

📚 API Reference

client.build_graph

async def build_graph(
    file_path: str,
    ontology_path: Optional[str] = None,
    output_path: Optional[str] = None,
    save_to_neo4j: bool = False,
    refresh_graph: bool = False,
) -> Job:

Processes a file by uploading it, optionally with an ontology, running a job, and downloading the output.

Parameter	Type	Description	Default
file_path	str	The path to the file to process.
ontology_path	Optional[str]	The path to the ontology file to use.	None
output_path	Optional[str]	The path to save the output to. If not provided, a default path will be used.	None
save_to_neo4j	bool	Whether to save the output to Neo4j.	False
refresh_graph	bool	Whether to force a new job to be created (refresh the graph).	False

📂 Examples

For more detailed examples, check out the examples/ directory. Each example has its own README with instructions.

Simple Examples

• Build Graph: Build a knowledge graph from a text file.
• File Operations: Upload and manage files.
• Ontology Operations: Upload and manage ontologies.
• Delete Operations: Delete files and ontologies.

Advanced Example

• Graph RAG Reporting: A complete workflow to turn a PDF into a knowledge graph and generate a report.

🤝 Contributing

Contributions are welcome! Feel free to open an issue or submit a pull request.

📧 Contact

For support or questions, please reach out at hello@lettria.com.

📄 License

This SDK is licensed under the MIT License.