Sciphi Triplex: A Powerful and Cost-Effective Alternative to Microsoft Graph RAG 🚀

Introduction 🤔

This is a breakdown of Sciphi Triplex, a game-changer for creating knowledge graphs from unstructured data, especially compared to Microsoft’s Graph RAG.

Why Sciphi Triplex? 💡

• Cost-Effective: 10x cheaper than Microsoft Graph RAG. 💰
• High-Performance: Comparable to GPT-4 in performance, with even better efficiency!
• User-Friendly: Easy to use, especially with R2R’s simplified setup and integration with Neo4j for visualization.

Understanding Graph RAG vs Basic RAG 📚

• Basic RAG:

  • Converts data to embeddings and stores them in a vector database.
  • Answers queries by searching the vector database and sending the results to an LLM for response generation.
  • Results in lower quality responses compared to Graph RAG.

• Graph RAG:

  • Extracts entities and relationships from data and saves them in a knowledge graph database (like Neo4j).
  • Answers queries by performing a knowledge graph search and sending the entities and relationships to an LLM for response generation.
  • Provides higher quality and more relevant responses.

How Sciphi Triplex Works 🛠️

1. Input: Feed it your text, specify entity types (e.g., person, organization) and relationships (e.g., works at, founded).
2. Extraction: The model, fine-tuned on a massive dataset, identifies and extracts entities and relationships from your text.
3. Output: You get a structured representation of your data as triplets – subject, predicate, object (e.g., Elon Musk – founded – SpaceX).

Running Sciphi Triplex: 🏃‍♂️

• Hugging Face: Requires a GPU; good for experimentation and understanding the underlying concepts.
• Ollama: Run locally on your computer, even without a GPU, making it free and accessible!
• R2R (Recommended): Simplifies the entire process:
  • Ingests data.
  • Performs entity and relationship extraction with Sciphi Triplex.
  • Stores the resulting knowledge graph in Neo4j.
  • Offers a user-friendly interface for querying and visualization.

Resources 🧰

• Sciphi Triplex Blog Post: https://mer.vin/2024/07/sciphi-triple… – Provides a detailed explanation of Sciphi Triplex and its benefits.
• GraphRAG vs. Basic RAG Comparison: https://mer.vin/2024/07/graphrag-vs-b… – Explains the differences between Graph RAG and Basic RAG and their use cases.
• R2R with Sciphi Triplex: https://mer.vin/2024/07/r2r-sciphi-tr… – Provides a guide on how to use Sciphi Triplex with R2R to simplify the process of building a knowledge graph.
• GraphRAG with Microsoft Products: https://mer.vin/2024/07/graphrag-with… – Explains how to use Microsoft products for GraphRAG.
• GPU Discount: https://bit.ly/mervin-praison Coupon: MervinPraison (50% Discount) – Get a 50% discount on a GPU using the code “MervinPraison”.
• Patreon: / mervinpraison – Support the creator and get access to exclusive content.
• Ko-fi: https://ko-fi.com/mervinpraison – Support the creator with a one-time donation.
• Discord: / discord – Join the community for discussions and support.
• Twitter/X: / mervinpraison – Follow for updates and insights.

Conclusion 🎉

Sciphi Triplex offers a powerful, efficient, and affordable way to unlock the potential of knowledge graphs. Give it a try and see the difference!