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 📚
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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.
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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 🛠️
- Input: Feed it your text, specify entity types (e.g., person, organization) and relationships (e.g., works at, founded).
- Extraction: The model, fine-tuned on a massive dataset, identifies and extracts entities and relationships from your text.
- 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!