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✨ Effortless RAG With Text2CypherRetriever ✨ We’re excited to introduce the Text2CypherRetriever, which will improve the complexities of creating embedding indexes and using specific models to achieve effective data retrieval. Are you an experienced #Neo4j user or just getting started? Don't worry: the Text2CypherRetriever can significantly streamline your development process. https://bit.ly/40FVYmA #Neo4j #llm #Text2Cypher Will Tai 戴肇恩

Mayank Goyal

Generative AI || Franklin Templeton || IIT Guwahati || MPI-INF

2w

Great work! I’m curious—would the Text2CypherRetriever work well with more complex databases, for example, a graph with 50+ entities, each one atleast having 3-4 different relationships? I imagine it would be a bit more challenging compared to a movie database with fewer entities and relationships. Would love to hear your thoughts!

Homayoun .S

R&D Lead @ LegiSimple | Generative AI and Backend Developer

2d

That’s not what we used to do with langchain, openAI and neo4j? What’s the different here? It’s a finetuned model proposed by NEO4J to decrease the need of implementing all system by ourselves ?

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Love how this new tool simplifies the process of making embedding indexes. It seems that Text2CypherRetriever will have a significant effect on accelerating development processes.

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Very helpful indeed.

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Emanuele Carosi

Ind & Func AI Decision Science Analyst in Accenture | Luiss University Alumnus

2w
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