Google Cloud Vertex AI
SEC Filings GenAI Labs
This example consists of two sample applications that show how to use Neo4j with the generative AI capabilities in Google Cloud Vertex AI. We explore how to leverage Google generative AI to build and consume a knowledge graph in Neo4j.
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assetmanager - Parses data from the SEC containing quarterly filings of asset managers. We build a graph containing assets managers and the securities they hold. A chatbot that queries the knowledge graph is included as well.
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resume - Extracts entities like jobs and skills from a collection of resumes, then builds a graphs showing what talents individuals share. A chatbot that queries the knowledge graph is included as well.
Installation
The Demo is available on GitHub: https://github.com/neo4j-partners/neo4j-generative-ai-google-cloud
Knowledge Graph Generation with Gemini Pro
The LLM Graph Builder that extracts entities from unstructured text (PDFs, YouTube Transcripts, Wikipedia) can be configured to use VertexAI both as embedding model and Gemnini as LLM for the extraction. PDFs can be also be loaded from Google Cloud buckets.
It uses the underlying llm-graph-transformer library that we contributed to LangChain.