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read-and-write-embeddings-with-neo4j-vector-storage's Introduction

Read and Write Embeddings with Neo4j Vector Storage

✅ 1. Set Up & Connect: Initialized connections with Neo4j Aura DB, loaded necessary Python libraries, and established links to OpenAI's API for embedding processing.

✅ 2. Data Retrieval: Wrote Cypher queries to pull documents, and topics from the database.

✅ 3. Embedding Analysis with ChatGPT: For over 300 patents in the topic 'Machine Learning', I utilized OpenAI's powerful GPT-4 to summarize their abstracts in layman's terms.

✅ 4. Embedding Synthesis: Took these concise summaries and generated embeddings, storing them back in Neo4j.

✅ 5. Visual Analysis: Employed plotly & UMAP for dimensionality reduction and visualization.

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