Data Exploration With the Neo4j Runway Python Library
Blog post from Neo4j
The Neo4j Runway Python library is a tool for exploring and ingesting relational data into a Neo4j graph database. It provides a simplified user experience by abstracting communication with OpenAI to run discovery on the data and generate a data model, as well as tools for generating ingestion code and loading data into a Neo4j instance. The library relies on large language models (LLMs) from OpenAI to provide valuable insights from the data. It supports two code generation options: LOAD CSV and PyIngest YAML configuration, both of which generate necessary Cypher code to create constraints and load CSV data. The library also provides a built-in ingestion function via a modified PyIngest file. Runway is still in beta and encourages feedback and bug reporting.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 29 | 3,003 | 371 | 151 | +0% |
| Data Pipeline | 2 | 431 | 151 | 67 | -20% |
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