28M Hacker News comments as vector embedding search dataset
13 days ago
- #embeddings
- #generative-ai
- #semantic-search
- Sentence Transformers provide local, easy-to-use embedding models for capturing semantic meaning.
- The HackerNews dataset includes vector embeddings generated using the all-MiniLM-L6-v2 model.
- A Python script example demonstrates generating embeddings and performing cosine similarity search in ClickHouse.
- The script takes a user query, generates an embedding, and retrieves relevant posts from HackerNews.
- A summarization demo application uses embeddings, LangChain, and OpenAI's GPT-3.5-turbo to summarize retrieved content.
- The application is applicable to domains like customer sentiment analysis, technical support automation, and document mining.
- An example query about 'ClickHouse performance experiences' retrieves and summarizes relevant discussions.
- The summary highlights ClickHouse's performance, cost-efficiency, and comparisons with other databases.
- The code for the summarization application includes steps for embedding generation, retrieval, and summarization using LangChain and OpenAI.