Ask .NET Rocks! questions with Semantic Kernel, GPT, and Chroma DB
Blog post from AssemblyAI
In this tutorial, we built a simple .NET Core application that uses the OpenAI API to demonstrate the Retriever- Augmented Generation (RAG) pattern. We used semantic search to retrieve relevant pieces of text from a podcast transcript and then used a language model to generate answers based on those retrieved pieces of text. The code in this tutorial is for demonstration purposes only and should not be used as-is in production applications. Always ensure that your application complies with the terms of service of any third-party services it uses, including OpenAI's API.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 41 | 1,728 | 228 | 84 | +63% |
| RAG | 12 | 1,418 | 170 | 60 | +93% |
| LLM | 9 | 2,790 | 311 | 123 | +34% |
| Secrets Management | 7 | 865 | 106 | 64 | +106% |
| OpenTelemetry | 1 | 310 | 47 | 20 | -33% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.