If you want to use AI with RAG then go through these resources:
A great langchain RAG tutorial video from @pixegami
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https://www.youtube.com/watch?v=tcqEUSNCn8I
- accompanying github repo: https://github.com/pixegami/langchain-rag-tutorial
The front end for Vector Databases. Works with most of the vector databases such as Pinecone, Chroma, Q
https://vectoradmin.com/
https://www.pinecone.io/
Build knowledgeable AI
With its vector database at the core, Pinecone is the leading knowledge platform for building accurate, secure, and scalable AI applications.
https://www.trychroma.com/
Chroma is the open-source AI application database. Batteries included.
https://qdrant.tech/
High-Performance Vector Search at Scale
Powering the next generation of AI applications with advanced, open-source vector similarity search technology.
https://weaviate.io/
The AI-native database for a new generation of software
Bring intuitive AI-native applications to life with less hallucination, data leakage, and vendor lock-in with the open source vector database developers love.
Top comments (1)
Great resource compilation! For those exploring vector databases, it's also worth checking out Astra DB's vector capabilities - they have some interesting RAG examples and offer a generous free tier for testing. The serverless aspect makes it particularly convenient for prototyping RAG applications.