The Open Source AI Stack

You don’t need to spend a fortune to build an AI application. The best AI developer tools are open-source, and an excellent ecosystem is evolving that can make AI accessible to everyone.

The key components of this open-source AI stack are as follows:

Frontend

To build beautiful AI UIs, frameworks like NextJS and Streamlit are extremely useful. Also, Vercel can help with deployment.

Embeddings and RAG libraries

Embedding models and RAG libraries like Nomic, JinaAI, Cognito, and LLMAware help developers build accurate search and RAG features.

Backend and Model Access

For backend development, developers can rely on frameworks like FastAPI, Langchain, and Netflix Metaflow. Options like Ollama and Huggingface are available for model access.

Data and Retrieval

For data storage and retrieval, several options like Postgres, Milvus, Weaviate, PGVector, and FAISS are available.

Large-Language Models

Based on performance benchmarks, open-source models like Llama, Mistral, Qwen, Phi, and Gemma are great alternatives to proprietary LLMs like GPT and Claude.