Maximiliano0/RAG_LLM

The project is a textbook implementation of a RAG pipeline using the most common 'standard library' of 2023-2024 (LangChain + ChromaDB + Ollama). With 0 stars and 0 forks, it currently represents a personal learning project or a specific use-case demo rather than a defensible software product. The use of Maximum Marginal Relevance (MMR) for retrieval is a standard feature within LangChain, not a custom innovation. While the focus on Greenpeace environmental documents provides a specific niche, the technical architecture offers no moat; any developer following a 15-minute RAG tutorial could replicate this functionality. Frontier labs (OpenAI with 'Assistant API/File Search', Google with 'NotebookLM') and cloud providers (AWS Kendra/Q, Azure AI Search) are rapidly commoditizing this entire stack. The project faces immediate displacement by more mature local RAG projects like PrivateGPT, LocalGPT, or AnythingLLM, which offer more robust GUIs and multi-document handling.