by hoangsonww · Agent Tool · ★ 44
RAG AI Portfolio Support Platform: Product And Operations Handbook A comprehensive agentic RAG platform for portfolio intelligence, evidence-backed chat, and API-enriched responses. This repository ships a complete application stack: () for chat, strategy controls, sessions, and traceability. () for retrieval, orchestration, and response generation, with reranking support. () for structured portfolio data APIs used by tool chaining. Deployment and operations assets for Docker, Kubernetes, progressive delivery, and Terraform.
| Stars | 44 |
| Forks | 14 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 62.1281813184249/100 |
| Open Issues | 7 |
| Last Updated | 2026-06-17 |
| Created | 2025-02-05 |
| Est. Tokens | ~22k |
These tools work well together with RAG-LangChain-AI-System for enhanced workflows:
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RAG-LangChain-AI-System is 🧠 A production-grade, agentic RAG platform for portfolio intelligence, combining LangChain, Chroma/FAISS, Hugging Face embeddings, and Ollama with dynamic entity extraction, backend API tool-chaining. It is categorized as a Agent Tool with 44 GitHub stars.
RAG-LangChain-AI-System is primarily written in Jupyter Notebook. It covers topics such as bert, expressjs, faiss.
You can find installation instructions and usage details in the RAG-LangChain-AI-System GitHub repository at github.com/hoangsonww/RAG-LangChain-AI-System. The project has 44 stars and 14 forks, indicating an active community.
RAG-LangChain-AI-System is released under the MIT license, making it free to use and modify according to the license terms.