I’m building a platform where several AI agents run side-by-side, each with its own speciality and toolset yet still able to collaborate. Every agent must • operate both autonomously and under manual override • access only its assigned tools—data-visualisation modules, chat interfaces and external API hooks—through a clear permission layer • learn from a dedicated, private data set so its expertise remains distinct My goal is to end up with a single codebase (Python preferred, but I’m open) that spins up new agents easily, handles training on custom data, and provides a lightweight dashboard for monitoring, hand-off control and conversation history. Deliverables 1. Modular architecture with agent registration, authentication and orchestration 2. Training pipeline that ingests my datasets and fine-tunes each agent 3. Working demo: at least two agents showing different capabilities, producing visual insights, answering via chat and calling an external API 4. Setup scripts plus concise documentation so I can add more agents or retrain existing ones without touching core code Code quality, transparency and clear instructions are the success criteria.