Ouroboros Flow
Regression Output from Agents

Project Description: Ouroboros - Collaborative LLM-Agent Team

Over the past year, the language model (LLM) revolution has spurred innovations in diverse domains. From initial text prompt completions to fine-tuning instructions, the power of in-context learning has led to creative prompt engineering, retrieval augmented generation, and the emergence of 'agents' equipped with memory and tools.

Multi-Agent Collaboration

A recent trend involves multiple agents collaborating toward shared goals, surpassing current model capabilities. Projects like ChatDev, MetaGPT and AutoGen exemplify this shift, automating not only specific tasks but entire processes, from ideation to marketing. This collaborative setting enables machine intelligences to not only utilize tools but also critique and refine outputs, mirroring human collaboration.

Introducing Ouroboros

As machine learning engineers, this inspired us to explore the question: can machine learning automate machine learning? Enter Ouroboros, a team of LLM-agents working collaboratively to address data science and data engineering problems. The team's dynamic composition includes Managers, Data Engineers, Developers, and Analysts, summoned as needed.

Seamless Interaction

To engage Ouroboros, simply describe your task and, if applicable, upload your datasets. Witness the team's transparent collaboration as they extract key insights and provide solutions—a level of transparency rarely achievable in human-only settings.

Enjoy the journey as Ouroboros transforms your requirements into actionable results effortlessly.