Hi everyone! I’m Neeraja P, a third year B.Tech Computer Science student from Amrita Vishwa Vidyapeetham, India.
I have been working with Python, Flask, and machine learning, and I’m genuinely interested in contributing to Project #8 this GSoC.
Two of my projects feel relevant here: MindTune, a mood classification system using simulated EEG signals that maps Alpha/Beta wave patterns to playlist recommendations, and DreamBalance, a dream journaling platform that uses NLP concepts for emotion tagging and weekly mental health trend visualisation. Both are on my GitHub: JANE7J (JANEJ7) · GitHub
I also had the opportunity to work as an AI intern at IBM SkillsBuild on applied AI projects around mental health analysis, and recently as a project coordinator for an AI/ML intern team at UpToSkills, both experiences gave me a better understanding of how AI systems are built collaboratively.
I’ve cloned the LLAMOSC repository, installed all dependencies, pulled llama3 via Ollama, and spent time going through the codebase. I noticed that collaborative_team.py currently forms teams by ranking contributors on bid score and experience, but the agents don’t actually discuss or deliberate together on an issue, and the README lists this as future work under Issue #64.
I’d like to work on this, my initial thinking is a round-robin discussion loop where agents each propose an approach, respond to each other, and the Lead agent uses the LLM to synthesise a final decision. I’m still exploring the codebase and would love feedback on whether this fits the architectural vision.
A question for the mentors: should this collaboration layer live inside the ConversationSpace being developed by Kalpana, or operate as a separate deliberation layer within collaborative_team.py itself?
Thank you for putting together such a well-documented project, looking forward to learning from and contributing to OREL!