🧠 Welcome to the LLMaven Wiki

LLMaven is an open, extensible multi-agent platform designed to integrate large language models (LLMs) into research workflows—going beyond chatbots to deliver intelligent, reproducible, and collaborative scientific tooling.

Built by the Scientific Software Engineering Center (SSEC), LLMaven supports containerized tools, standardized agent communication protocols, and domain-specific customization for Research Software Engineers (RSEs), scientists, and developers.

🚀 What Is LLMaven?

LLMaven empowers research teams to:

• Embed agentic LLMs into scientific workflows.
• Use structured communication protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent Protocol).
• Fine tuned models for scientific domains and research software engineering tasks.
• Integrate retrieval-augmented generation (RAG) and evaluation strategies.
• Ensure reproducibility with containerized and versioned workflows.

🗺️ Wiki Overview

📄 Getting Started Set up your development/deployment environment and run the LLMaven platform.

🧩 Architecture Overview Understand the components of LLMaven, including MCP, A2A, and Agent Interfaces.

🛠️ Agents and Workflows Explore built-in agents, workflows, and how to create your own.

📦 Model Selection & Fine-Tuning Evaluate open-source LLMs, embed domain knowledge, and track fine-tuning goals.

📚 Data Sources & Embeddings Understand the role of domain-specific data and compare embedding strategies.

🧪 Evaluation Framework Learn how we benchmark agent performance with human and automated metrics.

🧰 Developer Guide Contribution guidelines, CI/CD pipelines, and code structure.

📈 Roadmap Upcoming milestones and long-term vision for LLMaven.

👥 Contributors & Community

• Project led by the Scientific Software Engineering Center (SSEC)
• Contact: [Insert contact email or GitHub handle]
• Join the discussion in Discussions or open an Issue

🌐 Related Projects

• SSEC Website