AI-Researcher
LLM Agent Research Automation System
Python / CLI / RAG / Tool Use / Validation Gates / Markdown Vault / LaTeX-PDF Pipeline / Docker
- Designed and implemented a local/server research operator that unifies literature retrieval, research planning, bounded experiments, validation gates, Markdown memory, and publication artifact generation into one reproducible workflow.
- Built an evidence-first execution loop with review gates, runtime checks, failure records, and rollback-aware quality control, making AI-generated research outputs traceable and auditable.
- Implemented CLI workflows for setup, service orchestration, and autonomous research loops, enabling local workstation use and server-side continuous execution.
- Maintained a 347-commit Apache-2.0 repository with 110 Python source files, 105 test files, CI workflow, Docker/deploy assets, and documentation across 20 source areas.