AI-powered mentor for academic research with CLI and Textual TUI front-ends
Project description
Academic Research Mentor
Objective
Accelerate AI research with AI. We are building an AI Research Mentor that guides researchers through the entire research lifecycle so they can move from idea to published work faster.
Key Capabilities
- Research-aware CLI powered by LangChain agents and dynamic tool routing.
- O3-backed literature search with graceful fallbacks and citation synthesis.
- Mentorship guidelines and experiment planning helpers to keep projects on track.
- File and PDF ingestion so the mentor can ground responses in user-provided material.
- Conversation logging with the ability to resume saved sessions from the CLI.
Setup
# Install dependencies
uv sync
# Run tests (optional)
uv run pytest -q
Environment
cp .example.env .env
Edit .env and add your OPENROUTER_API_KEY (recommended). Other provider keys are optional fallbacks.
Usage
# Verify configuration
uv run academic-research-mentor --check-env
# Start the mentor CLI
uv run academic-research-mentor
# Alternate entrypoint
uv run python main.py
Troubleshooting
- Ensure Python 3.11+ is installed.
- Re-run
uv syncafter dependency changes. - Set additional API keys (OpenAI, Anthropic, etc.) if you prefer alternative models.
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