Architecture map
How the repo is organized
Click systems in the graph to inspect responsibilities, important files, and nearby dependencies.
Architecture map
Use this map to orient around systems, dependencies, and files worth reading first.
Click a system in the map
Explore arklexai/arksim by selecting services, gateways, clients, and data stores. Each node shows the files, responsibilities, and neighboring systems an agent should keep in scope.
Pan, zoom, and use the minimap to keep large repos navigable.
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Key systems
What an agent should understand first
Command-line entry point for simulate, evaluate, init, ui, and setup-claude commands
Interactive browser-based control plane for job management and result viewing
YAML parsing, agent/simulation config validation, CLI override merging
FastAPI routes for simulation, evaluation, filesystem, and results endpoints
Multi-turn conversation orchestration with synthetic user LLM and agent execution
Creates agent instances from config: custom Python, Chat Completions HTTP, or A2A protocol
Scores conversations with quantitative metrics, detects errors, matches trajectories
Abstraction for OpenAI, Anthropic, Google LLM APIs (synthetic user and evaluator)
Evidence coverage
What this context is grounded in
Coverage
- Citations
- 7
- Findings
- 5
- Files discovered
- 476
- Architecture systems
- 12
- Architecture relationships
- 13
- Agent graph
- Agent graph entities
- 1,097
- Agent graph relationships
- 1,839