LLM-powered risk statement generator and evidence validator for ControlBridge
Project description
controlbridge-ai
LLM-powered features for ControlBridge: risk statement generation and (in Phase 3) evidence validation.
Uses LiteLLM for provider-agnostic LLM calls and Instructor for structured output extraction into Pydantic models.
Provides
- Risk Statement Generator — Convert control gaps into NIST SP 800-30-compliant risk statements
- Evidence Validator (Phase 3) — Assess evidence sufficiency using LLM analysis
- LLM Client — Provider-agnostic wrapper around LiteLLM with retry, rate limiting, and structured output
Supported providers
Any provider supported by LiteLLM:
- Anthropic Claude (default:
claude-sonnet-4-6) - OpenAI GPT
- Google Gemini
- AWS Bedrock
- Azure OpenAI
- Local models via Ollama, vLLM, etc.
Install
pip install controlbridge-ai
License: Apache 2.0
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