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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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