evidentia-ai
LLM-powered features for Evidentia: 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 evidentia-ai
License: Apache 2.0
Metadata
Release files for evidentia-ai 0.12.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| evidentia_ai-0.12.1.tar.gz | 24.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| evidentia_ai-0.12.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 51.8 kB
Release files / evidentia_ai-0.12.1.tar.gz
| Download URL | evidentia_ai-0.12.1.tar.gz |
|---|---|
| Size | 24.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / evidentia_ai-0.12.1-py3-none-any.whl
| Download URL | evidentia_ai-0.12.1-py3-none-any.whl |
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| Size | 27.2 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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