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Evaluations Python Packages

Python packages with the GitHub topic evaluations. Sorted by monthly downloads, with stars and forks.
nseney1
soma-governance

Deterministic governance and guardrails for autonomous AI coding agents. Features AST verification, evidence-based rule execution, and native MCP support for Antigravity and Claude Code.

20K 2 1
RailtownAI
railtracks

An agentic framework that helps developers build resilient agentic systems

4K 233 62
burakkaygusuz
clastogen

Do your LLM evals catch a broken prompt? Mutation testing for system prompts, in pytest.

4K 0 0
log10-io
log10-io

Python client library for improving your LLM app accuracy

1K 97 12
gabe-mousa
apolien

AI Safety Evaluation Library

1K 5 1
RailtownAI
railtracks-cli

An agentic framework that helps developers build resilient agentic systems

791 233 62
evaluation-context-protocol
ecp-runtime

ECP is a standardized interface for orchestrating, auditing, and enforcing authority limits in AI Agent evaluations. It moves evaluation from "brittle Python scripts" to a deterministic infrastructure protocol

606 9 5
evaluation-context-protocol
ecp-sdk

ECP is a standardized interface for orchestrating, auditing, and enforcing authority limits in AI Agent evaluations. It moves evaluation from "brittle Python scripts" to a deterministic infrastructure protocol

567 9 5
BhagyasriUddandam
evallint

Audits LLM eval datasets for the flaws that make evaluations silently lie — discrimination failure, near-duplicates, class imbalance.

315 1 0
mandoline-ai
mandoline

Official Python client for the Mandoline API

229 2 0
kaivid-labs
evret

Evals framework for Information Retrieval Systems

200 19 4
yisaienkov
evaluations

This library implements various metrics (including Kaggle Competition, Medicine) for evaluating ML, DL, AI models, and algorithms. 📐📊📈📉📏

198 14 1
aniketgopal
aniket-agentlens-sdk

Open-source observability, security, and evaluation platform for AI agents

91 0 0
Roshan3580
helios-observatory-sdk

AI systems observability platform for tracing, evaluating, and debugging LLM applications, agents, and RAG pipelines.

85 1 0
    • Original data from PyPI, GitHub, and OSV; downloads served through ClickHouse
    • Sources & methodology