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Python AI Ecosystem Registry

Global Database of Python-Native AI Frameworks, Standards & Infrastructure

The PY.AI Registry is a curated global index of Python-native AI frameworks, agentic systems, edge inference stacks, governance standards, and core libraries that define how modern intelligent systems are built, deployed, and regulated.

20+

Verified Frameworks

4

Strategic Pillars
Agents
Agno

Framework for designing autonomous systems that think, plan, and act independently.

Agents
CrewAI

Orchestrates teams of AI agents for high-complexity multi-stage process automation.

Agents
LangGraph

Graph-based state management for building cyclic, reasoning-heavy AI workflows.

Agents
SmolAgents

Hugging Face's lightweight multi-agent solution focused on efficiency and code-use.

Agents
Letta

Enables agents with long-term memory and persistent state across sessions.

Agents
MCP (Model Context Protocol)

The standard for connecting agents to external tools and secure data sources.

Edge Intelligence
Whisper

State-of-the-art automatic speech recognition for local, secure Python inference.

Edge Intelligence
YOLO (v11+)

Real-time object detection optimized for edge hardware like Jetson and NPU.

Edge Intelligence
TensorRT

NVIDIA's SDK for high-performance deep learning inference on local GPUs.

Edge Intelligence
Mediapipe

Google's cross-platform framework for live perception (hand, face, pose tracking).

Edge Intelligence
Quantization

Reducing model precision (FP16/INT8) to run LLMs on low-resource mobile/IoT devices.

Governance
Weights & Biases

Enterprise-grade tracking and visualization for machine learning experiment reproducibility.

Governance
PromptLayer

A middleware for logging and managing prompts to ensure safety and performance audit trails.

Governance
NIST AI RMF

The primary risk management framework for building trustworthy AI systems.

Governance
Differential Privacy

Mathematical techniques to allow AI training without exposing individual user data.

Core
PyTorch

The leading Python library for deep learning research and production scaling.

Core
RAG (Retrieval-Augmented)

The architecture that grounds LLMs in real-time, private data to prevent hallucinations.

Core
pandas

The industry standard for data manipulation and analysis in Python ecosystems.

Core
PydanticAI

Strict data validation for agent outputs, ensuring reliable tool-calling and response formats.

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