pydantic/pydantic-ai
How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
Loading star history...
Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 33 days ago, with 475 contributors on GitHub.
Peaked at #55 in the weekly ranking the week of Apr 26, its best in the past year.
Use Cases & Benefits
- Provides a Python agent framework to build production-grade Generative AI applications with typed end-to-end validation.
- Delivers type-safe, model-agnostic AI development with seamless Pydantic validation and integration for consistent, structured outputs.
- Use for creating AI-powered support agents that validate and structure responses with dependency injection for dynamic data access.
- Use for building real-time AI applications that stream validated LLM outputs with immediate feedback and error handling.
- Use for developing complex AI workflows using Python-native control flow and graph-based agent composition to avoid spaghetti code.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Agent Framework / shim to use Pydantic with LLMs
Pydantic AI is a Python agent framework designed to make it less painful to build production grade applications with Generative AI.
FastAPI revolutionized web development by offering an innovative and ergonomic design, built on the foundation of Pydantic Validation.
Similarly, virtually every agent framework and LLM library in Python uses Pydantic Validation, yet when we began to use LLMs in Pydantic Logfire, we couldn't find anything that gave us the same feeling.
We built Pydantic AI with one simple aim: to bring that FastAPI feeling to GenAI app development.
(This example is complete, it can be run "as is")
Not very interesting yet, but we can easily add "tools", dynamic system prompts, and structured responses to build more powerful agents.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
3.1K+592
Open issues
1.9K+1.1K
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| D4Vinci/Scrapling | 101.1K | +6.3K | 75 | 6 days ago |
| thedotmack/claude-mem | 115.8K | +4.7K | 75 | today |
| heygen-com/hyperframes | 82.3K | +4.0K | 75 | today |
| harry0703/MoneyPrinterTurbo | 142.0K | +3.8K | 75 | 3 days ago |
| github/spec-kit | 149.2K | +2.6K | 75 | today |
| pydantic/pydantic-ai | 21.1K | — | 58 | 33 days ago |
| Category median | 115.8K | +4.0K | 75 | — |
Also by pydantic
Other repositories from this maintainer that GStars tracks
Discover Repositories
Search across tracked repositories by name or description