About this episode
In this episode, I’m talking with Vincent Warmerdam about treating LLMs as just another API in your Python app, with clear boundaries, small focused endpoints, and good monitoring. We’ll dig into patterns for wrapping these calls, caching and inspecting responses, and deciding where an LLM API actually earns its keep in your architecture. Episode sponsors Seer: AI Debugging, Code TALKPYTHON NordStellar Talk Python Courses Links from the show Vincent on X : @fishnets88 Vincent on Mastodon : @koaning LLM Building Blocks for Python Co-urse : training.talkpython.fm Top Talk Python Episodes of 2024 : talkpython.fm LLM Usage - Datasette : llm.datasette.io DiskCache - Disk Backed Cache (Documentation) : grantjenks.com smartfunc - Turn docstrings into LLM-functions : github.com Ollama : ollama.com LM Studio - Local AI : lmstudio.ai marimo - A Next-Generation Python Notebook : marimo.io Pydantic : pydantic.dev Instructor - Complex Schemas & Validation (Python) : python.useinstructor.com Diving into PydanticAI with marimo : youtube.com Cline - AI Coding Agent : cline.bot OpenRouter - The Unified Interface For LLMs : openrouter.ai Leafcloud : leaf.cloud OpenAI looks for its "Google Chrome" moment with new Atlas web browser : arstechnica.com Watch this episode on YouTube : youtube.com Episode #528 deep-dive : talkpython.fm/528 Episode transcripts : talkpython.fm Theme Song: Developer Rap 🥁 Served in a Flask 🎸 : talkpython.fm/flasksong ---== Don't be a stranger ==--- YouTube : youtube.com/@talkpython Bluesky : @talkpython.fm Mastodon : @talkpython@fosstodon.org X.com : @talkpython Michael on Bluesky : @mkennedy.codes Michael on Mastodon : @mkennedy@fosstodon.org Michael on X.com : @mkennedy