Calling tools w/ Python improves LLM perf. vs MCP (77.1% on BrowseComp)
If agent's tools are exposed as functions/objects in a Python REPL (as opposed to JSON schemas) they perform better, I linked the explainer article we wrote, but if you want to jump straight in check out the docs!
반응 (1)
비슷한 프로덕트
설명이 비슷한 순
Forge
github.comGuardrails take an 8B model from 53% to 99% on agentic tasks
MonkeyPatch
github.comCheap, fast and predictable LLM functions in Python
An implementation of the Codemode workflow detailed by Cloudflare.
PicoFlow
news.ycombinator.coma tiny DSL-style Python library for LLM agent workflows
Llmswap
pypi.orgPython package to reduce LLM API costs by 50-90% with caching