lmcc — the calling convention for calling a model
When a program calls a function in another language, a calling convention says where each argument goes, how the result comes back, and how each type crosses. A model is another language; lmcc is its calling convention. It lays out each call as an lm15 request and reads each reply back into typed values. It never touches the network.
import lmcc
@lmcc.fn
def answer(question: str) -> str:
"""Answer the question in one sentence."""
xml = lmcc.adapter(messages=[
lmcc.system("{instruction}\n{% for f in outputs %}<{f.name}>\n{f.value}\n</{f.name}>\n{% endfor %}"),
lmcc.user("{question}"),
])
plan = answer.bind(xml)
request = plan.render(question="Why is the sky blue?").request("gpt-4.1-mini") # an lm15 request
plan.read("<Answer>\nRayleigh scattering.\n</Answer>").values # {'answer': ...}, misspelling repaired and reported
pip install "lmcc[lm15]" adds the typed bridge to lm15 (lmcc_lm15).
The tutorial, how-to guides, the normative specification and the
conformance corpus are in the repository:
https://github.com/MaximeRivest/lmcc
Release files for lmcc 0.8.1
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Source distribution (sdist)
| File | Size | Uploaded | |
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| lmcc-0.8.1.tar.gz | 136.9 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| lmcc-0.8.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 242.6 kB
Release files / lmcc-0.8.1.tar.gz
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