sefia
Stateless Engraved Function Inference Abstraction
sefia turns typed Python functions into durable, replayable LLM-backed calls.
An @infer function is an abstract method whose implementer is an LLM: the
signature is the input contract, the return type is the validated output
contract, the docstring is the instruction, and the body is ....
import glyff
from pydantic import BaseModel
from sefia import Domain
class Summary(BaseModel):
key_points: list[str]
uncertainty: str
infer = Domain(glyff.Domain("com.example.summaries", version="1")).infer
@infer
async def summarize(article: str) -> Summary:
"""Summarize the article for a technical audience; note key uncertainty."""
...
Because model and tool steps replay on re-invocation, a call can pause, resume after a restart, and drive human-in-the-loop flows over ordinary request/response handlers — with no workflow engine or graph DSL.
Install
pip install sefia
sefia is the core framework: decorators, session, profiles, and the tool
system. It is model-provider-agnostic; to talk to an actual LLM provider, add
an adapter such as
sefia-litellm, or install the
batteries-included stack sefios.
Documentation
See the repository for the full README, tutorial, and architecture docs.
Status
Early development. APIs may change before v1.0.
License
MIT
1 maintainer
Release files for sefia 0.5.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| sefia-0.5.0.tar.gz | 92.4 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sefia-0.5.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 170.8 kB
Release files / sefia-0.5.0.tar.gz
| Download URL | sefia-0.5.0.tar.gz |
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| Tags | Source |
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| Tags | Python 3 |
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