Files
DECNET/decnet/orchestrator/emailgen/llm/base.py
anti 6d520eaa6f refactor(emailgen): pluggable LLM backend (base/factory/impl)
Lift the Ollama subprocess shell-out out of EmailDriver and into a
proper provider subpackage shape:

  decnet/orchestrator/emailgen/llm/
    base.py        — LLMBackend Protocol + LLMResult + LLMTimeout
    factory.py     — get_llm() reads DECNET_EMAILGEN_LLM
    impl/ollama.py — current 'ollama run' subprocess path
    impl/fake.py   — canned-output backend used by tests

Driver now takes an LLMBackend on construction (or inherits the
factory default).  Tests inject FakeBackend instead of monkeypatching
the subprocess layer, which is cleaner and ~10x faster.  Swapping
Ollama for the Anthropic API / vLLM / llama.cpp is now a third branch
in factory.py; no driver rewrite needed.

Mirrors the convention used by decnet.web.db.factory + decnet.bus.factory
per the provider-subpackages-from-day-one rule in memory.
2026-04-26 22:43:36 -04:00

48 lines
1.4 KiB
Python

"""Backend protocol shared by every LLM transport.
Deliberately narrow: emailgen needs one async ``generate`` call that
takes a prompt string and returns the model's output text plus enough
metadata for the worker to populate the orchestrator-email payload
(model name, latency, success bit). Streaming, embeddings, multi-turn
chat — all out of scope here; emailgen only ever does one-shot
single-prompt generations.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any, Protocol
class LLMTimeout(Exception):
"""Raised when a generation exceeds the backend's wall-clock cap.
Backends MUST raise this rather than returning silently empty
output; the driver discriminates timeout from "model produced
nothing useful" so payloads carry the right ``stage`` value.
"""
@dataclass
class LLMResult:
"""Outcome of one ``generate`` call.
``success`` is ``False`` when the backend ran cleanly but produced
no usable output (e.g. an empty stdout). Hard failures (subprocess
crash, network error) raise; soft failures land here so the driver
can persist + log them as one event.
"""
success: bool
text: str
model: str
latency_ms: int
extra: dict[str, Any] = field(default_factory=dict)
class LLMBackend(Protocol):
"""Minimal contract for an emailgen LLM provider."""
model: str
timeout: float
async def generate(self, prompt: str) -> LLMResult: ...