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.

decnet/orchestrator/emailgen/llm/impl/fake.py

@@ -0,0 +1,50 @@
+"""In-process fake backend for tests.
+
+Returns a canned ``Subject:\\n\\nbody`` string so the driver path can be
+exercised without an Ollama install.  Configurable via ``DECNET_EMAILGEN_FAKE_OUTPUT``
+(env) or the ``output`` constructor arg — the env-var path lets
+integration tests run the worker end-to-end with deterministic output.
+"""
+from __future__ import annotations
+
+import os
+import time
+from typing import Optional
+
+from decnet.orchestrator.emailgen.llm.base import LLMBackend, LLMResult
+
+
+_DEFAULT_OUTPUT = (
+    "Subject: Quick update\n\n"
+    "Hi,\n\nFollowing up on the topic.\n\nBest regards,\nFake Persona\n"
+)
+
+
+class FakeBackend(LLMBackend):
+    def __init__(
+        self,
+        *,
+        model: str = "fake-model",
+        timeout: float = 1.0,
+        output: Optional[str] = None,
+        success: bool = True,
+    ) -> None:
+        self.model = model
+        self.timeout = timeout
+        self._output = (
+            output
+            if output is not None
+            else os.environ.get("DECNET_EMAILGEN_FAKE_OUTPUT", _DEFAULT_OUTPUT)
+        )
+        self._success = success
+
+    async def generate(self, prompt: str) -> LLMResult:    # noqa: ARG002
+        t0 = time.monotonic()
+        latency_ms = int((time.monotonic() - t0) * 1000)
+        return LLMResult(
+            success=self._success,
+            text=self._output if self._success else "",
+            model=self.model,
+            latency_ms=latency_ms,
+            extra={"rc": 0 if self._success else 1},
+        )