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fix(notifications): inject llm_backend into build_pipeline

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build_pipeline previously constructed its own LLMBackend from
config.llm, which:
  - duplicated main.py's already-running backend instance
  - failed to inherit env-loaded LLM_API_KEY when called from
    short-lived scripts (eyeball checks, tests), forcing fallback
  - prevented pipeline components from sharing the live backend

build_pipeline and build_pipeline_components now require an
llm_backend parameter. main.py passes the same instance it
constructed for its primary responder. Tests pass mocks. The
digest accumulator now uses the live, authenticated backend.

Added test_build_pipeline_uses_provided_backend to lock in the
injection contract.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
K7ZVX 2026-05-15 03:08:31 +00:00
commit a4cb29002d
3 changed files with 47 additions and 40 deletions
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50
meshai/notifications/pipeline/__init__.py
View file

@ -12,7 +12,7 @@ Phase 2.4:
Usage:
from meshai.notifications.pipeline import build_pipeline, start_pipeline, stop_pipeline
bus = build_pipeline(config)
bus = build_pipeline(config, llm_backend) # llm_backend from main.py
bus.emit(event)
# Async lifecycle
@ -35,40 +35,20 @@ from meshai.notifications.pipeline.digest import DigestAccumulator, Digest
from meshai.notifications.pipeline.scheduler import DigestScheduler
def _create_llm_backend(config):
"""Create an LLM backend from config, or return None if unavailable."""
try:
from meshai.backends import OpenAIBackend, AnthropicBackend, GoogleBackend
api_key = config.resolve_api_key()
if not api_key:
return None
backend_name = config.llm.backend.lower()
# Use minimal memory settings for digest summaries
if backend_name == "openai":
return OpenAIBackend(config.llm, api_key, 0, 0)
elif backend_name == "anthropic":
return AnthropicBackend(config.llm, api_key, 0, 0)
elif backend_name == "google":
return GoogleBackend(config.llm, api_key, 0, 0)
else:
return OpenAIBackend(config.llm, api_key, 0, 0)
except Exception:
return None
def build_pipeline(config) -> EventBus:
def build_pipeline(config, llm_backend) -> EventBus:
"""Build the pipeline and return the EventBus.
Args:
config: Full Config object.
llm_backend: An already-constructed LLMBackend instance
(from main.py or a test). Pipeline components share
this single instance. May be None for fallback behavior.
Components are stashed on bus._pipeline_components for lifecycle use.
"""
bus = EventBus()
dispatcher = Dispatcher(config, create_channel)
# Build LLM backend for digest summarization
llm_backend = _create_llm_backend(config)
# Build include_toggles from config
digest_cfg = getattr(config.notifications, "digest", None)
include_toggles = None
@ -116,17 +96,21 @@ def build_pipeline(config) -> EventBus:
return bus
def build_pipeline_components(config) -> tuple:
def build_pipeline_components(config, llm_backend) -> tuple:
"""Like build_pipeline, but returns all components for tests.
Returns (bus, inhibitor, grouper, toggle_filter, dispatcher, accumulator).
Args:
config: Full Config object.
llm_backend: An already-constructed LLMBackend instance
(from main.py or a test). Pipeline components share
this single instance. May be None for fallback behavior.
Returns:
(bus, inhibitor, grouper, toggle_filter, dispatcher, accumulator).
"""
bus = EventBus()
dispatcher = Dispatcher(config, create_channel)
# Build LLM backend for digest summarization
llm_backend = _create_llm_backend(config)
# Build include_toggles from config
digest_cfg = getattr(config.notifications, "digest", None)
include_toggles = None