trustgraph/trustgraph-flow/trustgraph/cores/service.py
Cyber MacGeddon d6dff0e411 feat: separate flow service from config service with explicit queue
lifecycle management

The flow service is now an independent service that owns the lifecycle
of flow and blueprint queues. System services own their own queues.
Consumers never create queues.

Flow service separation:
- New service at trustgraph-flow/trustgraph/flow/service/
- Uses async ConfigClient (RequestResponse pattern) to talk to config
  service
- Config service stripped of all flow handling

Queue lifecycle management:
- PubSubBackend protocol gains create_queue, delete_queue,
  queue_exists, ensure_queue — all async
- RabbitMQ: implements via pika with asyncio.to_thread internally
- Pulsar: stubs for future admin REST API implementation
- Consumer _connect() no longer creates queues (passive=True for named
  queues)
- System services call ensure_queue on startup
- Flow service creates queues on flow start, deletes on flow stop
- Flow service ensures queues for pre-existing flows on startup

Two-phase flow stop:
- Phase 1: set flow status to "stopping", delete processor config
  entries
- Phase 2: retry queue deletion, then delete flow record

Config restructure:
- active-flow config replaced with processor:{name} types
- Each processor has its own config type, each flow variant is a key
- Flow start/stop use batch put/delete — single config push per
  operation
- FlowProcessor subscribes to its own type only

Blueprint format:
- Processor entries split into topics and parameters dicts
- Flow interfaces use {"flow": "topic"} instead of bare strings
- Specs (ConsumerSpec, ProducerSpec, etc.) read from
  definition["topics"]
2026-04-16 17:06:20 +01:00

237 lines
6.9 KiB
Python
Executable file

"""
Knowledge core service, manages cores and exports them
"""
from functools import partial
import asyncio
import base64
import json
import logging
from .. base import AsyncProcessor, Consumer, Producer, Publisher, Subscriber
from .. base import ConsumerMetrics, ProducerMetrics
from .. base.cassandra_config import add_cassandra_args, resolve_cassandra_config
from .. schema import KnowledgeRequest, KnowledgeResponse, Error
from .. schema import knowledge_request_queue, knowledge_response_queue
from .. schema import Document, Metadata
from .. schema import TextDocument, Metadata
from .. exceptions import RequestError
from . knowledge import KnowledgeManager
# Module logger
logger = logging.getLogger(__name__)
default_ident = "knowledge"
default_knowledge_request_queue = knowledge_request_queue
default_knowledge_response_queue = knowledge_response_queue
default_cassandra_host = "cassandra"
class Processor(AsyncProcessor):
def __init__(self, **params):
id = params.get("id")
knowledge_request_queue = params.get(
"knowledge_request_queue", default_knowledge_request_queue
)
knowledge_response_queue = params.get(
"knowledge_response_queue", default_knowledge_response_queue
)
cassandra_host = params.get("cassandra_host")
cassandra_username = params.get("cassandra_username")
cassandra_password = params.get("cassandra_password")
# Resolve configuration with environment variable fallback
hosts, username, password, keyspace = resolve_cassandra_config(
host=cassandra_host,
username=cassandra_username,
password=cassandra_password,
default_keyspace="knowledge"
)
# Store resolved configuration
self.cassandra_host = hosts
self.cassandra_username = username
self.cassandra_password = password
super(Processor, self).__init__(
**params | {
"knowledge_request_queue": knowledge_request_queue,
"knowledge_response_queue": knowledge_response_queue,
"cassandra_host": self.cassandra_host,
"cassandra_username": self.cassandra_username,
"cassandra_password": self.cassandra_password,
}
)
knowledge_request_metrics = ConsumerMetrics(
processor = self.id, flow = None, name = "knowledge-request"
)
knowledge_response_metrics = ProducerMetrics(
processor = self.id, flow = None, name = "knowledge-response"
)
self.knowledge_request_topic = knowledge_request_queue
self.knowledge_request_subscriber = id
self.knowledge_request_consumer = Consumer(
taskgroup = self.taskgroup,
backend = self.pubsub,
flow = None,
topic = knowledge_request_queue,
subscriber = id,
schema = KnowledgeRequest,
handler = self.on_knowledge_request,
metrics = knowledge_request_metrics,
)
self.knowledge_response_producer = Producer(
backend = self.pubsub,
topic = knowledge_response_queue,
schema = KnowledgeResponse,
metrics = knowledge_response_metrics,
)
self.knowledge = KnowledgeManager(
cassandra_host = self.cassandra_host,
cassandra_username = self.cassandra_username,
cassandra_password = self.cassandra_password,
keyspace = keyspace,
flow_config = self,
)
self.register_config_handler(self.on_knowledge_config, types=["flow"])
self.flows = {}
logger.info("Knowledge service initialized")
async def start(self):
await self.pubsub.ensure_queue(
self.knowledge_request_topic, self.knowledge_request_subscriber
)
await super(Processor, self).start()
await self.knowledge_request_consumer.start()
await self.knowledge_response_producer.start()
async def on_knowledge_config(self, config, version):
logger.info(f"Configuration version: {version}")
if "flow" in config:
self.flows = {
k: json.loads(v)
for k, v in config["flow"].items()
}
else:
self.flows = {}
logger.debug(f"Flows: {self.flows}")
async def process_request(self, v, id):
if v.operation is None:
raise RequestError("Null operation")
logger.debug(f"Knowledge request: {v.operation}")
impls = {
"list-kg-cores": self.knowledge.list_kg_cores,
"get-kg-core": self.knowledge.get_kg_core,
"delete-kg-core": self.knowledge.delete_kg_core,
"put-kg-core": self.knowledge.put_kg_core,
"load-kg-core": self.knowledge.load_kg_core,
"unload-kg-core": self.knowledge.unload_kg_core,
}
if v.operation not in impls:
raise RequestError(f"Invalid operation: {v.operation}")
async def respond(x):
await self.knowledge_response_producer.send(
x, { "id": id }
)
return await impls[v.operation](v, respond)
async def on_knowledge_request(self, msg, consumer, flow):
v = msg.value()
# Sender-produced ID
id = msg.properties()["id"]
logger.info(f"Handling knowledge input {id}...")
try:
# We don't send a response back here, the processing
# implementation sends whatever it needs to send.
await self.process_request(v, id)
return
except RequestError as e:
resp = KnowledgeResponse(
error = Error(
type = "request-error",
message = str(e),
)
)
await self.knowledge_response_producer.send(
resp, properties={"id": id}
)
return
except Exception as e:
resp = KnowledgeResponse(
error = Error(
type = "unexpected-error",
message = str(e),
)
)
await self.knowledge_response_producer.send(
resp, properties={"id": id}
)
return
logger.debug("Knowledge input processing complete")
@staticmethod
def add_args(parser):
AsyncProcessor.add_args(parser)
parser.add_argument(
'--knowledge-request-queue',
default=default_knowledge_request_queue,
help=f'Config request queue (default: {default_knowledge_request_queue})'
)
parser.add_argument(
'--knowledge-response-queue',
default=default_knowledge_response_queue,
help=f'Config response queue {default_knowledge_response_queue}',
)
add_cassandra_args(parser)
def run():
Processor.launch(default_ident, __doc__)