trustgraph/trustgraph-base/trustgraph/messaging/translators/embeddings.py
cybermaggedon 4fb0b4d8e8
Pub/sub abstraction: decouple from Pulsar (#751)
Remove Pulsar-specific concepts from application code so that
the pub/sub backend is swappable via configuration.

Rename translators:
- to_pulsar/from_pulsar → decode/encode across all translator
  classes, dispatch handlers, and tests (55+ files)
- from_response_with_completion → encode_with_completion
- Remove pulsar.schema.Record from translator base class

Queue naming (CLASS:TOPICSPACE:TOPIC):
- Replace topic() helper with queue() using new format:
  flow:tg:name, request:tg:name, response:tg:name, state:tg:name
- Queue class implies persistence/TTL (no QoS in names)
- Update Pulsar backend map_topic() to parse new format
- Librarian queues use flow class (persistent, for chunking)
- Config push uses state class (persistent, last-value)
- Remove 15 dead topic imports from schema files
- Update init_trustgraph.py namespace: config → state

Confine Pulsar to pulsar_backend.py:
- Delete legacy PulsarClient class from pubsub.py
- Move add_args to add_pubsub_args() with standalone flag
  for CLI tools (defaults to localhost)
- PulsarBackendConsumer.receive() catches _pulsar.Timeout,
  raises standard TimeoutError
- Remove Pulsar imports from: async_processor, flow_processor,
  log_level, all 11 client files, 4 storage writers, gateway
  service, gateway config receiver
- Remove log_level/LoggerLevel from client API
- Rewrite tg-monitor-prompts to use backend abstraction
- Update tg-dump-queues to use add_pubsub_args

Also: pubsub-abstraction.md tech spec covering problem statement,
design goals, as-is requirements, candidate broker assessment,
approach, and implementation order.
2026-04-01 20:16:53 +01:00

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Python

from typing import Dict, Any, Tuple
from ...schema import EmbeddingsRequest, EmbeddingsResponse
from .base import MessageTranslator
class EmbeddingsRequestTranslator(MessageTranslator):
"""Translator for EmbeddingsRequest schema objects"""
def decode(self, data: Dict[str, Any]) -> EmbeddingsRequest:
return EmbeddingsRequest(
texts=data["texts"]
)
def encode(self, obj: EmbeddingsRequest) -> Dict[str, Any]:
return {
"texts": obj.texts
}
class EmbeddingsResponseTranslator(MessageTranslator):
"""Translator for EmbeddingsResponse schema objects"""
def decode(self, data: Dict[str, Any]) -> EmbeddingsResponse:
raise NotImplementedError("Response translation to Pulsar not typically needed")
def encode(self, obj: EmbeddingsResponse) -> Dict[str, Any]:
return {
"vectors": obj.vectors
}
def encode_with_completion(self, obj: EmbeddingsResponse) -> Tuple[Dict[str, Any], bool]:
"""Returns (response_dict, is_final)"""
return self.encode(obj), True