semvec/pypi-packages huggingface dataset:
srmhga 1.0.0
SRM-HGA: Semantic Routing Memory based Hybrid Governance Architecture for Long-Lived AI Agents
License: MIT
Requires Python: >=3.10
Keywords: memory, llm, agents, hybrid-memory, governance, semantic-routing, long-term-memory, rag

# SRM-HGA

SRM-HGA is a production-oriented Python library that implements a **three-layer hybrid memory architecture** for long-lived LLM agents.

- **L1 — AQSRL:** vector-quantized semantic routing (fast path)
- **L2 — DV:** deterministic vault for exact and auditable records
- **L3 — PM:** stable profile memory for user preferences and constraints

This repository vendors a compatible SRM implementation under `src/srm/`.
celery-task-class 0.1.0
Write Celery task as a class
License: MIT
Requires Python: >=3.9

Added `as_task()` method:

```python
from celery import Celery
from celery import shared_task

from celery_task_class import Task

app = Celery(
    broker="redis://localhost:6379/0",
    backend="redis://localhost:6379/0",
)


class MyTask(Task):
    def run(self, *args, **kwargs):
        print('MyTask.run()')


@shared_task(base=MyTask, bind=True)
def run(self, *args, **kwargs):
    print('run() function task')
    super(self.__class__, self).run(*args, **kwargs)


class MyTask2(MyTask):
    def run(self, *args, **kwargs):
        print('MyTask2.run()')
        super().run(*args, **kwargs)


my_task = MyTask.as_task()
my_task2 = MyTask2.as_task()
```

Caller:

```python
from mycode import my_task

my_task.delay()
```