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Python: RedisCollection.ensure_collection_deleted can return successfully without deleting the index

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Nadie ha tomado este issue todavía.

Evaluación

Dificultad
3/5
Tiempo estimado
1-2 días
Aptitud para principiantes
65/100
Tipo de issue
Error
Claridad
Bien especificado
Estado de actividad
Activo
Stack tecnológico
python, redis
Área
backend, databases

Línea de trabajo

The issue is in python/semantic_kernel/connectors/redis.py. Look at the ensure_collection_deleted method and its dependency on collection_exists. First, run the existing tests for the Redis connector to understand the current behavior. Then, examine the redis-py library documentation or source to find the exact exception type raised by FT.DROPINDEX when an index does not exist. The fix should mirror the pattern in chroma.py: attempt dropindex directly and handle the specific 'index not found' exception quietly, raising a VectorStoreOperationException for other errors. Write a test that simulates a timeout during FT.INFO to verify the fix.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

python triage
Describe the bug

RedisCollection.ensure_collection_deleted can return successfully without deleting anything.

# python/semantic_kernel/connectors/redis.py
async def collection_exists(self, **kwargs) -> bool:
    try:
        await self.redis_database.ft(self.collection_name).info()
        return True
    except Exception:
        return False

async def ensure_collection_deleted(self, **kwargs) -> None:
    exists = await self.collection_exists()
    if exists:
        await self.redis_database.ft(self.collection_name).dropindex(**kwargs)
    else:
        logger.debug("Collection does not exist, skipping deletion.")

collection_exists() reaches Redis to answer, so it can fail for reasons unrelated to whether the index is there - a timeout, an authentication failure, an unreachable node. Every one of those returns False, and ensure_collection_deleted then logs at debug level and returns normally.

The caller is told the collection is deleted. It is not. Nothing raises and nothing is logged above debug.

The same library already does this correctly

ChromaCollection.ensure_collection_deleted in python/semantic_kernel/connectors/chroma.py distinguishes the two cases:

try:
    self.client.delete_collection(name=self.collection_name)
except ValueError:
    logger.info(f"Collection {self.collection_name} could not be deleted because it doesn't exist.")
except Exception as e:
    raise VectorStoreOperationException(
        f"Failed to delete collection {self.collection_name} with error: {e}"
    ) from e

Absent is handled quietly. Anything else raises. That is the behaviour I would expect from ensure_collection_deleted on any connector, and the Redis one is the odd one out.

ChromaCollection.collection_exists has the same except Exception: return False shape, but its delete path does not depend on it, so the consequence there is smaller.

To reproduce

Call ensure_collection_deleted() on a RedisCollection while Redis is reachable at connect time but the FT.INFO call fails - a timeout is the easiest to induce. The method returns without raising and the index is still present.

Expected behavior

A failed check is not an absent collection. ensure_collection_deleted should either delete the index or raise.

Suggested fix

Mirror the Chroma connector: attempt dropindex and handle only the specific "index does not exist" error quietly, raising VectorStoreOperationException for anything else.

I am filing this rather than opening a pull request because the right fix depends on exactly which exception FT.DROPINDEX raises for a missing index in the redis-py version this pins, and I did not want to assert that without a Redis instance to confirm it against. If a maintainer can confirm the exception type, I am happy to open the PR.

Platform

Python, main as of 23 September 2026.

Lenguaje dominante
C#
Estrellas
28.6k
Forks
4.8k
Merge medio
12 h 20 min
PR fusionados (30 d)
12

Preparar el entorno

Primeros pasos

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  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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