Review count() implementation - consider FT.AGGREGATE

Summary

The current FindQuery.count() implementation uses FT.SEARCH with LIMIT 0 0 and nocontent=True:

async def count(self):
    query = self.copy(offset=0, limit=0, nocontent=True)
    result = await query.execute(exhaust_results=True, return_raw_result=True)
    return result[0]

This works, but FT.AGGREGATE with a count reducer may be a better approach.

Why FT.AGGREGATE might be better

1. Purpose-built for aggregations - FT.AGGREGATE is designed for operations like counting, grouping, etc.
2. More flexible - Could support count() with grouping (e.g., count by category)
3. Potentially more efficient - Aggregation pipeline is optimized for this use case

Example with FT.AGGREGATE

FT.AGGREGATE idx * GROUPBY 0 REDUCE COUNT 0 AS total

This returns just the count without any document data.

Tasks

• Benchmark current FT.SEARCH LIMIT 0 0 vs FT.AGGREGATE for count
• Evaluate if FT.AGGREGATE provides any performance benefits
• Consider adding grouped count support (e.g., Model.find().count(group_by="category"))

Start at the FindQuery.count() implementation shown in the issue and review how it currently executes FT.SEARCH. Benchmark that approach against the proposed FT.AGGREGATE count, then assess whether grouped counts should be included. Done means the performance comparison and implementation scope have a documented conclusion.