FEAT: Add remove_seeds_from_memory_async to memory

[blahdeblahde]

Description

PyRIT memory can add seed prompt datasets (via add_seed_datasets_to_memory_async / add_seeds_to_memory_async) and query them with get_seeds, but there is no counterpart for removing seeds. Today users have to drop into raw SQL, which is error-prone and differs across the supported backends (DuckDB, SQLite, Azure SQL).

This PR adds remove_seeds_from_memory_async, which accepts the same filter parameters as get_seeds (dataset_name, dataset_name_pattern, added_by, harm_categories, authors, groups, source, value_sha256, data_types, seed_type, parameters, metadata, prompt_group_ids) and returns the number of seeds removed.

Recommended workflow — preview, then delete with the same filters:

# See what matches before deleting
to_delete = memory.get_seeds(dataset_name="illegal")

# Remove them; returns the count deleted
removed = await memory.remove_seeds_from_memory_async(dataset_name="illegal")

Implementation

• Extracted the filter-building logic out of get_seeds into a shared private helper (_build_seed_filter_conditions) so both query and removal build conditions from a single source and cannot drift.
• remove_seeds_from_memory_async deletes matching rows in a single transaction using the SQLAlchemy ORM (rollback on error), so it behaves consistently across DuckDB, SQLite, and Azure SQL.

Safety

• At least one filter must be provided; a no-filter call raises ValueError to prevent accidentally wiping the entire seed database.

Tests and Documentation

Tests — tests/unit/memory/memory_interface/test_interface_remove_seeds.py covers:

• exact dataset_name match
• dataset_name_pattern (SQL LIKE)
• multi-filter narrowing (dataset_name + added_by)
• no-filter call raises ValueError
• zero-match returns 0 and deletes nothing
• harm_categories (list field) and source filters

Documentation — added a "Removing Seeds from the Database" section to doc/code/memory/8_seed_database.py (and the synced .ipynb) demonstrating the preview-then-remove workflow.