Fts milvus dataset

[Denise2004]

This PR migrates the FTS test dataset source from local files to remote automatic download.

Main Achievements

New IR_DATASETS Data Source: Integrated ir_datasets library to enable automatic download and conversion of MS MARCO datasets

Ground Truth Evaluation Optimization: Switched FTS evaluation ground truth from qrels to scoreddocs for more comprehensive retrieval result assessment

Core Features

1. Remote Dataset Download

• Added IR_DATASETS data source type
• Integrated ir_datasets.load("msmarco-passage/dev/small") API
• Automatic download and conversion to TSV format files
• Support for queries.small.tsv, docs.small.tsv, qrels.small.tsv, scoreddocs.small.tsv

2. Ground Truth Data Optimization

• Switched evaluation ground truth from qrels (human-annotated relevant documents) to scoreddocs (BM25 top-1000 retrieval results)

3. Environment Configuration Optimization

• Set IR_DATASETS_HOME and IR_DATASETS_TMP environment variables
• Redirect dataset cache and temporary files to project tmp directory

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[XuanYang-cn]

Code Review: FTS (Full-Text Search) Implementation for Milvus

Thanks for adding FTS benchmarking support! The overall approach follows existing patterns well. A few issues to address before merging:

---

Critical Issues (Must Fix)

1. Duplicated code in vectordb_bench/models.py:347-360

The if/else branches have identical try/except blocks - only the index_value assignment differs. Refactor to:

if case_config.get("case_id") in [502, 503, 504]:
    index_value = IndexType.FTS_AUTOINDEX

try:
    task_config["db_case_config"] = db.case_config_cls(index_type=index_value)(**raw_case_cfg)
except Exception:
    log.exception(f"Couldn't get class for index '{index_value}' ({full_path})")
    task_config["db_case_config"] = EmptyDBCaseConfig(**raw_case_cfg)

2. Magic numbers for case IDs (models.py:348)

if case_config.get("case_id") in [502, 503, 504]:

Case IDs 502 and 504 are referenced but only 503 (FTSmsmarcoPerformance) is defined in CaseType. Consider using enum values instead of magic numbers, or remove undefined IDs.

---

Important Issues (Should Fix)

3. Resource leak in FtsDocumentIterator (dataset.py)

The file handle opened in __next__ may leak on exception. __del__ is unreliable for cleanup. Consider making it a context manager or ensuring proper cleanup.

4. Assertion used for validation (milvus/milvus.py)

assert self.col is not None

Replace with proper validation that raises RuntimeError - assertions can be disabled in production.

5. Hardcoded dataset name in _get_ir_datasets_name() (dataset.py)

Returns "msmarco-passage/dev/small" regardless of self.data properties. This won't scale when additional FTS datasets are added.

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Minor Suggestions

• Missing period in description (cases.py:668-670) - "...MS MARCO dataset " should end with a period
• Chinese comments in milvus/config.py:441-475 - consider translating for consistency
• Unused logging in milvus/cli.py - log = logging.getLogger(__name__) is defined but not used
• BM25 parameter validation - comments document ranges [1.2, 2.0] for bm25_k1 and [0.0, 1.0] for bm25_b, but no validators enforce them
• Unnecessary hasattr checks in milvus/config.py - these are class attributes, so hasattr always returns True

---

Positives

• Good separation of FTS classes from vector search classes
• Follows existing codebase patterns well
• Proper context manager usage in Milvus init()
• Comprehensive metric support (MRR, FTS-specific recall/NDCG)
• Good bug fixes for Qdrant logging included