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bf4864e614
### What problem does this PR solve? Fixes #14997. RAPTOR builds on the Infinity backend have been broken since v0.25.2 introduced the `extra` field in code (`rag/svr/task_executor.py:1011`) without declaring it in `conf/infinity_mapping.json`. Every RAPTOR job fails with: ``` infinity.common.InfinityException: (3013, 'Fail to bind the expression: extra@src/planner/expression_binder_impl.cpp:99') ``` The auto-migration in `common/doc_store/infinity_conn_base.py:_migrate_db()` adds any columns it finds in the mapping JSON to existing tables — so the only thing standing between users and a working RAPTOR build is that one missing declaration. OceanBase, ES, and OpenSearch were unaffected because they store `extra` as a native JSON type; only Infinity (which has a strict `varchar`/`integer`/`float` schema) needed the addition. ### The fix Two-part change: 1. **`conf/infinity_mapping.json`**: declare `"extra": {"type": "varchar", "default": ""}`. On next startup, `_migrate_db()` adds the column to all existing chunk tables — no manual DDL needed for upgrading installations. 2. **`rag/utils/infinity_conn.py` `insert()`**: serialize the `extra` dict to a JSON string at write time, since Infinity's `varchar` can't store a Python dict directly. Modelled on the existing `chunk_data` handling a few lines above. The read path (`rag/utils/raptor_utils.py:_as_extra_dict`) already normalises both dict and JSON-string inputs, so no read-side change is needed. Other backends are untouched — `task_executor.py` still writes the dict, and the OceanBase/ES/OpenSearch insert paths handle dicts natively. ### Verification Tested on a v0.25.4 deployment with the Infinity backend by applying the same two changes via mounted-volume override: - Confirmed `_migrate_db()` adds the `extra` column to all pre-existing chunk tables on startup (column visible via Infinity's `show_columns()`). - Triggered RAPTOR builds on four datasets (~21k chunks total) via `POST /api/v1/datasets/<id>/index?type=raptor`. - All four progressed past the previously-failing `get_raptor_chunk_methods()` call into actual entity-extraction and clustering work without the (3013) error. - GraphRAG builds (which can trigger the same path indirectly via `task_executor.py:857`) also progressed cleanly. ### Type of change - [X] Bug Fix (non-breaking change which fixes an issue)
45 lines
3.0 KiB
JSON
45 lines
3.0 KiB
JSON
{
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"id": {"type": "varchar", "default": ""},
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"doc_id": {"type": "varchar", "default": ""},
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"kb_id": {"type": "varchar", "default": "", "index_type": {"type": "secondary", "cardinality": "low"}},
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"mom_id": {"type": "varchar", "default": ""},
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"mom": {"type": "varchar", "default": ""},
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"create_time": {"type": "varchar", "default": ""},
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"create_timestamp_flt": {"type": "float", "default": 0.0},
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"img_id": {"type": "varchar", "default": ""},
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"docnm": {"type": "varchar", "default": "", "analyzer": ["rag-coarse", "rag-fine"], "comment": "docnm_kwd, title_tks, title_sm_tks"},
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"name_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"tag_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"important_kwd_empty_count": {"type": "integer", "default": 0},
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"important_keywords": {"type": "varchar", "default": "", "analyzer": ["rag-coarse", "rag-fine"], "comment": "important_kwd, important_tks"},
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"questions": {"type": "varchar", "default": "", "analyzer": ["rag-coarse", "rag-fine"], "comment": "question_kwd, question_tks"},
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"content": {"type": "varchar", "default": "", "analyzer": ["rag-coarse", "rag-fine"], "comment": "content_with_weight, content_ltks, content_sm_ltks"},
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"authors": {"type": "varchar", "default": "", "analyzer": ["rag-coarse", "rag-fine"], "comment": "authors_tks, authors_sm_tks"},
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"page_num_int": {"type": "varchar", "default": ""},
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"top_int": {"type": "varchar", "default": ""},
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"position_int": {"type": "varchar", "default": ""},
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"weight_int": {"type": "integer", "default": 0},
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"weight_flt": {"type": "float", "default": 0.0},
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"chunk_order_int": {"type": "integer", "default": 0},
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"rank_int": {"type": "integer", "default": 0},
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"rank_flt": {"type": "float", "default": 0},
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"available_int": {"type": "integer", "default": 1, "index_type": {"type": "secondary", "cardinality": "low"}},
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"knowledge_graph_kwd": {"type": "varchar", "default": ""},
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"entities_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"pagerank_fea": {"type": "integer", "default": 0},
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"tag_feas": {"type": "varchar", "default": "", "analyzer": "rankfeatures"},
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"from_entity_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"to_entity_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"entity_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"entity_type_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"source_id": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"n_hop_with_weight": {"type": "varchar", "default": ""},
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"mom_with_weight": {"type": "varchar", "default": ""},
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"removed_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"doc_type_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"toc_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"raptor_kwd": {"type": "varchar", "default": "", "analyzer": "whitespace-#"},
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"raptor_layer_int": {"type": "integer", "default": 0},
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"extra": {"type": "varchar", "default": ""}
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}
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