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### What problem does this PR solve? Currently, RAGFlow's Search and Chat interfaces display only raw vectorized text chunks during retrieval, without contextual information about their source documents. Users cannot see document titles, page numbers, upload dates, or custom metadata fields that would help them understand and trust the retrieved results. This PR introduces an **optional metadata display feature** that enriches retrieved chunks with document-level metadata in both the Search tab and Chatbot interface. **Key improvements:** - **Search results**: Display document metadata as styled badges beneath chunk snippets - **Chat citations**: Show metadata in citation popovers and reference lists for better source context - **LLM context**: Metadata is injected into the LLM prompt to enable more accurate, citation-aware responses - **External API support**: Applications using RAGFlow's SDK retrieval endpoints (`/v1/retrieval`, `/v1/searchbots/retrieval_test`) can opt-in via request parameters - **User control**: Multi-select dropdown UI allows users to choose which metadata fields to display **Implementation approach:** - ✅ Reuses existing `DocMetadataService` infrastructure (no new database tables or indices) - ✅ Settings stored in existing JSON configuration fields (`search_config.reference_metadata`, `prompt_config.reference_metadata`) - ✅ No database migrations required - ✅ Disabled by default (fully opt-in and backward-compatible) - ✅ Dynamic metadata field selection populated from actual document metadata keys - ✅ Fixed critical bug where Python's builtin `set()` was shadowed by a route handler function **Modified endpoints (all backward-compatible):** - `POST /v1/retrieval` (Public SDK) - `POST /v1/searchbots/retrieval_test` (Searchbots) - `POST /v1/chunk/retrieval_test` (UI/Internal) - Chat completions endpoints (via `extra_body.reference_metadata` or `prompt_config`) ### Type of change - [x] New Feature (non-breaking change which adds functionality) ###Images - <img width="879" height="1275" alt="image" src="https://github.com/user-attachments/assets/95b2d731-31ae-45a1-b081-bf5893f52aeb" /> <br><br> <br><br> <img width="1532" height="362" alt="image" src="https://github.com/user-attachments/assets/9cebc65b-b7a7-459f-b25e-3b13fa9b638e" /> <br><br> <br><br> <img width="2586" height="1320" alt="image" src="https://github.com/user-attachments/assets/2153d493-d899-461f-a7a9-041391e07776" /> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Attili-sys <Attili-sys@users.noreply.github.com> Co-authored-by: Ahmad Intisar <ahmadintisar@Ahmads-MacBook-M4-Pro.local>
126 lines
4.5 KiB
Python
126 lines
4.5 KiB
Python
#
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# Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import logging
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logger = logging.getLogger(__name__)
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def resolve_reference_metadata_preferences(
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request_payload: dict | None = None,
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config_payload: dict | None = None,
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) -> tuple[bool, set[str] | None]:
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"""
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Resolve metadata include/fields from request and optional config.
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Request values take precedence over config values.
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Supports legacy request keys: include_metadata / metadata_fields.
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"""
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request_payload = request_payload or {}
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config_payload = config_payload or {}
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config_ref = config_payload.get("reference_metadata", {})
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request_ref = request_payload.get("reference_metadata", {})
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resolved: dict = {}
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if isinstance(config_ref, dict):
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resolved.update(config_ref)
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if isinstance(request_ref, dict):
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resolved.update(request_ref)
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if "include_metadata" in request_payload:
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resolved["include"] = bool(request_payload.get("include_metadata"))
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if "metadata_fields" in request_payload:
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resolved["fields"] = request_payload.get("metadata_fields")
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include_metadata = bool(resolved.get("include", False))
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fields = resolved.get("fields")
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if fields is None:
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return include_metadata, None
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if not isinstance(fields, list):
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logger.warning(
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"reference_metadata.fields is not a list; include_metadata=%s fields=%r type=%s resolved=%r. "
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"enrich_chunks_with_document_metadata will skip enrichment.",
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include_metadata,
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fields,
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type(fields).__name__,
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resolved,
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)
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return include_metadata, set()
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return include_metadata, {f for f in fields if isinstance(f, str)}
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def enrich_chunks_with_document_metadata(
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chunks: list[dict],
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metadata_fields: set[str] | None = None,
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*,
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kb_field: str = "kb_id",
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doc_field: str = "doc_id",
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output_field: str = "document_metadata",
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) -> None:
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"""
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Mutates chunk payloads in-place by attaching `document_metadata`.
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Field names can be customized for different chunk schemas.
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"""
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if metadata_fields is not None and not metadata_fields:
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return
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doc_ids_by_kb: dict[str, set[str]] = {}
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for chunk in chunks:
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kb_ids = chunk.get(kb_field)
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doc_id = chunk.get(doc_field)
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if not kb_ids or not doc_id:
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continue
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if isinstance(kb_ids, (list, tuple)):
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for kid in kb_ids:
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if kid:
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doc_ids_by_kb.setdefault(kid, set()).add(doc_id)
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else:
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doc_ids_by_kb.setdefault(kb_ids, set()).add(doc_id)
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if not doc_ids_by_kb:
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return
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# Resolve service lazily so callers/tests that swap service modules at runtime
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# (e.g. via monkeypatch) don't get stuck with a stale class reference.
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from api.db.services.doc_metadata_service import DocMetadataService
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metadata_getter = getattr(DocMetadataService, "get_metadata_for_documents", None)
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if not callable(metadata_getter):
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logging.warning(
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"DocMetadataService.get_metadata_for_documents is unavailable; "
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"skipping metadata enrichment."
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)
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return
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meta_by_doc: dict[str, dict] = {}
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for kb_id, doc_ids in doc_ids_by_kb.items():
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meta_map = metadata_getter(list(doc_ids), kb_id)
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if meta_map:
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meta_by_doc.update(meta_map)
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logging.debug("Fetched metadata for %d docs in kb_id=%s", len(meta_map), kb_id)
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for chunk in chunks:
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doc_id = chunk.get(doc_field)
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if not doc_id:
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continue
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meta = meta_by_doc.get(doc_id)
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if not meta:
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continue
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if metadata_fields is not None:
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meta = {k: v for k, v in meta.items() if k in metadata_fields}
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if meta:
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chunk[output_field] = meta
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logging.debug("Enriched chunk for doc_id=%s with %d metadata fields: %s", doc_id, len(meta), list(meta.keys()))
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