### 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>
### What problem does this PR solve?
remove delete_documents uuid validation
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
## Summary
Fixed a bug where the **File Logs** tab in the dataset ingestion page
always showed "No logs" even after files were parsed successfully.
## Root Cause
Both the **File Logs** and **Dataset Logs** tabs on the frontend called
the same backend endpoint `/datasets/{dataset_id}/ingestions`. However,
the backend only queried `get_dataset_logs_by_kb_id`, which
hard-filtered records by `document_id == GRAPH_RAPTOR_FAKE_DOC_ID`
(dataset-level logs). As a result, real file-level logs were never
returned, causing the table to appear empty.
## Changes
### Backend
- **`api/apps/restful_apis/dataset_api.py`**
- Added two new query parameters to `list_ingestion_logs`:
- `log_type` — `"file"` or `"dataset"` (default: `"dataset"`)
- `keywords` — search keyword for filtering by document / task name
- **`api/apps/services/dataset_api_service.py`**
- Updated `list_ingestion_logs` signature to accept `log_type` and
`keywords`.
- Added conditional routing:
- When `log_type == "file"`, call
`PipelineOperationLogService.get_file_logs_by_kb_id`
- Otherwise, call
`PipelineOperationLogService.get_dataset_logs_by_kb_id`
- **`api/db/services/pipeline_operation_log_service.py`**
- Extended `get_dataset_logs_by_kb_id` with an optional `keywords`
parameter so dataset logs can also be searched.
### Frontend
- **`web/src/pages/dataset/dataset-overview/hook.ts`**
- Removed the separate API function switching (`listPipelineDatasetLogs`
vs `listDataPipelineLogDocument`).
- Unified both tabs to call `listDataPipelineLogDocument` with the new
`log_type` query parameter (`"file"` or `"dataset"`).
- Ensured `keywords` and filter values are passed through correctly.
## Behavior After Fix
| Tab | `log_type` | Returned Records | Searchable Field |
|---|---|---|---|
| File Logs | `file` | Real document-level logs | `document_name` (file
name) |
| Dataset Logs | `dataset` | GraphRAG / RAPTOR / MindMap logs |
`document_name` (task type) |
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: noob <yixiao121314@outlook.com>
Co-authored-by: Wang Qi <wangq8@outlook.com>
Co-authored-by: Yingfeng Zhang <yingfeng.zhang@gmail.com>
## Problem
In the Dataset Configuration page, changing the RAPTOR **Generation
scope** from "Single file" to "Dataset" and clicking **Save** did not
persist the change. After refreshing or re-entering the page, the scope
always reverted to "Single file".
## Root Cause
1. **Backend**: The `RaptorConfig` Pydantic model in
`api/utils/validation_utils.py` was configured with `extra="forbid"` but
did not declare a `scope` field. When the frontend sent `"scope":
"dataset"`, Pydantic rejected the request.
2. **Frontend**: The `extractRaptorConfigExt` utility in
`web/src/hooks/parser-config-utils.ts` treated `scope` as an unknown
field and moved it into the nested `ext` object. Consequently, the
backend could not read `raptor_config.get("scope", "file")` correctly,
so the default `"file"` was always used.
## Changes
- Added `scope: Literal["file", "dataset"]` to the backend
`RaptorConfig` model with a default of `"file"`.
- Added `scope` to the known-field whitelist in the frontend
`extractRaptorConfigExt` helper so it is transmitted as a top-level
raptor field instead of being buried in `ext`.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: noob <yixiao121314@outlook.com>
### What problem does this PR solve?
Fix: Dataset: When configuring the "general chunk method," options such
as chunk size and parent-child slicing are unavailable.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: balibabu <assassin_cike@163.com>
### What problem does this PR solve?
## Summary
Migrate two web API endpoints to REST-style HTTP API endpoints,
following the pattern established in #14222:
| Old Endpoint | New Endpoint |
|---|---|
| `POST /v1/chunk/retrieval_test` | `POST
/api/v1/datasets/<dataset_id>/search` |
| `GET /v1/chunk/knowledge_graph` | `GET
/api/v1/datasets/<dataset_id>/graph` |
### What problem does this PR solve?
Fix: google authentication - gmail && google-drive
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Feat: enable sync delted files for connectors
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Always return success if no such task id to follow existing code logic.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Before migration
Web API: POST /v1/document/change_parser
HTTP API: PATCH /api/v1/datasets/<dataset_id>/documents
After consolidation, Restful API
PATCH /api/v1/datasets/<dataset_id>/documents
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Before migration: GET /v1/document/thumbnails
After migration: GET /api/v1/thumbnails
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Before migration: POST /v1/document/run
After migration: POST /api/v1/documents/ingest/
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Before migration
Web API: POST /v1/document/change_status
After consolidation, Restful API
POST /api/v1/datasets/<dataset_id>/documents/batch-update-status
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Before migration: POST /v1/document/upload_info/
After migration: POST /api/v1/documentss/upload/
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Before migration: GET /v1/document/artifact/<filename>
After migration: GET /api/v1/documents/artifact/<filename>
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Fixes#14196
## Problem
When using DeepDOC to parse large PDFs (over 1000 pages), the parser
silently truncated processing at 300 pages due to a hardcoded default
`page_to=299` in `RAGFlowPdfParser.__images__()`. This caused:
- **Errors** on pages beyond the limit
- **Poor image quality** as the parser attempted to compensate with
missing page data
- **Inconsistent chunk splitting** between full PDF imports and partial
imports
Additionally, the codebase scattered magic numbers (`299`, `600`,
`10000`, `100000`, `100000000`, `10000000000`, `10**9`) across 22 files
as sentinel values for "parse all pages", making future maintenance
error-prone.
## Root Cause
```python
# deepdoc/parser/pdf_parser.py (before)
def __images__(self, fnm, zoomin=3, page_from=0, page_to=299, callback=None):
# Only the first 300 pages were rendered; everything beyond was silently dropped
```
While most callers in `rag/app/*.py` correctly passed `to_page=100000`,
the base class `RAGFlowPdfParser.__call__()` and `parse_into_bboxes()`
invoked `__images__` **without** forwarding `page_from`/`page_to`,
falling back to the restrictive default of 299.
## Solution
### 1. Define constants in `common/constants.py`
```python
MAXIMUM_PAGE_NUMBER = 100000 # Used by the parsing layer
MAXIMUM_TASK_PAGE_NUMBER = MAXIMUM_PAGE_NUMBER * 1000 # Used by the task/DB layer
```
### 2. Replace all hardcoded sentinel values
| Layer | Files Changed | Old Values | New Value |
|---|---|---|---|
| **Deepdoc parsers** | `pdf_parser.py`, `mineru_parser.py`,
`docling_parser.py`, `opendataloader_parser.py`, `paddleocr_parser.py`,
`docx_parser.py` | `299`, `600`, `10**9`, `100000000` |
`MAXIMUM_PAGE_NUMBER` |
| **Chunk parsers** | `naive.py`, `book.py`, `qa.py`, `one.py`,
`manual.py`, `paper.py`, `presentation.py`, `laws.py`, `resume.py`,
`email.py`, `table.py` | `100000`, `10000`, `10000000000` |
`MAXIMUM_PAGE_NUMBER` |
| **Task/DB layer** | `db_models.py`, `task_service.py`,
`document_service.py`, `file_service.py` | `100000000` |
`MAXIMUM_TASK_PAGE_NUMBER` |
### 3. Fix `parse_into_bboxes()` missing parameters
Added `from_page`/`to_page` parameters to `parse_into_bboxes()` so that
the `rag/flow/parser/parser.py` DeepDOC path no longer falls back to the
restrictive default.
## Files Changed (22)
- `common/constants.py`
- `deepdoc/parser/pdf_parser.py`
- `deepdoc/parser/mineru_parser.py`
- `deepdoc/parser/docling_parser.py`
- `deepdoc/parser/opendataloader_parser.py`
- `deepdoc/parser/paddleocr_parser.py`
- `deepdoc/parser/docx_parser.py`
- `rag/app/naive.py`
- `rag/app/book.py`
- `rag/app/qa.py`
- `rag/app/one.py`
- `rag/app/manual.py`
- `rag/app/paper.py`
- `rag/app/presentation.py`
- `rag/app/laws.py`
- `rag/app/resume.py`
- `rag/app/email.py`
- `rag/app/table.py`
- `api/db/db_models.py`
- `api/db/services/task_service.py`
- `api/db/services/document_service.py`
- `api/db/services/file_service.py`
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
---------
Signed-off-by: noob <yixiao121314@outlook.com>
### What problem does this PR solve?
## Summary
Closes#6102
When using Infinity as the document store engine (GPU version), calling
`update()` on a non-existent table throws an unhandled
`InfinityException` with error code 3022 (`TABLE_NOT_EXIST`). This
causes users to see a raw "3022" error when clicking on a parsed
document.
## Root Cause
The `update()` methods in both `rag/utils/infinity_conn.py` and
`memory/utils/infinity_conn.py` call `db_instance.get_table(table_name)`
without catching `InfinityException`. In contrast, other CRUD methods
(`insert`, `delete`, `search`) all handle this exception gracefully:
| Method | Handles table-not-exist? | Behavior |
|----------|--------------------------|----------|
| `insert` | ✅ Yes | Auto-creates the table |
| `search` | ✅ Yes | Skips the table |
| `delete` | ✅ Yes | Returns 0 |
| `update` | ❌ **No** | Crashes with 3022 |
Additionally, `api/apps/document_app.py` worked around this with a
fragile string match (`"3022" in msg`) to detect the error.
## Changes
- **`rag/utils/infinity_conn.py`**: Catch `InfinityException` in
`update()`. When `TABLE_NOT_EXIST` is detected, log a warning and return
`False` — consistent with `delete()`.
- **`memory/utils/infinity_conn.py`**: Apply the same fix to its
`update()` method.
- **`api/apps/document_app.py`**: Remove the fragile `"3022"`
string-matching workaround. Table-not-exist is now handled by the `if
not ok` path with an improved error message.
### Type of change
- [x] Refactoring
---------
Signed-off-by: noob <yixiao121314@outlook.com>
### What problem does this PR solve?
The POST /upload_info?url=<url> endpoint accepted a user-supplied URL
and passed it directly to AsyncWebCrawler without any validation. There
were no restrictions on URL scheme, destination hostname, or resolved IP
address. This allowed any authenticated user to instruct the server to
make outbound HTTP requests to internal infrastructure — including RFC
1918 private networks, loopback addresses, and cloud metadata services
such as http://169.254.169.254 — effectively using the server as a proxy
for internal network reconnaissance or credential theft.
This PR adds an SSRF guard (_validate_url_for_crawl) that runs before
any crawl is initiated. It enforces an allowlist of safe schemes
(http/https), resolves the hostname at validation time, and rejects any
URL whose resolved IP falls within a private or reserved network range.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Allow image2text models (multimodal) to be used as chat models.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
The Langfuse Python SDK v3+ removed `start_generation()` method.
RagFlow's code called this non-existent method, causing AttributeError
when Langfuse tracing is enabled.
Replace all `start_generation()` calls with
`start_observation(as_type="generation")` which is the correct v4 SDK
API.
Affected files:
- api/db/services/llm_service.py (12 occurrences)
- api/db/services/dialog_service.py (1 occurrence)
Fixes#14204
Related to #9243
### What problem does this PR solve?
_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
### What problem does this PR solve?
`check_ragflow_server_alive()` in `api/utils/health_utils.py` calls
`requests.get(url)` without a `timeout` parameter. Unlike
`check_minio_alive()` which correctly specifies `timeout=10`, this
health check can hang indefinitely if the server is unresponsive.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Changes
Added `timeout=10` to the `requests.get()` call, consistent with
`check_minio_alive()`.
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
### What problem does this PR solve?
Before migration
Web API: POST /v1/document/metadata/update
After migration, Restful API
PATCH /api/v2/datasets/<dataset_id>/documents/metadatas
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Before migration
Web API: POST /v1/document/update_metadata_setting
After consolidation, Restful API
PUT
/api/v1/datasets/<dataset_id>/documents/<document_id>/metadata/config
### Type of change
- [x] Refactoring
