### What problem does this PR solve?
Before consolidation
Web API: POST /v1/document/filter
Http API - GET /api/v1/datasets/<dataset_id>/documents
After consolidation, Restful API -- GET
/api/v1/datasets/<dataset_id>/documents?type=filter
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Fixes#14206.
This issue is a regression. PR #9520 previously changed Gemini models
from `image2text` to `chat` to fix chat-side resolution, but PR #13073
later restored those Gemini entries to `image2text` during model-list
updates, which reintroduced the bug.
The underlying problem is that Gemini models are multimodal and
advertise both `CHAT` and `IMAGE2TEXT`, while tenant model resolution
still depends on a single stored `model_type`. That makes chat-only
flows such as memory extraction fragile when a compatible model is
stored as `image2text`.
This PR fixes the issue at the model resolution layer instead of
changing `llm_factories.json` again:
- keep the stored tenant model type unchanged
- try exact `model_type` lookup first
- if no exact match is found, fall back only when the model metadata
shows the requested capability is supported
- coerce the runtime config to the requested type for chat callers
- fail fast in memory creation instead of silently persisting
`tenant_llm_id=0`
This preserves existing multimodal and `image2text` behavior while
restoring chat compatibility for memory-related flows.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Testing
- Re-checked the current memory creation and memory message extraction
paths against the updated resolution logic
- Verified locally that a Gemini-style tenant model stored as
`image2text` but tagged with `CHAT` can still be resolved for `chat`
- Verified `get_model_config_by_type_and_name(..., CHAT, ...)` returns a
chat-compatible runtime config
- Verified `get_model_config_by_id(..., CHAT)` also returns a
chat-compatible runtime config
- Verified strict resolution still fails when the model metadata does
not advertise chat capability
### What problem does this PR solve?
Before consolidation
Web API: POST /v1/document/list
Http API - GET /api/v1/datasets/<dataset_id>/documents
After consolidation, Restful API -- GET
/api/v1/datasets/<dataset_id>/documents
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Correctly set and display parent-child config in parser_config, and
allow to pass `tenant_id` in PATCH `/api/v1/chats`.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Closes#9078
### What problem does this PR solve?
The `retrieval_test` endpoint in `chunk_app.py` never forwarded the
`highlight` request parameter to `retriever.retrieval()`, so the search
engine never produced highlight snippets. Additionally, the frontend
always rendered `content_with_weight` instead of preferring the
`highlight` field, and the CSS rule color `var(--accent-primary)` didn't
work because the variable stores an RGB triplet `(45,212,191)` requiring
the `rgb()` wrapper.
### Before
- Search page: displayed raw content_with_weight as a wall of plain
white text with no term highlighting, including markdown headings
rendered as literal text
- Retrieval testing page: showed `content_with_weight` in a plain `<p>`
tag, no `<em>` tags rendered, no highlight coloring
- Children chunks: when child chunks were consolidated into a parent via
`retrieval_by_children`, any highlight data from children was discarded
- TOC chunks: chunks fetched via `retrieval_by_toc` had no `highlight`
field, appearing as plain text while other chunks had highlights
**Retrieval testing**:
<img width="1449" height="1178"
alt="before-retrieval-no-highlight-cropped"
src="https://github.com/user-attachments/assets/5c6f5a5e-6c11-461a-bdb4-049d7dfb7a33"
/>
**Search**:
<img width="1378" height="711" alt="before-search-no-highlight-cropped"
src="https://github.com/user-attachments/assets/be7b5152-72ef-40da-a8fd-921e997ae7d3"
/>
### After
- Search page: displays the highlight field with search terms rendered
in teal/cyan color (`rgb(var(--accent-primary))`)
- Retrieval testing page: sends highlight: true in the request, uses
`HighLightMarkdown` component to render `<em>` tags with proper coloring
- Children chunks: highlights from child chunks are joined and preserved
on the parent
- TOC chunks: when other chunks have highlights, TOC-fetched chunks use
`content_with_weight` as a highlight fallback
**Retrieval testing**:
<img width="1410" height="1015" alt="05-retrieval-testing-results"
src="https://github.com/user-attachments/assets/f0cff8cf-0962-4320-b559-cd5037f622d2"
/>
**Search**:
<img width="1294" height="455" alt="03-search-highlight-results"
src="https://github.com/user-attachments/assets/a90e0e3e-3837-46be-8ddd-2412ff7cbc19"
/>
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Trivial fix log creation, follow on PR:
https://github.com/infiniflow/ragflow/pull/14136
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fixes#6034
Changes the `size` field in both `Document` and `File` models from
`IntegerField` (32-bit, max ~2GB) to `BigIntegerField` (64-bit, max
~9.2EB), and adds corresponding database migrations.
## Problem
When uploading a file larger than 2GB, the `size` value overflows a
32-bit signed integer (max 2,147,483,647). This causes:
- The stored `size` wraps around to an incorrect value (e.g., a 3GB file
shows as 2,097,152 KB in File Management).
- Subsequent file operations (e.g., download) fail because the corrupted
size leads to invalid storage lookups.
## Changes
- `Document.size`: `IntegerField` → `BigIntegerField`
- `File.size`: `IntegerField` → `BigIntegerField`
- Added `alter_db_column_type` migrations in `migrate_db()` for both
`document.size` and `file.size` columns to ensure existing deployments
are upgraded automatically.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Signed-off-by: noob <yixiao121314@outlook.com>
Closes#6541
### What problem does this PR solve?
Add content validation to `update_chunk` (SDK and non-SDK) to reject
empty or whitespace-only content before it reaches the embedding model.
**Before:** Calling `update_chunk` with space-only content (like `" "`,
`""`, `"\n"`) bypassed validation and was sent directly to the embedding
model, which returned an error. This was the same bug previously fixed
for `add_chunk` in #6390, but `update_chunk` was missed.
**After:** Empty/whitespace-only content is caught by validation and
returns an error: `` `content` is required ``
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Resolve#14115 .
## Problem
On the shared chat link page (`/chats/share?shared_id=...`), querying
the knowledge base returns "no relevant information was found", while
the same query works correctly on the editor chat page.
## Root Cause
Knowledge base retrieval in `async_chat()` is gated by the check `if
"knowledge" in param_keys` (line 598), where `param_keys` is derived
from `prompt_config["parameters"]`. If `parameters` is empty or missing
the `{"key": "knowledge", "optional": false}` entry, retrieval is
entirely skipped.
This can happen because `_apply_prompt_defaults()` — which ensures
`parameters` contains the `knowledge` entry — is only called in the
`create` (POST) and `update_chat` (PUT) handlers, but **not** in
`patch_chat` (PATCH). If a chat's `prompt_config` was updated via PATCH
without including `parameters`, the `knowledge` entry would be absent.
Additionally, `prompt_config["parameters"]` would raise a `KeyError` if
the key was missing entirely.
## Fix
Added a defensive safety net in `async_chat()`
(`api/db/services/dialog_service.py`) that auto-injects the `knowledge`
parameter when:
- `dialog.kb_ids` is set (knowledge bases are configured)
- `"knowledge"` is not already in `param_keys`
- `{knowledge}` placeholder exists in the system prompt
Also changed `prompt_config["parameters"]` to
`prompt_config.get("parameters", [])` to prevent `KeyError` when the key
is absent.
## Files Changed
- `api/db/services/dialog_service.py` — added auto-injection of
`knowledge` parameter and safe `.get()` access for `parameters`
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Signed-off-by: noob <yixiao121314@outlook.com>
## Summary
- remove eval-based parsing from retrieval rank feature scoring
- validate `tag_feas` at write time in chunk APIs and SDK routes
- add regression tests for safe parsing and malicious payload rejection
## Details
`tag_feas` is intended to be structured rank-feature data, but the
retrieval ranking path was evaluating stored values as Python
expressions. This change treats `tag_feas` strictly as data.
### What changed
- replace `eval()` in `rag/nlp/search.py` with safe parsing via
`json.loads()` and optional `ast.literal_eval()` compatibility for
legacy Python-dict strings
- strictly filter parsed values down to `dict[str, finite number]`
- reject invalid `tag_feas` payloads at write time in web chunk routes
and SDK document chunk routes
- add focused regression tests to prove executable strings are ignored
and invalid payloads are rejected
## Validation
- `python -m pytest test/unit_test/common/test_tag_feature_utils.py
test/unit_test/rag/test_rank_feature_scores.py -q`
---------
Co-authored-by: unknown <zhenglinkai@CCN.Local>
Co-authored-by: Yingfeng Zhang <yingfeng.zhang@gmail.com>
## What's the problem
Both `async_chat()` and `async_ask()` call `decorate_answer()` to build
the final SSE payload — it inserts citation markers (`##N$$`) into the
answer text and prunes `doc_aggs` to only the cited documents.
Immediately after, both functions overwrite `final["answer"]` with `""`:
```python
# async_chat(), line ~774 (issue #13828)
final = decorate_answer(thought + full_answer)
final["final"] = True
final["audio_binary"] = None
final["answer"] = "" # discards decorated text
yield final
# async_ask(), line ~1444 (same bug, different path)
final = decorate_answer(full_answer)
final["final"] = True
final["answer"] = "" # discards decorated text
yield final
```
The client receives filtered references (built for a citation-decorated
answer it never sees) while displaying the raw, undecorated streaming
text. Citations can never match.
## Root cause
`final["answer"] = ""` was left over from an earlier design where
clients were meant to reconstruct the full answer purely from delta
events. Once `decorate_answer()` started placing citation markers, this
blank-out broke the contract: the final event is where the decorated
answer should land.
## Fix
Remove the two blank-override lines — one in `async_chat()`, one in
`async_ask()`:
```diff
- final["answer"] = ""
```
`decorate_answer()` already sets `final["answer"]` to the correct
decorated string; there is nothing to override.
## Relation to #13828
Issue #13828 and PR #13835 identify the bug in `async_chat()`. This PR
absorbs that fix and also corrects the identical pattern in
`async_ask()` (used by the `/retrieval` route in `chat_api.py`), which
PR #13835 does not touch.
## Regression test
Added
`test/unit_test/api/db/services/test_dialog_service_final_answer.py`
with three tests:
| Test | Purpose |
|------|---------|
| `test_buggy_pattern_drops_answer` | Documents the old behaviour:
blank-override empties the final answer |
| `test_fixed_pattern_preserves_decorated_answer` | Core invariant:
final event carries the decorated text from `decorate_answer()` |
| `test_final_event_reference_matches_decorated_result` | Citation
markers in the answer must match the pruned `doc_aggs` in the same event
|
Local run result:
```
test_dialog_service_final_answer.py::test_buggy_pattern_drops_answer PASSED
test_dialog_service_final_answer.py::test_fixed_pattern_preserves_decorated_answer PASSED
test_dialog_service_final_answer.py::test_final_event_reference_matches_decorated_result PASSED
3 passed in 0.04s
```
`ruff check` passes with no issues on all changed files.
---------
Co-authored-by: edenfunf <edenfunf@gmail.com>
Co-authored-by: Yingfeng <yingfeng.zhang@gmail.com>
### What problem does this PR solve?
Consolidation WEB API & HTTP API for document upload
Before consolidation
Web API: POST /v1/document/upload
Http API - POST /api/v1/datasets/<dataset_id>/documents
After consolidation, Restful API -- POST
/api/v1/datasets/<dataset_id>/documents
### Type of change
- [x] Refactoring
## What problem does this PR solve?
Add a warning log when `get_flatted_meta_by_kbs` returns 10,000 results,
which indicates the query limit has been reached and metadata may be
silently truncated.
## Type of change
- [x] Improvement (non-breaking change which improves observability)
### What problem does this PR solve?
Fixes#14051.
The chat UI already sends an `internet` flag with each request, but the
backend previously triggered Tavily web retrieval whenever
`prompt_config.tavily_api_key` was configured. As a result, web search
could still run even when the internet toggle was off.
This PR makes web search an explicit opt-in at request time:
- `tavily_api_key` only indicates that web search is available
- Tavily retrieval runs only when `internet` is explicitly enabled
- the same behavior now applies to both the normal retrieval path and
the deep-research / reasoning path
This also fixes the no-KB fallback case so chats without KBs fall back
to normal solo chat when `internet` is off.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
1. Remove unused token related API
2. Fix typo
### Type of change
- [x] Refactoring
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Before change, update_document in api/apps/restful_apis/document_api.py
is using "PUT".
After change, it will use "PATCH" which is more suitable.
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Closes#13907
The template catalog had duplicate files (e.g. `*_r.json`) only to place
the same template into multiple sidebar groups.
This increases maintenance cost and makes template updates error-prone.
This PR adds first-class support for multiple template categories in a
single file via `canvas_types`, then removes duplicate template files.
What changed:
- Added `canvas_types` to `CanvasTemplate` model and DB migration.
- Added normalization logic when loading templates:
- accepts legacy `canvas_type`
- accepts new `canvas_types`
- merges/deduplicates values
- preserves backward compatibility by keeping `canvas_type` as first
normalized value.
- Updated template import flow to load only `.json` files and in stable
sorted order.
- Updated frontend template filtering to match on `canvas_types` first,
with fallback to legacy `canvas_type`.
- Consolidated duplicated template pairs into single files and removed:
- `deep_search_r.json`
- `reflective_academic_paper_generator_r.json`
- `seo_article_writer_r.json`
- Added regression/edge-case tests for category normalization and route
serialization expectations.
### Type of change
- [ ] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
### What problem does this PR solve?
Consolidate "set_meta" API into "update_document" .
Before consolidation
Web API: POST /api/v1/document/set_meta
Http API - PUT /v1/datasets/<dataset_id>/document/<document_id>
After consolidation, Restful API -- PUT
/v1/datasets/<dataset_id>/document/<document_id>
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Consolidation WEB API & HTTP API for document metadata summary
Before consolidation
Web API: POST /api/v1/document/metadata/summary
Http API - GET /v1/datasets/<dataset_id>/metadata/summary
After consolidation, Restful API -- GET
/v1/datasets/<dataset_id>/metadata/summary
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Visit
`http://127.0.0.1:9381/?__debugger__=yes&cmd=resource&f=debugger.js`
will expose the flask code:
```
docReady(() => {
if (!EVALEX_TRUSTED) {
initPinBox();
}
// if we are in console mode, show the console.
if (CONSOLE_MODE && EVALEX) {
createInteractiveConsole();
}
const frames = document.querySelectorAll("div.traceback div.frame");
if (EVALEX) {
addConsoleIconToFrames(frames);
}
addEventListenersToElements(document.querySelectorAll("div.detail"), "click", () =>
document.querySelector("div.traceback").scrollIntoView(false)
);
addToggleFrameTraceback(frames);
addToggleTraceTypesOnClick(document.querySelectorAll("h2.traceback"));
addInfoPrompt(document.querySelectorAll("span.nojavascript"));
wrapPlainTraceback();
});
function addToggleFrameTraceback(frames) {
frames.forEach((frame) => {
frame.addEventListener("click", () => {
frame.getElementsByTagName("pre")[0].parentElement.classList.toggle("expanded");
});
})
}
```
### Type of change
- [x] Other (please describe): Fix security risk
## Summary
Fixes#13996
Replace `json.load(open(...))` with `with open(...) as f: json.load(f)`
in two files to ensure file descriptors are properly closed.
**Affected files:**
- `common/doc_store/infinity_conn_base.py` — schema loading for Infinity
doc store
- `api/db/init_data.py` — agent template loading at startup
## Why this matters
In a long-running server process like RAGFlow, leaked file descriptors
from `json.load(open(...))` can accumulate over time. While CPython's
refcounting usually cleans these up, it's not guaranteed (especially
under memory pressure or with alternative Python runtimes), and can lead
to `OSError: [Errno 24] Too many open files`.
## Test plan
- [ ] Verify Infinity doc store schema loading still works correctly
- [ ] Verify agent templates load correctly on startup
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Refactor**
* Improved file handling in internal data processing to ensure proper
resource cleanup.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Co-authored-by: easonysliu <easonysliu@tencent.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
### What problem does this PR solve?
As title
### Type of change
- [x] Refactoring
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Chores**
* Improved authentication error logging to better distinguish between
JWT and API token failures.
* Enhanced code documentation with clarifying comments for better
maintainability.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Feat: enable sync deleted files for connector
1. first comes with github
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Added "sync deleted files" feature for data sources, enabling
automatic removal of files deleted from the source system.
* Added multilingual support for the new sync deleted files setting
across multiple languages.
* **UI Improvements**
* Improved checkbox form field rendering and layout.
* Enhanced full-width display for authentication token input fields.
### What problem does this PR solve?
Refactor: merge document.rename into document.update_document
### Type of change
- [x] Refactoring
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Added a unified document update API (PUT) supporting name, metadata,
parser/chunk settings, and status changes.
* **Breaking Changes**
* Legacy single-parameter rename endpoint removed; renames now require
dataset + document identifiers.
* `/list` now reads dataset id from a different query parameter.
* **Validation / Bug Fixes**
* Stricter meta_fields and parser-config validation; unauthenticated
requests return 401.
* **Frontend**
* UI now sends dataset id when saving document names.
* **Tests**
* Numerous unit and HTTP tests adjusted or removed to match new API and
validations.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
Co-authored-by: MkDev11 <94194147+MkDev11@users.noreply.github.com>
Co-authored-by: mkdev11 <YOUR_GITHUB_ID+MkDev11@users.noreply.github.com>
Co-authored-by: mkdev11 <MkDev11@users.noreply.github.com>
Co-authored-by: Qi Wang <wangq8@outlook.com>
Co-authored-by: dataCenter430 <161712630+dataCenter430@users.noreply.github.com>
Co-authored-by: balibabu <cike8899@users.noreply.github.com>
### What problem does this PR solve?
- ping
- token
- log level
### Type of change
- [x] Refactoring
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Refactor**
* System endpoints consolidated under /api/v1/system: ping, health
check, and token management moved to the centralized API surface.
* Token management unified at /api/v1/system/tokens with
list/create/delete behavior.
* **Documentation**
* API reference updated to reflect the new /api/v1/system paths.
* **Tests**
* Client fixtures and test utilities updated to use
/api/v1/system/tokens; one unit test for health/oceanbase status
removed.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
As title.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Bug Fixes**
* Standardized the query parameter used when listing documents so
listings behave consistently across the web and client interfaces.
* Clarified the error message shown when a required dataset ID is
missing to give clearer guidance to users.
* **Tests**
* Updated test coverage to reflect the standardized dataset identifier
usage.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
…
### What problem does this PR solve?
Closes#13857
Parent-child chunking was introduced in v0.23.0 but is only configurable
through the web UI. Users managing datasets programmatically cannot
enable it via the HTTP API or Python SDK because `ParserConfig` uses
`extra="forbid"`, rejecting the `children_delimiter` field at
validation.
### What does this PR change?
Adds a `parent_child` nested config to `ParserConfig`, following the
same pattern as `raptor` and `graphrag`:
```json
"parser_config": {
"parent_child": {
"use_parent_child": true,
"children_delimiter": "\n"
}
}
```
- api/utils/validation_utils.py — new ParentChildConfig model, added to
ParserConfig
- api/utils/api_utils.py — naive defaults + flatten to
children_delimiter for the execution layer
- api/apps/services/dataset_api_service.py — flatten on the update path
- test/testcases/configs.py — updated DEFAULT_PARSER_CONFIG
-
test/testcases/test_http_api/test_dataset_management/test_create_dataset.py
— 4 valid + 2 invalid test cases
No changes to the execution layer (rag/app/naive.py, rag/nlp/search.py).
Existing UI flow via ext is unaffected.
### Type of change
- [ ] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Added parent-child chunking configuration for dataset creation and
updates with new `use_parent_child` toggle and customizable
`children_delimiter` setting to specify how parent chunks are split into
child chunks.
* **Documentation**
* Updated HTTP and Python API references with parent-child chunking
configuration details and examples.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
### What problem does this PR solve?
Implements automatic adjustment of knowledge base chunk recall weights
based on user feedback (upvotes/downvotes). When users upvote or
downvote a response, the system locates the corresponding knowledge
snippets and adjusts their recall weight to improve future retrieval
quality.
**Closes #12670**
**How it works:**
1. User upvotes/downvotes a response via `POST /thumbup`
2. System extracts chunk IDs from the conversation reference
3. For each referenced chunk:
- Reads current `pagerank_fea` value from document store
- Increments (+1) for upvote or decrements (-1) for downvote
- Clamps weight to [0, 100] range
- Updates chunk in ES/Infinity/OceanBase
4. Future retrievals score these chunks higher/lower based on
accumulated feedback
**Files changed:**
- `api/db/services/chunk_feedback_service.py` - New service for updating
chunk pagerank weights
- `api/apps/conversation_app.py` - Integrated feedback service into
thumbup endpoint
- `test/testcases/test_web_api/test_chunk_feedback/` - Unit tests
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Chat message feedback now updates per-chunk relevance weights
(feature-flag gated), with configurable weighting and atomic updates
across storage backends.
* **Bug Fixes**
* Stricter validation for message feedback inputs and more robust
handling of feedback transitions.
* **Tests**
* Expanded test coverage for chunk-feedback behavior, weighting
strategies, storage backends, and thumb-flip scenarios.
* **Chores**
* CI workflow extended to run the new chunk-feedback web API tests.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: mkdev11 <YOUR_GITHUB_ID+MkDev11@users.noreply.github.com>
Co-authored-by: mkdev11 <MkDev11@users.noreply.github.com>
### What problem does this PR solve?
Refactor version API to RESTful style. Python and go server API also
updated.
### Type of change
- [x] Refactoring
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
## Release Notes
* **Refactor**
* Migrated core API endpoints to the `/api/v1/` namespace for improved
consistency and organization.
* Standardized system version, search, and chat list endpoints under the
new API versioning structure.
* **New Features**
* Added MinIO region configuration support, allowing specification of
storage engine regional settings via environment variables or
configuration files.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Add validation logic for parser_config.
Refactor the processing flow. Before change, validation logics and
update logics are mixed up - some validation logis executes followed by
some update logic executes and then another such
"validation-and-then-update" which is not good. After change, all
validation logic executes firstly. Update logic will be executed after
ALL validation logic executed.
Validation logic for parameters (that come from front end) will be
checked using Pydantic. For validation logic that depends on data from
DB, they will be in separate methods.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
### What problem does this PR solve?
Implement UpdateDataset and UpdateMetadata in GO
Add cli:
UPDATE CHUNK <chunk_id> OF DATASET <dataset_name> SET <update_fields>
REMOVE TAGS 'tag1', 'tag2' from DATASET 'dataset_name';
SET METADATA OF DOCUMENT <doc_id> TO <meta>
### Type of change
- [ ] Refactoring
### What problem does this PR solve?
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
---------
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
### What problem does this PR solve?
This PR fixes a race in batch document parsing where overlapping parse
requests for the same document could clear/rewrite chunk state and make
previously parsed content appear lost. It adds an atomic per-document
parse guard so only one parse can run at a time for that document (Fixes
#13864 ).
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Previously, `apikey_required` called
`request.headers.get('Authorization').split()[1]` without checking for
None or insufficient parts, causing an unhandled AttributeError or
IndexError (500) instead of a proper 403 JSON response.
This applies the same guarding pattern already used by `token_required`
in the same file.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
Add REST APIs to dynamically query and modify log levels at runtime for
both Python (Flask) and Go servers.
Changes:
- common/log_utils.py: add set_log_level() and get_log_levels()
functions
- admin/server/routes.py: add GET/PUT /api/v1/admin/log_levels endpoints
- api/apps/system_app.py: add GET/PUT /api/{version}/system/log_levels
endpoints
- internal/logger/logger.go: add GetLevel() and SetLevel() with atomic
level support
- internal/handler/system.go: add GetLogLevel, SetLogLevel, Health
handlers
- internal/router/router.go: route /health to systemHandler
- internal/admin/handler.go: add GetLogLevel, SetLogLevel handlers
- internal/admin/router.go: add /api/v1/admin/log_level routes
### 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] New Feature (non-breaking change which adds functionality)
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
### What problem does this PR solve?
Enable reading Tag Set tags via API (expose tag_kwd field). The result
of the queried list chunks is as shown below:
<img width="1422" height="818" alt="image"
src="https://github.com/user-attachments/assets/abd1960a-fe34-489e-9d72-525f8e574938"
/>
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Co-authored-by: heyang.why <heyang.why@alibaba-inc.com>
### What problem does this PR solve?
fixes issue #13799 where team members get model not authorized when
running RAG on an admin-shared knowledge base after the admin changes
the KB embedding model (for example to bge-m3).
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
