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
### What problem does this PR solve?
normalize think tags in final chat answer
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Before consolidation
Web API: POST /v1/document/rm
Http API - DELETE /api/v1/datasets/<dataset_id>/documents
After consolidation, Restful API -- DELETE
/api/v1/datasets/<dataset_id>/documents
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Refactor /api/v1/chats to be more RESTful.
### Type of change
- [x] Refactoring
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Before consolidation
Web API: POST /v1/document/infos
Http API - GET /api/v1/datasets/<dataset_id>/documents
After consolidation, Restful API -- GET
/api/v1/datasets/<dataset_id>/documents?ids=id1&ids=id2
### Type of change
- [ ] Refactoring
### 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
