### What problem does this PR solve?
When I run RAGFlow_server.py:
```
2026-06-24 10:27:01,938 ERROR 3413485 fetch task exception
Traceback (most recent call last):
File "/home/infiniflow/Documents/development/ragflow/api/db/services/document_service.py", line 948, in _sync_progress
if t.progress_msg.strip():
^^^^^^^^^^^^^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'strip'
```
fixed:
```python
if t.progress_msg.strip():
# fix:
if (t.progress_msg or "").strip():
```
Fix crash in `_sync_progress` when `progress_msg` is `None`.
#### Root Cause
`progress_msg` from task records can be `None`, causing:
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What does this PR do?
This PR adds a new DingTalk chat channel integration and hardens the
inbound callback path.
### Summary
- Adds DingTalk as a selectable chat channel in the UI and backend
channel registry.
- Adds the DingTalk chat channel icon asset.
- Acknowledges DingTalk Stream callbacks and deduplicates repeated
inbound messages to avoid duplicate replies.
### What problem does this PR solve?
Implement OpenAI chat completions in GO
POST /api/v1/openai/<chat_id>/chat/completions
OpenAI chat cli: internal/development.md
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Adds qqbot as a built-in chat channel so it can be discovered and
started by the channel bootstrapper and shown in the chat channel
settings UI.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Fix chat channel message routing to use the connected `chat_id`, and
make the Feishu websocket client bind to the thread-local event loop.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Use a 95% max_length threshold before truncating embedding inputs, which
reduces the chance of provider-side invalid-parameter errors on
near-limit chunks.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
The `get_ingestion_log` endpoint (both Python
`dataset_api_service.get_ingestion_log` and Go
`DatasetService.GetIngestionLog`) was returning only the
**dataset-level** field set, which omits critical fields such as `dsl`,
`document_id`, `parser_id`, `document_name`, `pipeline_id`, etc.
This caused the front-end **dataflow-result page** to be unable to
render the pipeline timeline and chunks when viewing a single ingestion
log, regardless of whether the log was a dataset-level operation
(graph/raptor/mindmap) or a per-file parse.
### Background
`PipelineOperationLogService` provides two field sets:
| Method | Fields |
|---|---|
| `get_dataset_logs_fields` | Minimal set (progress, status, timestamps,
etc.) |
| `get_file_logs_fields` | Superset — includes `document_id`, `dsl`,
`parser_id`, `document_name`, `pipeline_id`, … |
When listing logs, the API correctly distinguishes dataset-level vs
file-level logs and uses the appropriate converter. However, when
**fetching a single log by ID**, both the Python and Go implementations
were hardcoded to the dataset-level set, dropping the extra fields that
the front-end needs.
The parser pods suffer from OOM kills when processing large PDF
documents. The root cause is in api/db/services/task_service.py: when
layout_recognize is not DeepDOC (e.g. Plain Text), page_size was set to
MAXIMUM_TASK_PAGE_NUMBER (100 million), causing the entire PDF to be
processed as a single task with all pages loaded into memory
simultaneously.
This PR fixes the issue by paginating non-DeepDOC PDF parsing tasks the
same way DeepDOC already does.
### What problem does this PR solve?
The parser pods suffer from OOM kills when processing large PDF
documents. The root cause is in api/db/services/task_service.py: when
layout_recognize is not DeepDOC (e.g. Plain Text), page_size was set to
MAXIMUM_TASK_PAGE_NUMBER (100 million), causing the entire PDF to be
processed as a single task with all pages loaded into memory
simultaneously.
This PR fixes the issue by paginating non-DeepDOC PDF parsing tasks the
same way DeepDOC already does.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [ ] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [ ] Refactoring
- [x] Performance Improvement
- [ ] Other (please describe):
## Summary
- The `ChatChannel` DB column was renamed from `dialog_id` to `chat_id`
via a migration (added in a prior commit).
- Aligns the REST API layer (`chat_channel_api.py`,
`chat_channel_service.py`) to use `chat_id` consistently.
- Updates the frontend (`interface.ts`, `hooks.ts`,
`connect-dialog-modal.tsx`, `added-channel-card.tsx`) to read/write
`chat_id` instead of `dialog_id`.
- The joined `dialog_name` alias in the list query is unchanged (backend
still returns it under that name).
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
### What problem does this PR solve?
Fix:
- Pass session_id to langfuse.
- Get correct status for add model_type.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Adds a legacy mode for /chat/completions that restores v0.23.0-style
output by converting start_to_think/end_to_think back into raw
<think></think> markers and streaming cumulative answer text.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Feat:
- Allow upsert model_type for instance model
Fix:
- Allow create instance with duplicate api_key
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
Guard the agent-attachment download against a missing or empty storage blob so the caller gets a structured 4xx (`Document not found!`) instead of an HTTP 500. Same bug class as #15365 on document preview.
Resolve#15502
### What problem does this PR solve?
| # | Method | Endpoint | Description | Git Equivalent |
|---|--------|----------|-------------|----------------|
| 1 | `POST` | `/api/v1/{prefix}/{folder_id}/commits` | Create a
snapshot commit with file changes (add/modify/delete/rename) | `git add`
+ `git commit` |
| 2 | `GET` | `/api/v1/{prefix}/{folder_id}/commits` | List commit
history (paginated) | `git log` |
| 3 | `GET` | `/api/v1/{prefix}/{folder_id}/commits/{commit_id}` | Get
commit detail with file changes | `git show` |
| 4 | `GET` | `/api/v1/{prefix}/{folder_id}/commits/{commit_id}/files` |
List file changes in a commit | `git show --name-status` |
| 5 | `GET` |
`/api/v1/{prefix}/{folder_id}/commits/diff?from=...&to=...` | Compare
two commits and return differences | `git diff` |
| 6 | `GET` | `/api/v1/{prefix}/{folder_id}/changes` | Get uncommitted
changes (add/modify/delete) | `git status` |
| 7 | `GET` | `/api/v1/{prefix}/{folder_id}/commits/{commit_id}/tree` |
Get the folder tree snapshot at commit time | `git ls-tree` |
| 8 | `GET` |
`/api/v1/{prefix}/{folder_id}/commits/{commit_id}/files/{file_id}/content`
| Get a file's content as it existed in a specific commit | `git show
HEAD:file` |
| 9 | `GET` | `/api/v1/{prefix}/{file_id}/versions` | Get version
history for a specific file across all commits | `git log -- file` |
Where `{prefix}/{id}` can be:
- `folders/{folder_id}` — direct folder access
- `workspaces/{workspace_id}` — alias of `folders/{folder_id}`
- `datasets/{dataset_id}` — resolves to the dataset's folder
- `memories/{memory_id}` — resolves to the memory's folder
- `skills/{skill_id}` — resolves to the skill's folder
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
### What problem does this PR solve?
#15844
Adds a **Chat channels** capability so a RAGFlow assistant (Dialog) can
be exposed as a bot on external messaging platforms (Feishu/Lark,
Discord, Telegram, Slack, WeCom, LINE, etc.). An admin configures a bot
in the UI, connects it to an assistant, and inbound messages are
answered from that assistant's knowledge base — replies are delivered
back on the channel.
**Feishu/Lark is implemented and tested end-to-end.** Discord, Telegram,
LINE, and WeCom are scaffolded against the same interface; the remaining
listed channels are tracked as follow-ups.
### Design
**Backend**
- New `chat_channel` table (`tenant_id`, `name`, `channel`, `config`
JSON holding `{credential: {...}}`, `dialog_id`, `status`) +
`ChatChannelService` and RESTful CRUD under `/api/v1/chat_channels`.
- Channel framework under `api/channels/`: a `core` registry +
per-channel packages that self-register a builder and implement a common
`Channel` interface (`start`/`stop`/`send` + inbound normalization) over
`IncomingMessage`/`OutgoingMessage`.
- Embedded **reconcile loop** in `ragflow_server`
(`api/channels/bootstrap.py`): loads enabled bots, and
starts/stops/restarts them as rows change (no server restart needed).
Inbound messages run the connected dialog via the non-streaming
completion path, keeping per-end-user conversation history.
- Missing optional channel SDKs degrade gracefully (channel skipped with
a warning; others unaffected). Channel-level errors are logged, not
crashed.
- Feishu's WebSocket client runs in a dedicated thread with its own
event loop to avoid cross-loop/contextvars conflicts with the channel
runtime.
**Frontend**
- **Settings → Chat channels** panel: available-channels grid +
configured-bots list with add/edit/delete and a **Connect assistant**
popup that binds a bot to a dialog.
- Brand icons via simple-icons / reused shared data-source assets, with
colored fallbacks for brands not available.
- Route, sidebar entry, i18n (en/zh), and a top-nav segment-boundary fix
so the settings page no longer highlights the Chat tab.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### Notes
- DB: new `chat_channel` table is auto-created; `chat_channel.dialog_id`
is also covered by a `migrate_db` `alter_db_add_column` for existing
installs.
- Channel SDKs (`lark-oapi`, `discord.py`, `python-telegram-bot`,
`line-bot-sdk`, `wechatpy`, `aiohttp`) added to dependencies.
- Screenshots / per-channel credential docs to follow.
<img width="1338" height="1290" alt="Image"
src="https://github.com/user-attachments/assets/042cb2f9-0dad-4e6a-bcf7-43ced4bbd704"
/>
<img width="1344" height="738" alt="Image"
src="https://github.com/user-attachments/assets/373cd08e-ec40-4c67-9c51-4d948b1ba617"
/>
<img width="672" height="887" alt="Image"
src="https://github.com/user-attachments/assets/5a34953f-a9a3-4c1e-869e-5eff0dc64c84"
/>
---------
### What problem does this PR solve?
The Profile **Name** field currently lacks application-level validation
and allows users to save excessively long names and unsupported special
characters.
While the database enforces a maximum length of 100 characters, neither
the frontend nor backend validates nickname format before persistence.
This can result in inconsistent user data, poor user experience, and UI
layout issues when long names wrap across multiple lines.
This PR introduces consistent frontend and backend validation for
profile names, enforces length and character constraints, provides clear
validation feedback, and prevents invalid values from being saved.
Fixes#15693
### Type of change
* [x] Bug Fix (non-breaking change which fixes an issue)
## Summary
This PR passes `session_id` into Langfuse trace observations so
multi-turn chat messages can be grouped under the same session in
Langfuse.
Changes include:
- Propagate `session_id` from chat/session APIs into
`dialog_service.async_chat`.
- Pass `session_id` into Langfuse `start_observation(...)`.
- Share Langfuse `trace_context` with chat, embedding, rerank, and TTS
model bundles where applicable.
- Add unit coverage to verify Langfuse observations receive
`session_id`.
- Update affected test stubs for the new optional Langfuse context
arguments.
## Related Issue
Closes: #15636
## Change Type
- [x] Feature
- [x] Bug fix
- [x] Test
- [ ] Refactor
- [ ] Documentation
- [ ] Breaking change
## Real Behavior Proof
Before this change:
- Langfuse observations were created without `session_id`.
- Multi-turn chat traces could not be grouped by session in Langfuse.
After this change:
- Chat/session flows pass `session_id` into `async_chat`.
- Langfuse observations include `session_id`.
- Related model bundles receive shared trace context and session
metadata.
Validation result:
```bash
uv run python -m py_compile \
api/db/services/tenant_llm_service.py \
api/db/services/llm_service.py \
api/db/services/dialog_service.py \
api/db/services/conversation_service.py \
api/apps/restful_apis/chat_api.py \
test/unit_test/api/db/services/test_dialog_service_final_answer.py \
test/unit_test/api/db/services/test_dialog_service_use_sql_source_columns.py
```
Passed.
```bash
uv run pytest \
test/unit_test/api/db/services/test_dialog_service_final_answer.py \
test/unit_test/api/db/services/test_dialog_service_use_sql_source_columns.py -q
```
Result:
```text
11 passed in 16.89s
```
```bash
git diff --check
```
Passed.
## Checklist
- [x] Analyzed the issue requirement.
- [x] Checked existing Langfuse trace integration.
- [x] Implemented only the requested session grouping behavior.
- [x] Added/updated unit tests.
- [x] Ran focused tests successfully.
- [x] Ran Python compile validation.
- [x] Ran whitespace diff validation.
## Summary
`get_model_config_from_provider_instance()` was not including
`max_tokens` in its returned dict, causing all downstream consumers
(dialog truncation, message fitting, knowledge base trimming, embedding,
graphrag, RAPTOR) to fall back to the hardcoded default of **8192
tokens** regardless of the actual model context window size (e.g.,
GPT-4o 128K, Claude 200K).
Closes#15944
## Root Cause
The function builds `model_config` with only: `llm_factory`, `api_key`,
`llm_name`, `api_base`, `model_type`, `is_tools`. `max_tokens` is never
included.
Yet the data exists in four independent sources:
1. `TenantModel.extra` JSON field — written by
`provider_api_service.py:659`
2. `conf/llm_factories.json` — every model entry has `max_tokens`
3. `rag/llm/model_meta.py` — 9 provider classes fetch real context
windows from APIs
4. `TenantLLM.max_tokens` database column
None of them are read by this function.
## Fix
Two lines added, one per return path:
- **Path B** (model_obj exists → provider-instance model): reads
`max_tokens` from `model_obj.extra` JSON
- **Path C** (fallback → factory config): reads `max_tokens` from
`llm_info` (sourced from `llm_factories.json`)
Both fall back to 8192 when the value is absent, preserving backward
compatibility.
## Impact
This single 5-line change fixes the context window budget for all **78+
call sites** across **20 files** that construct `LLMBundle` or read
`max_tokens` from the config dict, including:
| Consumer | File | Effect |
|---|---|---|
| Dialog chat truncation | `dialog_service.py:562` |
`message_fit_in(msg, max_tokens * 0.95)` now uses real context window |
| Knowledge base trimming | `dialog_service.py:752` |
`kb_prompt(kbinfos, max_tokens)` now fits more retrieved content |
| Agent message fitting | `agent/component/llm.py:322` | Agent prompts
no longer truncated at 7946 tokens |
| Embedding truncation | `task_executor.py:704` | Embedding input uses
actual model limit |
| GraphRAG extraction | `graphrag/*/extractor.py` | Entity extraction
gets full context budget |
| LLM4Tenant.max_length | `tenant_llm_service.py:513` | Chat model
wrapper exposes real context window |
### What problem does this PR solve?
Fix: Remove the pagination from the search and retrieval pages.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## What problem does this PR solve?
Closes#15874
Both the `POST /api/v1/datasets/<dataset_id>/chunks` (re-parse) and
`DELETE /api/v1/datasets/<dataset_id>/chunks` (stop-parsing) handlers
called `settings.docStoreConn.delete` unconditionally. When the
tenant/dataset index has not been created yet — fresh dataset, first
parse interrupted before any chunks were indexed, or index manually
removed — the delete call throws and the handler returns HTTP 500
**after** the document state was already mutated (RUNNING with zeroed
counters for the parse path; CANCEL with zeroed counters for the stop
path), leaving the document in an inconsistent state.
The newer `parse_documents` path in `document_api.py` already uses
`index_exist` before deleting:
## How to fix?
Apply the same `index_exist` guard to both call sites in `chunk_api.py`:
- **`parse`** (POST path, line ~192): guard the delete before
`TaskService.filter_delete`.
- **`stop_parsing`** (DELETE path, line ~242): guard the delete after
`DocumentService.update_by_id`.
Both sites already have the correct `search.index_name(tenant_id)` and
`dataset_id` parameters; the guard is a one-line addition at each site.
## Type of change
- [x] Bug fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Wang Qi <wangq8@outlook.com>
Fixes#15529 .
### Problem
`async_ask()` accessed `kbs[0]` without verifying that
`KnowledgebaseService.get_by_ids()` returned any knowledge bases. Empty
or stale `kb_ids` raised `IndexError`, which surfaced as HTTP 500 on
search/bot SSE endpoints.
### Fix
- Add an early guard when `kbs` is empty, yielding a final SSE error
event (consistent with `gen_mindmap()` in the same module).
- Add regression tests for empty `kb_ids` and deleted/invalid KB IDs.
### Test plan
- [ ] `pytest
test/unit_test/api/db/services/test_dialog_service_final_answer.py -k
"async_ask_empty or async_ask_stale"`
- [ ] Manual: `POST /api/v1/searchbots/ask` with invalid `kb_ids`
returns SSE error, not HTTP 500
---------
Co-authored-by: Wang Qi <wangq8@outlook.com>
### What problem does this PR solve?
`POST /api/v1/datasets/{dataset_id}/documents/stop`
(`stop_parse_documents`) cancels parsing tasks and sets `run` to
`CANCEL`, but it does **not** remove chunks already indexed in the doc
store or reset `progress` / `chunk_num`. REST callers can end up with a
“cancelled” document that still returns partial chunks in `GET
.../chunks` and in retrieval.
Legacy `DELETE /api/v1/datasets/{dataset_id}/chunks` (`stop_parsing`)
already performs full cleanup: it resets counters and calls
`docStoreConn.delete`. This PR aligns the newer stop endpoint with that
behavior so both paths leave the dataset consistent.
Fixes [#15788](https://github.com/infiniflow/ragflow/issues/15788).
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [ ] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
### Changes
- Update `stop_parse_documents` in `document_api.py` to reset `progress`
and `chunk_num` to `0` and delete partial chunks via
`docStoreConn.delete` after `cancel_all_task_of`.
- Add unit test `test_stop_parse_documents_cleans_partial_chunks` to
assert counters reset and doc store delete is invoked.
### Test plan
- [x] Unit test: `pytest
test/testcases/test_http_api/test_file_management_within_dataset/test_doc_sdk_routes_unit.py::TestDocRoutesUnit::test_stop_parse_documents_cleans_partial_chunks
-v`
- [ ] Manual: upload a slow document, start parse, call `POST
.../documents/stop` while `RUNNING`, verify `GET .../chunks` returns
zero chunks and UI `chunk_count` is 0
- [ ] Control: legacy `DELETE .../chunks` behavior unchanged
---------
Co-authored-by: Wang Qi <wangq8@outlook.com>
