## Summary
Improve the UX of the **"Delimiter for text"** field on the dataset
configuration page. The field is a single string with a backtick-based
mini-syntax, but both the tooltip and the surrounding UI failed to
surface what delimiters the backend would actually derive from a given
value — leaving users to discover by trial-and-error that the same
string produces different splits depending on file type (see #7436,
#4704, #9680).
### Summary
This PR adds **aimlapi.com** as a model provider, so a RAGFlow user can
enter one API key in the model settings and use AIMLAPI's models across
the app. AIMLAPI ([aimlapi.com](https://aimlapi.com)) is an
OpenAI-compatible aggregator that serves 700+ models (LLM, embedding,
vision, TTS, ASR) from many providers behind a single API.
The change mirrors the repo's existing "add provider" pattern (e.g.
FuturMix / OpenRouter): provider logic lives in the same files those
providers use, and shared / UI files get only registration entries.
**Backend**
- `conf/llm_factories.json` — the `aimlapi.com` factory entry.
- `rag/llm/__init__.py`, `rag/llm/{chat,embedding,cv}_model.py` —
LiteLLM adapters (chat, embedding, image2text) with a production base
URL, overridable via `AIMLAPI_API_URL`.
- `rag/llm/model_meta.py` — an `AIMLAPI` model-meta so the provider
lists its full `/v1/models` catalog dynamically (classified by the
endpoint `type`), the same way OpenRouter does.
- `api/apps/restful_apis/aimlapi_api.py` — an optional "Get API key"
flow using AIMLAPI's agent-authorization (OAuth 2.0 Device Authorization
Grant, RFC 8628). The device code is kept server-side (Redis); only the
issued key reaches the browser.
**Frontend (`web/`)**
- Provider registration (constant, icon allowlist, brand logo), the
model picker (`LIST_MODEL_PROVIDERS` + a `buildLocalConfig` entry), and
the "Get API key" button in the provider dialog. Locales added to `en`
and `zh`.
**Configuration** — production defaults are compiled in; endpoints and
the partner id are overridable through `AIMLAPI_*` environment
variables, so the same build works across environments.
**Testing** — the `web` build passes; chat, embedding and dynamic model
listing were smoke-tested against the live API.
Follow-up to #16468.
PR #16468 fixed the Python
(`api/db/joint_services/tenant_model_service.py
split_model_name`) and Go (`internal/service/model_service.go
parseModelName`)
parsers to right-anchor the '@'-split on the composite
"model_name@instance@provider" key, but the matching helper in the
front-end
(`web/src/utils/llm-util.ts parseModelValue`) was missed.
parseModelValue used `split('@')` (anchored on the first '@'), which
silently
mangles composite keys whose model_name itself contains '@' (e.g. LM
Studio
embedding IDs like `text-embedding-nomic-embed-text-v1.5@q8_0`):
text-embedding-nomic-embed-text-v1.5@q8_0@lmstudio@LM-Studio
became
model_name: text-embedding-nomic-embed-text-v1.5
model_instance: q8_0@lmstudio
model_provider: LM-Studio
`PATCH /api/v1/models/default` then sent those to the server, which
returned
HTTP 200 with body `{"code": 102, "message": "Instance 'q8_0@lmstudio'
not
found for provider 'LM-Studio'"}`. The UI swallowed the body-level error
code, so the failure was silent: no toast, the Embedding field stayed
empty.
This change makes parseModelValue do a right-anchored split that mirrors
the
Python `split_model_name` `rsplit('@', 2)` exactly:
- 3-part form: model_name@instance@provider -> same three fields.
- 2-part form: model_name@provider -> model_instance defaults to
"default"
(matching Python).
- 4+-part form (embedded '@' in model name): last two fields are
anchored
as instance and provider, everything to the left is the bare model name.
`parseModelUuid` is updated to the same right-anchored split so the
factoryId portion of `model_name@factory_id[#instance]` keeps the last
'@'
as the separator even when the model name itself contains '@'.
Adds jest cases under `web/src/utils/tests/llm-util.test.ts` (12 total)
covering the plain 3-part, 2-part, 4-part, multi-'@' name,
buildModelValue
round-trip and parseModelUuid variants.
Note for reviewers: the front-end is bundled into the published docker
image, so a release containing this fix will need `docker compose build
--no-cache ragflow-cpu` (or equivalent) for it to be visible to end
users.
Refs #16468, #16467
Both backends serve GET /api/v1/language. Frontend calls it once and
caches. By this way, front end can know the backend is go or python and
thus can determine which part of logic to load.
---------
Co-authored-by: Claude <noreply@anthropic.com>
## Summary
Fixes#14985 — clicking the **Thinking** button in a shared/embedded
chat returns 401 and bounces the user to the login page, even though
the same share page can chat with the agent just fine.
## Root cause
In shared chat, `useGetSharedChatSearchParams` binds `conversationId`
to the URL's `shared_id` query param — which is the **beta APIToken**,
not the real agent id. That `conversationId` propagates through the
component tree:
```tsx
<WorkFlowTimeline canvasId={conversationId}>
→ useFetchMessageTrace(canvasId)
→ GET /api/v1/agents/<sharedId>/logs/<messageId>
```
But `/agents/<agent_id>/logs/<message_id>` is decorated with
`@login_required` (`api/apps/restful_apis/agent_api.py:842-846`).
The share page only holds the beta token — there is no session JWT
— so the request 401s and quart-auth redirects to the login page.
The reporter's server log matches exactly:
```
load_user from jwt got exception No b'.' found in value
load_user: No APIToken found for token=ULG10SWG3E...
Unauthorized request (quart_auth)
GET /api/v1/agents/394013f8d42211f0bad6123fa55e8ed9/logs/96fd72e2-... 1.1 401
```
The `394013f8...` segment in the URL is the `shared_id` (beta
token), not an actual agent id. `_load_user` already accepts the
regular `APIToken.token` field, but not `APIToken.beta`, by design
— beta is a much weaker share-link credential than a personal API
key.
The sibling endpoints `/agentbots/<id>/completions` and
`/agentbots/<id>/inputs` already use the right auth pattern for
this scope (beta-token via `_get_sdk_authorization_token` →
`APIToken.query(beta=token)`). Trace just didn't have a parallel.
## Fix
### Backend (`api/apps/restful_apis/bot_api.py`)
Added a beta-token sibling endpoint:
```
GET /api/v1/agentbots/<shared_id>/logs/<message_id>
```
- Same auth shape as the existing `agentbots` endpoints.
- The `<shared_id>` path segment is a client-supplied label only.
The real `agent_id` used to build the Redis key
(`<agent_id>-<message_id>-logs`) is taken from
`APIToken.dialog_id` on the looked-up token, so the endpoint
never trusts client-supplied identifiers for the data lookup.
- Returns the same `{data: ...}` shape as the existing
`/agents/<id>/logs/<message_id>` endpoint, so the frontend
doesn't need to reshape the response.
### Frontend
- `web/src/utils/api.ts`: added `sharedTrace(sharedId, messageId)`
URL builder.
- `web/src/services/agent-service.ts`: added
`fetchSharedTrace({ shared_id, message_id })`.
- `web/src/hooks/use-agent-request.ts`: `useFetchMessageTrace`
takes an optional `isShare` argument. When set, it calls
`fetchSharedTrace`; `isShare` is also folded into the
`queryKey` so the two modes never share cached results.
- `web/src/pages/agent/log-sheet/workflow-timeline.tsx`:
forwards the already-existing `isShare` prop into the hook.
All other existing call sites of `useFetchMessageTrace` (webhook
timeline, pipeline log, dataflow result) pass no `isShare`
argument → undefined → falsy → unchanged behavior.
## Test plan
- [ ] In the regular Agent UI (logged-in user): open the trace /
log sheet for any message and click into "Thinking" — the
timeline should still load via `/agents/<id>/logs/<msg>`,
same as before.
- [ ] From the Agent page, click **Chat in new tab** to open
`/chat/share?shared_id=<token>&from=agent`. Send a message,
wait for a response, then click **Thinking** on the
assistant turn. The trace panel should load instead of
redirecting to the login page.
- [ ] Same flow but with the agent embedded in an iframe ("Embed
into webpage") — confirm there is no login redirect.
- [ ] In DevTools → Network, confirm the share-chat trace request
goes to `/api/v1/agentbots/<sharedId>/logs/<msgId>` and
returns 200 with the same JSON shape as the logged-in path.
- [ ] Confirm the chat completions, inputs, and upload flows in
the share page still work — they were not touched.
- [ ] Send a bogus / expired beta token to the new endpoint and
confirm it returns the standard "Authentication error: API
key is invalid!" response (no traceback, no 500).
- [ ] Run `uv run pytest` to make sure no existing tests regress.
### 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):
---------
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
### What problem does this PR solve?
This PR follows up on
[#15863](https://github.com/infiniflow/ragflow/pull/15863) (Korean i18n)
with translation refinements and i18n coverage for hardcoded strings
found in the UI.
- Refine awkward Korean phrasing (e.g. 'Chunk 만들기' → 'Chunk 생성', '유형' →
'타입', etc.)
- Apply i18n to hardcoded strings in `message-item`,
`next-message-item`, `multi-select`, `chat-prompt-engine`, and various
filter hooks
- Rename `use-selelct-filters.ts` → `use-select-filters.ts` (typo fix)
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Replaces the Python agent canvas runtime with a Go implementation that
runs inside `cmd/server_main`.
The canvas compiles into an eino Workflow that pauses on wait-for-user
via native Interrupt/Resume (no sentinel flag) and resumes from a
Redis-backed CheckPointStore.
All 21 Python agent components and ~35 tools are ported with functional
parity.
Sandbox providers now read their JSON config from the admin-panel
system_settings table with env fallback.
234 files / +35,413 / -6,111. All Go files are gofmt-clean (CI gate
added); drops the v2 DSL E2E step and the gap-analysis plan (both
redundant after the port ships).
## Type of change
- [x] Refactoring
- [x] New feature
- [x] Bug fix
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude <noreply@anthropic.com>
### 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?
feat：Unify the 'Add Model Provider' modal
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
Fix: Model provider add verify and fixed form in modal not resetting
issue
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Python implementation of the Go-based model_provider API suite.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: bill <yibie_jingnian@163.com>
### What problem does this PR solve?
Fix: Uploading TSV format documents to the knowledge base did not
generate any error messages.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Follow on PR #15146 to reslove the backwad compatability issue.
1. /agents/<attachment_id>/download ->
/agents/attachments/<attachment_id>/download
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
This PR improves the table upload flow for CSV/Excel files by allowing
table column role configuration at upload time.
Previously, users had to:
1. Upload and parse a table file.
2. Open parser settings and manually set table column roles.
3. Re-parse the file for the roles to take effect.
This was inefficient and required an unnecessary second parse.
With this change:
1. When the knowledge base uses table parsing, the upload dialog
extracts CSV/Excel headers client-side.
2. Users can choose Auto mode or Manual mode.
3. In Manual mode, users can assign per-column roles before upload.
4. The selected parser config is sent with the upload request and
applied server-side during document creation.
Result: configured table column roles are applied from the first parse.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Co-authored-by: Ahmad Intisar <ahmadintisar@Ahmads-MacBook-M4-Pro.local>
### What problem does this PR solve?
move agent attachment download api to the correct route and update
frontend callers
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Notes
- Move the attachment download endpoint from document routes to agent
routes.
- Update frontend download callers to use the agent attachment endpoint.
- Reuse the shared file response header helper instead of duplicating it
in `agent_api.py`.
### What problem does this PR solve?
This PR improves the connector dashboard task management experience and
adds better visibility into connector execution logs.
### Overview:
#### Before
<img width="700" alt="image"
src="https://github.com/user-attachments/assets/e4a8ed6f-2e18-4f0f-8528-41a514550052"
/>
#### Now:
<img width="700" alt="Screenshot from 2026-05-18 16-31-30"
src="https://github.com/user-attachments/assets/d4ca193b-847a-49ae-9e4f-5fbca60ea627"
/>
### 1. Add a new logging page to the connector dashboard
A new logging page has been added so users can view connector task
execution logs directly from the connector dashboard.
### 2. Merge the Resume button into Confirm
The separate **Resume** button has been removed. The **Confirm** button
now represents different actions depending on the current task state:
- **Save**: Save form changes and reschedule tasks.
- **Stop**: Cancel currently scheduled or running tasks.
- **Resume**: Create new scheduled tasks after the previous tasks have
been stopped.
- **Start**: Start tasks when no task has been started yet.
### 3. Separate syncing and pruning tasks
Connector tasks are now separated into **syncing** and **pruning**.
Pruning is controlled by the **Sync deleted files** option:
- When **Sync deleted files** is disabled, only syncing tasks are shown.
- When **Sync deleted files** is enabled, both syncing and pruning tasks
are shown.
**Now: Sync deleted files disabled**
<img width="700" alt="Sync deleted files disabled"
src="https://github.com/user-attachments/assets/dbd9232e-614a-407f-a0b1-c109e5fa567d"
/>
**Now: Sync deleted files enabled**
<img width="700" alt="Sync deleted files enabled"
src="https://github.com/user-attachments/assets/1f527f48-ccb3-4ee8-97ca-086891489296"
/>
### 4. Update logs in backend
<img width="700" alt="image"
src="https://github.com/user-attachments/assets/10a95a3f-98c1-4e67-8afa-ddf6cda5b0b2"
/>
### 5. Remove connector resume API
- Removed: `POST /v1/connectors/<connector_id>/resume`
- Replaced by: `PATCH /v1/connectors/<connector_id>`
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
```
RAGFlow(user)> ocr with 'hunyuanocr@test@gitee' file './picture.png'
+----------------------------------------------------------+
| text |
+----------------------------------------------------------+
| 生活不是等待风暴过去，而是学会在雨中翩翩起舞。
——佚名 |
+----------------------------------------------------------+
RAGFlow(user)> list 'test@gitee' tasks;
+---------+----------------------------------+
| status | task_id |
+---------+----------------------------------+
| success | C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5 |
+---------+----------------------------------+
RAGFlow(user)> show 'test@gitee' task 'C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5';
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
| content | index |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
| # PDF 1: Purpose of RAGFlow
RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine designed to turn raw documents into reliable context for large language models.Its purpose is to make it practical to build an Al assistant that can ans... | 1 |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
## Summary
Closes#14774.
Adds free-form tags on agents (UserCanvas) with full UI + API:
- Stored as comma-separated `tags` column on `UserCanvas` with online
migration.
- New endpoints: `GET /v1/agents/tags` (aggregate counts) and `PUT
/v1/agent/<id>/tags` (write). `GET /v1/agents` accepts a `tags=` query.
- "Edit tags" item in agent dropdown opens a chip-style editor dialog;
tags render as badges on each agent card.
- New "Tags" facet in the agents filter bar, with counts.
## Implementation notes
- **Tag matching is exact-token**: the SQL filter wraps stored tags as
`,…,` and matches `,ml,` so `ml` doesn't match `ml-ops`.
- **Server-side normalization** in `UserCanvasService.update_tags`:
dedup (case-insensitive), per-tag cap of 64 chars, total length capped
at 512 chars to fit the column, commas inside tag values are replaced
with spaces.
- **Tenant authorization**: `PUT /v1/agent/<id>/tags` gates on
`UserCanvasService.accessible(canvas_id, tenant_id)`.
- **Tag listing scope**: `UserCanvasService.list_tags` follows the same
own + team-shared rule as `get_by_tenant_ids`.
- **i18n**: keys added to `en.ts` and `zh.ts` only (per project
convention; other locales fall back).
- **`HomeCard`** gets a non-breaking `extra?: ReactNode` slot for the
chip row; no `src/components/ui/` files modified.
## Test plan
- [ ] Backend boot runs `migrate_db` → confirm `user_canvas.tags` column
exists (`DESCRIBE user_canvas`).
- [ ] Agents page renders cards normally (no console error from missing
field).
- [ ] `⋯ → Edit tags` opens a dialog that stays open (regression: dialog
was unmounting with the dropdown).
- [ ] Typing a tag without pressing Enter and clicking Save persists it
(regression: last typed tag was being dropped).
- [ ] Chip input supports Enter/comma to commit, Backspace on empty to
remove, `×` to remove individual chip.
- [ ] Tag containing a comma sent via API is stored with the comma
replaced by a space.
- [ ] 20 long tags sent via API does not error (length cap silently
truncates).
- [ ] "Tags" filter in the filter bar shows counts and narrows the list.
- [ ] Filtering by `ml` does **not** return agents tagged `ml-ops`.
- [ ] UI in Chinese shows 编辑标签 / 添加标签以整理和筛选你的智能体 etc.
- [ ] `PUT /v1/agent/<other-tenant-id>/tags` returns `Agent not found or
no permission.`
# feat: Add Generic REST API Connector
## What problem does this PR solve?
RAGFlow supports many specific data source connectors (MySQL, Slack,
Google Drive, etc.), but there was no way to connect an arbitrary REST
API as a data source. Users with custom or third-party APIs had to write
a new connector class for each one.
This PR adds a **generic, configuration-driven REST API connector** that
lets users connect any REST API as a data source entirely through the UI
— no code changes needed per API.
---
## Features
### Core Connector (`common/data_source/rest_api_connector.py`)
- Implements `LoadConnector` and `PollConnector` interfaces for full and
incremental sync
- **Configurable authentication:** None, API Key (custom header), Bearer
Token, Basic Auth
- **Pluggable pagination:** Page-based, Offset-based, Cursor-based, or
None
- Smart page-size inference from user's query parameters to avoid
duplicate/conflicting params
- Configurable request delay between pages to prevent API rate limiting
- Auto-detection of the items array in JSON responses (`items`,
`results`, `data`, `records`, or first list found)
- **Advanced field mapping** with dot-notation (`country.name`), array
wildcards (`newsType[*].name`), type hints, and default values
- Optional content template rendering (`"Title: {title}\nBody: {body}"`)
- HTML stripping for content fields
- Stable document IDs via `hash128` from a configurable ID field or
auto-generated from item content
- Pydantic configuration schema with automatic coercion of UI string
inputs to dicts/lists
### Backend Registration (`rag/svr/sync_data_source.py`,
`common/constants.py`, `common/data_source/config.py`)
- `REST_API` sync class wired into RAGFlow's `func_factory`
- Full sync (`load_from_state`) and incremental polling (`poll_source`)
support
- Credentials and config passed from task to connector following
existing patterns (MySQL, SeaFile, etc.)
### Test Connection Endpoint (`api/apps/connector_app.py`)
- `POST /v1/connector/<id>/test` validates config schema,
authentication, and API connectivity without triggering a sync
- Clear error messages for auth failures vs. config issues
### Frontend UI (`web/src/pages/user-setting/data-source/constant/`)
- **Postman-style configuration:** Base URL, Query Parameters (key=value
per line), Auth, Content Fields, Metadata Fields, Pagination Type
- Auth-type-aware form: fields for API key header/value, Bearer token,
or Basic username/password appear only when relevant
- **Advanced Settings** toggle for: Custom Headers, Max Pages, Request
Delay, Poll Timestamp Field, Request Body (POST)
- Connector icon (SVG) and i18n strings (English)
- **"Test Connection"** button to validate before syncing
---
## Controls & Safety
- Configurable max pages safety cap (default: 1000, adjustable in UI)
- Configurable request delay between pages (default: 0.5s, adjustable in
UI)
- Auth errors (401/403) fail immediately without retries; transient
errors retry with exponential backoff
- Diagnostic logging: auth setup confirmation, request details on
failure, content field extraction status
---
## Type of change
- [x] New Feature (non-breaking change which adds functionality)
##Visual Screenshots of Features
<img width="482" height="510" alt="Screenshot 2026-03-11 at 5 19 52 PM"
src="https://github.com/user-attachments/assets/dcb7ab4a-1622-44f3-bb02-d6f0527314c4"
/>
(Connector can be configured within the external data sources tab)
Configuration Parameters:
<img width="661" height="682" alt="Screenshot 2026-03-11 at 5 20 46 PM"
src="https://github.com/user-attachments/assets/5e154e71-4ab5-4872-bfb2-04f02b73c18a"
/>
<img width="661" height="682" alt="Screenshot 2026-03-11 at 5 20 54 PM"
src="https://github.com/user-attachments/assets/00cb14b7-0bcf-4b94-9d71-34e93369ecb2"
/>
Connection can be tested before attaching to dataset:
<img width="981" height="681" alt="Screenshot 2026-03-11 at 5 21 40 PM"
src="https://github.com/user-attachments/assets/aaa6eeeb-89a7-4349-bc34-2423bf8be9ee"
/>
Ingestion tested with API connector (works perfectly fine):
<img width="1062" height="705" alt="Screenshot 2026-03-11 at 5 22 30 PM"
src="https://github.com/user-attachments/assets/afcd0d58-cadd-4152-badc-d2f14d96fbec"
/>
Search & Retrieval works as well with metadata flow:
<img width="1062" height="705" alt="Screenshot 2026-03-11 at 5 23 05 PM"
src="https://github.com/user-attachments/assets/d41ee935-dcf7-4456-b317-22a76ca032c0"
/>
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Co-authored-by: Ahmad Intisar <ahmadintisar@Ahmads-MacBook-M4-Pro.local>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
### What problem does this PR solve?
## Problem
During the REST API refactoring (#13690), the
`/api/v2/kb/check_embedding` endpoint was removed and never migrated to
the new RESTful structure. The frontend was pointed to the
`/api/v1/datasets/{id}/embedding` endpoint (which is `run_embedding` — a
completely different function). Additionally, a hard guard was
introduced that rejects any `embd_id` change when `chunk_num > 0`,
making it impossible to switch embedding models on datasets with
existing chunks.
## Root Cause
1. **Missing endpoint**: The old `check_embedding` logic (sample random
chunks, re-embed with the new model, compare cosine similarity) was not
carried over to the new REST API service layer.
2. **Wrong frontend URL**: `checkEmbedding` in `api.ts` pointed to
`/datasets/{id}/embedding` (`run_embedding`) instead of a dedicated
check endpoint.
3. **Overly restrictive guard**: `dataset_api_service.py` line 310
blocked all `embd_id` updates when `chunk_num > 0`. This check did not
exist in the pre-refactor code — it was incorrectly introduced during
the refactor.
## Changes
### Backend
- **`api/apps/services/dataset_api_service.py`**
- Remove the `chunk_num > 0` hard guard on `embd_id` updates
- Add `check_embedding()` service function: samples random chunks,
re-embeds them with the candidate model, computes cosine similarity,
returns compatibility result (avg ≥ 0.9 = compatible)
- Add `import re` for the `_clean()` helper
- **`api/apps/restful_apis/dataset_api.py`**
- Add `POST /datasets/<dataset_id>/embedding/check` endpoint following
the new REST API conventions
- Clean up unused top-level imports (`random`, `re`, `numpy`)
### Frontend
- **`web/src/utils/api.ts`**
- Fix `checkEmbedding` URL from `/datasets/${datasetId}/embedding` →
`/datasets/${datasetId}/embedding/check`
### Tests
-
**`test/testcases/test_http_api/test_dataset_management/test_update_dataset.py`**
- Update `test_embedding_model_with_existing_chunks` to assert success
(`code == 0`) instead of expecting the old `102` error
-
**`test/testcases/test_web_api/test_dataset_management/test_dataset_sdk_routes_unit.py`**
- Update `test_update_route_branch_matrix_unit` to assert
`RetCode.SUCCESS` when updating `embd_id` on a chunked dataset,
replacing the old `chunk_num` error assertion
### 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?
Refactor : Allow search multiple datasets
1. support /datasets/search
2. get rid of /graph/search, use /graph
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
## Summary
- **Collapsible thinking**: Replace `<section>` with `<details>` for
`<think>` content, so model thinking output is collapsed by default
(click to expand). Works for all models that output `<think>` tags
(Qwen3, DeepSeek, Gemini, Claude, etc.).
- **Fix double thinking tags**: When reasoning/deep research mode is
enabled in knowledge base chat, both the retrieval progress and model
thinking were wrapped in `<think>` tags, producing two "Thinking..."
blocks. Now retrieval progress uses a dedicated `<retrieving>` tag
rendered as a separate "Retrieving..." collapsible with a distinct green
accent.
### Before
- Thinking content displayed as flat gray-bordered `<section>`,
occupying significant screen space
- Deep research + model thinking both use `<think>` → two identical
"Thinking..." blocks
### After
- Thinking content collapsed by default in a `<details>` element, click
"Thinking..." to expand
- Deep research shows "Retrieving..." (green border), model thinking
shows "Thinking..." (gray border)
## Changes
**Backend (`api/db/services/dialog_service.py`)**
- Deep research callback: replace `start_to_think`/`end_to_think` marker
flags with direct `<retrieving>`/`</retrieving>` answer text
**Frontend**
- `web/src/utils/chat.ts`: `replaceThinkToSection()` now uses
`<details>` instead of `<section>`; add new
`replaceRetrievingToSection()`
- 4 tsx files: import and pipe `replaceRetrievingToSection`, whitelist
`details`, `summary`, `retrieving` in DOMPurify `ADD_TAGS`
- 4 less files: `section.think` → `details.think` with `<summary>`
styles; add `details.retrieving` with green accent; dark mode and RTL
variants
## Test plan
- [ ] Open a chat WITHOUT knowledge base, ask a question to a model with
thinking (e.g. Qwen3) → thinking content should be collapsed by default,
click "Thinking..." to expand
- [ ] Open a chat WITH knowledge base and reasoning enabled, ask a
question → "Retrieving..." (green) shows retrieval progress,
"Thinking..." (gray) shows model thinking, each independently
collapsible
- [ ] Verify dark mode renders correctly for both collapsible blocks
- [ ] Verify RTL layout renders correctly
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: wanghualoong <wanghualoong@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
