### What problem does this PR solve?
Closes#15379
Around 29 Go model providers in `internal/entity/models/` share an
`http.Client` configured with `Timeout: 120 * time.Second`, and reuse
that same client for `ChatStreamlyWithSender`. Go's
`http.Client.Timeout` is a hard ceiling on the whole request that also
covers reading the response body, so it behaves as a wall clock on
streaming. Any streamed chat response that lasts longer than 120 seconds
gets cut off in the middle with a timeout error. Long generations,
reasoning model outputs, and slow or overloaded upstreams are the common
victims.
The providers that already behave correctly (`groq`, `mistral`,
`voyage`, `anthropic`) set no client `Timeout` and instead wrap each
request in a `context.WithTimeout`. This change converges the affected
providers onto that same pattern.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Feature: #14961
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
Fix auto metadata type issue
https://github.com/infiniflow/ragflow/issues/15323
Type information is missing at frontend - backend correctly store the
type information for the auto metadata type.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: The newly added model did not appear in the drop-down menu.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: If the filename is too long, it overflows the confirmation box for
deleting the file.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Closes#15332.
RAGFlow can index Gmail and generic IMAP mailboxes but had no native
connector for Outlook / Microsoft 365 mail. Organisations on Microsoft
365 had no way to bring mailbox content into a knowledge base through
Microsoft Graph.
This PR adds a net-new Outlook data source that:
- Authenticates against Microsoft Graph with the same MSAL
client-credentials flow already used by the SharePoint and Teams
connectors (no new auth primitives).
- Pages over `/users/{id}/mailFolders/{folder}/messages/delta` per
mailbox and persists `@odata.deltaLink` values in
`OutlookCheckpoint.delta_links`, so incremental syncs only fetch changed
messages.
- Supports two scoping modes:
- **Tenant-wide** (default): enumerates every user in the tenant via
`/users` and syncs each mailbox. Requires `User.Read.All`.
- **Targeted**: when `user_ids` is provided (comma-separated UPNs or
object IDs), only those mailboxes are synced. `User.Read.All` is not
needed in this mode.
- Lets the caller pick the mail folder (`inbox`, `sentitems`, `archive`,
...). Defaults to `inbox`.
- Maps each message to a `Document` shaped after the Gmail connector:
one `TextSection` carrying `From/To/Cc/Subject` headers + body, with
HTML bodies stripped to text inline (no extra dependency).
- Surfaces typed errors on the validation probe:
401 → `ConnectorMissingCredentialError`, 403 →
`InsufficientPermissionsError` (with `Mail.Read` / `User.Read.All`
hint), 404 on a configured mailbox → `ConnectorValidationError`, 5xx →
`UnexpectedValidationError`.
- Skips messages flagged `@removed` by the delta semantics and messages
whose `receivedDateTime` is older than `poll_range_start`.
#### Files
| File | Change |
|------|--------|
| `common/data_source/outlook_connector.py` | **New** —
`OutlookConnector` (`CheckpointedConnectorWithPermSync` +
`SlimConnectorWithPermSync`) + `OutlookCheckpoint` + tiny `_strip_html`
helper. |
| `common/data_source/config.py` | `DocumentSource.OUTLOOK = "outlook"`.
|
| `common/constants.py` | `FileSource.OUTLOOK = "outlook"`. |
| `common/data_source/__init__.py` | Export `OutlookConnector`. |
| `rag/svr/sync_data_source.py` | `Outlook(SyncBase)` with `batch_size`
normalisation, CSV/list parsing of `user_ids`; registered in
`func_factory`. |
| `web/src/pages/user-setting/data-source/constant/index.tsx` |
`DataSourceKey.OUTLOOK`, visibility map (`syncDeletedFiles: true`), info
entry, form fields (tenant_id, client_id, client_secret, folder,
user_ids, batch_size), default values. |
| `web/src/locales/en.ts`, `web/src/locales/zh.ts` |
`outlookDescription` + 5 tooltip keys (EN + ZH). |
| `test/unit_test/data_source/test_outlook_connector_unit.py` | **New**
— 19 unit tests (`p1`/`p2`/`p3`) covering auth, validation (tenant-wide
vs specific user vs error paths), checkpoint helpers, user enumeration
pagination, message filtering, HTML body stripping. |
#### Required Azure AD permissions
- `Mail.Read` (Application, admin-granted) — always.
- `User.Read.All` (Application, admin-granted) — only when `user_ids` is
left blank so the connector can enumerate mailboxes.
#### Out of scope
- **Attachment indexing.** The current connector emits message body +
headers; binary attachments are flagged via `metadata.has_attachments`
but not pulled. Adding attachment hydration is straightforward but
scoped out per the issue's "decide whether attachments are indexed in
the first version" note.
- **Delegated (per-user) OAuth.** The connector uses app-only
credentials, consistent with the SharePoint / Teams precedent in this
codebase.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Closes#15330.
RAGFlow had no connector for OneDrive / OneDrive for Business. Users who
store working documents in OneDrive could not index them into a
knowledge base without manually downloading and re-uploading files.
This PR adds a net-new OneDrive data source that:
- Authenticates against Microsoft Graph with the same MSAL
client-credentials flow already used by the SharePoint and Teams
connectors (no new auth primitives).
- Enumerates every drive visible to the service principal and pages
through `/drives/{id}/root/delta`, persisting `@odata.deltaLink` values
per drive so subsequent syncs only fetch changed items.
- Optionally narrows ingestion to a sub-folder (`folder_path`) without
needing a separate code path.
- Surfaces typed errors on the validation probe (`GET /drives?$top=1`):
401 → `ConnectorMissingCredentialError`, 403 →
`InsufficientPermissionsError` (with a `Files.Read.All` hint), 5xx →
`UnexpectedValidationError`.
- Filters folders, soft-deleted items, and unsupported extensions (`.pdf
.docx .doc .xlsx .xls .pptx .ppt .txt .md .csv`).
#### Files
| File | Change |
|------|--------|
| `common/data_source/onedrive_connector.py` | **New** —
`OneDriveConnector` + `OneDriveCheckpoint`. |
| `common/data_source/config.py` | `DocumentSource.ONEDRIVE =
"onedrive"`. |
| `common/constants.py` | `FileSource.ONEDRIVE = "onedrive"`. |
| `common/data_source/__init__.py` | Export `OneDriveConnector`. |
| `rag/svr/sync_data_source.py` | `OneDrive(SyncBase)` with `batch_size`
normalisation; registered in `func_factory`. |
| `web/src/pages/user-setting/data-source/constant/index.tsx` |
`DataSourceKey.ONEDRIVE`, visibility map (`syncDeletedFiles: true`),
info entry, form fields (tenant_id, client_id, client_secret,
folder_path, batch_size), default values. |
| `web/src/locales/en.ts`, `web/src/locales/zh.ts` |
`onedriveDescription` + 4 tooltip keys (EN + ZH). |
| `test/unit_test/data_source/test_onedrive_connector_unit.py` | **New**
— 13 unit tests (`p1`/`p2`) covering auth, validation, checkpoint
helpers, and document filtering. |
#### Required Azure AD permission
`Files.Read.All` (Application, admin-granted).
#### Out of scope
- Interactive end-user OAuth (delegated permissions) — the connector
uses app-only credentials, consistent with the SharePoint / Teams
precedent.
- Binary download of file contents — the sync layer emits `Document`s
carrying `webUrl` + metadata; bytes are hydrated downstream by the parse
pipeline.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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?
Closes#15191.
RAGFlow shipped a Microsoft Teams connector stub
(`common/data_source/teams_connector.py`) whose document-loading methods
all returned `[]`, `Teams._generate()` was a `pass`, and Teams was
commented out of the data-source settings UI. As a result there was no
way to index Teams channel conversations into a knowledge base.
This PR implements the connector end to end on top of Microsoft Graph
(Office365-REST-Python-Client). It shares the MSAL client-credentials
auth shape with the SharePoint connector.
**Backend**
- `common/data_source/teams_connector.py`
- `load_credentials()` now builds the Graph client using an MSAL
client-credentials **token callback** — the form `GraphClient` actually
expects. (The previous stub passed a raw access-token string to
`GraphClient(...)`, which is not how that client is driven.) Token
acquisition is lazy, so credential loading performs no network call.
- `validate_connector_settings()` lists teams via Graph.
- `load_from_checkpoint()` is now a generator that pages teams →
channels → messages, flattens each top-level post together with its
replies into one blob-based `Document` (`extension` `.txt`/`.html`,
`blob`, `size_bytes`, `doc_updated_at`). Incremental syncs are bounded
by message `lastModifiedDateTime` (falling back to `createdDateTime`).
Per-message errors surface as `ConnectorFailure` instead of aborting the
run.
- `retrieve_all_slim_docs_perm_sync()` yields id-only `SlimDocument`
batches and the checkpoint helpers return proper `TeamsCheckpoint`s.
- ACL → `ExternalAccess` mapping is intentionally left best-effort
(`load_from_checkpoint_with_perm_sync` delegates to the standard load)
because the sync pipeline does not currently persist `ExternalAccess`.
- `rag/svr/sync_data_source.py`
- Implemented `Teams._generate()` using the existing
`CheckpointOutputWrapper` pattern (same shape as Confluence/Jira/Google
Drive), supporting full reindex and incremental polling from
`poll_range_start`.
- `TeamsConnector` is already exported from
`common/data_source/__init__.py`.
**Frontend (`web/`)**
- Enabled the `TEAMS` data-source enum and added its form fields
(`tenant_id`, `client_id`, `client_secret`), default values, display
metadata, and a Teams icon.
- Added `teamsDescription` / `teamsTenantIdTip` to `en.ts` and `zh.ts`.
**Tests**
- `test/unit_test/data_source/test_teams_connector_unit.py`: mock-based
unit tests covering credential loading (incomplete creds raise, happy
path sets the Graph client, fetch-without-creds raises), post/reply
flattening (incl. the HTML vs text extension), incremental
`lastModifiedDateTime` filtering, and slim-doc listing. All 6 pass;
`ruff check` is clean.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Closes#15187.
RAGFlow shipped a Slack connector
(`common/data_source/slack_connector.py`) but it was never usable:
`Slack._generate()` in the sync worker was a `pass` stub, the
connector's document-generating code was incompatible with the current
data model,
and Slack was commented out of the data-source settings UI. As a result,
teams had no way to index Slack channels/threads into a knowledge base.
This PR completes the connector end to end.
**Backend**
- `common/data_source/slack_connector.py`
- Rewrote `thread_to_doc` to produce a blob-based `Document`
(`extension`/`blob`/`size_bytes`). The previous implementation built the
doc with a `sections=[...]` argument and omitted the now-required
`blob`/`extension`/ `size_bytes` fields, so it raised a validation error
against the current `Document` model. Thread messages are now cleaned
and flattened into a single UTF-8 text blob.
- Added `load_from_state()` / `poll_source(start, end)` generators. The
connector's checkpoint interface is a no-op stub, so both full and
incremental syncs run through a single channel-iterating generator built
on the existing module helpers (`get_channels`, `filter_channels`,
`get_channel_messages`, `_process_message`), with per-channel thread
de-duplication.
- `rag/svr/sync_data_source.py`
- Implemented `Slack._generate()`. Credentials are loaded via
`StaticCredentialsProvider` (the connector requires `slack_bot_token`
and does not support `load_credentials`). Supports full reindex and
incremental polling from `poll_range_start`, plus the optional channel
filter. Modeled on the Confluence/Dropbox wrappers.
- `SlackConnector` was already exported from
`common/data_source/__init__.py`.
**Frontend (`web/`)**
- Enabled the `SLACK` data-source enum and added its form fields (Slack
bot token + optional channel filter), default values, display metadata,
and a Slack icon.
- Added `slackDescription` / `slackBotTokenTip` / `slackChannelsTip`
strings to `en.ts` and `zh.ts`.
**Tests**
- `test/unit_test/data_source/test_slack_connector_unit.py`: unit tests
covering credential loading (`load_credentials` raises,
`set_credentials_provider` initializes clients, missing credentials
raises) and document generation (standalone message + flattened thread,
blob/extension/size_bytes/metadata, and the incremental poll time
window). All 5 pass; `ruff check` is clean.
Required Slack scopes: `channels:read`, `channels:history`,
`users:read`.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Closes#15189.
RAGFlow shipped a SharePoint connector stub
(`common/data_source/sharepoint_connector.py`) whose document-loading
methods all returned `[]`, `SharePoint._generate()` was a `pass`, and
SharePoint was commented out of the data-source settings UI. As a result
there was no way to index files stored in SharePoint document libraries.
This PR implements the connector end to end on top of Microsoft Graph
(Office365-REST-Python-Client).
**Backend**
- `common/data_source/sharepoint_connector.py`
- `load_credentials()` now builds the Graph client using an MSAL
client-credentials **token callback** — the form `GraphClient` actually
expects. (The previous stub passed a raw access-token string to
`GraphClient(...)`, which is not how that client is driven.) Token
acquisition is lazy, so credential loading does no network call.
- `validate_connector_settings()` resolves the configured site via
Graph.
- `load_from_checkpoint()` is now a generator that enumerates every
document library under the site, walks folders depth-first, downloads
each file, and yields blob-based `Document` objects (`extension` /
`blob` / `size_bytes` / `doc_updated_at`). Incremental syncs are bounded
by file `lastModifiedDateTime`. Per-file errors are surfaced as
`ConnectorFailure` rather than aborting the run.
- `retrieve_all_slim_docs_perm_sync()` yields id-only `SlimDocument`
batches (no downloads) and the checkpoint helpers return proper
checkpoints.
- ACL → `ExternalAccess` mapping is intentionally left best-effort
(`load_from_checkpoint_with_perm_sync` delegates to the standard load)
because the sync pipeline does not currently persist `ExternalAccess`;
this can be extended once that plumbing exists.
- `rag/svr/sync_data_source.py`
- Implemented `SharePoint._generate()` using the existing
`CheckpointOutputWrapper` pattern (same shape as Confluence/Jira/Google
Drive), supporting full reindex and incremental polling from
`poll_range_start`.
- `SharePointConnector` is already exported from
`common/data_source/__init__.py`.
**Frontend (`web/`)**
- Enabled the `SHAREPOINT` data-source enum and added its form fields
`site_url`, `tenant_id`, `client_id`, `client_secret`), default values,
display metadata, and a SharePoint icon.
- Added `sharepointDescription` / `sharepointSiteUrlTip` to `en.ts` and
`zh.ts`.
**Tests**
- `test/unit_test/data_source/test_sharepoint_connector_unit.py`:
mock-based unit tests covering credential loading (incomplete creds
raise, happy path sets the Graph client, fetch-without-creds raises),
drive traversal + file download, incremental `lastModifiedDateTime`
filtering, and slim-doc listing. All 6 pass; `ruff check` is clean.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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)
### What problem does this PR solve?
Fix: The Creativity parameter of chat was not saved.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: Fixed metadata issue
- The dataset's built-in metadata is now active, but it appears to be
disabled in the individual file configuration.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: The prompt variable for the agent operator disappears after input.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Feat: Enable agent messages to display base64 images
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Fix: Replace the red highlight at the top of the PDF document with
yellow.
### 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>
Declare doc_id, filename, mime_type, and size as separate outputs on the
Document Generation component so downstream nodes (e.g., the Code
component) can consume them via the variable picker. The existing
download JSON blob is preserved unchanged for the Message component's
download-chip rendering.
### What problem does this PR solve?
The Document Generation component previously exposed only a single
`download` output —
a JSON-encoded blob containing the file's `doc_id`, `filename`,
`mime_type`, `size`,
and base64 payload. On top of that, the variable picker actively hides
this `download`
entry from every consumer except the Message component (because the
embedded base64 is
too heavy to splat into arbitrary downstream nodes).
The combined effect: users wiring the Doc Generator's output into a Code
component had
no way to retrieve basic file info such as `file_name` or `doc_id` from
the picker,
blocking workflows that need to post-process the generated file (e.g.,
registering it
elsewhere, custom delivery, follow-up API calls).
This PR declares `doc_id`, `filename`, `mime_type`, and `size` as
**discrete outputs**
on the Document Generation component, alongside the existing `download`
blob. The new
fields:
- Appear in the variable picker for **all** downstream nodes, including
the Code
component, so users can bind them directly to script arguments.
- Are cheap scalars only — no base64 payload leaks into other
components.
- Leave the existing `download` JSON blob completely untouched, so the
Message
component's download-chip rendering (which parses that blob via
`_is_download_info`)
keeps working with no behavior change.
Changes:
- `agent/component/docs_generator.py` — declare the four new outputs in
`DocGeneratorParam` and emit them via `set_output(...)` in `_invoke`.
- `web/src/pages/agent/constant/index.tsx` — extend
`initialDocGeneratorValues.outputs`
with the new keys.
- `web/src/pages/agent/form/doc-generator-form/index.tsx` — mirror the
new outputs in
the zod schema so the form is valid.
No changes needed to the picker's existing `download`-hiding filter — it
matches only
on the literal output name `download`, so the new metadata entries fall
through
naturally.
Reported in: https://github.com/infiniflow/ragflow/issues/14461.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
1. Fix /chat/completions to send only the latest message
2. Allo chat stream=False
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### 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 adds a new `Browser` operator to Agent workflows, enabling
prompt-driven browser automation in RAGFlow.Technically based
‘Browser-Use’
It includes:
- Backend browser component execution with tenant LLM integration
- Upload source support (file IDs, URLs, variables, CSV/JSON array)
- Downloaded file persistence to RAGFlow storage
- Frontend node/operator integration, form config, icon, and i18n
updates
- Unit tests for upload/download and ID parsing logic
- Dependency and Docker updates for browser-use runtime support
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Fix: The logs on the data source details page are not fully displayed.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Feat: add local & ssh provider in admin panel
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Fix: The folder tree menu for moving folders cannot be scrolled.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### 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?
1. expose batch_chunk_token_size for configuration
2. retrieve chunks when build subgraph for the doc, not retreive all
docs chunks at the begining
3. get all chunks for a document, used to be hard coded 10000
4. delete not used method run_graphrag
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
Follow on: #14617
### What problem does this PR solve?
LLM/chat and search UIs render Markdown in several places (document
preview, floating chat widget, next-search, etc.). Plugin lists and
behavior were duplicated or inconsistent, and single newlines in model
output were not always rendered as visible line breaks, which hurts
readability for chat-style content.
This PR centralizes shared **remark/rehype** configuration (including
**`remark-breaks`** for newline handling) and wires the main Markdown
surfaces to use it, so behavior is consistent and easier to maintain.
### Type of change
- [x] Refactoring
---------
Co-authored-by: Yingfeng Zhang <yingfeng.zhang@gmail.com>
Fixes#13975
## Problem
The GitHub data source connector had both `include_pull_requests` and
`include_issues` defaulting to `false` in both the frontend form and the
backend sync code. This meant that with the default configuration, **no
content was synced at all** from a GitHub repository — silently
producing zero results.
Additionally, the form field labels contained a typo: "Inlcude" instead
of "Include".
## Solution
- Changed `include_pull_requests` default from `false` to `true` in the
frontend form fields and default values
- Changed `include_issues` default from `false` to `true` in the
frontend form fields and default values
- Changed both backend defaults in `sync_data_source.py` from `False` to
`True`
- Fixed label typos: "Inlcude Pull Requests" → "Include Pull Requests"
and "Inlcude Issues" → "Include Issues"
This makes the GitHub connector consistent with the GitLab connector,
which already defaults `include_mrs`, `include_issues`, and
`include_code_files` all to `true`.
## Testing
- The connector now syncs both pull requests and issues by default when
a new GitHub data source is created
- Users who want to exclude PRs or issues can uncheck the corresponding
checkboxes in the form
Co-authored-by: octo-patch <octo-patch@github.com>
### 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>
### What problem does this PR solve?
This PR fixes two issues in Agent Retrieval behavior and configuration
UX:
1. `top_k` configured in Agent Retrieval was not passed down to the
backend retriever call, so retrieval could ignore the configured vector
recall limit.
2. Similarity weight slider semantics were confusing in Agent forms
because the Agent field stores `keywords_similarity_weight` while UI
interactions were interpreted as vector weight. This could cause
displayed values and actual behavior to diverge.
This PR ensures Agent retrieval uses configured `top_k`, and makes the
slider behavior consistent and explicit for both vector and keyword
weight modes.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## Problem
When a user uploads a file attachment in their first message (Q1) and
then sends a follow-up message (Q2) that triggers a backend response,
the uploaded file attachment disappears from Q1 in the chat UI.
Fixes#13959
## Root Cause
In `single-chat-box.tsx`, a `useEffect` hook syncs `derivedMessages`
from `conversation?.messages` whenever the conversation data changes
(e.g., after a new assistant reply arrives):
```typescript
useEffect(() => {
const messages = conversation?.messages;
if (Array.isArray(messages)) {
setDerivedMessages(messages); // ← overwrites local state
}
}, [conversation?.messages, setDerivedMessages]);
```
The problem is that `conversation.messages` comes from the server, which
stores messages as plain JSON. Browser `File` objects (uploaded by the
user) cannot be serialized to JSON, so they are never stored on the
server. Each time the server data is applied to local state, the `files`
array on the user's first message is lost.
## Fix
Instead of replacing the local messages wholesale, preserve any `files`
entries from the previous local state by ID before applying the server
data:
```typescript
useEffect(() => {
const messages = conversation?.messages;
if (Array.isArray(messages)) {
setDerivedMessages((prevMessages) => {
const filesMap = new Map(
prevMessages
.filter((m) => m.files?.length)
.map((m) => [m.id, m.files]),
);
if (filesMap.size === 0) {
return messages;
}
return messages.map((m) => ({
...m,
files: filesMap.get(m.id) ?? m.files,
}));
});
}
}, [conversation?.messages, setDerivedMessages]);
```
This is a minimal, targeted fix: when there are no local files to
preserve the behavior is identical to before (early return with plain
assignment). When local file objects exist they are re-attached to the
corresponding server messages by ID.
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Bug Fixes**
* Improved search query processing to properly handle special characters
and apostrophes in search terms and synonyms.
* Fixed chat message file attachments to persist when syncing with
server.
* **Refactor**
* Simplified OCR detection return values by removing timing metadata.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: ximi <octo-patch@github.com>
### What problem does this PR solve?
Feat: This enables SelectWithSearch to search by label.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Co-authored-by: balibabu <assassin_cike@163.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.`
Introduce comprehensive floating widget customization: add new widget
settings (title, subtitle, footer, colors, mute, streaming) with types
and defaults, and expose them via EmbedDialog UI (split into Embed Setup
and Widget Customization tabs). Persist and load settings through Agent
page by reading/writing globals and wiring an onSaveWidgetSettings
handler to setAgent; show a loading ButtonLoading for saving. Update
embed iframe query params and FloatingChatWidget to honor URL params
(colors, text, mute/streaming) with validation/normalization, color
darkening for gradients, footer link normalization, and improved
styling. Also add copy-to-clipboard in message toolbar, adjust syntax
highlighter layout and Copy button, and add i18n key for muteWidget.
### What problem does this PR solve?
Adds a few fields to the embed widget modal to customize the appearance
of the floating widget when embedded into a page.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Noah <Noah.Thompson@ecn.forces.gc.ca>
# 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"
/>
---------
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?
Fix: Set embedded models during form initialization.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
… modal
- Add vertical resizing functionality for the text field
### What problem does this PR solve?
_Fix the issue where the text content of the knowledge base editing
parsing block is too long to scroll._
<img width="701" height="775" alt="image"
src="https://github.com/user-attachments/assets/b258422e-fbc1-466d-abab-062e642c21d5"
/>
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Co-authored-by: chenyun <chenyun@chenyundemacbook-pro.local>
### What problem does this PR solve?
Feat: When a Wait Node precedes a Message Node within a Loop Node, the
outgoing message is split into two separate messages.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
