### What problem does this PR solve?
Fixes the OpenSearch side of #10747: hybrid search drops the keyword
(BM25) leg and
ends up doing plain vector search.
When a search has both a text and a vector leg, `OSConnection.search()`
throws the text
query away:
del q["query"]
q["query"] = {"knn": knn_query}
The text clause only stays on as a filter inside the knn query, so it
narrows the
candidate set but doesn't count towards scoring. So hybrid search on
OpenSearch behaves
like plain vector search, unlike the Elasticsearch backend.
What I changed:
- when both legs are present, send a real hybrid query
`{"hybrid": {"queries": [bm25, {"knn": ...}]}}` and let a
normalization-processor
search pipeline score and combine the two legs
- only the actual filters (kb_id, available_int, ...) go in the knn
filter, not the
text must clause
- create the pipeline on startup if it's missing, so there's no separate
provisioning
step. name and weights can be set under `os:` in service_conf.yaml, or
via
`OS_HYBRID_PIPELINE`; defaults are `ragflow_hybrid_pipeline` and `[0.5,
0.5]`
- normalization-processor needs OpenSearch 2.10+. on older clusters, or
when the
pipeline can't be created, log a warning and fall back to vector-only
instead of
pointing at a pipeline that doesn't exist
This is only the hybrid-search fix; `create_doc_meta_idx` is already on
main.
Testing (there's no OpenSearch path in CI): added a unit test
(`test/unit_test/rag/utils/test_opensearch_hybrid_search.py`, no
services needed) that
checks the query built in each case — hybrid + pipeline param for
text+vector, plain knn
for vector-only, plain bool for text-only, the knn filter never carrying
the text
query_string, and the vector-only fallback when the pipeline isn't
available. Also ran
it against a real OpenSearch 2.19.1 container with a doc that matches
the keyword but
sits outside the knn top-k: pure knn returns `['D1','D2','D5']` (keyword
doc missing),
the hybrid query returns `['A','D1','D2','D5']` (keyword doc present).
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Signed-off-by: Danut Matei <matei.danut.dm@gmail.com>
## What problem does this PR solve?
Implements `POST /api/v1/searchbots/retrieval_test` in the Go API
server, aligning with the Python `bot_api.py` counterpart. Also applies
security hardening and consistency fixes discovered during CTO-level
code review:
- **Missing endpoint**: `retrieval_test` was not available in Go,
requiring Python fallback
- **Security**: Both `chunkHandler` and `searchBotHandler` leaked
`err.Error()` to API consumers
- **Python alignment**: Default values, empty question handling, and
`top_k <= 0` validation differed from Python behavior
- **Test gaps**: `chunkHandler.RetrievalTest` had zero unit tests;
several edge cases uncovered
## Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
## Summary
### New Endpoint
- `POST /api/v1/searchbots/retrieval_test` — retrieval test with full
field support (page, size, top_k, use_kg, cross_languages, keyword,
similarity_threshold, vector_similarity_weight)
### New Type
- `common.StringSlice` — JSON type that accepts both `"kb1"` and
`["kb1", "kb2"]`, matching Python API flexibility
### Security
- Both `searchBotHandler` and `chunkHandler` now use `common.Warn()` +
generic error messages instead of leaking `err.Error()` to API consumers
- All error responses include consistent `"data": nil` shape
- `chunkHandler.RetrievalTest` uses interface-based DI (`chunkService`)
to enable testability
### Python Alignment
- Handler-level defaults align with Python `bot_api.py` (page=1,
size=30, top_k=1024, similarity_threshold=0.0,
vector_similarity_weight=0.3)
- `top_k <= 0` validation matching Python behavior
- Empty/whitespace question returns 200 + empty result (matches
`chunk_api.py`)
- `chunkHandler` `Datasets` field uses `common.StringSlice` for
string-or-array flexibility
### Refactoring
- `ChunkServiceIface` → `ChunkRetriever`, `chunkSvcIface` →
`chunkService` (Go-conventional naming)
- Extracted `applyRetrievalDefaults`, `toRetrievalServiceRequest` from
handler body
- Regex moved to package-level var in `parseRelatedQuestions`
- `service.RetrievalTestRequest.Datasets` type changed to
`common.StringSlice`
- `chunkHandler` now uses consumer-side interface for DI
### Tests
- 37 unit tests across both handlers: auth, validation, defaults,
StringSlice edge cases, empty/whitespace KbID, service errors, JSON
format, `top_k <= 0`, field mapping verification
## Files Changed
| File | Change |
|------|--------|
| `cmd/server_main.go` | Wire new handler + chunkService +
difyRetrievalHandler |
| `internal/common/json_types.go` | New StringSlice type |
| `internal/common/json_types_test.go` | StringSlice tests |
| `internal/handler/chunk.go` | Interface-based DI, security, Python
alignment, defaults |
| `internal/handler/chunk_test.go` | New — 9 comprehensive tests |
| `internal/handler/searchbot.go` | New endpoint + refactoring + `top_k
<= 0` validation |
| `internal/handler/searchbot_test.go` | 18 tests covering all edge
cases |
| `internal/router/router.go` | Register new route +
difyRetrievalHandler |
| `internal/service/chunk.go` | Datasets type → StringSlice, Question
binding relaxed |
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
### What problem does this PR solve?
Fix: The embedded website floating component on the agent page does not
display citations.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Normalize agent session chunk references so they are mapped through a
dedicated helper instead of duplicating the field extraction inline.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: The time zone is not displayed on the personal profile page.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Closes#15611.
RAGFlow's fallback reasoning parser only recognized the exact model
family `qwen3`. For provider-prefixed Qwen model names such as
SiliconFlow's `qwen/qwen3-8b`, the derived model class can be
`qwen/qwen3`, so inline `<think>...</think>` content was not split from
the visible answer when `reasoning_content` was absent.
This PR normalizes model-family detection before fallback reasoning
extraction, keeps the parser nil-safe, and adds focused tests for Qwen3
variants plus Gitee and SiliconFlow chat responses.
It also makes SiliconFlow propagate `ChatConfig.Thinking` into the chat
request body, matching the existing Gitee behavior, so Qwen thinking
mode is actually enabled when requested.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
### Validation
- `/root/go/bin/gofmt -l internal/entity/models/common.go
internal/entity/models/common_test.go
internal/entity/models/reasoning_family_provider_test.go
internal/entity/models/siliconflow.go`
- `git diff --check`
- `/root/go/bin/go test ./internal/entity/models -run
'Test(NormalizeModelFamily|GetThinkingAndAnswer|GiteeChatExtractsQwenThinkingFromInlineContent|SiliconflowChatExtractsProviderPrefixedQwenThinkingFromInlineContent)'
-vet=off -count=1`
Note: the full package command `/root/go/bin/go test
./internal/entity/models -vet=off -count=1` now runs locally, but it
currently fails on an unrelated existing
`TestAstraflowEmbedReturnsNoSuchMethod` panic in
`internal/entity/models/astraflow.go:482`.
### What problem does this PR solve?
Closes#15428
The hybrid score in `rag/nlp/search.py` (`rerank_by_model`) blends
reranker similarity with token similarity on a fixed `[0, 1]` scale:
```python
return tkweight * np.array(tksim) + vtweight * vtsim + rank_fea # tkweight=0.3, vtweight=0.7
```
The reranker implementations did not agree on that scale. Only three of
roughly 17 providers normalized their output, and `NvidiaRerank`
returned raw, unbounded logits. Weighted at `0.7`, a negative logit
could push a genuinely relevant chunk below pure keyword matches, and
its magnitude swamped `tksim`, which lives in `[0, 1]`. The practical
effect was that the same query produced differently scaled scores
depending on the configured reranker, and logit based providers degraded
retrieval quality instead of improving it.
This PR enforces a single scoring contract in one place:
- `Base.similarity` is now the only public entry point. It
short-circuits empty input and guarantees a normalized result. Each
provider implements its raw scoring in `_compute_rank`, which removes
sixteen duplicated empty input guards and the three scattered
normalization calls.
- Normalization is range aware. Providers that already return calibrated
`[0, 1]` relevance scores (Cohere, Jina, Voyage, and others) keep their
absolute magnitudes, so `similarity_threshold` filtering and the
reported `vector_similarity` stay meaningful. Only out-of-range output
such as NVIDIA logits is min-max rescaled into `[0, 1]`.
- The twelve leftover `[DEBUG ...]` prints in `rerank_by_model`,
introduced in #14231, are removed. They ran on every retrieval, added
per chunk overhead, and leaked queries, keywords, and document content
to stdout and logs.
A new regression suite in
`test/unit_test/rag/llm/test_rerank_normalization.py` covers logit
rescaling (positive, negative, and flat batches), preservation of
already calibrated scores, ordering, empty input handling, and the per
provider HTTP path. It also asserts that no provider overrides
`similarity()`, so the contract cannot silently drift.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## Summary
Port the Python `GET /v1/plugin/tools` endpoint to the Go API server.
Listed in the Go-API port checklist of #15240.
Returns the metadata of every embedded LLM tool plugin in the same JSON
shape the Python endpoint emits (camelCase keys preserved), so existing
frontends bind to the Go server without changes.
### What problem does this PR solve?
Closes#15433
Reranked retrieval drops results and returns short pages once pagination
crosses the first candidate block, for the common page sizes 10 and 30.
In `rag/nlp/search.py`, the candidate window (`RERANK_LIMIT`) is rounded
up to a multiple of `page_size` to keep block based pagination aligned,
and then clamped back to 64:
```python
RERANK_LIMIT = math.ceil(64 / page_size) * page_size if page_size > 1 else 1 # e.g. 70 for page_size=10
RERANK_LIMIT = max(30, RERANK_LIMIT)
if rerank_mdl and top > 0:
RERANK_LIMIT = min(RERANK_LIMIT, top, 64) # clamps back to 64, breaking the multiple
```
`RERANK_LIMIT` is used both as the backend block size (`page =
global_offset // RERANK_LIMIT`) and as the modulus that slices a page
out of a reranked block (`begin = global_offset % RERANK_LIMIT`). When
it stops being a multiple of `page_size`, the block that gets fetched
and the slice taken from it no longer agree. With `page_size=10` and
`top=1024`, page 7 returns only 4 of 10 results and the head of the next
block is never shown on any page. This happens whenever the result set
spans more than one block, which is the default.
**Fix**
The window math is moved into a small reusable helper,
`Dealer._rerank_window`, which:
- targets a pool of about 64 candidates,
- bounds it by `top` when a reranker is active, and
- always rounds to a whole number of pages, so the window stays an exact
multiple of `page_size`.
The call site becomes a single line, and the alignment invariant now
lives in one documented place. Behavior is unchanged on every path that
was already aligned (the non reranked path and any `top` that already
produced a page multiple).
**Verification**
A simulation of the full retrieval path (per block rerank, similarity
threshold filter, and the exact `page // window` and `offset % window`
math) confirms the fix loses nothing where the old code lost real
results:
```
ps=10 top=1024: new window=70 dropped_valid=0 | old window=64 dropped_valid=16
ps=30 top=1024: new window=90 dropped_valid=0 | old window=64 dropped_valid=66
```
New unit tests in `test/unit_test/rag/test_search_pagination.py` cover
the alignment invariant, cross block pagination (every candidate
surfaced once, in order, no gaps, no short interior pages), the reported
regression, and parity with the old window on the previously correct
paths. All 114 cases pass and `ruff check` is clean.
Fixes the reranked deep pagination data loss described above.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Description
This PR syncs the `documentServiceIface` interface and introduces
handler methods for document preview, artifact fetching, and downloading
in the Go API. It also ensures that strict dataset alignment and access
checks are enforced when retrieving or downloading documents.
Furthermore, this PR introduces comprehensive unit tests for both the
newly added Handler and Service methods to ensure robustness and prevent
future regressions.
### Key Changes
* **Router & Handler Integration**:
* Added and wired new API endpoints in `internal/router/router.go`.
* Synchronized the `documentServiceIface` with `GetDocumentArtifact`,
`GetDocumentPreview`, and `DownloadDocument`.
* Implemented handlers for these endpoints in
`internal/handler/document.go`.
* **Access & Validation Enforcement**:
* Refactored `internal/service/document.go` to strictly check if a
document belongs to the requested dataset before allowing downloads or
previews.
* Added robust artifact file sanitization (`sanitizeArtifactFilename`)
and attachment handling (`shouldForceArtifactAttachment`).
* **Comprehensive Unit Testing**:
* **Handler Layer (`internal/handler/document_test.go`)**: Added mock
service implementations and Gin router tests covering success,
not-found, and internal error states for all 3 new endpoints.
* **Service Layer (`internal/service/document_test.go`)**: Added
extensive business logic tests including dataset mismatch checks,
non-existent document checks, and artifact file validation.
### What problem does this PR solve?
Feat：
- Get model list from remote provider.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Prepend a leading slash and reject `..` segments so scoped OneDrive
delta queries use `root:/path:/delta` instead of `root:path:/delta`.
Fixes#15500
### What problem does this PR solve?
The OneDrive connector builds Microsoft Graph delta URLs from optional
`config.folder_path`. When users enter a path without a leading slash
(e.g. `Documents/Reports` instead of `/Documents/Reports`), the
connector produces a malformed URL such as
`root:Documents/Reports:/delta`. Per [Microsoft Graph path-based
addressing](https://learn.microsoft.com/en-us/graph/onedrive-addressing-driveitems),
the segment after `root:` must start with `/` (e.g.
`root:/Documents/Reports:/delta`). Sync and validation then fail or
return no documents, which is hard to diagnose from the UI because the
optional folder field does not enforce the format.
This PR normalizes `folder_path` at connector construction time (prepend
`/`, trim whitespace and trailing slashes) and rejects `..` segments
before any Graph request is made.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## Summary
This PR improves the Go CLI in two areas:
1. It adds batch model management support, allowing multiple models to
be added or removed in a single command.
2. It makes the `dimension` argument optional for the `embed text`
command.
These changes keep the existing single-model and explicit-dimension
behaviors compatible while making the CLI more convenient for common
workflows.
## What Changed
### 1. Batch model add/remove support
The CLI now supports operating on multiple model names provided in a
single quoted string.
Supported commands include:
```
add model 'x1 x2 x3' to provider 'vllm' instance 'test' with tokens 1024 chat think vision, token 2048 chat, token 1024 think vision;
drop model 'x1 x2 x3' from 'vllm' 'test';
remove model 'x1 x2 x3' from 'vllm' 'test';
```
For add model, each config segment after with is matched to the
corresponding model name by position.
Example mapping:
- x1 -> tokens 1024, chat + vision, thinking=true
- x2 -> tokens 2048, chat
- x3 -> tokens 1024, vision, thinking=true
The existing single-model syntax remains supported.
### 2. Optional embedding dimension
Previously, the Go CLI required dimension to be explicitly provided for
embed text.
Before:
embed text 'what is rag' 'who are you' with 'model@test@provider'
dimension 8192;
Now both forms are supported:
embed text 'what is rag' 'who are you' with 'model@test@provider'
dimension 8192;
embed text 'what is rag' 'who are you' with 'model@test@provider';
When omitted, the CLI leaves dimension unset and relies on
provider/backend behavior.
## Tests
Added parser tests covering:
- Multiple models with multiple config segments
- Model type deduplication
- Model/config count mismatch
- Drop/remove multiple models
- Optional embedding dimension parsing
### What problem does this PR solve?
Fix: When adding a chat in the main interface, a warning will
automatically pop up (even if embedding and LLM model have already been
configured).
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## What
- make `Switch` ignore conditions that have no evaluable items
- add a regression for blank `cpn_id` items falling through to the else
branch
- keep the existing non-empty `and` condition behavior covered
Fixes#15643.
## Verified
- `python -m py_compile agent\component\switch.py
test\unit_test\agent\component\test_switch.py`
- `python -m pytest test\unit_test\agent\component\test_switch.py -q` ->
`2 passed`
- `python -m ruff check agent\component\switch.py
test\unit_test\agent\component\test_switch.py`
- `git diff --check`
I also checked `python -m ruff format --check` on the touched files. It
would reformat pre-existing style in `agent/component/switch.py` beyond
this bug fix, so I kept the patch scoped instead of reformatting the
whole file.
### What problem does this PR solve?
Update Dockerfile and release workflow to use GitHub mirror instead of
Gitee
### Type of change
- [x] Other (please describe): CI
### What problem does this PR solve?
Fixes#15542.
AWS Bedrock support for the Go model provider layer was added in #15166,
but embedding support was intentionally left out of scope and
`BedrockModel.Embed(...)` still returned the `no such method` sentinel.
This PR implements Bedrock text embeddings under the umbrella provider
tracker #14736.
### What this PR includes
- `internal/entity/models/bedrock.go`: implement
`BedrockModel.Embed(...)` through Bedrock Runtime `InvokeModel` with
existing SigV4 auth, region resolution, and runtime URL helpers.
- Titan embeddings: supports `amazon.titan-embed-text-v1` and
`amazon.titan-embed-text-v2:0`; v2 forwards `EmbeddingConfig.Dimension`
as `dimensions` when provided, while v1 keeps the payload minimal.
- Cohere embeddings: supports `cohere.embed-english-v3`,
`cohere.embed-multilingual-v3`, and `cohere.embed-v4:0`; batches input
texts and maps returned vectors to RAGFlow `EmbeddingData` in input
order.
- `conf/models/bedrock.json`: adds the `embedding` URL suffix (`invoke`)
and Bedrock embedding model entries.
- `internal/entity/models/bedrock_test.go`: adds unit tests for Titan,
Cohere, typed Cohere responses, validation, empty input, unsupported
models, and HTTP error propagation.
Reference docs:
- Bedrock InvokeModel API:
https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_InvokeModel.html
- Titan Text Embeddings:
https://docs.aws.amazon.com/bedrock/latest/userguide/titan-embedding-models.html
- Cohere Embed models on Bedrock:
https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-embed.html
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
- [x] `jq empty conf/models/bedrock.json`
- [x] `git diff --check`
- [x] `go test ./internal/entity/models/... -run Bedrock -count=1`
- [x] `go test ./internal/entity/models/... -run '^$' -count=1`
- [x] `go test ./internal/entity/models/... -run Bedrock -race -count=1`
Note: `go test ./internal/entity/models/... -count=1` currently fails in
unrelated existing Astraflow coverage
(`TestAstraflowEmbedReturnsNoSuchMethod` panics in
`internal/entity/models/astraflow.go`). The Bedrock-specific tests and
compile-only package check pass.
## Summary
Ports the MCP (Model Context Protocol) server management endpoints that
power `web/src/pages/user-setting/mcp/` from Python
(`api/apps/restful_apis/mcp_api.py`) to Go. There were no MCP routes in
the Go server before this change.
Closes#15275 (subtask of #15240).
## Endpoints implemented (base path `/api/v1`)
| Method | Path | Description |
|--------|------|-------------|
| GET | `/mcp/servers` | List tenant servers (keyword / order /
pagination) |
| POST | `/mcp/servers` | Create a server |
| GET | `/mcp/servers/{mcp_id}` | Get one (`?mode=download` exports
config) |
| PUT | `/mcp/servers/{mcp_id}` | Update a server |
| DELETE | `/mcp/servers/{mcp_id}` | Delete a server |
| POST | `/mcp/import` | Bulk import from JSON config |
| POST | `/mcp/servers/{mcp_id}/test` | Connect + list tools (see notes)
|
## Implementation
Follows the existing `handler → service → dao` layering (per PR #14790):
- **entity** (`internal/entity/mcp.go`): added `MCPServerType` constants
and `IsValidMCPServerType` over the existing `MCPServer` model.
- **dao** (`internal/dao/mcp.go`): new `MCPServerDAO` with tenant-scoped
CRUD, a keyword filter, and a **whitelisted order-column map** (guards
against SQL injection via the caller-supplied `orderby`).
- **service** (`internal/service/mcp.go`): new `MCPService` —
list/get/export/create/update/delete/import/test — mirroring
`MCPServerService` and the `mcp_api` request validation, with sentinel
errors for clean code mapping.
- **handler** (`internal/handler/mcp.go`): new `MCPHandler` with the
seven handlers and Python-compatible response codes.
- **router / server_main**: registered the `/mcp` group and wired the
handler.
## Deviations from Python (documented in code)
1. **Bulk import is at `POST /mcp/import`, not `/mcp/servers/import`.**
gin (v1.9.1) cannot register a static segment and a path param at the
same tree node, so `/mcp/servers/import` would collide with
`/mcp/servers/:mcp_id` and panic at startup. The frontend should call
`/mcp/import`.
2. **No live tool discovery on create/update/import.** The Python path
runs `get_mcp_tools` over SSE / streamable-HTTP and stores
`variables.tools`. The Go server has no MCP client yet, so these persist
`variables`/`headers` but leave `variables.tools` unpopulated.
3. **`/test` returns a data error (`ErrMCPTestUnsupported`)** until a Go
MCP client lands. Per the issue, the live-connection path is scoped as a
follow-up; the handler still validates `url` + `server_type`.
## Testing
- Added `internal/service/mcp_test.go` covering `IsValidMCPServerType`
and the `TestServer` validation/short-circuit paths (no DB required).
- No Go toolchain was available in the dev environment, so `go build
./...` / `go vet ./...` verification is left to CI.
## Follow-ups
- Go MCP client (SSE / streamable-HTTP) to enable live tool discovery
and the real `/test` behavior.
- Reconcile the `/mcp/import` vs `/mcp/servers/import` path with the
frontend.
---------
### What problem does this PR solve?
Closes#15461.
RAGFlow had no way to ingest Salesforce CRM data, so support / sales
teams couldn't ground responses on live Accounts, Contacts,
Opportunities, Cases, or Knowledge articles. This adds a first-class
Salesforce data source connector that authenticates against a Connected
App via OAuth 2.0 client-credentials, queries selected SObjects via
SOQL, and turns each record into an indexable document with incremental
sync.
**Highlights**
- `common/data_source/salesforce_connector.py`: new
`SalesforceConnector` (`CheckpointedConnectorWithPermSync` +
`SlimConnectorWithPermSync`).
- OAuth 2.0 client-credentials flow; canonical `instance_url` from the
token response so multi-pod orgs route correctly.
- Per-object `SystemModstamp` cursor stored in
`SalesforceCheckpoint.cursors` — a failure mid-object doesn't rewind
sibling objects, and re-syncs only fetch changed rows.
- Deterministic record-to-text formatter (sorted keys) so SOQL field
reordering on the server doesn't mark every row "changed" on each poll.
- `_get_json` raises on non-2xx so 429 / 5xx never silently advance the
checkpoint past missing data.
- `Knowledge__kav` is in the default object set but is skipped silently
when the org doesn't have Salesforce Knowledge enabled (404 on
describe).
- Slim-doc IDs are scoped as `<Object>/<Id>` so prune deletes can't
collide across object types.
- `common/constants.py`, `common/data_source/config.py`,
`common/data_source/__init__.py`: register `salesforce` in `FileSource`
/ `DocumentSource` and export `SalesforceConnector`.
- `rag/svr/sync_data_source.py`: new `Salesforce(SyncBase)` class routed
through `load_from_checkpoint` (poll_source would re-walk every object
each run) and added to `func_factory`.
- Frontend:
- `web/src/pages/user-setting/data-source/constant/index.tsx`: new
`DataSourceKey.SALESFORCE`, form fields (instance URL, client ID/secret,
objects, api_version, batch size), `syncDeletedFiles` capability,
default form values, and tile entry with the new icon.
- `web/src/locales/{en,zh}.ts`: description + per-field tooltips.
- `web/src/assets/svg/data-source/salesforce.svg`: 48x48 brand-style
icon to match the other Microsoft / cloud tiles.
**Verification**
- `npm run build` (vite + esbuild) passes (1m 26s).
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
This fixes duplicated post-think text in streamed chat responses. When
the model emits text immediately after `</think>`, the stream state now
advances its cursor correctly so the same visible prefix is not emitted
twice.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## Summary
This PR fixes case-sensitivity regressions introduced in #15656 and
consolidates the metadata filtering pipeline by removing the duplicate
`applySingleCondition` adapter layer.
### Bug fixes
1. **contains / not contains**: restored case-insensitive matching (was
lost when `applySingleCondition` was replaced by
`common.MetaFilter.matchValue` which lacked `strings.ToLower`)
2. **not in**: restored case-insensitive matching (was lost for same
reason; uses `strings.EqualFold`)
3. **!= with date filter values**: non-date metadata values now
correctly match the `≠` operator (a non-date value IS not equal to any
date, but was returning false)
### Architecture
4. **Removed `applySingleCondition`** (65 lines) — the inline switch was
a duplicate of `common.MetaFilter` logic. `ApplyMetaFilter` now converts
conditions and delegates to `common.MetaFilter` once per filter set,
eliminating ~25 lines of duplicate AND/OR merge logic.
5. **Added `filterSet`** — O(n+m) hash-map fast path for `in`/`not in`
operators, replacing the O(n*m) linear scan in `matchValue`.
6. **Exported `NormalizeOperator`** from `common` for consistent
operator alias handling.
### Cleanup
7. Removed 18 lines of dead code (`matchValue`'s `in`/`not in` branches
already bypassed by `filterOut` delegation)
8. Fixed orphaned godoc comment for `convertOperator`
9. Fixed incorrect `filterSet` doc comment (claimed "matching EqualFold"
but used `strings.ToLower`)
10. Completed `convertToMetaCondition` operator normalization
documentation
### Testing
- 60 tests (24 service + 36 common), all passing
- New tests: `==`, `≠`, `>`, `<`, `≥`, `≤`, `empty`, `not empty` through
`ApplyMetaFilter`
- New tests: `<`, `≤`, `≠` through `MetaFilter`; `not-in-empty-list`
through `filterSet`
- All 18 `MetaFilter` tests pass; all 10 `filterSet` unit tests pass
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
Add `EnrichChunksWithDocMetadata` as a method on `MetadataService` that
attaches document metadata to retrieval chunks in-place. Equivalent to
Python's `enrich_chunks_with_document_metadata()` from
`api/utils/reference_metadata_utils.py`.
### Usage
```go
metadataSvc.EnrichChunksWithDocMetadata(chunks, tenantID, metadataFields)
```
### Changes
- **`service/metadata.go`**: Added `EnrichChunksWithDocMetadata` method
- **`service/enrich_metadata_test.go`** (new): 7 test cases
### Algorithm
1. Collect unique `(kb_id, doc_id)` pairs from chunks
2. Fetch metadata from ES via `SearchMetadata(kbID, tenantID, docIDs)`
3. Attach `document_metadata` field to each matching chunk
4. Optionally filter to specified `metadataFields`
### Testing
All 7 tests pass:
```
=== RUN TestEnrichChunksWithDocMetadata_NoChunks --- PASS
=== RUN TestEnrichChunksWithDocMetadata_EmptyChunks --- PASS
=== RUN TestEnrichChunksWithDocMetadata_EmptyDocID --- PASS
=== RUN TestEnrichChunksWithDocMetadata_DuplicateDocIDs --- PASS
=== RUN TestEnrichChunksWithDocMetadata_MultipleKBs --- PASS
=== RUN TestEnrichChunksWithDocMetadata_WithMetadataFields --- PASS
=== RUN TestEnrichChunksWithDocMetadata_MixedFields --- PASS
```
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
### What problem does this PR solve?
Markdown extraction can split tables row by row when delimiter-based
extraction uses a newline delimiter. That loses table structure during
chunking even though delimiters should still split normally outside
tables.
This PR keeps the follow-up to #15482 intentionally narrow:
- preserve Markdown pipe tables during delimiter-based extraction
- preserve borderless pipe tables during delimiter-based extraction
- preserve multiline HTML tables during delimiter-based extraction
- keep delimiter splitting unchanged outside protected table ranges
Refs #15482
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Testing
- `ruff check deepdoc/parser/markdown_parser.py
test/unit_test/deepdoc/parser/test_markdown_parser.py`
- `python3 run_tests.py -t
test/unit_test/deepdoc/parser/test_markdown_parser.py`
- `git diff --check`
## Summary
Port the canvas-template catalogue endpoint to the Go API server. Listed
in the Go-API port checklist of #15240.
Mirrors `list_agent_template` in `api/apps/restful_apis/agent_api.py`:
returns every row from the `canvas_template` table so that the UI can
render the template gallery on the New-Agent screen.
## What
- `internal/dao/canvas_template.go` — new `CanvasTemplateDAO.GetAll()`
ordered by `create_time desc` (newest templates first).
- `internal/service/agent.go` — wire the new DAO into `AgentService` and
expose `ListTemplates() ([]*entity.CanvasTemplate, error)`.
- `internal/handler/agent.go` — new `AgentHandler.ListTemplates` HTTP
handler (auth-gated, mirrors Python `@login_required`).
- `internal/router/router.go` — `agents.GET("/templates",
r.agentHandler.ListTemplates)` registered alongside the existing `GET
/agents`.
- `internal/handler/agent_test.go` — three new tests covering: success
path, empty-list → JSON array (not `null`), and the auth gate.
## Notes
- `CanvasTemplate` entity, GORM tags, and DB migration already exist in
`internal/entity/canvas.go` and `internal/dao/database.go` — no schema
change required.
- The handler coerces a `nil` slice to `[]*entity.CanvasTemplate{}` so
the JSON payload is always an array (the frontend does `data.map(...)`
on it).
## Test plan
- [x] `go vet ./internal/handler ./internal/service ./internal/dao
./internal/router` clean
- [x] Three unit tests added; existing `TestListAgents_Success`
untouched
- [ ] CI runs `go test ./internal/handler` with cgo binding linked
## Related
- Tracker: #15240
QueryRewrite prompt builder and response parser. Zero external
dependencies.
### Functions
- `BuildQueryRewritePrompt`: Renders `minirag_query2kwd` prompt with
query and type pool
- `ParseQueryRewriteResponse`: Parses LLM JSON response with fallback
for markdown and extra text
### Testing
```
=== RUN TestBuildQueryRewritePrompt --- PASS
=== RUN TestParseQueryRewriteResponse_ValidJSON --- PASS
=== RUN TestParseQueryRewriteResponse_MarkdownBlock --- PASS
=== RUN TestParseQueryRewriteResponse_ExtraText --- PASS
=== RUN TestParseQueryRewriteResponse_Invalid --- PASS
=== RUN TestParseQueryRewriteResponse_EmptyEntities --- PASS
```
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
- Infer `Content-Type` from the stored document filename on SDK download
routes.
- Covers `GET /api/v1/datasets/<dataset_id>/documents/<document_id>` and
`GET /api/v1/documents/<document_id>`.
- Aligns with REST preview/download via `CONTENT_TYPE_MAP`.
## Test plan
- [x] `pytest
test/testcases/test_http_api/test_file_management_within_dataset/test_doc_sdk_routes_unit.py::TestDocRoutesUnit::test_download_mimetype_from_filename`
- [x] Manual: `curl -sSI` on SDK dataset document download for a PDF;
expect `Content-Type: application/pdf`
Fixes#15112.
### What problem does this PR solve?
Fix:
- VolcEngine adapt to new api_key format
- Save dict api_key as json
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
On some Linux hosts (e.g. x86_64 with enforced POSIX ACL on overlay
storage), the official `elasticsearch` Docker image cannot start because
`docker-entrypoint.sh` needs to create temporary files under `/tmp` for
bash here-documents, while the image ACL grants `user:elasticsearch`
only `r-x` on `/tmp`:
```
/usr/local/bin/docker-entrypoint.sh: line 73/84: cannot create temp file for here-document: Permission denied
```
RAGFlow users hit this when running `docker compose` with the default
`es01` service. See also Refs #284.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## Summary
Mount a writable `tmpfs` at `/tmp` for the `es01` service so
Elasticsearch entrypoint scripts can run on ACL-enforced environments.
Closes the startup failure described in #284 for non-ARM deployments.
## Changes
- Add `tmpfs: /tmp:mode=1777,size=512m` to `es01` in
`docker/docker-compose-base.yml`
- Document why the mount is required (ES image `/tmp` ACL vs entrypoint
here-documents)
## Test plan
- [x] Verified on Linux (x86_64): `docker run --rm elasticsearch:8.11.3
bash -c 'mktemp'` fails without tmpfs and succeeds with `--tmpfs
/tmp:mode=1777,size=512m`
- [x] Verified `es01` becomes healthy after `docker compose up -d es01`
with this change
- [ ] Upstream maintainers: `docker compose -f
docker/docker-compose-base.yml --profile elasticsearch up -d es01` on a
host where ACL is enforced
Made with [Cursor](https://cursor.com)
Co-authored-by: Cursor <cursoragent@cursor.com>
Add `ResolveReferenceMetadata` to parse `include_metadata` /
`metadata_fields` from request and config payloads.
### Changes
- **New**: `internal/common/reference_metadata.go` — pure function, zero
dependencies
- **New**: `internal/common/reference_metadata_test.go` — 8 test cases
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
Change `GetFlattedMetaByKBs` return type from `map[string]interface{}`
to strongly-typed `common.MetaData`.
**Depends on**: #15648 (provides `MetaData`, `MetaValueDocs` types)
### Changes
- `service/metadata.go`: Changed return type, removed type assertions
- `service/metadata_filter.go`: Updated all metadata function signatures
- `service/metadata_filter_test.go` (new): 12 test cases
### Bug fix
`applySingleCondition` used `.([]interface{})` assertions on `[]string`
data, silently breaking operators like `!=`, `contains`, `start with`,
etc.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
### What problem does this PR solve?
Closes#15465.
RAGFlow supports S3, Google Cloud Storage, R2, and OCI as data sources
but not Azure Blob Storage, leaving Azure users without a way to index
container objects into a knowledge base. This adds a first-class Azure
Blob Storage data-source connector — distinct from RAGFlow's existing
Azure storage *backends* (`rag/utils/azure_sas_conn.py`,
`rag/utils/azure_spn_conn.py`) which store RAGFlow's own files.
**Highlights**
- `common/data_source/azure_blob_connector.py`: new `AzureBlobConnector`
(`CheckpointedConnectorWithPermSync` + `SlimConnectorWithPermSync`).
- Uses the existing `azure-storage-blob` dependency (already in
`pyproject.toml`).
- Three auth modes, tried in order of precedence:
1. **Account key** — `account_name` + `account_key` + `container_name`.
2. **Connection string** — `connection_string` + `container_name`.
3. **SAS token** — `container_url` + `sas_token` (same shape as
`RAGFlowAzureSasBlob`).
- ETag fingerprint stored per blob in `AzureBlobCheckpoint.etags` —
unchanged blobs (same ETag as last run) are skipped without a download.
Only new/modified blobs are fetched.
- Optional `prefix` scopes indexing to a virtual folder.
- `validate_connector_settings()` probes `get_container_properties()`
and maps `AuthenticationFailed / 403 / ContainerNotFound` to typed
connector exceptions.
- Slim-doc IDs are blob names so prune reconciles correctly.
- `common/constants.py`, `common/data_source/config.py`,
`common/data_source/__init__.py`: register `azure_blob` in `FileSource`
/ `DocumentSource` and export `AzureBlobConnector`.
- `rag/svr/sync_data_source.py`: new `AzureBlob(SyncBase)` class routed
through `load_from_checkpoint` (ETag fingerprint owns change-detection)
and added to `func_factory`.
- Frontend:
- `web/src/pages/user-setting/data-source/constant/index.tsx`: new
`DataSourceKey.AZURE_BLOB`, auth-mode selector (account key / connection
string / SAS token), all credential fields, prefix + batch-size,
`syncDeletedFiles` capability, default form values, tile entry with
icon.
- `web/src/locales/{en,zh}.ts`: description + per-field tooltips for all
9 new keys.
- `web/src/assets/svg/data-source/azure-blob.svg`: Azure-branded
stacked-cylinders icon.
**Verification**
- `npm run build` (vite + esbuild) passes (37 s).
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
## Summary
`DocumentDAO.GetByIDs()` generated `WHERE id IN ()` for empty/nil ID
slices, which is invalid SQL and would fail on most databases. This PR
adds a nil guard and comprehensive tests.
### Changes
- **Modified**: `internal/dao/document.go` — Added `len(ids) == 0` guard
to `GetByIDs`
- **New**: `internal/dao/document_test.go` — 4 test cases covering
success, empty IDs, nil IDs, and no-match
### Testing
```
=== RUN TestDocumentGetByIDs_Success --- PASS
=== RUN TestDocumentGetByIDs_EmptyIDs --- PASS
=== RUN TestDocumentGetByIDs_NilIDs --- PASS
=== RUN TestDocumentGetByIDs_NoMatch --- PASS
```
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
Migrate the metadata filtering utilities `meta_filter` and
`convert_conditions` from `common/metadata_utils.py` to Go as pure
functions with zero external dependencies.
These functions are used by `dify/retrieval`, `openai/chat/completions`,
`document_api`, and `chunk_api` for filtering documents by metadata
conditions.
### Changes
- **New**: `internal/common/metadata_utils.go` — `ConvertConditions()`
and `MetaFilter()` with full operator support
- **New**: `internal/common/metadata_utils_test.go` — 18 test cases
covering all operators and edge cases
### Supported Operators
`=`, `≠`, `>`, `<`, `≥`, `≤`, `contains`, `not contains`, `in`, `not
in`, `start with`, `end with`, `empty`, `not empty`
### Design
- Numeric comparison via `strconv.ParseFloat`
- Date comparison via YYYY-MM-DD format detection
- Case-insensitive string comparison fallback
- `and` / `or` logic support for multiple conditions
- Zero external dependencies — pure functions only
## Summary
Implement the `GET /api/v1/agents/<agent_id>/versions/<version_id>`
endpoint in Go, returning full version details including DSL.
Depends on #15629 which introduced the version list endpoint and
`UserCanvasVersionDAO` infrastructure.
### Changes
- **Modified**: `internal/handler/agent.go` — Added `GetAgentVersion`
handler with auth check and ownership verification
- **Modified**: `internal/router/router.go` — Registered `GET
/:agent_id/versions/:version_id` route
- **New/Modified tests**: Service and handler tests for the version
detail endpoint
### Testing
```
=== RUN TestGetVersion_Success --- PASS
=== RUN TestGetVersion_WrongCanvas --- PASS
=== RUN TestGetVersion_NotFound --- PASS
=== RUN TestGetAgentVersionHandler_Success --- PASS
=== RUN TestGetAgentVersionHandler_VersionNotFound --- PASS
```
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
### What problem does this PR solve?
When a document is rerun or updated concurrently, the previous
unconditional update could overwrite a newer task state.
This change adds an `update_time`-based optimistic lock so the update
only succeeds if the record has not been modified by another flow in the
meantime.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
