### What problem does this PR solve?
Fix release
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
## Summary
This PR fixes two issues discovered during testing of the PaddleOCR
async API refactoring:
### 1. PP-OCRv6 returns `ocrResults` instead of `layoutParsingResults`
Models like PP-OCRv6 are pure text recognition models that return
results in `ocrResults.prunedResult.rec_texts` format rather than the
`layoutParsingResults.prunedResult.parsing_res_list` format used by
layout-aware models (PaddleOCR-VL series).
**Changes:**
- `deepdoc/parser/paddleocr_parser.py`: Extract `ocrResults` alongside
`layoutParsingResults` in `_send_request()`, add fallback logic in
`_transfer_to_sections()` and `parse_image()`
- `internal/entity/models/paddleocr.go`: Add `ocrResults` struct and
fallback extraction in Go OCR handler
### 2. Image parsing not integrated into picture chunker
The `parse_image()` method existed in PaddleOCRParser but was never
called from `rag/app/picture.py` (the module that handles image file
uploads). Users configuring PaddleOCR as their layout recognizer would
still get local deepdoc OCR for images.
**Changes:**
- `rag/app/picture.py`: When `layout_recognize` is set to PaddleOCR, use
`PaddleOCROcrModel.parse_image()` instead of local OCR. Falls back
gracefully to local OCR on failure.
## Testing
Verified end-to-end in Docker:
- PaddleOCR-VL-1.6 PDF parsing: ✅ (10 text blocks with bbox)
- PaddleOCR-VL-1.6 image parsing: ✅ (219 chars)
- PP-OCRv6 PDF parsing with ocrResults fallback: ✅ (10 text blocks)
- PP-OCRv6 image parsing with ocrResults fallback: ✅ (136 chars)
## Related PRs
- #15967 (merged) - PaddleOCR async Job API refactoring + new models
- #16086 (merged) - PaddleOCR image parsing support
### What problem does this PR solve?
- Tools management
- Pregel engine wrapper for better usage
- UT race
- Coding style
### Type of change
- [x] Refactoring
### What problem does this PR solve?
```
RAGFlow(admin)> show model 'abc';
+------------+----------------------------------------------------------------+
| field | value |
+------------+----------------------------------------------------------------+
| command | get_model_by_model_name |
| error | 'get model by model name' is implemented in enterprise edition |
| model_name | abc |
+------------+----------------------------------------------------------------+
RAGFlow(admin)> list models;
+-----------------+--------------------------------------------------------+
| command | error |
+-----------------+--------------------------------------------------------+
| list_all_models | 'list all models' is implemented in enterprise edition |
+-----------------+--------------------------------------------------------+
```
### Type of change
- [x] Refactoring
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Implement:
1. `/api/v1/datasets/<dataset_id>/documents/<document_id>/chunks GET`
2.
`/api/v1/datasets/<dataset_id>/documents/<document_id>/chunks/<chunk_id>
PATCH`
3. `/api/v1/datasets/<dataset_id>/documents/<document_id>/chunks PATCH`
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Provider default public key for CLI
### Type of change
- [x] Refactoring
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
Refactor the Go agent port's logging so every log line — gin access,
agent canvas events, harness warnings, fatal boot errors — flows through
a single common.Logger (zap) backed by a rotated file, with structured
fields, level filtering, and configurable rotation.
---------
Co-authored-by: Claude <noreply@anthropic.com>
## Summary
Stabilizes the Go unit-test surface so the test suite can run reliably
in CI and locally via \`bash build.sh --test\`.
## Verification
\`\`\`bash
bash build.sh --test -- -count=10 -run TestWithCancel_SequentialAgent
./internal/harness/core/
bash build.sh --test -- -count=5 -run TestSiliconflowChatExtracts
./internal/entity/models/
bash build.sh --test # full suite
\`\`\`
All previously failing packages (\`admin\`, \`cli\`, \`handler\`,
\`parser\`,
\`router\`, \`service\`, \`service/chunk\`) now build and test
successfully.
\`TestWithCancel_SequentialAgent\` passes 10/10 (was flaky). SiliconFlow
reasoning test passes after switching the assertion to the SiliconFlow
wire
format.
---------
Co-authored-by: Claude <noreply@anthropic.com>
### What problem does this PR solve?
```
RAGFlow(admin)> show role 'user' default models;
+--------------------------+-----------------------------------------------------------------+-----------+
| command | error | role_name |
+--------------------------+-----------------------------------------------------------------+-----------+
| show_role_default_models | 'show role default models' is implemented in enterprise edition | user |
+--------------------------+-----------------------------------------------------------------+-----------+
RAGFlow(admin)> set role 'user' default chat 'glm4.5@test@zhipu-ai';
+------------+---------------------------------------------------------------+
| field | value |
+------------+---------------------------------------------------------------+
| model_id | |
| model_type | chat |
| role_name | user |
| command | set_role_default_model |
| error | 'set role default model' is implemented in enterprise edition |
+------------+---------------------------------------------------------------+
RAGFlow(admin)> reset role 'user' default chat;
+------------+-----------------------------------------------------------------+
| field | value |
+------------+-----------------------------------------------------------------+
| command | reset_role_default_model |
| error | 'reset role default model' is implemented in enterprise edition |
| model_type | chat |
| role_name | user |
+------------+-----------------------------------------------------------------+
```
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
## Summary
- add public Go route for `/api/v1/searchbots/detail`
- implement beta-token auth flow for shared search access
- add tenant-based access check for shared search apps
- add joined search detail query for the share response
- align Go response shape with the current Python runtime behavior
- add DAO / service / handler tests for the new endpoint
close#16132
## Summary
This PR completes the Go-side merge and cleanup for chat channel APIs,
including handler/service wiring, route registration, and test coverage.
Implemented and aligned 5 chat channel APIs:
```
- POST `/api/v1/chat-channels`
- GET `/api/v1/chat-channels`
- GET `/api/v1/chat-channels/:channel_id`
- PATCH `/api/v1/chat-channels/:channel_id`
- DELETE `/api/v1/chat-channels/:channel_id`
```
Co-authored-by: Haruko386 <tryeverypossible@163.com>
### What problem does this PR solve?
```
fixed:
RAGFlow(api/default)> use model 'minimax-m2.5@test@minimax'
SUCCESS
RAGFlow(api/default)> chat message 'who r u'
Answer: Hey! I'm MiniMax-M2.5, an AI assistant here to help you with questions, tasks, or whatever you need. What can I do for you?
Time: 1.727263
```
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
As title.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
- list configs;
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
- list resources
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
1. Remove unused file
2. Remove duplicate models
3. Resort the function order
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Implement OpenAI chat completions in GO
POST /api/v1/openai/<chat_id>/chat/completions
OpenAI chat cli: internal/development.md
### Type of change
- [x] Refactoring
### What problem does this PR solve?
1. add modelID for delete_model and update_status
2. fix the bug when update-status delete model
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
RAGFlow(admin)> show tasks summary;
+---------+-----------------------------------------------------------------+
| field | value |
+---------+-----------------------------------------------------------------+
| command | show_users_quota_summary |
| error | 'Show users quota summary' is implemented in enterprise
edition |
+---------+-----------------------------------------------------------------+
### 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?
Prepare for enterprise command
### 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?
- Migrated MCP server detail and export (download) API from Python to
Go.
- Registered route: `GET /api/v1/mcp/servers/:mcp_id` (supporting
`?mode=download` query parameter).
### What problem does this PR solve?
This PR implements the Go backend counterpart for the document partial
update API:
`PATCH /api/v1/datasets/:dataset_id/documents/:document_id`
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
This PR improves code readability in the CLI parser by renaming the loop
index `i` to `modelIndex`. It also renames the loop label `A` to
`optionsLoop` to align with standard Go naming conventions.
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Fixes two bugs in the OpenRouter streaming chat request builder
(`internal/entity/models/openrouter.go`, `ChatStreamlyWithSender`):
1. **qwen/glm models streamed to a broken URL.** The code routed any
`qwen`/`glm` model to
`URLSuffix.AsyncChat`, but `conf/models/openrouter.json` defines no
`async_chat` suffix
(empty), so the request was POSTed to `<base>/` instead of
`<base>/chat/completions` —
breaking streaming for every qwen/glm model. The non-stream path has no
such branch.
Fix: all models use the standard `Chat` suffix, consistent with the
non-stream path.
2. **Streaming reasoning was never enabled.** The request set reasoning
via a non-standard
`thinking` key, which OpenRouter ignores. OpenRouter's API — and this
provider's own
non-stream request (line ~110) and its streamed `delta.reasoning` parser
(line ~311) —
use the `reasoning` object. Fix: send `reasoning: {"enabled":
<thinking>}` (and
`{"effort": ...}` when set, taking precedence as in the non-stream
path).
Closes#16110
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Part of #15853 (provider model-list refactor).
Refactors **Ollama** `ListModels` onto the shared `ParseListModel`
pattern and fixes two correctness issues:
- **Endpoint:** switch the models suffix from `api/ps` (only
currently-running models) to `api/tags` (all installed models) — the
latter is what a model picker should show.
- **Parsing:** Ollama returns `{"models":[{"name","model"}]}`, a
non-OpenAI shape. Decode it into a typed struct, map the names into
`ModelList`, then enrich through `ParseListModel`. This removes the
previous unchecked type assertions (`result["models"].([]interface{})` /
`.(map[string]interface{})` / `.(string)`) that **panicked** when the
body was missing the `models` array or any field, and adds a fallback to
the `model` field when `name` is blank.
- Drops the no-op GET request body and a dead base-URL reassignment.
#### Drive-by fix
Shared gitee_test.go `DSModelList` -> `ModelList` compile fix (renamed
in #15900) so the models test package builds; auto-resolves against the
sibling #15853 PRs.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
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?
The `get_ingestion_log` endpoint (both Python
`dataset_api_service.get_ingestion_log` and Go
`DatasetService.GetIngestionLog`) was returning only the
**dataset-level** field set, which omits critical fields such as `dsl`,
`document_id`, `parser_id`, `document_name`, `pipeline_id`, etc.
This caused the front-end **dataflow-result page** to be unable to
render the pipeline timeline and chunks when viewing a single ingestion
log, regardless of whether the log was a dataset-level operation
(graph/raptor/mindmap) or a per-file parse.
### Background
`PipelineOperationLogService` provides two field sets:
| Method | Fields |
|---|---|
| `get_dataset_logs_fields` | Minimal set (progress, status, timestamps,
etc.) |
| `get_file_logs_fields` | Superset — includes `document_id`, `dsl`,
`parser_id`, `document_name`, `pipeline_id`, … |
When listing logs, the API correctly distinguishes dataset-level vs
file-level logs and uses the appropriate converter. However, when
**fetching a single log by ID**, both the Python and Go implementations
were hardcoded to the dataset-level set, dropping the extra fields that
the front-end needs.
### What problem does this PR solve?
Part of #15853 (provider model-list refactor). Final two providers.
- **voyage:** Voyage AI exposes no live model-list endpoint — its public
API only has `/v1/embeddings` and `/v1/rerank` — so the previous
`ListModels` was a `no such method` stub. Replace it with a
static-catalog listing sourced from the loaded provider definition,
carrying each model's `max_tokens`, `model_types`, and embedding
`dimensions`. `list models from voyage` now returns the 13-model catalog
instead of erroring.
- **fishaudio:** route the existing `/model` voice listing through the
shared `ParseListModel` helper for consistency; keep the human-readable
`title` as the model name and fall back to `_id` when a title is blank.
#### Drive-by fix
Shared gitee_test.go `DSModelList` -> `ModelList` compile fix (renamed
in #15900); auto-resolves against the sibling #15853 PRs.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
Co-authored-by: Haruko386 <tryeverypossible@163.com>
## Changes
1. **Entity (`internal/entity/chat_channel.go`)**:
- Implemented `ChatChannel` struct mapping the `chat_channel` database
table.
- Declared `ChatChannelListResponse` as a DTO to filter out sensitive
credentials (`config` field) and fetch the associated `dialog_name` via
left join.
2. **GORM Migration (`internal/dao/database.go`)**:
- Registered `&entity.ChatChannel{}` in the `dataModels` array inside
`InitDB()` to enable safe GORM schema synchronization.
3. **DAO (`internal/dao/chat_channel.go`)**:
- Implemented `ChatChannelDAO` wrapping GORM CRUD methods (`Create`,
`GetByID`, `UpdateByID`, `DeleteByID`).
- Implemented `ListByTenantID` performing a `LEFT JOIN` on the `dialog`
table to retrieve `dialog_name` while excluding `config` values to avoid
credential leaks.
4. **Test (`internal/dao/chat_channel_test.go`)**:
- Added integration unit tests testing the full CRUD lifecycle and GORM
left-join mapping list querying.
## Summary
Migrate PaddleOCR integration from the deprecated synchronous HTTP API
to the new asynchronous Job API (`submit → poll → fetch`), aligning with
PaddleOCR 3.6.0+ architecture.
## Changes
### Python (`deepdoc/parser/paddleocr_parser.py`)
- Replace synchronous `requests.post()` with async Job API flow (submit
→ poll → fetch)
- Authentication: `token {token}` → `Bearer {token}`
- File transfer: base64 JSON body → multipart file upload
- Polling: exponential backoff (initial 3s, ×1.5, max 15s, timeout
controlled by `request_timeout`)
- Result: fetch full JSONL from result URL, preserving `prunedResult`
with bbox info for crop functionality
- Rename `api_url` → `base_url` (backward compatible: `api_url` still
accepted as fallback)
### Python (`rag/llm/ocr_model.py`)
- Prefer `paddleocr_base_url` / `PADDLEOCR_BASE_URL`, fallback to
`paddleocr_api_url` / `PADDLEOCR_API_URL`
### Go (`internal/entity/models/paddleocr.go`)
- Add `Client-Platform: ragflow` header to submit and poll requests
- Change polling from fixed 3s to exponential backoff (initial 3s, ×1.5,
max 15s)
### Python (`common/constants.py`)
- Add `PADDLEOCR_BASE_URL` to env keys and default config
## Backward Compatibility
- Old env var `PADDLEOCR_API_URL` still works (used as fallback)
- Frontend field `paddleocr_api_url` still works (backend reads it as
fallback)
- No user-facing configuration changes required for existing setups
## Why not use the `paddleocr` SDK package directly?
RAGFlow's `_transfer_to_sections()` relies on `prunedResult` (containing
`block_bbox`, `block_label`, `parsing_res_list`) from the raw API
response for PDF crop functionality. The SDK's public `parse_document()`
API only returns `DocParsingResult` with `markdown_text`, discarding the
bbox data. Therefore we implement the async Job API flow directly via
HTTP, following the same logic as the SDK internally.
### What problem does this PR solve?
Merge password related functions
### Type of change
- [x] Refactoring
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Fix DB migration issue.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Fix register user
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
This PR enhances the CLI parser to support dimension configurations for
custom embedding models. Users can now specify the maximum dimension and
other supported dimensions directly after the embedding keyword.
```
add model 'x1 x2 x3 x4 x5' to provider 'vllm' instance 'test' with
tokens 1024 chat think vision,
token 2048 chat,
token 1024 think vision,
token 0 embedding 2048 64 1024 2048,
token 0 embedding 2048;
```
- The first integer following embedding represents the max_dimension.
- Any subsequent integers represent specific alternative dimensions.
- If no subsequent integers are provided, dimensions defaults to empty,
indicating all sizes under max_dimension are supported.
