### What problem does this PR solve?
Updated supported model providers and the corresponding URLs.
~~Synced supported model providers and base URLs with
**llm_factories.json**, while keeping the AI Badgr configuration example
via the OpenAI-API-Compatible provider.~~
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
As title
```
/api/v1/datasets/<dataset_id>/documents/<document_id>/metadata/config PUT
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Co-authored-by: Yingfeng <yingfeng.zhang@gmail.com>
### What problem does this PR solve?
Add two API in go
```
/api/v1/agents/test_db_connection POST
/api/v1/agents/<agent_id>/sessions DELETE
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Yingfeng <yingfeng.zhang@gmail.com>
Implements POST /api/v1/searchbots/ask in Go with streaming SSE,
citations, and think-tag processing. 23 files, 90+ unit tests.
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
This PR re-enables the Go test steps in CI that were previously
commented out, and fixes all compilation errors that have accumulated in
`internal/entity/models/` since the `ListModels` return type was changed
from `[]string` to `[]ListModelResponse`.
## Changes
### CI (`.github/workflows/tests.yml`)
- Re-enable **Prepare test resources** step (clones resource repo with
WordNet data)
- Re-enable **Test Go packages** step (runs `go test ./internal/...`)
- Fix resource path race condition by using
`/tmp/resource-${GITHUB_RUN_ID}` instead of `/tmp/resource`
- Exclude `/cli` package from Go tests (contains `main` redeclarations)
### Test fixes (16 model provider test files)
All errors were caused by the upstream change from `[]string` to
`[]ListModelResponse` in the `ListModels` interface:
- Add `joinModelNames` test helper to extract `.Name` from
`[]ListModelResponse` slices
- `strings.Join(models, ",")` → `joinModelNames(models, ",")` (11 files)
- `ids[i] != "..."` → `ids[i].Name != "..."` (cometapi, mistral)
- `got[i] != want[i]` → `got[i].Name != want[i]` (bedrock)
- `[]string` return types → `[]ListModelResponse` (google)
### Pre-existing bugs in model_test.go
Bugs introduced by the upstream `entity/` → `entity/models/` directory
rename:
- Add missing `pm := GetProviderManager()` calls in 3 test functions
- Fix `InitProviderManager` signature (`_, err :=` → `err :=`)
- Fix `MaxTokens` `*int` dereference (6 comparisons)
- Fix `readProviderConfig` relative path (3 levels up instead of 2)
### model.go
- Add `findRepoRoot()` to make `conf/all_models.json` resolution work
from any CWD, fixing `TestSiliconFlowProviderConfigLoadsLatestProModels`
### Test validation
```bash
go build ./internal/... # ✅
go test ./internal/entity/models/... -count=1 # ✅ all pass
```
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
### Summary
Closes#15795
Knowledge-graph queries rank entities by `pagerank * sim` in `KGSearch`,
but the entity chunks written at index time stopped carrying the values
that ranking depends on. `graph_node_to_chunk` only stored
`entity_type`, `description`, and `source_id`, dropping the node
`pagerank` and the n-hop neighbour paths, while `search.py` still read
them back as `rank_flt` and `n_hop_with_weight`.
The producer of these fields, `update_nodes_pagerank_nhop_neighbour`,
was removed in #6513, but the read side in `KGSearch` was never updated.
The result is that on every knowledge-graph query:
- `pagerank` resolves to `0`, so the `pagerank * sim` sort key is `0`
for every entity and selection falls back to arbitrary order.
- Every displayed entity score is `0.00`.
- The n-hop relation-enrichment block is dead code because `n_hop_ents`
is always empty, leaving `merge_tuples` and `is_continuous_subsequence`
orphaned.
This PR restores the missing index-time fields so the documented `P(E|Q)
= pagerank * sim` ranking and the n-hop enrichment work again.
What changed:
- `graph_node_to_chunk` now writes `rank_flt` from the node pagerank and
`n_hop_with_weight` from the recomputed n-hop neighbour paths.
- Reintroduced the n-hop path computation (`n_neighbor`) in
`rag/graphrag/utils.py`, reusing the previously orphaned `merge_tuples`
/ `is_continuous_subsequence` helpers, with a direction-agnostic
edge-weight lookup for undirected graphs. `set_graph` computes the paths
per added or updated node and passes them through.
- `KGSearch` now selects `n_hop_with_weight` in the entity keyword
search so Infinity and OceanBase return it (Elasticsearch and OpenSearch
already read it from `_source`), and the read is hardened against
missing keys or empty strings before `json.loads`.
- Added the `n_hop_with_weight` column to OceanBase, including the
`EXTRA_COLUMNS` migration entry so existing tables get it. The other
engines already map both fields via dynamic templates or the Infinity
mapping.
Scope note: pagerank and n-hop are re-indexed for the added or updated
nodes in each pass, consistent with the existing incremental indexing
design.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Testing
Added unit tests in
`test/unit_test/rag/graphrag/test_graphrag_utils.py`:
- `n_neighbor`: path and weight shape, one-hop vs two-hop, isolated
nodes, missing weights, and direction-agnostic lookup.
- `graph_node_to_chunk`: `rank_flt` populated from pagerank and
defaulting to `0`, `n_hop_with_weight` serialized and defaulting to an
empty list.
```
uv run pytest test/unit_test/rag/graphrag/ # 106 passed
uv run ruff check rag/graphrag/ rag/utils/ob_conn.py
```
## Summary
- Complete the Go Elasticsearch result functions that remained stubbed
after #15160.
- Add focused unit coverage for field mapping, aggregation, IDs, and
highlighting behavior.
- Update a stale query-builder test type import discovered during
validation.
## What changed
- Keep the Elasticsearch Go implementation merged in #15160 and fill in
`GetFields`, `GetAggregation`, `GetHighlight`, and `GetDocIDs` in
`internal/engine/elasticsearch/chunk.go`.
- Add regression and invariant coverage in
`internal/engine/elasticsearch/chunk_helpers_test.go`.
- Update `internal/service/nlp/query_builder_test.go` to use the current
`types.MatchTextExpr` type.
## Why
- #15160 implemented the main Go Elasticsearch surface, but
retrieval/tag flows still call result functions that returned stubs.
- Completing these functions keeps Elasticsearch result processing
aligned with the expected document-engine behavior for field extraction,
tag aggregation, doc ID extraction, and snippet highlighting.
## Validation
- `go test ./internal/engine/elasticsearch`
- `GOARCH=arm64 CGO_ENABLED=1 go test ./internal/service/nlp -run
TestQueryBuilder`
- `git diff --check`
- CodeRabbit review reported 0 issues after follow-up fixes.
- Codex Security diff scan found no reportable issues.
## Notes
- This PR is now a follow-up to #15160 rather than a competing
implementation.
- A full local `go test ./internal/service/nlp` run is blocked by local
WordNet resource prerequisites; the query-builder tests touched by this
PR pass with the arm64 CGO path.
### What problem does this PR solve?
Fix: The variables in the Visual Input File of the agent operator are
not displayed.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fixes four Go paths that dereference a pointer with no prior nil check,
each
causing a **runtime panic**. Closes#15814.
| # | File | Bug | Fix |
|---|------|-----|-----|
| 1 | `internal/entity/models/deepseek.go` | streaming path runs `switch
*chatModelConfig.Effort` inside `if *Thinking`; panics when
`Thinking=true` and `Effort==nil` | nil-check with default `"high"`,
matching the non-streaming path in the same file |
| 2 | `internal/entity/models/volcengine.go` | identical oversight:
`switch *modelConfig.Effort` with no guard | nil-check with default
`"medium"`, matching its non-streaming path |
| 3 | `internal/handler/auth.go` | `AuthMiddleware` does `if
*user.IsSuperuser`; panics on every authenticated request when the DB
column is `NULL` | guard with `user.IsSuperuser != nil &&`, matching
every other call site (`admin/handler.go`, `admin/service.go`,
`user.go`) |
| 4 | `internal/service/heartbeat_sender.go` |
`responseBody["code"].(float64)` panics on any non-200 response lacking
a numeric `code`; the upstream `recover()` calls `Fatal()` →
`os.Exit(1)`, taking down the whole server | comma-ok assertion (`code,
ok := ...`); return an error instead of panicking |
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fixes four panic / spurious-error paths in the Go model layer. Closes
#15818.
| # | File | Bug | Fix |
|---|------|-----|-----|
| 1 | | Thinking-mode streaming path: accessed unconditionally; Gemini
emits usage-only chunks with an empty slice, causing a runtime panic |
Guard each step: , , before indexing |
| 2 | | is a plain for ordinary requests; the cast to silently returns ,
then panics immediately | Switch on concrete type; handle both and |
| 3 | | Identical panic on the streaming path | Same switch-on-type fix
|
| 4 | | The field is optional (absent for non-thinking models) but the
code returned an error when it was missing, breaking every ordinary
Ollama completion | Change to a silent comma-ok assertion; is empty
string when the field is absent |
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
### What problem does this PR solve?
feat: support custom editing for model list
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
## Problem
When users configure auto-metadata for a dataset, parsing crashes with:
```
KeyError: 'properties' in gen_metadata → schema["properties"]
```
## Root Cause
Pydantic `AutoMetadataField` defaults `enum` and `description` to `None`
when the frontend omits these fields:
```python
class AutoMetadataField(Base):
enum: Annotated[list[str] | None, Field(default=None)]
description: Annotated[str | None, Field(default=None)]
```
These `None` values propagate through the call chain and cause two
crashes:
### What problem does this PR solve?
Dedup api_key and migrate `is_tools `in migration.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
When setting the API key for the BaiduYiyan provider, all model
validations fail with the error "Fail to access model using this api
key. No valid response received".
**Root cause:**
1. `BaiduYiyanChat` in `rag/llm/chat_model.py` does not override
`async_chat_streamly()`. The `verify_api_key()` function uses
`mdl.async_chat_streamly()` to validate, but `BaiduYiyanChat` inherits
`Base.async_chat_streamly()` which uses the OpenAI client, not the Baidu
Qianfan SDK (qianfan). Since BaiduYiyan has no OpenAI-compatible
base_url, validation always fails.
2. `verify_api_key()` in `provider_api_service.py` does not format the
raw API key string into the JSON format (`{"yiyan_ak": "...",
"yiyan_sk": "..."}`) that `BaiduYiyanChat.__init__()` expects via
`json.loads(key)`.
**Fix:**
1. Add `async_chat_streamly()` method to `BaiduYiyanChat` using the
qianfan SDK, consistent with the existing `chat_streamly()` method.
2. Add BaiduYiyan API key formatting in `provider_api_service.py`
`verify_api_key()` to match the format expected by
`BaiduYiyanChat.__init__()`.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [ ] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
### What problem does this PR solve?
Force image parser runtime output format to JSON so downstream chunking
reads OCR results from the JSON output and image parser chunks can be
displayed.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Co-authored-by: Wang Qi <wangq8@outlook.com>
### What problem does this PR solve?
The last column definition `INDEX idx_instance_id (instance_id),` in the
`CREATE TABLE tenant_model` statement has a trailing comma, which causes
a MySQL syntax error during deployment.
Closes#15832
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### How was this tested?
- [x] Visual inspection: the trailing comma on line 837 has been removed
### What problem does this PR solve?
Propagate `tenant_id` from memory task messages into task collection so
refactored task execution can build a valid context.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Description
This PR ports the `GET /api/v1/agents/prompts` endpoint from the Python
backend to the Go backend.
### Changes Made
- **Handler**: Added `GetPrompts` method to `internal/handler/agent.go`.
- **Router**: Registered the `agents.GET("/prompts")` route in
`internal/router/router.go`.
- **Logic**: Leveraged the existing `service.LoadPrompt` utility to read
`analyze_task_system`, `analyze_task_user`, `next_step`, `reflect`, and
`citation_prompt` templates directly from the `rag/prompts` directory.
- **Unit Test**: Added `TestGetPrompts_Success` to
`internal/handler/agent_test.go` to mock the HTTP context and validate
the JSON response structure.
### Motivation
This is part of the ongoing effort to port the Agent API surface to Go.
Since this specific endpoint only serves static prompt templates and
does not require the complex DAG/Canvas execution engine, it can be
seamlessly and safely handled by the Go backend.
### Testing
- [x] Added automated unit test `TestGetPrompts_Success` (verified
passing).
- [x] Tested locally via `curl` against the Go server (port 9380) and
Python server (port 9384).
- [x] Verified that the Go JSON response structure and loaded prompt
text are logically 100% identical to the Python implementation.
### What problem does this PR solve?
Fix: An error message appears when accessing the agent's launch page:
"pagesize exceeds maximum value".
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: balibabu <assassin_cike@163.com>
## Summary
This PR adds checkpoint/resume support for the GraphRAG
`extract_community` and `resolve_entities` stages.
The implementation stores successful intermediate results in the
document store so interrupted ingestion can resume without repeating
already-completed LLM work. Checkpoints are loaded before each stage,
reused when available, saved after successful batch/community
processing, and cleaned up after the stage completes successfully.
## Related Issue
Closes: #15518
## Change Type
- [x] Feature
- [x] Bug fix
- [x] Test
- [ ] Refactor
- [ ] Documentation
- [ ] Breaking change
## Real Behavior Proof
Validation commands run locally:
```bash
uv run python -m py_compile \
rag/graphrag/checkpoints.py \
rag/graphrag/general/community_reports_extractor.py \
rag/graphrag/entity_resolution.py \
rag/graphrag/general/index.py \
test/unit_test/rag/graphrag/test_checkpoints.py
```
Result:
```text
Passed
```
```bash
uv run pytest test/unit_test/rag/graphrag/test_checkpoints.py
```
Result:
```text
4 passed
```
```bash
uv run pytest \
test/unit_test/rag/graphrag/test_phase_markers.py \
test/unit_test/rag/graphrag/test_graphrag_utils.py \
test/unit_test/rag/graphrag/test_checkpoints.py
```
Result:
```text
95 passed
```
```bash
git diff --check
```
Result:
```text
Passed
```
## Checklist
- [x] Implemented checkpoint/resume support for `extract_community`.
- [x] Implemented checkpoint/resume support for `resolve_entities`.
- [x] Avoided touching unrelated API behavior.
- [x] Added unit tests for the new checkpoint helper logic.
- [x] Verified Python syntax compilation.
- [x] Ran related GraphRAG unit tests successfully.
- [x] Ran `git diff --check`.
- [ ] Ran full project test suite.
---------
Co-authored-by: Wang Qi <wangq8@outlook.com>
### What problem does this PR solve?
Display intl `base_url` for Tongyi-Qianwen
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
fix: resolve issue where some models do not use modelInfo parameter
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
OceanBase could start without the `ragflow` tenant, so RAGFlow failed to
connect with `root@ragflow`. This PR adds a safe startup reconcile step
and documents the required host limits before using OceanBase.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Documentation Update
## Summary
The embedding branch of `verify_api_key` was missing `await` on
`asyncio.wait_for(...)`, so valid embedding-only providers always failed
API-key verification.
## Root cause
`arr, tc = asyncio.wait_for(...)` (no `await`) returns a coroutine;
unpacking it raises `TypeError: cannot unpack non-iterable coroutine`,
which the `except` swallows as a failure. The chat branch (`await
asyncio.wait_for(check_streamly())`) and rerank branch (`arr, tc = await
asyncio.wait_for(...)`) already `await` correctly.
## Fix
```diff
- arr, tc = asyncio.wait_for(
+ arr, tc = await asyncio.wait_for(
asyncio.to_thread(mdl.encode, ["Test if the api key is available"]),
timeout=timeout_seconds,
)
```
## Files changed
- `api/apps/services/provider_api_service.py`
## Verification
- `ruff check` — clean
- Fix mirrors the already-correct chat/rerank branches in the same
function. Local full pytest not run (heavy RAG deps); CI validates.
## Note
Implemented with LLM assistance (model: claude-opus-4-8).
Closes#15619
Co-authored-by: dearsishs <MCarter112116@outlook.com>
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
`SearchService.get_detail` crashed with `AttributeError` (HTTP 500) when
no matching row existed, because it called `.first().to_dict()` before
the `if not search` guard — making that guard dead code.
## Root cause
`.first()` returns `None` when the query matches nothing (deleted search
app, or joined `User` not `VALID`). `None.to_dict()` raises before the
guard runs.
## Fix
```diff
.first()
- .to_dict()
)
if not search:
return {}
- return search
+ return search.to_dict()
```
Guard the `None` first, then serialize — restoring the intended `{}`
"not found" return that every caller (`search_api`, `bot_api`,
`chat_api`, `dataset_api_service`) already handles.
## Files changed
- `api/db/services/search_service.py`
## Verification
- `ruff check` — clean
- Logic: `.first()` → `None` now hits `return {}` instead of
`None.to_dict()`. Local full pytest not run (heavy RAG deps); CI
validates.
## Note
Implemented with LLM assistance (model: claude-opus-4-8).
Closes#15621
Co-authored-by: dearsishs <MCarter112116@outlook.com>
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Problem
`TestXiaomiNewModelWithCustomDefaultTransport` panics on Go 1.25:
```
panic: interface conversion: http.RoundTripper is models.roundTripperFunc, not *http.Transport
```
In Go 1.25, `http.DefaultTransport` is no longer `*http.Transport`, so
the unchecked type assertion in `NewXiaomiModel` panics when the test
replaces it with a `roundTripperFunc`.
## Fix
Use a safe type assertion with fallback to a new `http.Transport`,
matching the pattern already used in `modelscope.go`.
## Verification
```bash
go test -run TestXiaomiNewModelWithCustomDefaultTransport ./internal/entity/models/...
# PASS
```
Internal contributors only.
🤖 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?
`is_english()` in `rag/nlp/__init__.py` compiles a **single-character**
regex class and `fullmatch`es it against each item:
```python
pattern = re.compile(r"[`a-zA-Z0-9\s.,':;/\"?<>!\(\)\-]") # no quantifier
...
eng = sum(1 for t in texts if pattern.fullmatch(t.strip()))
```
For a **string** argument the text is first split into single characters
(`texts = list(texts)`), so each `fullmatch` sees one character and
works. But for a **list** argument each item is a whole multi-character
string, and `fullmatch` of a one-character pattern against a
multi-character string always fails — so `is_english()` returns `False`
for **any** list, regardless of content.
```python
is_english("This is English") # True (ok)
is_english(["The quick brown fox jumps.", "Hello world."]) # False (bug — should be True)
is_english(["这是中文。"]) # False (right answer, wrong reason)
```
Many call sites pass lists and were therefore silently always-`False`,
e.g.:
- `rag/llm/chat_model.py:1088`, `rag/llm/cv_model.py:168,1155` —
`is_english([ans])` when an answer is truncated at `max_tokens`, so an
English reply gets the Chinese "······由于长度的原因，回答被截断了，要继续吗？" continuation
suffix instead of the English one.
- `rag/app/book.py` — `remove_contents_table(...,
eng=is_english([...sections...]))`, so English books have their contents
table stripped in Chinese mode.
- `common/doc_store/es_conn_base.py:339`,
`rag/utils/opensearch_conn.py:733` — `is_english(txt.split())` in
highlight handling.
- plus `rag/app/qa.py`, `rag/flow/parser/utils.py`,
`common/doc_store/infinity_conn_base.py`.
### Fix
Add a `+` quantifier so an all-English multi-character item matches:
```python
pattern = re.compile(r"[`a-zA-Z0-9\s.,':;/\"?<>!\(\)\-]+")
```
The string path is unchanged (single characters still match) and
non-English lists still return `False`. Adds
`test/unit_test/rag/test_is_english.py`; the two list cases fail before
this change and pass after.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Used the Claude CLI while working on this.
### What problem does this PR solve?
Support model list for VolcEngine.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
## What problem does this PR solve?
Go test files are never compiled in CI — only production binaries via
`go build`. This allowed a missing `"sort"` import in
`metadata_filter_test.go` to be merged without detection.
## Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
## Changes
- Add `go test -count=1 ./internal/...` step after Go build in CI
workflow
- Fix missing `"sort"` import in `metadata_filter_test.go` (pre-existing
compile error)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
## Summary
Normalizes Qwen model-family names before reasoning extraction so
provider-prefixed Qwen models use the existing `<think>...</think>`
fallback.
## Summary
- keep MiniMax chat calls in non-streaming mode and streaming calls in
SSE mode
- make MiniMax model listing and connection checks use a bodyless GET
/v1/models
- add focused MiniMax request/response regression tests
### What problem does this PR solve?
**Verified from CLI**
```
RAGFlow(user)> chat with 'mimo-v2.5@test@xiaomi' message 'who r u'
Answer: Hello! I'm MiMo-v2.5, a large language model developed by Xiaomi's LLM Core Team. You can think of me as a friendly AI assistant ready to help you answer questions, have conversations, or work on creative tasks. My context window can handle up to 1 million tokens, so we can dive into pretty long discussions or documents if you'd like. What can I help you with today?
Time: 3.831830
RAGFlow(user)> stream chat with 'mimo-v2.5@test@xiaomi' message 'who r u'
Answer: there! I'm MiMo-v2.5, an AI assistant created by the Xiaomi LLM Core Team. I'm here to chat, help out, answer questions, or just have a friendly conversation. Think of me as a helpful buddy with a pretty big memory (1 million tokens worth!). What can I do for you today?😊
Time: 2.421630
RAGFlow(user)> think chat with 'mimo-v2.5@test@xiaomi' message 'who r u'
Thinking: The user is asking a simple question about who I am. According to my system prompt, I should:
- Identify myself as **MiMo-v2.5**
- State that I was developed by the **Xiaomi LLM Core Team**
- Answer in first person and be warm and conversational
Answer: Hey there! 👋
I'm **MiMo**, an AI assistant created by the **Xiaomi LLM Core Team**. Think of me as a friendly chat buddy who's here to help you with all sorts of questions and tasks!
I love having conversations, answering questions, brainstorming ideas, and helping people figure things out. Whether you want to chat, need help with something specific, or just want to explore ideas together — I'm here for it! 😊
What can I help you with today?
Time: 6.651589
RAGFlow(user)> tts with 'mimo-v2.5-tts@test@xiaomi' text 'hello? show yourself' play format 'wav' param '{"voice": "Chloe"}'
SUCCESS
RAGFlow(user)> asr with 'mimo-v2.5-asr@test@xiaomi' audio './internal/test.wav' param '{"language": "zh"}'
+------------------------------------------------------------------------------------------------------------------------+
| text |
+------------------------------------------------------------------------------------------------------------------------+
| 1 The examination and testimony of the experts enabled the commission to conclude that five shots may have been fired. |
+------------------------------------------------------------------------------------------------------------------------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
## Summary
- keep Moonshot chat calls in non-streaming mode and streaming calls in
SSE mode
- make Moonshot model listing and balance checks use bodyless GET
requests
- add focused Moonshot request/response regression tests
### What problem does this PR solve?
Fix LM-Studio provider connection verification so embedding checks await
the async wrapper correctly and log the full traceback on failures.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: Add a waiting status to the messages on the chat page.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
fix: Resolve error when checking pipeline parsing result
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Table parser metadata aggregation previously only ran when
`table_column_mode` was set to `manual`. In auto mode (default), all
columns default to `"both"` role, meaning they should also be aggregated
into document-level metadata for UI/chat filters. Additionally, the task
snapshot could be stale — `table_column_names` are written to KB
`parser_config` during `chunk()` but the task may have been created
before that.
Changes:
- Renames `aggregate_table_manual_doc_metadata` →
`aggregate_table_doc_metadata`
- Supports both `"manual"` and `"auto"` `table_column_mode` (defaults to
`"auto"`)
- Reloads `table_column_names` from KB DB when missing from task
snapshot
- Removes the manual-only guard in `task_executor` and refactored
`post_processor`
- Updates all tests with new function name and adds auto mode test cases
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
