### What problem does this PR solve?
This PR adds Google BigQuery as a first-class data source connector in
RAGFlow.
It enables users to ingest and sync BigQuery data using the same
row-to-document model used by relational database connectors: selected
content columns become document text, metadata columns become document
metadata, an optional ID column provides stable document IDs, and an
optional timestamp column enables cursor-based incremental sync.
The connector supports service-account JSON credentials, table mode,
custom query mode, GoogleSQL queries, cursor-based incremental sync,
deleted-row pruning support, configurable query limits such as
`maximum_bytes_billed`, dry-run validation, batch loading, stable
document IDs, and BigQuery-aware value serialization.
### What problem does this PR solve?
Feat:
- Allow upsert model_type for instance model
Fix:
- Allow create instance with duplicate api_key
### 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?
FIx replicate model provider failing with valid api key
### 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?
Support factory models with multiple model types, so visual chat models
can be exposed as both image2text and chat while preserving the database
model-type-per-record design.
This also updates the SILICONFLOW model list and adds a helper script to
refresh SiliconFlow models from the provider API.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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?
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?
Support model list for VolcEngine.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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?
Feat：
- Get model list from remote provider.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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?
Not display `success` when check not passed.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix:
- Verify provider with empty llm list in llm_factories.json
- Set search bot's chat_llm_name, use tenant default chat model as
default
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix:
- Handle siliconflow and siliconflow_intl api_key
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix:
- Use @ to avoid split by `_` in model_name.
- Verify api_key when add instance.
- Pop api_key in list intances response.
- Remove useless index.
- Sort providers, instances and models by name.
- Get `is_tools` from llm_factories.json
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Python implementation of the Go-based model_provider API suite.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: bill <yibie_jingnian@163.com>
