## Summary
- Add tool call support for SiliconFlow, Qiniu, Huawei Cloud, and Jina
while consolidating shared OpenAI-compatible helpers used by Aliyun
- Handle streaming tool call deltas and advertise tool support for
eligible provider models
- Add cross-provider tool call tests and enable Qiniu connection
verification through the models endpoint
#16990
### Summary
As title
verif ied from CLI
```
RAGFlow(api/default)> asr with 'paraformer@test@funasr' audio './internal/test.wav' param '{"language": "en"}'
+----------------------------------------------------------------------------------------------------------------------+
| text |
+----------------------------------------------------------------------------------------------------------------------+
| The examination and testimony of the experts enabled the commission to conclude that five shots may have been fired. |
+----------------------------------------------------------------------------------------------------------------------+
```
---
<img width="2876" height="1377" alt="image"
src="https://github.com/user-attachments/assets/4cee62c6-1c71-43ce-b398-4d9fbff33c3c"
/>
```bash
INFO: 127.0.0.1:51910 - "POST /v1/audio/transcriptions HTTP/1.1" 200 OK██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 2.19it/s]
INFO: 127.0.0.1:60934 - "GET /v1/models HTTP/1.1" 200 OK%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 2.10it/s]
```
---------
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
### Summary
We have updated our model driver to work with go.
It is based on OpenAI-API-Compatible model provider.
Draft
#15519
Our old model provider
#13425
## 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.
After upgrading to v0.26.0, the Ollama provider returns an empty model
list because the Go rewrite uses `/api/ps` (only running models) instead
of `/api/tags` (all installed models). This PR changes the endpoint to
`/api/tags`, restoring the ability to list and add Ollama models.
Closes#16000
### 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?
**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
### 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.
### What problem does this PR solve?
remove old and add latest cohere models
### Type of change
- [x] Refactoring
- [x] Other (please describe): update models
add the newanthropic and voyage models. Strip opus 4.7 and 4.8 of
certain usnspported keys
Co-authored-by: Idriss Sbaaoui <112825897+6ba3i@users.noreply.github.com>
### What problem does this PR solve?
The Go GPUStack driver returned a stub error for `Embed()` even though
GPUStack exposes OpenAI-compatible embeddings on the **v1-openai** route
(not `v1/embeddings`).
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Added 4 new models:
deepseek-ai/DeepSeek-V4-Pro
deepseek-ai/DeepSeek-V4-Flash
Pro/moonshotai/Kimi-K2.6
Pro/zai-org/GLM-5.1
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
As title
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
`ReplicateModel.Rerank` in `internal/entity/models/replicate.go` was a
`"replicate, no such method"` stub. The chat path landed in #14958 and
the embed path in #15073; rerank is the last major retrieval surface
still missing on this provider.
Until this PR, a tenant who selected a Replicate reranker model got the
sentinel error on every rerank call.
Co-authored-by: sxxtony <sxxtony@users.noreply.github.com>
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Closes#15090.
Adds GiteeAI support to the Go model-provider layer so GiteeAI chat
models can be routed through the Go API server using the same
OpenAI-compatible chat, streaming, model listing, and connection-check
flow used by other SaaS providers.
GiteeAI is implemented as a separate provider from the existing `gitee`
provider.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
## Summary
- Added a GiteeAI Go model driver.
- Added the GiteeAI provider catalog with default base URL
`https://ai.gitee.com/v1`.
- Registered `giteeai` in the model factory separately from `gitee`.
- Added focused provider tests for sync chat, streaming chat, model
listing, connection checks, base URL override, SSE parsing, `[DONE]`
handling, and unsupported methods.
## What changed
- Implemented `ChatWithMessages` for `POST /chat/completions`.
- Implemented `ChatStreamlyWithSender` with SSE parsing, `delta`
extraction, `finish_reason`, `[DONE]`, and `<think>` tag handling.
- Implemented `ListModels` for `GET /models`.
- Implemented `CheckConnection` by delegating to `ListModels`.
- Returned standard `no such method` errors for unsupported embedding,
rerank, image-to-text, ASR, and TTS paths.
## Tests
```bash
go test -vet=off ./internal/entity/models -run 'TestGiteeAI' -count=1
go test -vet=off ./internal/entity -run 'Test.*Provider|Test.*Model' -count=1
```
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
This PR adds Qiniu provider integration for the Go model driver layer in
RAGFlow.
Supported capabilities:
- [X] Chat
- [X] Think Chat
- [X] Stream Chat
- [X] Stream Think Chat
- [X] Model listing
- [X] Provider configuration and factory registration
Verified examples from the CLI:
```
login user '***' password '***';
ADD PROVIDER 'qiniu';
CREATE PROVIDER 'qiniu' INSTANCE 'test' KEY '***';
chat with 'deepseek/deepseek-v3.1-terminus-thinking@test@qiniu' message
'hello';
think chat with 'deepseek/deepseek-v3.1-terminus-thinking@test@qiniu'
message 'hello';
stream chat with 'deepseek/deepseek-v3.1-terminus-thinking@test@qiniu'
message 'hello, what are you';
stream think chat with
'deepseek/deepseek-v3.1-terminus-thinking@test@qiniu' message 'hello,
what are you';
stream think chat with 'qwen3-max-2026-01-23@test@qiniu' message 'hello,
what are you';
LIST MODELS FROM 'qiniu' 'test';
```
### Type of change
- [X] New Feature
- [X] Provider integration
## Summary
- add the VolcEngine `models` URL suffix used by the existing Go
`ListModels` implementation
- return a clear error when the VolcEngine models suffix is missing
- add focused VolcEngine model-listing regression tests
## What changed
- Added `url_suffix.models` to `conf/models/volcengine.json`.
- Normalized the configured models suffix before building the request
URL.
- Covered config loading, successful model listing, upstream errors, and
missing suffix handling.
## Why
`VolcEngine.ListModels` already builds requests from `URLSuffix.Models`,
but the bundled VolcEngine config did not define that suffix. That left
the model-listing path unable to call the documented `/models` endpoint
from the existing provider config.
Fixes#14701
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
## Summary
- route hosted MinerU.Net and PaddleOCR.Net provider names to their
existing Go drivers
- add regression coverage for loading the hosted OCR provider configs
through ProviderManager
## What changed
- Added canonical provider-name aliases for the hosted OCR provider
display names.
- Covered both bundled configs with a focused provider-manager test.
## Why
The hosted provider configs use display names with `.Net`, while model
factory dispatch lowercases the provider name. Without aliases, those
configs fall through to `DummyModel` instead of using the existing
MinerU and PaddleOCR drivers.
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
## Summary
- Add LongCat model-list support through the documented
OpenAI-compatible models endpoint.
## What changed
- Add the LongCat `models` URL suffix for `/openai/v1/models`.
- Implement `ListModels` for the LongCat Go driver.
- Delegate `CheckConnection` to the lightweight model-list request.
- Add focused regression coverage for successful, malformed, oversized,
and missing-key responses.
## Why
LongCat documents a models endpoint under the OpenAI-compatible API
surface, but the Go driver still returned `no such method` for model
listing and connection checks.
## Validation
- `go test ./internal/entity/models -run TestLongCat -count=1`
- `go test -race ./internal/entity/models -run TestLongCat -count=1`
- `go test ./internal/entity -count=1`
- `git diff --check`
## Notes
- Related to the broader Go model provider tracking in #14736, but this
PR only handles LongCat model listing.
- `go test ./internal/entity/models -count=1` is currently blocked by an
unrelated Astraflow test panic outside this LongCat change.
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
## Summary
- add the xAI `models` URL suffix used by the existing Go `ListModels`
implementation
- return a clear error when the xAI models suffix is missing
- add focused xAI model-listing and connection-check regression tests
## What changed
- Added `url_suffix.models` to `conf/models/xai.json`.
- Normalized the configured models suffix before building the request
URL.
- Covered config loading, successful model listing, upstream errors,
API-key validation, missing suffix handling, and `CheckConnection`
delegation.
## Why
`XAIModel.ListModels` already builds requests from `URLSuffix.Models`,
and `CheckConnection` delegates to that method. The bundled xAI config
did not define that suffix, which left the model-listing path unable to
call the provider `/models` endpoint from the existing provider config.
## Validation
- `go test ./internal/entity/models -run TestXAI -count=1`
- `go test ./internal/entity -count=1`
- `git diff HEAD~1..HEAD --check`
## Notes
- `go test ./internal/entity/models -count=1` currently fails in
unchanged Astraflow coverage: `TestAstraflowEmbedReturnsNoSuchMethod`
panics before reaching any xAI assertions.
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
implement provider `OrcaRouter`
**The following functionalities are now supported:**
**Cohere:**
- [x] Chat / Think Chat / Stream Chat / Stream Think Chat
- [x] Model listing
- [x] TTS
- [ ] Balance
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
Closes#15040.
ModelScope was listed unchecked in the Go-rewrite tracker #14736 and
already had an llm_factories.json entry (tags: LLM) but no Go driver, so
the new Go API server could not route ModelScope instances. The Python
side has supported it through the OpenAI-compatible base at
rag/llm/chat_model.py:618 (ModelScopeChat), which requires a
user-supplied base URL and appends /v1.
This adds:
- internal/entity/models/modelscope.go: self-hosted OpenAI-compatible
driver with chat (sync + SSE stream with idle-timeout cancellation),
list_models, and check_connection. Auth header is optional, matching the
xinference pattern, so deployments without auth and auth-enabled
deployments both work. Base URL is normalized so users can configure
either the root endpoint or the /v1 endpoint.
- internal/entity/models/modelscope_test.go: 12 tests covering name, URL
normalization, factory routing, chat happy path / auth header /
reasoning_content extraction, stream happy path / stream=false rejection
/ idle cancellation, list_models + check_connection, missing-base-URL
clear error, and the no-such-method sentinels.
- conf/models/modelscope.json: shipped config (class: "local",
url_suffix v1/chat/completions and v1/models).
- internal/entity/models/factory.go: case "modelscope" →
ModelScopeModel.
- internal/service/llm.go: ModelScope added to the selfDeployed map
alongside Ollama, Xinference, LocalAI, LM-Studio, GPUStack — the Python
side requires user-supplied URL with no default, so the Go side
classifies it the same way.
Follow-on issues will add Embed and Rerank, in line with how Novita,
NVIDIA, TogetherAI, and other providers landed method-by-method.
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
This PR adds HuaweiCloud provider integration in RAGFlow.
Supported capabilities:
- [x] Chat / Think Chat / Stream Chat / Stream Think Chat
- [x] Embedding
- [x] Rerank
- [x] Model listing
- [x] Provider connection checking
Verified examples from the CLI:
```
check instance 'test' from 'HuaweiCloud';
chat with 'deepseek-v4-flash@test@HuaweiCloud' message 'hello';
think chat with 'deepseek-v4-flash@test@HuaweiCloud' message 'hello';
stream chat with 'deepseek-v4-flash@test@HuaweiCloud' message 'hello';
stream think chat with 'deepseek-v4-flash@test@HuaweiCloud' message
'hello';
embed text 'what is rag' 'who are you' with 'bge-m3@test@HuaweiCloud'
dimension 1024;
rerank query 'what is rag' document 'rag is retrieval augmented
generation' 'rag need llm' 'famous rag
project includes ragflow' with 'bge-reranker-v2-m3@test@HuaweiCloud' top
3;
list supported models from 'HuaweiCloud' 'test';
LIST MODELS FROM 'HuaweiCloud' 'test';
```
### Type of change
- [x] New Feature
- [x] Provider integration
## Summary
Closes#15165.
Implements the AWS Bedrock model provider for the Go API server, tracked
under #14736. Adds Converse + Converse-Stream chat and foundation-model
listing, with SigV4 signing over a hand-rolled `net/http` path that
matches the established pattern in `internal/entity/models/` (no new
direct `go.mod` deps).
## Linked tracker
Tracked under #14736 (Implement model providers of RAGFlow API server in
Go). Closes#15165.
### What problem does this PR solve?
The Go DeepInfra driver returned a stub error for `Rerank()` even though
DeepInfra serves reranker models at `POST /v1/inference/{model}` with
`query`, `documents`, and a `scores[]` response.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Co-authored-by: Cursor <cursoragent@cursor.com>
### What problem does this PR solve?
Add a Go driver for **FuturMix** (https://futurmix.ai/docs), one of the
unchecked providers on the umbrella tracking issue #14736. FuturMix is
documented as an "OpenAI-compatible API" aggregator over Claude / GPT /
Gemini / DeepSeek (~22 models per their `/models` page).
Until this PR, a tenant who configured `futurmix` as a model provider in
the Go layer fell through to the default branch of
`internal/entity/models/factory.go` and got the dummy driver.
---------
Co-authored-by: sxxtony <sxxtony@users.noreply.github.com>
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Closes#15142.
ZhipuAI lists `glm-ocr` as an OCR model, but the Go driver still
returned `no such method` from `OCRFile`. This wires the advertised
model to Z.AI's documented `layout_parsing` endpoint and returns the
`md_results` Markdown output through the existing `OCRFileResponse.Text`
field.
This PR also adds focused tests for URL input, raw file-content base64
input, and validation errors.
### 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):
### Test
- [x] `go test -vet=off ./internal/entity/models -run
'TestZhipuAIOCRFile'`
### What problem does this PR solve?
IDK how to implement **`Ollama`** on #14580 but it's totally wrong.
This is the rewrite version for **`Ollama`**
**Verified from CLI**
```
# Embed
RAGFlow(user)> embed text 'what is rag' 'who are you' with 'nomic-embed-text:latest@test12@ollama' dimension 1024;
+-----------+-------+
| dimension | index |
+-----------+-------+
| 768 | 0 |
| 768 | 1 |
+-----------+-------+
# Chat
RAGFlow(user)> think chat with 'qwen3:0.6b@test12@ollama' message 'who r u'
Thinking: Okay, the user asked, "Who r u?" I need to respond appropriately. First, I should acknowledge their question. Since I'm an AI, I don't have a physical form, but I can confirm that I'm a large language model. I should keep the response friendly and offer help. Let me make sure I'm not making up any information and that the response is natural. Also, I should check for any typos and ensure clarity. Alright, that should cover it.
Answer: I'm an AI language model, and I don't have a physical form. However, I can tell you that I'm designed to assist with questions and tasks. How can I help you today?
Time: 2.914285
RAGFlow(user)> stream think chat with 'qwen3:0.6b@test12@ollama' message 'who r u'
Thinking: , the user asked, "Who are you?" I need to respond appropriately. Since I'm an AI assistant, I should mention that I don't have a physical form or a mind. I should also clarify that I can help with various tasks like answering questions or providing information. It's important to keep the response friendly and informative while maintaining the correct tone.
Answer: don't have a physical form or a mind, but I'm here to help with your questions or tasks! What can I do for you today?
Time: 1.740047
# LisyModels
RAGFlow(user)> list supported models from 'ollama' 'test12'
+-------------------------+
| model_name |
+-------------------------+
| nomic-embed-text:latest |
| qwen3:0.6b |
+-------------------------+
```
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
### What problem does this PR solve?
Implement embed for Tencent Hunyuan
**Verified from CLI**
```
RAGFlow(user)> embed text 'what is rag' 'who are you' with 'hunyuan-embedding@test1@hunyuan' dimension 16;
+-----------+-------+
| dimension | index |
+-----------+-------+
| 1024 | 0 |
| 1024 | 1 |
+-----------+-------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
Go: implement provider: PaddleOCR_Local
**Verified from CLI**
```
RAGFlow(user)> ocr with 'PaddleOCR-VL@test@paddleocr_local' file './internal/test1.jpg'
+----------------------+
| text |
+----------------------+
| ## Parallel to these |
+----------------------+
```
### Type of change
- [X] Bug Fix (non-breaking change which fixes an issue)
- [X] New Feature (non-breaking change which adds functionality)
- [X] Refactoring
## Summary
- Adds a `Hunyuan` Go driver so the new API server can route Tencent
Hunyuan chat instances (registered in `conf/llm_factories.json:3830` as
`Tencent Hunyuan`). Follows the same SaaS-driver shape used for
Astraflow, Avian, Novita, TogetherAI, Replicate, DeepInfra, Upstage, and
LongCat.
Closes#15087
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Closes#15102.
OpenAI's Go provider config advertises `whisper-1` as ASR and `tts-1` as
TTS, but the Go driver returned `openai, no such method` for both audio
paths and did not define `url_suffix.asr` / `url_suffix.tts`.
This PR:
- adds OpenAI audio URL suffixes for `audio/transcriptions` and
`audio/speech`
- implements non-streaming `TranscribeAudio` using multipart form
uploads
- implements non-streaming `AudioSpeech` using the OpenAI speech JSON
request shape
- keeps streaming TTS explicitly unsupported instead of sending binary
audio through the text SSE sender
- adds focused tests for config coverage, ASR/TTS request shape,
required TTS voice validation, and unsupported streaming TTS
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
