## What
This pull request adds **MWS GPT Model Hub** as a built-in model
provider in RAGFlow.
The integration allows users to configure an MWS project endpoint and
token, discover the models available to that project, and use supported
MWS models for chat completion, embeddings, and reranking.
Co-authored-by: ilarionov_n <ilarionov_n@promis.ru>
### Summary
The **aimlapi.com** provider added in #17311 does not identify itself on
any of its outgoing requests, so its traffic cannot be attributed to the
integration. This PR adds the two headers AIMLAPI expects —
`X-AIMLAPI-Source` and `X-AIMLAPI-Partner-ID` — to every request the
provider makes.
## Summary
GreenPT is a European AI provider with an OpenAI-compatible API,
optimized infrastructure, and datacenters powered by 100% renewable
energy.
This adds native GreenPT support across RAGFlow’s Go-first provider
system and its Python compatibility layer:
- discovers the current catalog from `GET /v1/models`
- features `glm-5.2` and `kimi-k2.7-code` for chat and coding
- supports `green-embedding` through `/v1/embeddings`
- supports `green-rerank` through `/v1/rerank`
- supports `green-s` and `green-s-pro` speech-to-text through
`/v1/listen`
- adds provider configuration, UI icon, and supported-provider
documentation
### Summary
This PR adds **aimlapi.com** as a model provider, so a RAGFlow user can
enter one API key in the model settings and use AIMLAPI's models across
the app. AIMLAPI ([aimlapi.com](https://aimlapi.com)) is an
OpenAI-compatible aggregator that serves 700+ models (LLM, embedding,
vision, TTS, ASR) from many providers behind a single API.
The change mirrors the repo's existing "add provider" pattern (e.g.
FuturMix / OpenRouter): provider logic lives in the same files those
providers use, and shared / UI files get only registration entries.
**Backend**
- `conf/llm_factories.json` — the `aimlapi.com` factory entry.
- `rag/llm/__init__.py`, `rag/llm/{chat,embedding,cv}_model.py` —
LiteLLM adapters (chat, embedding, image2text) with a production base
URL, overridable via `AIMLAPI_API_URL`.
- `rag/llm/model_meta.py` — an `AIMLAPI` model-meta so the provider
lists its full `/v1/models` catalog dynamically (classified by the
endpoint `type`), the same way OpenRouter does.
- `api/apps/restful_apis/aimlapi_api.py` — an optional "Get API key"
flow using AIMLAPI's agent-authorization (OAuth 2.0 Device Authorization
Grant, RFC 8628). The device code is kept server-side (Redis); only the
issued key reaches the browser.
**Frontend (`web/`)**
- Provider registration (constant, icon allowlist, brand logo), the
model picker (`LIST_MODEL_PROVIDERS` + a `buildLocalConfig` entry), and
the "Get API key" button in the provider dialog. Locales added to `en`
and `zh`.
**Configuration** — production defaults are compiled in; endpoints and
the partner id are overridable through `AIMLAPI_*` environment
variables, so the same build works across environments.
**Testing** — the `web` build passes; chat, embedding and dynamic model
listing were smoke-tested against the live API.
### 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
Adds FunASR as a self-hosted speech-to-text provider through its
OpenAI-compatible `/v1/audio/transcriptions` endpoint.
This is a focused replacement for #15526 by @Rene0422 and relates to
#15448. The unrelated Markdown parser changes from the previous branch
are intentionally removed so this PR contains only the FunASR provider
integration.
- register FunASR as a `SPEECH2TEXT` factory;
- add `FunASRSeq2txt` with `sensevoice` and `http://localhost:8000/v1`
defaults, an optional API key, URL normalization, and inherited
transcription handling;
- wire FunASR into the current local-provider schema with a prefilled
local URL and official documentation link;
- discover the server's `/v1/models` dynamically and expose every
returned model as speech-to-text in the model picker;
- use RAGFlow's existing default provider icon fallback instead of
referencing a missing `funasr` asset;
- list FunASR in the supported-provider documentation;
- add focused backend and frontend regression tests.
### Validation
- focused backend pytest suite -> `7 passed`
- real CPU `funasr-server` + RAGFlow provider smoke test -> discovered
`fun-asr-nano`, `sensevoice`, and `paraformer`; transcribed a real WAV
as `我现在在录一段测试音频` (`10` tokens, `0.504s`)
- `ruff check` and `ruff format --check` on the changed Python files
- `python3 -m py_compile` on the provider and its test
- JSON parse and a semantic assertion for exactly one enabled FunASR
`SPEECH2TEXT` factory
- focused frontend Jest test -> `2 passed`
- ESLint and Prettier on all changed TypeScript files
- `npm run build` -> production build succeeded (`14,181` modules
transformed)
- `git diff --check`
### Deployment
Run FunASR separately and point the RAGFlow provider at it:
```bash
pip install funasr
funasr-server --device cuda --model sensevoice
```
The API key remains optional because the stock local server does not
require authentication. A key can still be supplied when the endpoint is
protected by a gateway.
---------
Signed-off-by: LauraGPT <LauraGPT@users.noreply.github.com>
Co-authored-by: LauraGPT <LauraGPT@users.noreply.github.com>
## Summary
Add support for **"New API"** as a model provider, enabling connection
to [New API](https://github.com/QuantumNous/new-api) /
[one-api](https://github.com/songquanpeng/one-api) compatible gateways
that aggregate multiple LLM backends behind a unified OpenAI-compatible
`/v1` endpoint.
### Features
- **All model types**: Chat, Embedding, Rerank, Image2Text, TTS,
Speech2Text
- **List Models discovery**: `NewAPI(OpenAIAPICompatible)` class in
`model_meta.py` queries the gateway's `/v1/models` to auto-discover
available models via the native `GET /api/v1/providers/<name>/models`
endpoint
- **Model parameter editing**: Pencil icon on each discovered model row
to edit `model_type`, `max_tokens`, and `features` (e.g. tool call
support) before submitting
- **Custom model addition**: "Add Custom Model" button at the bottom of
the List Models dropdown for models not returned by the API
- **Gear icon settings**: Enabled the Settings gear button on provider
instances to manage models on existing instances (viewMode)
- **viewMode credential passthrough**: Fixed List Models in viewMode —
merges `initialValues` credentials when `api_key`/`base_url` fields are
hidden by `hideWhenInstanceExists`
### Changes
**Backend** (8 files):
- `rag/llm/chat_model.py` — `NewAPIChat(Base)` class
- `rag/llm/embedding_model.py` — `NewAPIEmbed(OpenAIEmbed)` class (no
auto `/v1` append)
- `rag/llm/rerank_model.py` — `NewAPIRerank(Base)` class (uses `/rerank`
endpoint)
- `rag/llm/cv_model.py` — `NewAPICv(GptV4)` class
- `rag/llm/tts_model.py` — `NewAPITTS(OpenAITTS)` class
- `rag/llm/sequence2txt_model.py` — `NewAPISeq2txt(GPTSeq2txt)` class
- `rag/llm/model_meta.py` — `NewAPI(OpenAIAPICompatible)` class for List
Models discovery
- `conf/llm_factories.json` — New API factory entry with all model type
tags
**Frontend** (8 files + 1 new SVG):
- `web/src/assets/svg/llm/new-api.svg` — New API logo icon
- `web/src/constants/llm.ts` — `LLMFactory.NewAPI` enum + `IconMap`
entry
- `web/src/components/svg-icon.tsx` — `NewAPI` added to `svgIcons`
-
`web/src/pages/user-setting/setting-model/modal/provider-modal/field-config/local-llm-configs.ts`
— New API `buildLocalConfig`
-
`web/src/pages/user-setting/setting-model/modal/provider-modal/constants.ts`
— `LIST_MODEL_PROVIDERS` includes NewAPI
- `web/src/pages/user-setting/setting-model/components/used-model.tsx` —
Enable Settings gear button
-
`web/src/pages/user-setting/setting-model/modal/provider-modal/hooks/use-list-models-picker.ts`
— viewMode credential merge + model editing state/handlers
-
`web/src/pages/user-setting/setting-model/modal/provider-modal/hooks/use-list-models-options.tsx`
— Pencil edit icon per model row
-
`web/src/pages/user-setting/setting-model/modal/provider-modal/index.tsx`
— `AddCustomModelDialog` import + edit dialog rendering
**Note on Go implementation**: A Go model driver (`NewAPIModel`
delegating to `OpenAIModel`) has been prepared but is deferred until the
Go runtime is enabled in a future release (current v0.26.0 images use
`API_PROXY_SCHEME=python` and do not compile Go binaries). Will submit
as a follow-up PR.
## Related
- Depends on: #15996 (provider instance API improvements — server-side
credential lookup, idempotent `add_model`, security fixes — required for
viewMode gear icon and batch model submission)
## Test plan
- [ ] Add New API provider with api_key and base_url pointing to an
OpenAI-compatible gateway
- [ ] Click "List Models" — should discover and display available models
from `/v1/models`
- [ ] Click pencil icon on a model — should open edit dialog to change
model_type, max_tokens, features
- [ ] Select multiple models and click OK — should add all selected
models
- [ ] Click gear icon on the added instance — should open viewMode with
List Models working
- [ ] In viewMode, select new models including pre-existing ones, click
OK — should succeed (requires #15996)
- [ ] Verify all model types work: create a Chat assistant, Embedding
KB, Rerank setting
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Tim Wang <wanghualoong@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
## Summary
LocalAI exposes two API surfaces with conflicting naming conventions:
- `GET /api/tags` returns model names with `:latest` suffix (Ollama
format)
- `POST /v1/chat/completions` expects names without `:latest` (OpenAI
format)
RAGFlow discovered models via `/api/tags` and stored the tagged name,
then used it with `/v1/chat/completions`, causing a 404 error because
LocalAI didn't recognize `model:latest`.
## Fix
In `LocalAI.get_model_list()`, strip the tag suffix from model names
using `model["name"].rsplit(":", 1)[0]`, so stored names match what the
OpenAI-compatible endpoints expect.
### 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?
This PR adds `ModelMeta` implementations for four additional LLM/RAG
ecosystem platforms, building on the ModelMeta infrastructure introduced
in #15711.
Currently, only `Ollama` and `VolcEngine` have `ModelMeta` classes that
enable remote model list fetching. This PR extends that support to four
more platforms.
### Changes
Added four new `ModelMeta` subclasses in `rag/llm/model_meta.py`:
| Platform | `_FACTORY_NAME` | Has model list | Has full model info |
Approach |
|----------|-----------------|----------------|---------------------|----------|
| **Xinference** | `"Xinference"` | ✅ | ✅ | Parses `model_type` and
`context_length` from `/v1/models` response. Maps 6 model types
(LLM/embedding/rerank/image/TTS/speech2text). |
| **LocalAI** | `"LocalAI"` | ✅ | ✅ | Uses Ollama-compatible `GET
/api/tags` + `POST /api/show` endpoints. Returns capabilities
(completion/embedding/vision/tools/thinking) and
`general.context_length`. |
| **BaiduYiyan** | `"BaiduYiyan"` | ✅ | ✅ | Uses Qianfan SDK static
model catalog + `get_model_info()` for `max_input_tokens`. Returns 60
models (56 chat + 4 embedding) with real context lengths. |
| **Tencent Cloud** | `"Tencent Cloud"` | ❌ | ❌ | `NotImplementedError`
— uses SDK-based SID/SK HMAC signing, no model list REST API available.
|
All classes are automatically discovered and registered via the existing
`__init__.py` mechanism — no additional configuration needed.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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)
