### Summary
Brings both halves of the Tenki sandbox provider onto current SDKs and
removes `project_id`, which Tenki deleted from its API.
**Go:** `github.com/LuxorLabs/tenki-sdk-go/sandbox` `v0.5.2` → `v0.7.0`
(current latest).
**Python:** the provider's SDK was renamed on PyPI — `tenki-sandbox` is
frozen at 0.4.0 and everything from 0.5 ships as
[`tenki`](https://pypi.org/project/tenki/). The docs told operators to
`pip install tenki-sandbox`, which installs a stale SDK that no longer
matches this provider's expectations.
**`project_id` is gone.** Tenki removed project scoping from the sandbox
API in 0.5.x: `Client.create()` no longer accepts `project_id`, so the
current code path would raise `TypeError` against a current SDK. It was
also marked `required: True` in the config schema, so the Admin >
Sandbox Settings form asked for a value that no longer exists.
## 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>
### What problem does this PR solve?
Fixes#17623 by updating the retrieval API response example to use
`dataset_id`, matching the actual `POST /api/v1/retrieval` response
field and the implementation mapping from internal `kb_id`.
Co-authored-by: Codex <codex@openai.com>
### Summary
Adds a `tenki` sandbox provider that runs each agent code execution in a
disposable Tenki (https://tenki.cloud) microVM (create → exec → destroy,
no volumes or snapshots).
Registration mirrors PR #15039, configure `api_key` and `project_id` in
Admin > Sandbox Settings.
Both runtimes are covered:
- Python: `agent/sandbox/providers/tenki.py` (structured results +
artifact collection).
- Go: `internal/agent/sandbox/tenki.go`, mirroring the e2b provider and
wired into the provider manager.
`tenki-sandbox` is an optional dependency (it requires `protobuf>=6.31`,
which differs from RAGFlow's pinned gRPC stack), lazily imported with a
clear error when missing; installation is documented in the sandbox
quickstart.
Unit tests cover execution, structured results, artifacts
(symlink/size/extension limits), non-zero exit, timeout, error mapping,
and idempotent destroy.
---------
Co-authored-by: yiming.wang <yiming.wang@luxor.com>
## 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
Most files in `docs/guides/agent/agent_component_reference/` are `.mdx`,
but `begin` and
`message` are `.md`. Four links use the `.mdx` extension for those two,
so Docusaurus cannot
resolve the reference and they render as broken links.
Co-authored-by: Muhammad Zuhaib Zahid <288755265+muhzuhaib@users.noreply.github.com>
### 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>
Follow-up from #13896Fixes#13840
### What problem does this PR solve?
In #13896, only the docker-compose-base.yml was adjusted. However, in
the Helm chart, the unmaintained minio/minio image is still referenced.
This PR syncs the Helm chart with the docker compose setup again.
I also added a line to AGENTS.md, so agents should know to do this
automatically in the future.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [ ] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.26.0 to v0.26.1
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
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?
Syncs the /api/v1/chat/completions docs with the current behavior,
including the new legacy streaming mode.
### Type of change
- [x] Documentation Update
