### What problem does this PR solve?
Feat: add local & ssh provider in admin panel
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.25.3 to v0.25.4
- 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
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.25.2 to v0.25.3
- 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
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.25.1 to v0.25.2
- 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
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.25.0 to v0.25.1
- 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
## Add Astraflow Provider Support
This PR integrates [Astraflow](https://astraflow.ucloud.cn/) (by UCloud
/ 优刻得) as a new AI model provider in RAGFlow, with support for both
global and China endpoints.
### About Astraflow
Astraflow is an OpenAI-compatible AI model aggregation platform
supporting 200+ models from major providers including DeepSeek, Qwen,
GPT, Claude, Gemini, Llama, Mistral, and more.
| Variant | Factory Name | Endpoint | Env Var |
|---------|-------------|----------|---------|
| Global | `Astraflow` | `https://api-us-ca.umodelverse.ai/v1` |
`ASTRAFLOW_API_KEY` |
| China | `Astraflow-CN` | `https://api.modelverse.cn/v1` |
`ASTRAFLOW_CN_API_KEY` |
- **API key signup**: https://astraflow.ucloud.cn/
---
### Files Changed
| File | Change |
|------|--------|
| `rag/llm/__init__.py` | Register `Astraflow` and `Astraflow-CN` in
`SupportedLiteLLMProvider` enum, `FACTORY_DEFAULT_BASE_URL`, and
`LITELLM_PROVIDER_PREFIX` |
| `rag/llm/chat_model.py` | Add `AstraflowChat` and `AstraflowCNChat`
(OpenAI-compatible `Base` subclass) |
| `rag/llm/embedding_model.py` | Add `AstraflowEmbed` and
`AstraflowCNEmbed` (subclasses of `OpenAIEmbed`) |
| `rag/llm/rerank_model.py` | Add `AstraflowRerank` and
`AstraflowCNRerank` (subclasses of `OpenAI_APIRerank`) |
| `rag/llm/cv_model.py` | Add `AstraflowCV` and `AstraflowCNCV`
(subclasses of `GptV4`) |
| `rag/llm/tts_model.py` | Add `AstraflowTTS` and `AstraflowCNTTS`
(subclasses of `OpenAITTS`) |
| `rag/llm/sequence2txt_model.py` | Add `AstraflowSeq2txt` and
`AstraflowCNSeq2txt` (subclasses of `GPTSeq2txt`) |
| `conf/llm_factories.json` | Register `Astraflow` and `Astraflow-CN`
factories with a curated list of popular models |
---
### Supported Model Types
- ✅ **Chat / LLM** — DeepSeek-V3/R1, Qwen3, GPT-4o/4.1, Claude 3.5/3.7,
Gemini 2.0/2.5 Flash, Llama 3.3/4, Mistral, and 200+ more
- ✅ **Text Embedding** — text-embedding-3-small/large
- ✅ **Image / Vision (IMAGE2TEXT)** — GPT-4o, GPT-4.1, Claude, Gemini,
Llama-4, etc.
- ✅ **Text Re-Rank**
- ✅ **TTS** — tts-1
- ✅ **Speech-to-Text (SPEECH2TEXT)** — whisper-1
### Implementation Notes
- Uses the `openai/` LiteLLM prefix — consistent with other
OpenAI-compatible aggregation platforms (SILICONFLOW, DeerAPI, CometAPI,
OpenRouter, n1n, Avian, etc.)
- `Astraflow` (global, rank 250) and `Astraflow-CN` (China, rank 249)
are separate factory entries, allowing users to choose the optimal
endpoint based on their region.
- All model classes cleanly subclass existing base classes (`Base`,
`OpenAIEmbed`, `OpenAI_APIRerank`, `GptV4`, `OpenAITTS`, `GPTSeq2txt`)
with no custom logic needed — the provider is fully OpenAI-compatible.
---------
Co-authored-by: user <user@xzaaaMacBook-Air.local>
### What problem does this PR solve?
Refactor /api/v1/chats to be more RESTful.
### Type of change
- [x] Refactoring
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.24.0 to v0.25.0
- 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
### What problem does this PR solve?
This fixes two broken internal documentation links in the guides:
- `docs/develop/mcp/launch_mcp_server.md` linked
`./acquire_ragflow_api_key.md`, but the target page lives one level up
as `../acquire_ragflow_api_key.md`.
- `docs/guides/dataset/run_retrieval_test.md` linked
`./construct_knowledge_graph.md`, but the actual page lives under
`./advanced/construct_knowledge_graph.md`.
These broken links make it harder to follow the MCP and retrieval-test
docs from the local docs tree.
### Type of change
- [ ] 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):
### What problem does this PR solve?
Adds Perplexity contextualized embeddings API as a new model provider,
as requested in #13610.
- `PerplexityEmbed` provider in `rag/llm/embedding_model.py` supporting
both standard (`/v1/embeddings`) and contextualized
(`/v1/contextualizedembeddings`) endpoints
- All 4 Perplexity embedding models registered in
`conf/llm_factories.json`: `pplx-embed-v1-0.6b`, `pplx-embed-v1-4b`,
`pplx-embed-context-v1-0.6b`, `pplx-embed-context-v1-4b`
- Frontend entries (enum, icon mapping, API key URL) in
`web/src/constants/llm.ts`
- Updated `docs/guides/models/supported_models.mdx`
- 22 unit tests in `test/unit_test/rag/llm/test_perplexity_embed.py`
Perplexity's API returns `base64_int8` encoded embeddings (not
OpenAI-compatible), so this uses a custom `requests`-based
implementation. Contextualized vs standard model is auto-detected from
the model name.
Closes#13610
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
### What problem does this PR solve?
This PR adds support for parsing PDFs through an external Docling
server, so RAGFlow can connect to remote `docling serve` deployments
instead of relying only on local in-process Docling.
It addresses the feature request in
[#13426](https://github.com/infiniflow/ragflow/issues/13426) and aligns
with the external-server usage pattern already used by MinerU.
### Type of change
- [ ] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
### What is changed?
- Add external Docling server support in `DoclingParser`:
- Use `DOCLING_SERVER_URL` to enable remote parsing mode.
- Try `POST /v1/convert/source` first, and fallback to
`/v1alpha/convert/source`.
- Keep existing local Docling behavior when `DOCLING_SERVER_URL` is not
set.
- Wire Docling env settings into parser invocation paths:
- `rag/app/naive.py`
- `rag/flow/parser/parser.py`
- Add Docling env hints in constants and update docs:
- `docs/guides/dataset/select_pdf_parser.md`
- `docs/guides/agent/agent_component_reference/parser.md`
- `docs/faq.mdx`
### Why this approach?
This keeps the change focused on one issue and one capability (external
Docling connectivity), without introducing unrelated provider-model
plumbing.
### Validation
- Static checks:
- `python -m py_compile` on changed Python files
- `python -m ruff check` on changed Python files
- Functional checks:
- Remote v1 endpoint path works
- v1alpha fallback works
- Local Docling path remains available when server URL is unset
### Related links
- Feature request: [Support external Docling server (issue
#13426)](https://github.com/infiniflow/ragflow/issues/13426)
- Compare view for this branch:
[main...feat/docling-server](https://github.com/infiniflow/ragflow/compare/main...spider-yamet:ragflow:feat/docling-server?expand=1)
##### Fixes [#13426](https://github.com/infiniflow/ragflow/issues/13426)
### What problem does this PR solve?
Standardize term capitalization in `deploy_local_llm.mdx` and improve
code block formatting.
### Type of change
- [x] Documentation Update
…ff publishing this guide.
### What problem does this PR solve?
Removed failsure mode checklist per your request. @JinHai-CN
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
This PR adds a new guide: **"RAG failure modes checklist"**.
RAG systems often fail in ways that are not immediately visible from a
single metric like accuracy or latency. In practice, debugging
production RAG applications requires identifying recurring failure
patterns across retrieval, routing, evaluation, and deployment stages.
This guide introduces a structured, pattern-based checklist (P01–P12) to
help users interpret traces, evaluation results, and dataset behavior
within RAGFlow. The goal is to provide a practical way to classify
incidents (e.g., retrieval hallucination, chunking issues, index
staleness, routing misalignment) and reason about minimal structural
fixes rather than ad-hoc prompt changes.
The change is documentation-only and does not modify any code or
configuration.
Refs #13138
### Type of change
- [ ] 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):
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.23.1 to v0.24.0
- 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
### What problem does this PR solve?
Proofread the Sandbox Specification document and moved it to a dedicated
folder outside of the original docs.
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
### Type of change
- [ ] Bug Fix (non-breaking change which fixes an issue)
- [ ] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [x] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
### What problem does this PR solve?
Refact: update description for max_token in embedding #12792
### Type of change
- [x] Refactoring
Co-authored-by: Liu An <asiro@qq.com>
### What problem does this PR solve?
```
$ python admin/client/ragflow_cli.py -t user -u aaa@aaa.com -p 9380
ragflow> list datasets;
ragflow> list default models;
ragflow> show version;
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
