### 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
Improve the UX of the **"Delimiter for text"** field on the dataset
configuration page. The field is a single string with a backtick-based
mini-syntax, but both the tooltip and the surrounding UI failed to
surface what delimiters the backend would actually derive from a given
value — leaving users to discover by trial-and-error that the same
string produces different splits depending on file type (see #7436,
#4704, #9680).
### 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.
### What problem does this PR solve?
Fix Infinity compatibility issues in knowledge compilation.
This change:
- Stores compilation source ID lists as JSON arrays in Infinity.
- Parses JSON array fields when reading compiled documents.
- Uses `json_contains` for filtering JSON array fields.
- Adds the missing `name` column to the Infinity mapping.
- Updates dataset navigation KNN search to use the unified
`MatchDenseExpr` interface.
- Handles unavailable embeddings without querying an invalid `q_0_vec`
field.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## Summary
Adds page-range parsing support to the Go-native pipeline path and
introduces strict `parse_type` validation for both dataset and document
update endpoints.
## What changed
### Pages range parsing
- **`internal/utility/pdf_pages.go`** — `NormalizePDFPages`: normalizes
raw page ranges (list of `[from,to]` 1-indexed inclusive ranges) into
sorted, merged, deduplicated `[][]int`. Invalid ranges are dropped.
- **`internal/ingestion/pipeline/pdf_pages.go`** —
`NormalizeParserConfigPages`: walks any parser_config map and normalizes
`"pages"` values under every component → filetype setup, so the
persisted config always carries clean, merged ranges.
- **`internal/deepdoc/parser/pdf/parser.go`** — integrates
`resolvePagesToProcess` to filter parsed PDF pages by the configured
ranges.
- Pipeline integration (parser pages):
`internal/parser/parser/pdf_parser_common.go`, `chunk_process.go`, plus
associated e2e and unit tests.
### Parse type validation (shared logic)
- **`internal/service/parser_mode.go`** (new) — `ValidateParseTypeMode`:
shared function that validates `parse_type` (1=BuiltIn/parser_id,
2=Pipeline/pipeline_id) and ensures the corresponding field is present.
Used by both dataset and document update endpoints.
- **`internal/service/dataset/crud.go`** / `update.go` — replaces inline
`isPipelineMode`/`isBuiltinMode` computation with the shared
`service.ValidateParseTypeMode`.
- **`internal/service/document/document_dataset_update.go`** — adds
strict `parse_type` validation in `validateDatasetDocumentUpdate`,
simplifies the reparse logic to a two-way switch (isBuiltin/isPipeline)
now that parse_type is always valid.
- **`internal/service/document/document.go`** — adds `ParseType` field
to `UpdateDatasetDocumentRequest`.
- **`internal/service/document/document_dataset_update.go`** —
`updateDocumentParserConfig` fallback path when DSL loading fails.
- **`internal/service/parser_mode_test.go`** (new) — test coverage for
nil, invalid, and missing-field scenarios.
### Frontend
- **`web/src/interfaces/request/document.ts`** — adds `parseType` to
`IChangeParserRequestBody`.
- **`web/src/hooks/use-document-request.ts`** —
`useSetDocumentPipelineParser` sends `parse_type` in the PATCH payload.
- **`web/src/pages/dataset/dataset/use-change-document-parser.ts`** —
Go/Python branching for the document parser config dialog.
-
**`web/src/components/document-pipeline-dialog/use-document-pipeline-form.ts`**
— `buildSubmitData` returns `parseType` (bugfix: was dropped from the
return value).
### Test changes
- **Removed**: 2 tests that verified the old "mutually exclusive" error
(replaced by `ValidateParseTypeMode` coverage).
- **Modified**: 6 tests across document and dataset packages to include
`ParseType` in request structs.
- **Added**: new e2e tests for pages parsing (`pages_e2e_test.go`,
`pdf_parser_pages_e2e_test.go`) and unit tests for `NormalizePDFPages`,
`NormalizeParserConfigPages`, `resolvePagesToProcess`.
## Backward compatibility
- The `parse_type` field is **required** when `parser_id` or
`pipeline_id` is sent. This changes the contract for both dataset and
document PATCH endpoints, but aligns the Go backend with the existing
frontend behavior (the frontend already sends `parse_type`). Callers
that omit `parse_type` when updating parser/pipeline selections will
receive a clear error message.
- Existing callers that only update fields like `name`, `enabled`, or
`meta_fields` are unaffected.
- Test updates ensure all known call sites are compliant.
