## Summary
- Add language-aware Snowball stemmer to `RagTokenizer` supporting 16
languages (Dutch, German, French, Spanish, etc.)
- Thread the KB `language` parameter through the full tokenization
pipeline (14 parser modules + task executor)
- Add Dutch to the frontend language lists and cross-language form
## Problem
RAGFlow uses the English Porter stemmer + WordNet lemmatizer for **all**
BM25 tokenization, regardless of the knowledge base language setting.
This produces incorrect stems for non-English text. For example:
| Dutch word | Dutch stemmer | English Porter |
|---|---|---|
| documenten | document | documenten (unchanged!) |
| gebruikers | gebruiker | gebruik (over-stemmed) |
| instellingen | instell | instellingen (unchanged!) |
This degrades BM25 recall for any non-English knowledge base.
## Solution
NLTK already ships Snowball stemmers for 16 languages. This PR:
1. **`rag/nlp/rag_tokenizer.py`**: Overrides `tokenize()` with
`set_language()` and `_normalize_token()` that selects the correct NLTK
Snowball stemmer. Falls back to Porter for unmapped languages (Chinese,
Japanese, Korean, etc. — these use character-based tokenization anyway).
2. **`rag/nlp/__init__.py`** + **14 `rag/app/*.py` parsers** +
**`rag/svr/task_executor.py`**: Threads the `language` parameter through
`tokenize()`, `tokenize_chunks()`, `tokenize_table()`, and all callers.
3. **Frontend**: Adds Dutch (`Nederlands`) to `LanguageList`,
`LanguageMap`, `LanguageAbbreviationMap`, `LanguageTranslationMap`,
cross-language form field, and `en.ts` locale.
## Backward Compatibility
- Default language is `"English"`, preserving existing behavior for all
current users
- Languages without a Snowball stemmer mapping fall back to Porter (no
change)
- No new dependencies — NLTK Snowball is already bundled
## Summary
Fixes#15215 — attachments uploaded to an agent were not reaching the
LLM.
When a user uploads a file in an agent chat, `canvas.run` parses it into
the `sys.files` global (text content for documents, `data:image/...`
URIs
for images — see `agent/canvas.py:752-768`). But the LLM/Agent
component's
`_prepare_prompt_variables` only substitutes variables the user's prompt
template explicitly references via `{var}` placeholders. The default
prompt is `[{"role": "user", "content": "{sys.query}"}]` with no
`{sys.files}`, so the parsed attachment content never reaches the model.
In the reporter's logs, this is why the agent saw only the bare query
`附件 摘要 attachment summary` and went searching the dataset instead of
reading the uploaded PDF.
## Fix
`agent/component/llm.py` — added `_collect_sys_files()` and an
auto-injection step in `_prepare_prompt_variables`:
- If `sys.files` is non-empty **and** neither `sys_prompt` nor any entry
in `prompts` already contains `{sys.files}` (no double-injection),
split the entries into text vs. `data:image/...` URIs.
- Image URIs are merged into `self.imgs`, which the existing logic uses
to switch the chat model to `IMAGE2TEXT` and pass `images=...` to
`async_chat`.
- Text content is appended to the last `user` role message in `msg`,
mirroring how `dialog_service.async_chat_solo` handles attachments for
the non-agent chat path (`api/db/services/dialog_service.py:318-321`).
Both `LLM._invoke_async` and `Agent._invoke_async` (tool-using) go
through `_prepare_prompt_variables`, so plain LLM nodes and Agent nodes
are fixed in both streaming and non-streaming paths.
## Test plan
- [ ] Upload a PDF attachment to an agent with the default `{sys.query}`
prompt and ask "summarize the attachment" — the model should answer
from the file content rather than searching the knowledge base.
- [ ] Upload an image attachment to an agent and ask about its contents
—
the model should switch to the vision-capable LLM and answer from
the image.
- [ ] Verify that an agent whose prompt **does** include `{sys.files}`
still works and does **not** include the file content twice.
- [ ] Verify that an agent run with no attachments behaves unchanged.
- [ ] Run `uv run pytest` to make sure no existing tests regress.
### 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):
---------
Co-authored-by: yzc <yuzhichang@gmail.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>
Adds Keenable as a web search tool in the agent, alongside the existing
Tavily/DuckDuckGo/SearXNG/Google tools.
The main difference from the other search tools is that it doesn't
require an
API key. By default it uses Keenable's keyless public endpoint, so it
works out
of the box. Providing a key (in the tool config) switches to the
authenticated
endpoint and lifts the rate limits.
### Changes
- Backend: `agent/tools/keenable.py` — `KeenableSearch`, follows the
Tavily/DuckDuckGo tool shape (results go through `_retrieve_chunks`).
Auto-registered by `agent/tools/__init__.py`.
- Frontend: wired into the agent builder — operator + icon, config form
(optional API key, search mode, site filter, top N), the search tool
menu,
and the existing api_key export sanitizer.
### Config
- API key: optional. Blank = keyless free tier; set it to lift limits /
enable
`realtime` mode.
- `site`: restrict to a single domain.
- `mode`: `pro` (default) or `realtime`.
### Notes
`KEENABLE_API_URL` can override the API base (HTTPS enforced; defaults
to
`https://api.keenable.ai`). The tool only sends the query (no URL
fetch), so
there's no SSRF surface. Verified the frontend with `vite build` and the
backend search path against the public endpoint.
### What problem does this PR solve?
- Add `web/src/locales/ko.ts` with full Korean translation (~3100 keys)
- Register `Ko = 'ko'` in `LanguageAbbreviation` enum (`common.ts`)
- Add `[LanguageAbbreviation.Ko]: '한국어'` to `LanguageAbbreviationMap`
- Add lazy-load entry in `web/src/locales/config.ts`
- Add `korean` key to all existing locale files (`ja`, `id`, `es`,
`pt-br`, `vi`, `zh-traditional`)
- Fix duplicate enum value `FileMimeType.Mdx` (`'text/markdown'` →
`'text/mdx'`)
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Other (please describe): Korean (한국어) i18n translation + fix
duplicate FileMimeType.Mdx enum value
### What problem does this PR solve?
Python implementation of the Go-based model_provider API suite.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: bill <yibie_jingnian@163.com>
### What problem does this PR solve?
This PR adds a new `Browser` operator to Agent workflows, enabling
prompt-driven browser automation in RAGFlow.Technically based
‘Browser-Use’
It includes:
- Backend browser component execution with tenant LLM integration
- Upload source support (file IDs, URLs, variables, CSV/JSON array)
- Downloaded file persistence to RAGFlow storage
- Frontend node/operator integration, form config, icon, and i18n
updates
- Unit tests for upload/download and ID parsing logic
- Dependency and Docker updates for browser-use runtime support
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
LLM/chat and search UIs render Markdown in several places (document
preview, floating chat widget, next-search, etc.). Plugin lists and
behavior were duplicated or inconsistent, and single newlines in model
output were not always rendered as visible line breaks, which hurts
readability for chat-style content.
This PR centralizes shared **remark/rehype** configuration (including
**`remark-breaks`** for newline handling) and wires the main Markdown
surfaces to use it, so behavior is consistent and easier to maintain.
### Type of change
- [x] Refactoring
---------
Co-authored-by: Yingfeng Zhang <yingfeng.zhang@gmail.com>
### What problem does this PR solve?
Before consolidation
Web API: POST /v1/document/list
Http API - GET /api/v1/datasets/<dataset_id>/documents
After consolidation, Restful API -- GET
/api/v1/datasets/<dataset_id>/documents
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Fix: When creating a dataset, if no `chunk_method` is selected, there is
no indication that this is a required field.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
---------
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
### 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?
RAGFlow had no Turkish language support. This PR adds Turkish (tr)
locale translations to the UI.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Co-authored-by: Mustafa YILDIZ <mustafa.yildiz@cilek.com>
### What problem does this PR solve?
- Unify top level pages structure
- Standardize locale language codes (BCP 47) and time zones (IANA tz)
> **Note:**
> Newly created user info brings non-standard default values `timezone:
"UTC+8\tAsia/Shanghai"` and `language: "English"`.
### Type of change
- [x] Refactoring
### What problem does this PR solve?
This PR aims to extend the list of possible providers. Adds new Provider
"RAGcon" within the Ollama Modal. It provides all model types except OCR
via Openai-compatible endpoints.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Jakob <16180662+hauberj@users.noreply.github.com>
### What problem does this PR solve?
This PR adds end-to-end Arabic support in production. It also adds a
full Arabic README
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
### What problem does this PR solve?
Feat: When exporting the agent DSL, the tailkey, password, and history
fields need to be cleared. #13281
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Co-authored-by: Yingfeng <yingfeng.zhang@gmail.com>
### What problem does this PR solve?
This PR adds [Avian](https://avian.io) as a new LLM provider to RAGFlow.
Avian provides an OpenAI-compatible API with competitive pricing,
offering access to models like DeepSeek V3.2, Kimi K2.5, GLM-5, and
MiniMax M2.5.
**Provider details:**
- API Base URL: `https://api.avian.io/v1`
- Auth: Bearer token via API key
- OpenAI-compatible (chat completions, streaming, function calling)
- Models:
- `deepseek/deepseek-v3.2` — 164K context, $0.26/$0.38 per 1M tokens
- `moonshotai/kimi-k2.5` — 131K context, $0.45/$2.20 per 1M tokens
- `z-ai/glm-5` — 131K context, $0.30/$2.55 per 1M tokens
- `minimax/minimax-m2.5` — 1M context, $0.30/$1.10 per 1M tokens
**Changes:**
- `rag/llm/chat_model.py` — Add `AvianChat` class extending `Base`
- `rag/llm/__init__.py` — Register in `SupportedLiteLLMProvider`,
`FACTORY_DEFAULT_BASE_URL`, `LITELLM_PROVIDER_PREFIX`
- `conf/llm_factories.json` — Add Avian factory with model definitions
- `web/src/constants/llm.ts` — Add to `LLMFactory` enum, `IconMap`,
`APIMapUrl`
- `web/src/components/svg-icon.tsx` — Register SVG icon
- `web/src/assets/svg/llm/avian.svg` — Provider icon
- `docs/references/supported_models.mdx` — Add to supported models table
This follows the same pattern as other OpenAI-compatible providers
(e.g., n1n #12680, TokenPony).
cc @KevinHuSh @JinHai-CN
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
### What problem does this PR solve?
RAGFlow supports 12 UI languages but does not include Bulgarian. This PR
adds Bulgarian (`bg` / `Български`) as the 13th supported language,
covering the full UI translation (2001 keys across all 26 sections) and
OCR/PDF parser language mapping.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### Changes
- **`web/src/constants/common.ts`** — Registered Bulgarian in all 5
language data structures (`LanguageList`, `LanguageMap`,
`LanguageAbbreviation` enum, `LanguageAbbreviationMap`,
`LanguageTranslationMap`)
- **`web/src/locales/config.ts`** — Added lazy-loading dynamic import
for the `bg` locale
- **`web/src/locales/bg.ts`** *(new)* — Full Bulgarian translation file
with all 26 sections, matching the English source (`en.ts`). All
interpolation placeholders, HTML tags, and technical terms are preserved
as-is
- **`deepdoc/parser/mineru_parser.py`** — Mapped `'Bulgarian'` to
`'cyrillic'` in `LANGUAGE_TO_MINERU_MAP` for OCR/PDF parser support
### How it works
The language selector automatically picks up the new entry. When a user
selects "Български", the translation bundle is lazy-loaded on demand.
The preference is persisted to the database and localStorage across
sessions.
### What problem does this PR solve?
Fix: Bugs fixed
- metadata icon error
- search page's image not display
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix Gitee AI links and update the reranker model configuration
### Type of change
- [X] Bug Fix (non-breaking change which fixes an issue)
Co-authored-by: franco <1787003204@q.comq>
### What problem does this PR solve?
Feat: Add the history field to the agent's system variables. #7322
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Add PaddleOCR as a new PDF parser.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Feat: Fixed the issue where the newly created agent begin node displayed
"undefined". #10427
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Feat: Remove HMAC from the webhook #10427
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Feat: bedrock iam authentication #12008
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### PR details
feat: Add Excel export support and fix variable reference regex
Changes:
- Add Excel export output format option to Message component
- Apply nest_asyncio patch to handle nested event loops
- Fix async generator iteration in canvas_app.py debug endpoint
- Add underscore support in variable reference regex pattern
### What problem does this PR solve?
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Shivam Johri <shivamjohri@Shivams-MacBook-Air.local>
我已在下面的评论中用中文重复说明。
### What problem does this PR solve?
## Summary
This PR enhances the MinerU document parser with additional
configuration options, giving users more control over PDF parsing
behavior and improving support for multilingual documents.
## Changes
### Backend (`deepdoc/parser/mineru_parser.py`)
- Added configurable parsing options:
- **Parse Method**: `auto`, `txt`, or `ocr` — allows users to choose the
extraction strategy
- **Formula Recognition**: Toggle for enabling/disabling formula
extraction (useful to disable for Cyrillic documents where it may cause
issues)
- **Table Recognition**: Toggle for enabling/disabling table extraction
- Added language code mapping (`LANGUAGE_TO_MINERU_MAP`) to translate
RAGFlow language settings to MinerU-compatible language codes for better
OCR accuracy
- Improved parser configuration handling to pass these options through
the processing pipeline
### Frontend (`web/`)
- Created new `MinerUOptionsFormField` component that conditionally
renders when MinerU is selected as the layout recognition engine
- Added UI controls for:
- Parse method selection (dropdown)
- Formula recognition toggle (switch)
- Table recognition toggle (switch)
- Added i18n translations for English and Chinese
- Integrated the options into both the dataset creation dialog and
dataset settings page
### Integration
- Updated `rag/app/naive.py` to forward MinerU options to the parser
- Updated task service to handle the new configuration parameters
## Why
MinerU is a powerful document parser, but the default settings don't
work well for all document types. This PR allows users to:
1. Choose the best parsing method for their documents
2. Disable formula recognition for Cyrillic/non-Latin scripts where it
causes issues
3. Control table extraction based on document needs
4. Benefit from automatic language detection for better OCR results
## Testing
- [x] Tested MinerU parsing with different parse methods
- [x] Verified UI renders correctly when MinerU is selected/deselected
- [x] Confirmed settings persist correctly in dataset configuration
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [x] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
---------
Co-authored-by: user210 <user210@rt>
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
This PR introduces a new Docs Generator agent component for producing
downloadable PDF, DOCX, or TXT files from Markdown content generated
within a RAGFlow workflow.
### **Key Features**
**Backend**
- New component: DocsGenerator (agent/component/docs_generator.py)
-
- Markdown → PDF/DOCX/TXT conversion
-
- Supports tables, lists, code blocks, headings, and rich formatting
-
- Configurable document style (fonts, margins, colors, page size,
orientation)
-
- Optional header logo and footer with page numbers/timestamps
-
**Frontend**
- New configuration UI for the Docs Generator
-
- Download button integrated into the chat interface
-
- Output wired to the Message component
-
- Full i18n support
**Documentation**
Added component guide:
docs/guides/agent/agent_component_reference/docs_generator.md
**Usage**
Add the Docs Generator to a workflow, connect Markdown output from an
upstream component, configure metadata/style, and feed its output into
the Message component. Users will see a document download button
directly in the chat.
**Contributor Note**
We have been following RAGFlow since more than a year and half now and
have worked extensively on personalizing the framework and integrating
it into several of our internal systems. Over the past year and a half,
we have built multiple platforms that rely on RAGFlow as a core
component, which has given us a strong appreciation for how flexible and
powerful the project is.
We also previously contributed the full Italian translation, and we were
glad to see it accepted. This new Docs Generator component was created
for our own production needs, and we believe that it may be useful for
many others in the community as well.
We want to sincerely thank the entire RAGFlow team for the remarkable
work you have done and continue to do. If there are opportunities to
contribute further, we would be glad to help whenever we have time
available. It would be a pleasure to support the project in any way we
can.
If appropriate, we would be glad to be listed among the project’s
contributors, but in any case we look forward to continuing to support
and contribute to the project.
PentaFrame Development Team
---------
Co-authored-by: PentaFrame <info@pentaframe.it>
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Feat: Add mineru as a model manufacturer to the system. #10621
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: balibabu <assassin_cike@163.com>
### What problem does this PR solve?
Retrieval metadata filtering adds semi-automatic mode, and users can
manually check the metadata key that participates in LLM to generate
filter conditions.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Feat: Add configuration for webhook to the begin node. #10427
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
- Add complete Italian translation file with all UI sections
- Register Italian in LanguageAbbreviation enum and language maps
- Configure Italian translation in i18n config
- Add Italiano to language selector dropdown
### Type of change
- [x] Other (please describe):
## What
Added complete Italian language translation support to RAGFlow
## Changes
- Added comprehensive Italian translation file
([it.ts](ragflow/web/src/locales/it.ts:0:0-0:0)) with all UI sections
(1239 lines)
- Registered Italian in `LanguageAbbreviation` enum and all language
maps
- Configured Italian translation in i18n configuration
- Added "Italiano" to language selector dropdown
## Impact
- Italian users can now use RAGFlow in their native language
- All major UI components are translated including:
- Login/registration screens
- Knowledge base management
- Chat interface
- Settings and configuration
- Admin console
- Error messages and notifications
## Testing
- Verified all translation keys are present
- Confirmed language selector shows "Italiano" correctly
- Tested that no translation keys are missing
- All UI sections properly translated
Co-authored-by: PentaFrame <info@pentaframe.it>
### What problem does this PR solve?
Features: Memory page rendering and other bug fixes
- Rendering of the Memory list page
- Rendering of the message list page in Memory
- Fixed an issue where the empty state was incorrectly displayed when
search criteria were applied
- Added a web link for the API-Key
- modifying the index_mode attribute of the Confluence data source.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Feat: Replace antd with shadcn and delete the template node. #10427
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Feat: Delete useless knowledge base, chat, and search files. #10427
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Feat: Add loop operator node. #10427
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
