## Summary
Remediates CVE-2026-0994 (HIGH) in `protobuf` by adding
`protobuf>=5.29.6` to `constraint-dependencies` in `pyproject.toml`.
| CVE | Severity | Package | Installed | Fixed in |
|---|---|---|---|---|
| CVE-2026-0994 | HIGH | protobuf | 5.29.5 | 5.29.6 |
`protobuf` is a transitive dependency pulled in by `google-api-core`,
`googleapis-common-protos`, `grpcio-status`, and `opentelemetry-proto`.
It was stuck at 5.29.5 because the lockfile hadn't been re-resolved.
## Summary
Remediates three HIGH severity CVEs in `pyasn1` by bumping the existing
`constraint-dependencies` entry from `>=0.6.3` to `>=0.6.4` in
`pyproject.toml`.
| CVE | Severity | Package | Installed | Fixed in |
|---|---|---|---|---|
| CVE-2026-59884 | HIGH | pyasn1 | 0.6.3 | 0.6.4 |
| CVE-2026-59885 | HIGH | pyasn1 | 0.6.3 | 0.6.4 |
| CVE-2026-59886 | HIGH | pyasn1 | 0.6.3 | 0.6.4 |
`pyasn1` is a transitive dependency (pulled in via `google-auth` / `rsa`
/ `pyasn1-modules`). A previous constraint (`>=0.6.3`) was added for
CVE-2026-30922 but two additional vulnerabilities were disclosed that
require 0.6.4.
## Summary
Remediates two HIGH severity CVEs in `pdfminer.six` by upgrading its
parent dependency `pdfplumber` from `==0.10.4` to `==0.11.10` in
`pyproject.toml`.
| CVE | Severity | Package | Installed | Fixed in |
|---|---|---|---|---|
| CVE-2025-64512 | HIGH | pdfminer.six | 20221105 | 20251107 |
| CVE-2025-70559 | HIGH | pdfminer.six | 20221105 | 20251230 |
`pdfminer.six` is a transitive dependency exact-pinned by `pdfplumber`.
Version 0.10.4 pins `pdfminer.six==20221105` (vulnerable); version
0.11.10 pins `pdfminer.six==20260107` (patched).
## Summary
Remediates nine litellm CVEs (3 CRITICAL, 6 HIGH) by upgrading the exact
pin from `==1.82.5` to `==1.84.0` in `pyproject.toml`.
| CVE | Severity | Fixed in |
|---|---|---|
| CVE-2026-35030 | CRITICAL | 1.83.0 |
| CVE-2026-42208 | CRITICAL | 1.83.7 |
| CVE-2026-49468 | CRITICAL | 1.84.0 |
| CVE-2026-35029 | HIGH | 1.83.0 |
| CVE-2026-40217 | HIGH | 1.83.10 |
| CVE-2026-42203 | HIGH | 1.83.7 |
| CVE-2026-42271 | HIGH | 1.83.7 |
| CVE-2026-47101 | HIGH | 1.83.14 |
| CVE-2026-47102 | HIGH | 1.83.10 |
`litellm` was pinned to `==1.82.5` because versions 1.82.6 - 1.82.8 had
a broken `litellm.caching.caching` import chain, and 1.88.0 had a broken
`litellm.integrations.custom_logger` import.
Both issues are resolved in 1.84.0.
The exact pin is retained (rather than a range) due to litellm's history
of introducing regressions on minor bumps.
## Summary
Remediates five nltk CVEs by adding `nltk>=3.10.0` to
`constraint-dependencies` in `pyproject.toml`.
| CVE | Severity | Installed | Fixed in |
|---|---|---|---|
| CVE-2025-14009 | CRITICAL | 3.9.2 | 3.9.3 |
| CVE-2026-0846 | HIGH | 3.9.2 | 3.9.3 |
| CVE-2026-0847 | HIGH | 3.9.2 | — |
| CVE-2026-33231 | HIGH | 3.9.2 | 3.9.4 |
| CVE-2026-33236 | HIGH | 3.9.2 | — |
| CVE-2026-54293 | HIGH | 3.9.2 | 3.10.0 |
| CVE-2026-33230 | MEDIUM | 3.9.2 | 3.9.4 |
CVE-2026-0847 and CVE-2026-33236 have no confirmed fixed version.
`nltk` is a transitive dependency (pulled in by `crawl4ai` and
`infinity-sdk`). No package in the graph caps it below 3.10.0. It was
stuck at 3.9.2 simply because the lockfile had never been re-resolved.
## Summary
Remediates four CVEs in `lxml` and `lxml_html_clean` by upgrading
transitive dependency constraints and bumping `crawl4ai` to unblock the
resolution.
| CVE | Severity | Package | Installed | Fixed in |
|---|---|---|---|---|
| CVE-2026-41066 | HIGH | lxml | 5.4.0 | 6.1.0 |
| CVE-2026-49825 | HIGH | lxml_html_clean | 0.4.3 | 0.4.5 |
| CVE-2026-28348 | MEDIUM | lxml_html_clean | 0.4.3 | 0.4.5 |
| CVE-2026-28350 | MEDIUM | lxml_html_clean | 0.4.3 | 0.4.5 |
- Bumped `crawl4ai` from `>=0.9.0,<0.9.1` to `>=0.9.2,<0.9.3`, version
0.9.2 relaxes lxml constraint to `>=5.3,<7`. The strict `<0.9.3` upper
bound on crawl4ai is maintained per project convention
- Added `inscriptis>=2.7.3` to `constraint-dependencies`, version 2.7.3
relaxes lxml constraint to `>=5.4.0,<6.2.0`
- Added `lxml>=6.1.0` to `constraint-dependencies`
- Added `lxml_html_clean>=0.4.5` to `constraint-dependencies`
`exclude-dependencies` entry for `unclecode-litellm` (still declared by
crawl4ai 0.9.2) continues to prevent the namespace collision that
previously crashed RAGFlow.
## Verification
- `lxml` is used widely across the codebase for HTML/XML parsing. The
5.x → 6.x upgrade maintains API compatibility for standard usage
(`lxml.html`, `lxml.etree`).
- `lxml_html_clean` API is unchanged between 0.4.3 and 0.4.5.
- `crawl4ai` 0.9.2 is a patch bump from 0.9.0 with no API changes
affecting RAGFlow's usage.
- `inscriptis` 2.7.3 is a patch bump from 2.7.0.
## Testing
- Full unit test suite passes
- `uv sync` resolves cleanly
- Verified `crawl4ai` imports without litellm namespace collision
## Summary
Bumps `aiosmtplib` from `>=5.0.0` to `>=5.1.1,<6.0.0` in
`pyproject.toml`.
| CVE | Severity | Package | Installed | Fixed in |
|---|---|---|---|---|
| CVE-2026-53533 | MEDIUM | aiosmtplib | 5.0.0 | 5.1.1 |
This is a direct dependency upgrade, no override or constraint needed.
## Summary
Old `zhipuai==2.0.1` SDK (MetaGLM/zhipuai-sdk-python-v4) requires
`pyjwt~=2.8.0`, which blocks upgrading pyjwt past 2.8.0 to address
active CVEs. The upstream project now recommends the maintained
successor [`zai-sdk`](https://github.com/zai-org/z-ai-sdk-python).
`zai-sdk` relaxes the pyjwt constraint to `>=2.9.0,<3.0.0`, allowing
pyjwt 2.13.0+. The embedding API surface (`client.embeddings.create`) is
identical, no functional changes required.
Related CVE's:
- CVE-2026-48522
- CVE-2026-48524
- CVE-2026-48525
- CVE-2026-48526
- CVE-2026-32597
### What problem does this PR solve?
This PR adds Google BigQuery as a first-class data source connector in
RAGFlow.
It enables users to ingest and sync BigQuery data using the same
row-to-document model used by relational database connectors: selected
content columns become document text, metadata columns become document
metadata, an optional ID column provides stable document IDs, and an
optional timestamp column enables cursor-based incremental sync.
The connector supports service-account JSON credentials, table mode,
custom query mode, GoogleSQL queries, cursor-based incremental sync,
deleted-row pruning support, configurable query limits such as
`maximum_bytes_billed`, dry-run validation, batch loading, stable
document IDs, and BigQuery-aware value serialization.
### 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
# Summary
- The culprit is commit b4c8711d5 / PR #15415 (fix: upgrade crawl4ai to
0.8.0).
- That upgrade brought in unclecode-litellm, which installs the same
top-level litellm namespace as upstream litellm.
- The crash happens when files from one LiteLLM distribution are mixed
with files from the other: custom_guardrail.py expects
GuardrailTracingDetail, but types/utils.py can come from the older
conflicting package.
### What problem does this PR solve?
#15844
Adds a **Chat channels** capability so a RAGFlow assistant (Dialog) can
be exposed as a bot on external messaging platforms (Feishu/Lark,
Discord, Telegram, Slack, WeCom, LINE, etc.). An admin configures a bot
in the UI, connects it to an assistant, and inbound messages are
answered from that assistant's knowledge base — replies are delivered
back on the channel.
**Feishu/Lark is implemented and tested end-to-end.** Discord, Telegram,
LINE, and WeCom are scaffolded against the same interface; the remaining
listed channels are tracked as follow-ups.
### Design
**Backend**
- New `chat_channel` table (`tenant_id`, `name`, `channel`, `config`
JSON holding `{credential: {...}}`, `dialog_id`, `status`) +
`ChatChannelService` and RESTful CRUD under `/api/v1/chat_channels`.
- Channel framework under `api/channels/`: a `core` registry +
per-channel packages that self-register a builder and implement a common
`Channel` interface (`start`/`stop`/`send` + inbound normalization) over
`IncomingMessage`/`OutgoingMessage`.
- Embedded **reconcile loop** in `ragflow_server`
(`api/channels/bootstrap.py`): loads enabled bots, and
starts/stops/restarts them as rows change (no server restart needed).
Inbound messages run the connected dialog via the non-streaming
completion path, keeping per-end-user conversation history.
- Missing optional channel SDKs degrade gracefully (channel skipped with
a warning; others unaffected). Channel-level errors are logged, not
crashed.
- Feishu's WebSocket client runs in a dedicated thread with its own
event loop to avoid cross-loop/contextvars conflicts with the channel
runtime.
**Frontend**
- **Settings → Chat channels** panel: available-channels grid +
configured-bots list with add/edit/delete and a **Connect assistant**
popup that binds a bot to a dialog.
- Brand icons via simple-icons / reused shared data-source assets, with
colored fallbacks for brands not available.
- Route, sidebar entry, i18n (en/zh), and a top-nav segment-boundary fix
so the settings page no longer highlights the Chat tab.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### Notes
- DB: new `chat_channel` table is auto-created; `chat_channel.dialog_id`
is also covered by a `migrate_db` `alter_db_add_column` for existing
installs.
- Channel SDKs (`lark-oapi`, `discord.py`, `python-telegram-bot`,
`line-bot-sdk`, `wechatpy`, `aiohttp`) added to dependencies.
- Screenshots / per-channel credential docs to follow.
<img width="1338" height="1290" alt="Image"
src="https://github.com/user-attachments/assets/042cb2f9-0dad-4e6a-bcf7-43ced4bbd704"
/>
<img width="1344" height="738" alt="Image"
src="https://github.com/user-attachments/assets/373cd08e-ec40-4c67-9c51-4d948b1ba617"
/>
<img width="672" height="887" alt="Image"
src="https://github.com/user-attachments/assets/5a34953f-a9a3-4c1e-869e-5eff0dc64c84"
/>
---------
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.25.6 to v0.26.0
- 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
## Summary
Upgrade crawl4ai from 0.7.6 to 0.8.0 to fix CVE-2026-26217.
## Vulnerability
| Field | Value |
|-------|-------|
| **ID** | CVE-2026-26217 |
| **Severity** | CRITICAL |
| **Scanner** | trivy |
| **Rule** | `CVE-2026-26217` |
| **File** | `uv.lock` |
| **Assessment** | Likely exploitable |
**Description**: Crawl4AI Has Local File Inclusion in Docker API via
file:// URLs
## Evidence
**Scanner confirmation**: trivy rule `CVE-2026-26217` flagged this
pattern.
**Production code**: This file is in the production codebase, not
test-only code.
## Threat Model Context
This is a web service - vulnerabilities in request handlers are directly
exploitable by remote attackers.
## Changes
- `pyproject.toml`
- `uv.lock`
## Verification
- [x] Build passes
- [x] Scanner re-scan confirms fix
- [x] LLM code review passed
---
*This change addresses a pattern flagged by static analysis. The code
path handles user-influenced input and the fix reduces the attack
surface against both manual and automated exploitation.*
---
*Automated security fix by [OrbisAI Security](https://orbisappsec.com)*
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.25.5 to v0.25.6
- 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?
1. update python version to 3.13
2. upgrade ormsgpack to 1.6.0
### Type of change
- [x] Refactoring
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.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?
Feat: add local & ssh provider in admin panel
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Closes#14753
## What changed
| File | Change |
|---|---|
| `pyproject.toml` | `requires-python` → `>=3.13,<3.15`; remove
`strenum==0.4.15` |
| `Dockerfile` | `uv python install 3.13`, `uv sync --python 3.13` |
| `.github/workflows/tests.yml` | `uv sync --python 3.13` on both matrix
legs |
| `CLAUDE.md` | dev setup command + requirements note updated |
| `deepdoc/parser/mineru_parser.py` | `from strenum import StrEnum` →
`from enum import StrEnum` |
| `agent/tools/code_exec.py` | same |
`StrEnum` has been in the stdlib since Python 3.11 — the `strenum`
backport package is no longer needed once the floor is 3.13.
## Why uv.lock is not regenerated
`uv lock --python 3.13` fails because:
1. The infiniflow/graspologic fork pins `numpy>=1.26.4,<2.0.0`
2. `tensorflow-cpu>=2.20.0` (the first release with cp313 wheels)
depends on `ml-dtypes>=0.5.1`, which requires `numpy>=2.1.0`
3. These two constraints are irreconcilable on Python 3.13
The lockfile regeneration requires loosening the `numpy` upper bound in
the `infiniflow/graspologic` fork. Once that fork commit is updated and
the SHA in `pyproject.toml:49` is bumped, `uv lock --python 3.13` will
succeed.
## RFC corrections
Two claims in the original RFC (#14753) did not hold up under code
review:
- **"graspologic hard-blocks 3.13"** — the infiniflow fork at the pinned
commit has no `<3.13` Python constraint. The blocker is the transitive
`numpy<2.0.0` conflict with tensorflow-cpu's test dependency, not a
direct Python version cap.
- **"free-threading throughput gains for I/O-bound workload"** — Python
3.13 free-threading requires a special `--disable-gil` build and
provides no benefit for async I/O code (the GIL is already released
during I/O). The real motivation is forward compatibility and improved
error messages.
### 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?
GraphRAG feature - Part 1 - add spacy to extract entity and relation
<img width="1621" height="1288" alt="image"
src="https://github.com/user-attachments/assets/aadeddad-94da-46c6-adad-9c3784181f61"
/>
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
## Summary
- `CvModel["Bedrock"]` was absent from `rag/llm/cv_model.py`, causing
`model_instance()` to return `None` when a Bedrock model was used as a
PDF parser — even after correct model resolution.
- This PR adds `BedrockCV`, enabling Bedrock vision models (e.g.
`amazon.nova-pro-v1:0`, `anthropic.claude-3-5-sonnet`) to be used as PDF
parsers.
## What problem does this PR solve?
When a Bedrock model is selected as the PDF parser in a knowledge base,
ingestion failed with:
```
'LiteLLMBase' object has no attribute 'describe_with_prompt'
```
The root cause: `LiteLLMBase` (the Bedrock chat implementation) was the
only registered handler for the Bedrock factory. It does not implement
`describe_with_prompt`. `CvModel` had no Bedrock entry, so
`model_instance()` returned `None` for `image2text` requests.
## Type of change
- [x] New Feature (non-breaking change which adds functionality)
## Changes
**`rag/llm/cv_model.py`**
Adds `BedrockCV(Base)` with `_FACTORY_NAME = "Bedrock"`:
- Uses `litellm.completion` with the `bedrock/` prefix (consistent with
`LiteLLMBase`)
- Parses AWS credentials from the JSON key assembled by `add_llm`
(`auth_mode`, `bedrock_ak`, `bedrock_sk`, `bedrock_region`,
`aws_role_arn`)
- Supports three auth modes: `access_key_secret`, `iam_role` (via STS
`assume_role`), and default credential chain (IRSA, instance profile)
- Implements `describe_with_prompt` and `describe`
## Test plan
- [ ] Configure a Bedrock vision model (e.g. `amazon.nova-pro-v1:0`)
with valid AWS credentials
- [ ] Select it as PDF parser in a knowledge base
- [ ] Verify ingestion of a PDF document completes without errors
- [ ] Verify `CvModel["Bedrock"]` resolves to `BedrockCV`
🤖 Generated with [Claude Code](https://claude.ai/claude-code)
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
### 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?
Bump to infinity v0.7.0-dev6
(uv lock --upgrade-package infinity-sdk)
### 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
v0.25.0 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
The Langfuse Python SDK v3+ removed `start_generation()` method.
RagFlow's code called this non-existent method, causing AttributeError
when Langfuse tracing is enabled.
Replace all `start_generation()` calls with
`start_observation(as_type="generation")` which is the correct v4 SDK
API.
Affected files:
- api/db/services/llm_service.py (12 occurrences)
- api/db/services/dialog_service.py (1 occurrence)
Fixes#14204
Related to #9243
### What problem does this PR solve?
_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.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
In order to attach the debugger to a running docker container it has to
be inside the docker image
### What problem does this PR solve?
[#14224](https://github.com/infiniflow/ragflow/issues/14224)
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
