Compare commits

...

25 Commits

Author SHA1 Message Date
Junyan Qin
11ee0fef5d chore: update Python versions in CI workflow 2025-12-23 14:27:09 +08:00
Junyan Qin
9a9ba34717 chore: bump version v4.6.5 2025-12-23 14:26:52 +08:00
Junyan Qin
312e47bf46 chore: bump langbot-plugin to 0.2.4 2025-12-23 14:22:13 +08:00
Junyan Qin
628865fd06 fix: add timeout to image fetching in get_qq_image_bytes function (#1859) 2025-12-23 14:17:16 +08:00
Junyan Qin
806a03cd53 fix: dingtalk adapter lifecycle mgm issues (#1844, #1853) 2025-12-23 14:00:41 +08:00
Junyan Qin
24bd90fcf6 fix: alter_user_message typing issues 2025-12-23 13:24:52 +08:00
Junyan Qin
d2765577c8 chore: provide '--no-sync' arg in dockerfile 2025-12-23 12:39:42 +08:00
fdc310
60ca688bcb Fix/Incomplete JSON data returned by N8N streaming data causes the loss of chunks. (#1880)
* fix: Incomplete JSON data returned by N8N streaming data causes the loss of chunks.
2025-12-23 09:42:26 +08:00
ICE
76d8eea41d fix: group bot at rule (#1882) 2025-12-22 20:20:41 +08:00
Junyan Qin
635c3a04d8 perf: ja-JP translation for New 2025-12-22 18:46:15 +08:00
Junyan Qin
dde97abe38 feat: enhance HomeSidebar with new integration options and updated translations 2025-12-22 18:43:19 +08:00
Copilot
90a22d894d fix: prevent memory overflow from excessive logging in streaming and query processing (#1879)
* Initial plan

* fix: reduce excessive logging to prevent memory overflow

- Add log file rotation (10MB max per file, 5 backups)
- Reduce streaming response logging (every 10th chunk instead of every chunk)
- Remove debug logging from controller tight loop
- Add summary logging after streaming completes

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* refactor: address code review feedback

- Extract log rotation config to module-level constants
- Keep first streaming chunk at INFO level for connection debugging
- Use DEBUG level for subsequent chunks

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* style: fix code formatting whitespace

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-12-22 18:25:24 +08:00
Junyan Qin
88ef9cd6ae chore: remove platform field from docker-compose.yaml 2025-12-21 20:31:09 +08:00
fdc310
e3595b5c57 Feat/lark file and audio (#1874)
* fix: n8n streaming no sequence bug

* feat:add lark file and audio
fix: webhook

* feat:add lark file and audio
fix: webhook

* 更新 n8nsvapi.py

* del : print and log
2025-12-21 01:30:05 +08:00
Junyan Qin (Chin)
ce82f87e43 feat: add SeekDB vector database support for knowledge bases (#1814)
* feat: add SeekDB vector database support for knowledge bases

This commit adds complete integration of OceanBase's SeekDB as a vector
database option for LangBot's knowledge base feature.

## Changes

### Core Implementation
- Add SeekDB adapter implementing VectorDatabase interface
  - Support both embedded and server deployment modes
  - HNSW indexing with cosine similarity
  - Async operations with error handling
  - Comprehensive logging

### System Integration
- Register SeekDB in VectorDBManager
- Add pyseekdb>=0.1.0 dependency
- Add SeekDB configuration template
- Update README with vector database section

### Documentation
- Complete integration guide with platform compatibility warnings
- Configuration examples for all deployment modes
- Troubleshooting guide for common issues
- Code examples demonstrating usage patterns
- Comprehensive test reports and status documentation

## Testing

Architecture validated end-to-end using ChromaDB:
- File upload → parsing → chunking → embedding → storage
- 828 bytes → 3 chunks → 3 vectors stored successfully
- BGE-M3 model (384 dimensions)
- Status: Completed 

## Platform Compatibility

### Embedded Mode
-  Linux: Fully supported
-  macOS: Not supported (pylibseekdb is Linux-only)
-  Windows: Not supported (pylibseekdb is Linux-only)

### Server Mode
-  Linux: Fully supported
- ⚠️ macOS: Known issue (oceanbase/seekdb#36)
- ⚠️ Windows: Untested

### Remote Connection
-  All platforms supported

## Known Issues

macOS Docker server mode affected by upstream bug:
https://github.com/oceanbase/seekdb/issues/36

Workaround: Use ChromaDB/Qdrant or connect to remote SeekDB server.

## Files Added
- src/langbot/pkg/vector/vdbs/seekdb.py
- docs/SEEKDB_INTEGRATION.md
- examples/seekdb_example.py
- SEEKDB_INTEGRATION_SUMMARY.md
- SEEKDB_INTEGRATION_COMPLETE.md
- SEEKDB_TEST_STATUS.md
- SEEKDB_FINAL_SUMMARY.md
- SEEKDB_INTEGRATION_DONE.md
- GITHUB_ISSUE_36_COMMENT.md

## Files Modified
- src/langbot/pkg/vector/mgr.py
- src/langbot/pkg/vector/vdbs/__init__.py
- pyproject.toml
- src/langbot/templates/config.yaml
- README.md
- README_EN.md

🤖 Generated with [Claude Code](https://claude.com/claude-code)
via [Happy](https://happy.engineering)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Happy <yesreply@happy.engineering>

* chore: remove unused docs

* feature: minimal seekdb change (#1866)

* feat: add SeekDB embedding requester and configuration

This commit introduces a new SeekDB embedding requester, which utilizes the local embedding function from pyseekdb. It includes the necessary Python implementation and a corresponding YAML configuration file for integration. Additionally, a new SVG icon for SeekDB is added to enhance the visual representation in the UI.

* fix: update EmbeddingForm to conditionally render URL field based on model provider

This commit modifies the EmbeddingForm component to conditionally display the URL input field only when the current model provider is not 'seekdb-embedding'. Additionally, it updates the condition for rendering the API key field to exclude both 'ollama-chat' and 'seekdb-embedding' providers.

* chore: update Python version requirement in pyproject.toml to support Python 3.11

* fix: add config default value, when it makes fronted not show spec

* fix: seekdb.py clean metadata. change api

* fix: enhance error handling in SeekDB embedding initialization

This commit adds improved error handling to the SeekDB embedding function. It ensures that a RuntimeError is raised if the embedding function fails to initialize, and wraps the embedding call in a try-except block to catch and raise a RequesterError with a descriptive message in case of failure.

* refactor: update SeekDB database management to use AdminClient

This commit refactors the SeekDB database management logic to utilize the AdminClient for database operations. It replaces the previous temp_client with admin_client for listing and creating databases, ensuring a more robust interaction with the SeekDB API.

* refactor: update SeekDB embedding model initialization to use task manager

This commit refactors the SeekDB embedding model initialization by replacing the direct asyncio task creation with the task manager's create_task method. This change enhances task management and provides a clearer naming convention for the embedding model initialization task.

* perf: integration

* chore: remove unnecessary files

* fix: linter errors

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Happy <yesreply@happy.engineering>
Co-authored-by: 名为a的全局变量 <1051233107@qq.com>
2025-12-20 23:40:30 +08:00
fdc310
854b291c5a fix: n8n streaming no sequence bug (#1873) 2025-12-20 00:03:05 +08:00
Junyan Qin
9780fd059c chore: add back arm64 docker image (#1871) 2025-12-19 23:44:28 +08:00
Junyan Qin
adc65f66eb fix: pipeline duplication bug 2025-12-19 23:27:18 +08:00
Copilot
ae772074a1 feat: Add configurable password change toggle via system.allow_change_password (#1869)
* Initial plan

* Add password change toggle feature with config flag

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* Feature implementation complete and validated

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* chore: remove lock

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2025-12-18 15:14:03 +08:00
dependabot[bot]
16c1e9edd1 chore(deps): bump next from 15.5.7 to 15.5.9 in /web (#1868)
Bumps [next](https://github.com/vercel/next.js) from 15.5.7 to 15.5.9.
- [Release notes](https://github.com/vercel/next.js/releases)
- [Changelog](https://github.com/vercel/next.js/blob/canary/release.js)
- [Commits](https://github.com/vercel/next.js/compare/v15.5.7...v15.5.9)

---
updated-dependencies:
- dependency-name: next
  dependency-version: 15.5.9
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2025-12-18 12:21:02 +08:00
sheetung
3ab9ffb7b7 feat(plugins): add plugin new version detection (#1865)
* feat(plugins): 添加插件更新检测功能

* perf: card style

---------

Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2025-12-18 12:17:25 +08:00
Copilot
82e2123fe7 Fix Dify v1.11.0 conversation_id UUID validation error (#1860)
* Initial plan

* Fix Dify v1.11.0 conversation_id UUID validation error

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-12-12 18:35:47 +08:00
Junyan Qin
7a65f3d2f4 chore: update AGENTS.md 2025-12-12 17:35:02 +08:00
Junyan Qin
b5b5d499e5 feat: add back streaming switch for web chat 2025-12-11 18:54:16 +08:00
Hadong
173f9e9c30 feat(lark): 支持商店应用机器人 (#1855)
* feat(lark): 支持商店应用机器人

* feat(lark): app_type改成select模式,修复select配置无效,按照copilot建议隐藏log敏感信息

* fix: KeyError for backward compatibility

---------

Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2025-12-11 16:54:28 +08:00
53 changed files with 7553 additions and 3566 deletions

8
.dockerignore Normal file
View File

@@ -0,0 +1,8 @@
.github
.venv
.vscode
.data
.temp
web/.next
web/node_modules
web/.env

View File

@@ -3,7 +3,6 @@ on:
## 发布release的时候会自动构建
release:
types: [published]
workflow_dispatch:
jobs:
publish-docker-image:
runs-on: ubuntu-latest
@@ -42,7 +41,7 @@ jobs:
run: docker buildx create --name mybuilder --use
- name: Build for Release # only relase, exlude pre-release
if: ${{ github.event.release.prerelease == false }}
run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
- name: Build for Pre-release # no update for latest tag
if: ${{ github.event.release.prerelease == true }}
run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push
run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

View File

@@ -26,7 +26,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.10', '3.11', '3.12']
python-version: ['3.11', '3.12', '3.13']
fail-fast: false
steps:

View File

@@ -8,16 +8,17 @@ LangBot is a open-source LLM native instant messaging bot development platform,
LangBot has a comprehensive frontend, all operations can be performed through the frontend. The project splited into these major parts:
- `./pkg`: The core python package of the project backend.
- `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
- `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
- `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
- `./pkg/api`: The api module of the project, containing the http api controllers and services.
- `./pkg/plugin`: LangBot bridge for connecting with plugin system.
- `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
- `./templates`: Templates of config files, components, etc.
- `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
- `./docker`: docker-compose deployment files.
- `./src/langbot`: The main python package of the project, below are the main modules in this package:
- `./pkg`: The core python package of the project backend.
- `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
- `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
- `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
- `./pkg/api`: The api module of the project, containing the http api controllers and services.
- `./pkg/plugin`: LangBot bridge for connecting with plugin system.
- `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
- `./templates`: Templates of config files, components, etc.
- `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
- `./docker`: docker-compose deployment files.
## Backend Development

View File

@@ -20,4 +20,4 @@ RUN apt update \
&& uv sync \
&& touch /.dockerenv
CMD [ "uv", "run", "main.py" ]
CMD [ "uv", "run", "--no-sync", "main.py" ]

View File

@@ -7,7 +7,6 @@ services:
langbot_plugin_runtime:
image: rockchin/langbot:latest
container_name: langbot_plugin_runtime
platform: linux/amd64 # For Apple Silicon compatibility
volumes:
- ./data/plugins:/app/data/plugins
ports:
@@ -22,7 +21,6 @@ services:
langbot:
image: rockchin/langbot:latest
container_name: langbot
platform: linux/amd64 # For Apple Silicon compatibility
volumes:
- ./data:/app/data
restart: on-failure

259
docs/SEEKDB_INTEGRATION.md Normal file
View File

@@ -0,0 +1,259 @@
# SeekDB Vector Database Integration
This document describes how to use OceanBase SeekDB as the vector database backend for LangBot's knowledge base feature.
## What is SeekDB?
**OceanBase SeekDB** is an AI-native search database that unifies relational, vector, text, JSON and GIS in a single engine, enabling hybrid search and in-database AI workflows. It's developed by OceanBase and released under Apache 2.0 license.
### Key Features
- **Hybrid Search**: Combine vector search, full-text search and relational query in a single statement
- **Multi-Model Support**: Support relational, vector, text, JSON and GIS in a single engine
- **Lightweight**: Requires as little as 1 CPU core and 2 GB of memory
- **Multiple Deployment Modes**: Supports both embedded mode and client/server mode
- **MySQL Compatible**: Powered by OceanBase engine with full ACID compliance and MySQL compatibility
## Installation
SeekDB support is automatically included when you install LangBot. The required dependency `pyseekdb` is listed in `pyproject.toml`.
If you need to install it manually:
```bash
pip install pyseekdb
```
## ⚠️ Platform Compatibility
### Embedded Mode
| Platform | Status | Notes |
|----------|--------|-------|
| Linux | ✅ Supported | Full embedded mode support via `pylibseekdb` |
| macOS | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
| Windows | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
**Important**: Embedded mode requires the `pylibseekdb` library, which is only available on Linux. If you're on macOS or Windows, you must use server mode.
### Server Mode (Docker)
| Platform | Status | Notes |
|----------|--------|-------|
| Linux | ✅ Supported | Full Docker support |
| macOS | ⚠️ Known Issue | Docker container initialization failure - [See Issue #36](https://github.com/oceanbase/seekdb/issues/36) |
| Windows | ⚠️ Untested | Should work but not yet tested |
**macOS Users**: Currently, SeekDB Docker containers have an initialization issue on macOS ([oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36)). Until this is resolved, we recommend:
- Using ChromaDB or Qdrant as alternatives
- Connecting to a remote SeekDB server on Linux if available
### Server Mode (Remote Connection)
| Platform | Status | Notes |
|----------|--------|-------|
| All Platforms | ✅ Supported | Connect to SeekDB running on a remote Linux server |
**Recommendation for macOS/Windows users**: Deploy SeekDB on a Linux server and connect via server mode configuration.
## Configuration
### Embedded Mode (Recommended for Development)
Embedded mode runs SeekDB directly within the LangBot process, storing data locally. This is the simplest setup and requires no external services.
Edit your `config.yaml`:
```yaml
vdb:
use: seekdb
seekdb:
mode: embedded
path: './data/seekdb' # Path to store SeekDB data
database: 'langbot' # Database name
```
### Server Mode (For Production)
Server mode connects to a remote SeekDB server or OceanBase server. This is recommended for production deployments.
#### SeekDB Server
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'localhost'
port: 2881
database: 'langbot'
user: 'root'
password: '' # Can also use SEEKDB_PASSWORD env var
```
#### OceanBase Server
If you're using OceanBase with seekdb capabilities:
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'localhost'
port: 2881
tenant: 'sys' # OceanBase tenant name
database: 'langbot'
user: 'root'
password: ''
```
## Configuration Parameters
| Parameter | Required | Default | Description |
|-----------|----------|--------------|-------------|
| `mode` | No | `embedded` | Deployment mode: `embedded` or `server` |
| `path` | No | `./data/seekdb` | Data directory for embedded mode |
| `database` | No | `langbot` | Database name |
| `host` | No | `localhost` | Server host (server mode only) |
| `port` | No | `2881` | Server port (server mode only) |
| `user` | No | `root` | Username (server mode only) |
| `password` | No | `''` | Password (server mode only) |
| `tenant` | No | None | OceanBase tenant (optional, server mode only) |
## Usage
Once configured, SeekDB will be used automatically for all knowledge base operations in LangBot:
1. **Creating Knowledge Bases**: Vectors will be stored in SeekDB collections
2. **Adding Documents**: Document embeddings will be indexed in SeekDB
3. **Searching**: Vector similarity search will use SeekDB's efficient indexing
4. **Deleting**: Document removal will delete vectors from SeekDB
No code changes are required - just update your configuration!
## Architecture Details
### Implementation
The SeekDB adapter is implemented in `src/langbot/pkg/vector/vdbs/seekdb.py` and follows the same `VectorDatabase` interface as Chroma and Qdrant adapters.
Key methods:
- `add_embeddings()`: Add vectors with metadata to a collection
- `search()`: Perform vector similarity search
- `delete_by_file_id()`: Delete vectors by file ID metadata
- `get_or_create_collection()`: Manage collections
- `delete_collection()`: Remove entire collections
### Vector Storage
- Collections are created with HNSW (Hierarchical Navigable Small World) index
- Default distance metric: Cosine similarity
- Default vector dimension: 384 (adjusts automatically based on embeddings)
- Metadata is stored alongside vectors for filtering
## Advantages Over Other Vector Databases
### vs. ChromaDB
- ✅ Better MySQL compatibility
- ✅ Hybrid search capabilities (vector + full-text + SQL)
- ✅ Production-grade distributed mode support
- ✅ Lightweight embedded mode
### vs. Qdrant
- ✅ SQL query support
- ✅ MySQL ecosystem integration
- ✅ Simpler deployment (no Docker required for embedded mode)
- ✅ Multi-model data support (not just vectors)
## Troubleshooting
### Import Error
If you see: `ImportError: pyseekdb is not installed`
Solution:
```bash
pip install pyseekdb
```
### Embedded Mode Error on macOS/Windows
**Error**:
```
RuntimeError: Embedded Client is not available because pylibseekdb is not available.
Please install pylibseekdb (Linux only) or use RemoteServerClient (host/port) instead.
```
**Cause**: `pylibseekdb` is only available on Linux platforms.
**Solution**: Use server mode instead:
1. Deploy SeekDB on a Linux server or VM
2. Configure LangBot to use server mode:
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'your-seekdb-server-ip'
port: 2881
database: 'langbot'
user: 'root'
password: ''
```
**Alternative**: Use ChromaDB or Qdrant, which work on all platforms:
```yaml
vdb:
use: chroma # or qdrant
```
### Docker Container Fails on macOS
**Symptoms**:
```bash
docker run -d -p 2881:2881 oceanbase/seekdb:latest
# Container exits immediately with code 30
```
**Error in logs**:
```
[ERROR] Code: Agent.SeekDB.Not.Exists
Message: initialize failed: init agent failed: SeekDB not exists in current directory.
```
**Cause**: This is a known issue with SeekDB Docker containers on macOS. See [oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36).
**Status**: Under investigation by OceanBase team.
**Workaround Options**:
1. **Use alternatives**: ChromaDB or Qdrant work perfectly on macOS
2. **Remote server**: Deploy SeekDB on a Linux server and connect remotely
3. **Wait for fix**: Monitor the GitHub issue for updates
### Connection Error (Server Mode)
If SeekDB server is not reachable, check:
1. Server is running: `ps aux | grep observer`
2. Port is accessible: `nc -zv localhost 2881`
3. Credentials are correct in config
4. Firewall allows connections on port 2881
### Performance Issues
For large datasets:
- Use server mode instead of embedded mode
- Ensure adequate memory allocation
- Consider using OceanBase distributed mode for very large scale
- Adjust HNSW index parameters if needed
## Resources
- SeekDB GitHub: https://github.com/oceanbase/seekdb
- pyseekdb SDK: https://github.com/oceanbase/pyseekdb
- OceanBase Documentation: https://oceanbase.ai
- LangBot Documentation: https://docs.langbot.app
## License
SeekDB is licensed under Apache License 2.0.

View File

@@ -1,10 +1,10 @@
[project]
name = "langbot"
version = "4.6.4"
version = "4.6.5"
description = "Easy-to-use global IM bot platform designed for LLM era"
readme = "README.md"
license-files = ["LICENSE"]
requires-python = ">=3.10.1,<4.0"
requires-python = ">=3.11,<4.0"
dependencies = [
"aiocqhttp>=1.4.4",
"aiofiles>=24.1.0",
@@ -63,7 +63,8 @@ dependencies = [
"langchain-text-splitters>=0.0.1",
"chromadb>=0.4.24",
"qdrant-client (>=1.15.1,<2.0.0)",
"langbot-plugin==0.2.3",
"pyseekdb>=0.1.0",
"langbot-plugin==0.2.4",
"asyncpg>=0.30.0",
"line-bot-sdk>=3.19.0",
"tboxsdk>=0.0.10",

View File

@@ -1,3 +1,3 @@
"""LangBot - Easy-to-use global IM bot platform designed for LLM era"""
__version__ = '4.6.4'
__version__ = '4.6.5'

View File

@@ -1,8 +1,11 @@
import asyncio
import base64
import json
import time
import urllib.parse
from typing import Callable
import dingtalk_stream # type: ignore
import websockets
from .EchoHandler import EchoTextHandler
from .dingtalkevent import DingTalkEvent
import httpx
@@ -36,6 +39,7 @@ class DingTalkClient:
self.access_token_expiry_time = ''
self.markdown_card = markdown_card
self.logger = logger
self._stopped = False # Flag to control the event loop
async def get_access_token(self):
url = 'https://api.dingtalk.com/v1.0/oauth2/accessToken'
@@ -170,6 +174,9 @@ class DingTalkClient:
"""
处理消息事件。
"""
# Skip message handling if stopped
if self._stopped:
return
msg_type = event.conversation
if msg_type in self._message_handlers:
for handler in self._message_handlers[msg_type]:
@@ -378,4 +385,70 @@ class DingTalkClient:
async def start(self):
"""启动 WebSocket 连接,监听消息"""
await self.client.start()
self._stopped = False
self.client.pre_start()
while not self._stopped:
try:
connection = self.client.open_connection()
if not connection:
if self.logger:
await self.logger.error('DingTalk: open connection failed')
await asyncio.sleep(10)
continue
uri = '%s?ticket=%s' % (connection['endpoint'], urllib.parse.quote_plus(connection['ticket']))
async with websockets.connect(uri) as websocket:
self.client.websocket = websocket
keepalive_task = asyncio.create_task(self._keepalive(websocket))
try:
async for raw_message in websocket:
if self._stopped:
break
json_message = json.loads(raw_message)
asyncio.create_task(self.client.background_task(json_message))
finally:
keepalive_task.cancel()
try:
await keepalive_task
except asyncio.CancelledError:
pass
except asyncio.CancelledError:
# Properly exit when task is cancelled
break
except websockets.exceptions.ConnectionClosedError as e:
if self._stopped:
break
if self.logger:
await self.logger.error(f'DingTalk: connection closed, reconnecting... error={e}')
await asyncio.sleep(5)
continue
except Exception as e:
if self._stopped:
break
if self.logger:
await self.logger.error(f'DingTalk: unknown exception, reconnecting... error={e}')
await asyncio.sleep(3)
continue
async def _keepalive(self, ws, ping_interval=60):
"""Keep WebSocket connection alive"""
while not self._stopped:
await asyncio.sleep(ping_interval)
try:
await ws.ping()
except websockets.exceptions.ConnectionClosed:
break
async def stop(self):
"""停止 WebSocket 连接"""
self._stopped = True
# Close WebSocket connection if exists
if self.client.websocket:
try:
await self.client.websocket.close()
except Exception:
pass
# Clear message handlers to prevent stale callbacks
self._message_handlers = {'example': []}

View File

@@ -49,6 +49,14 @@ class PipelinesRouterGroup(group.RouterGroup):
return self.success()
@self.route('/<pipeline_uuid>/copy', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _(pipeline_uuid: str) -> str:
try:
new_uuid = await self.ap.pipeline_service.copy_pipeline(pipeline_uuid)
return self.success(data={'uuid': new_uuid})
except ValueError as e:
return self.http_status(404, -1, str(e))
@self.route(
'/<pipeline_uuid>/extensions', methods=['GET', 'PUT'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
)

View File

@@ -23,6 +23,9 @@ class SystemRouterGroup(group.RouterGroup):
if 'cloud_service_url' in self.ap.instance_config.data.get('plugin', {})
else 'https://space.langbot.app'
),
'allow_change_password': self.ap.instance_config.data.get('system', {}).get(
'allow_change_password', True
),
}
)

View File

@@ -70,6 +70,13 @@ class UserRouterGroup(group.RouterGroup):
@self.route('/change-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _(user_email: str) -> str:
# Check if password change is allowed
allow_change_password = self.ap.instance_config.data.get('system', {}).get(
'allow_change_password', True
)
if not allow_change_password:
return self.http_status(403, -1, 'Password change is disabled')
json_data = await quart.request.json
current_password = json_data['current_password']

View File

@@ -151,6 +151,52 @@ class PipelineService:
)
await self.ap.pipeline_mgr.remove_pipeline(pipeline_uuid)
async def copy_pipeline(self, pipeline_uuid: str) -> str:
"""Copy a pipeline with all its configurations"""
# Get the original pipeline
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
persistence_pipeline.LegacyPipeline.uuid == pipeline_uuid
)
)
original_pipeline = result.first()
if original_pipeline is None:
raise ValueError(f'Pipeline {pipeline_uuid} not found')
# Create new pipeline data
new_uuid = str(uuid.uuid4())
new_pipeline_data = {
'uuid': new_uuid,
'name': f'{original_pipeline.name} (Copy)',
'description': original_pipeline.description,
'for_version': self.ap.ver_mgr.get_current_version(),
'stages': original_pipeline.stages.copy() if original_pipeline.stages else default_stage_order.copy(),
'config': original_pipeline.config.copy() if original_pipeline.config else {},
'is_default': False,
'extensions_preferences': (
original_pipeline.extensions_preferences.copy()
if original_pipeline.extensions_preferences
else {
'enable_all_plugins': True,
'enable_all_mcp_servers': True,
'plugins': [],
'mcp_servers': [],
}
),
}
# Insert the new pipeline
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(persistence_pipeline.LegacyPipeline).values(**new_pipeline_data)
)
# Load the new pipeline
pipeline = await self.get_pipeline(new_uuid)
await self.ap.pipeline_mgr.load_pipeline(pipeline)
return new_uuid
async def update_pipeline_extensions(
self,
pipeline_uuid: str,

View File

@@ -1,4 +1,5 @@
import logging
import logging.handlers
import sys
import time
@@ -15,6 +16,10 @@ log_colors_config = {
'CRITICAL': 'cyan',
}
# Log rotation configuration to prevent unbounded log file growth
LOG_FILE_MAX_BYTES = 10 * 1024 * 1024 # 10MB per file
LOG_FILE_BACKUP_COUNT = 5 # Keep 5 backup files (total ~50MB max)
async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.Logger:
# Remove all existing loggers
@@ -43,9 +48,17 @@ async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.
# stream_handler.setFormatter(color_formatter)
stream_handler.stream = open(sys.stdout.fileno(), mode='w', encoding='utf-8', buffering=1)
# Use RotatingFileHandler to prevent unbounded log file growth
rotating_file_handler = logging.handlers.RotatingFileHandler(
log_file_name,
encoding='utf-8',
maxBytes=LOG_FILE_MAX_BYTES,
backupCount=LOG_FILE_BACKUP_COUNT,
)
log_handlers: list[logging.Handler] = [
stream_handler,
logging.FileHandler(log_file_name, encoding='utf-8'),
rotating_file_handler,
]
log_handlers += extra_handlers if extra_handlers is not None else []

View File

@@ -33,11 +33,14 @@ class Controller:
for query in queries:
session = await self.ap.sess_mgr.get_session(query)
self.ap.logger.debug(f'Checking query {query} session {session}')
# Debug logging removed from tight loop to prevent excessive log generation
# that can cause memory overflow in high-traffic scenarios
if not session._semaphore.locked():
selected_query = query
await session._semaphore.acquire()
# Only log when actually selecting a query
self.ap.logger.debug(f'Selected query {query.query_id} for processing')
break

View File

@@ -14,6 +14,7 @@ from ....utils import importutil
from ....provider import runners
import langbot_plugin.api.entities.builtin.provider.session as provider_session
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
import langbot_plugin.api.entities.builtin.provider.message as provider_message
importutil.import_modules_in_pkg(runners)
@@ -61,8 +62,14 @@ class ChatMessageHandler(handler.MessageHandler):
yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)
else:
if event_ctx.event.user_message_alter is not None:
# if isinstance(event_ctx.event, str): # 现在暂时不考虑多模态alter
query.user_message.content = event_ctx.event.user_message_alter
if isinstance(event_ctx.event.user_message_alter, list):
query.user_message.content = event_ctx.event.user_message_alter
elif isinstance(event_ctx.event.user_message_alter, str):
query.user_message.content = [
provider_message.ContentElement.from_text(event_ctx.event.user_message_alter)
]
elif isinstance(event_ctx.event.user_message_alter, provider_message.ContentElement):
query.user_message.content = [event_ctx.event.user_message_alter]
text_length = 0
try:
@@ -79,6 +86,7 @@ class ChatMessageHandler(handler.MessageHandler):
raise ValueError(f'Request Runner not found: {query.pipeline_config["ai"]["runner"]["runner"]}')
if is_stream:
resp_message_id = uuid.uuid4()
chunk_count = 0 # Track streaming chunks to reduce excessive logging
async for result in runner.run(query):
result.resp_message_id = str(resp_message_id)
@@ -91,15 +99,30 @@ class ChatMessageHandler(handler.MessageHandler):
await query.adapter.create_message_card(str(resp_message_id), query.message_event)
is_create_card = True
query.resp_messages.append(result)
self.ap.logger.info(
f'Conversation({query.query_id}) Streaming Response: {self.cut_str(result.readable_str())}'
)
chunk_count += 1
# Only log every 10th chunk to reduce excessive logging during streaming
# This prevents memory overflow from thousands of log entries per conversation
# First chunk uses INFO level to confirm connection establishment
if chunk_count == 1:
self.ap.logger.info(
f'Conversation({query.query_id}) Streaming started: {self.cut_str(result.readable_str())}'
)
elif chunk_count % 10 == 0:
self.ap.logger.debug(
f'Conversation({query.query_id}) Streaming chunk {chunk_count}: {self.cut_str(result.readable_str())}'
)
if result.content is not None:
text_length += len(result.content)
yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
# Log final summary after streaming completes
self.ap.logger.info(
f'Conversation({query.query_id}) Streaming completed: {chunk_count} chunks, {text_length} chars'
)
else:
async for result in runner.run(query):
query.resp_messages.append(result)

View File

@@ -31,4 +31,8 @@ class AtBotRule(rule_model.GroupRespondRule):
remove_at(message_chain)
remove_at(message_chain) # 回复消息时会at两次检查并删除重复的
should_respond_at = rule_dict.get('at', None)
if should_respond_at is not None:
return entities.RuleJudgeResult(matching=found and bool(should_respond_at), replacement=message_chain)
return entities.RuleJudgeResult(matching=found, replacement=message_chain)

View File

@@ -260,7 +260,8 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
await self.bot.start()
async def kill(self) -> bool:
return False
await self.bot.stop()
return True
async def is_muted(self) -> bool:
return False

View File

@@ -9,9 +9,13 @@ import re
import base64
import uuid
import json
import time
import datetime
import hashlib
from Crypto.Cipher import AES
import tempfile
import os
import mimetypes
import aiohttp
import lark_oapi.ws.exception
@@ -19,6 +23,8 @@ import quart
from lark_oapi.api.im.v1 import *
import pydantic
from lark_oapi.api.cardkit.v1 import *
from lark_oapi.api.auth.v3 import *
from lark_oapi.core.model import *
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
import langbot_plugin.api.entities.builtin.platform.message as platform_message
@@ -238,6 +244,7 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
lb_msg_list.append(platform_message.Source(id=message.message_id, time=msg_create_time))
if message.message_type == 'text':
element_list = []
@@ -301,6 +308,10 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
message_content['content'] = [
{'tag': 'file', 'file_key': message_content['file_key'], 'file_name': message_content['file_name']}
]
elif message.message_type == 'audio':
message_content['content'] = [
{'tag': 'audio', 'file_key': message_content['file_key'], "duration": message_content.get('duration',0)}
]
for ele in message_content['content']:
if ele['tag'] == 'text':
@@ -331,6 +342,60 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
image_format = response.raw.headers['content-type']
lb_msg_list.append(platform_message.Image(base64=f'data:{image_format};base64,{image_base64}'))
elif ele['tag'] == 'audio':
file_key = ele['file_key']
duration = ele['duration']
# Download audio file
request: GetMessageResourceRequest = (
GetMessageResourceRequest.builder()
.message_id(message.message_id)
.file_key(file_key)
.type('file')
.build()
)
try:
response: GetMessageResourceResponse = await api_client.im.v1.message_resource.aget(request)
if not response.success():
print(f'Failed to download audio: code: {response.code}, msg: {response.msg}')
lb_msg_list.append(platform_message.Plain(text='[Audio file download failed]'))
return platform_message.MessageChain(lb_msg_list)
# Read audio bytes
audio_bytes = response.file.read()
audio_base64 = base64.b64encode(audio_bytes).decode()
# Get content type from response headers
content_type = response.raw.headers.get('content-type', 'audio/mpeg')
mime_main = content_type.split(';')[0].strip()
ext = mimetypes.guess_extension(mime_main) or '.bin'
temp_dir = tempfile.gettempdir()
temp_file_path = os.path.join(temp_dir, f'lark_audio_{file_key}{ext}')
with open(temp_file_path, 'wb') as f:
f.write(audio_bytes)
# Create Voice message: prefer path/url + length, include base64 as optional data URI
lb_msg_list.append(
platform_message.Voice(
voice_id=file_key,
url=f'file://{temp_file_path}',
path=temp_file_path,
base64=f'data:{content_type};base64,{audio_base64}',
length=(duration // 1000) if duration else None,
)
)
except Exception as e:
print(f'Error downloading audio: {e}')
traceback.print_exc()
lb_msg_list.append(platform_message.Plain(text='[Audio file download error]'))
elif ele['tag'] == 'file':
file_key = ele['file_key']
file_name = ele['file_name']
@@ -353,12 +418,42 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
file_bytes = response.file.read()
file_base64 = base64.b64encode(file_bytes).decode()
file_format = response.raw.headers['content-type']
file_size = len(file_bytes)
# Determine extension from content-type if possible
content_type = response.raw.headers.get('content-type', '')
mime_main = content_type.split(';')[0].strip() if content_type else ''
ext = mimetypes.guess_extension(mime_main) or ''
# Ensure a safe filename (avoid path components)
safe_name = os.path.basename(file_name).replace('/', '_').replace('\\', '_')
if ext and not safe_name.lower().endswith(ext.lower()):
filename_with_ext = f'{safe_name}{ext}'
else:
filename_with_ext = safe_name
temp_dir = tempfile.gettempdir()
temp_file_path = os.path.join(temp_dir, f'lark_{file_key}_{filename_with_ext}')
with open(temp_file_path, 'wb') as f:
f.write(file_bytes)
# Create File message with local path and file:// URL
lb_msg_list.append(
platform_message.File(base64=f'data:{file_format};base64,{file_base64}', name=file_name)
platform_message.File(
id=file_key,
name=file_name,
size=file_size,
url=f'file://{temp_file_path}',
path=temp_file_path,
base64=f'data:{file_format};base64,{file_base64}', # not including base64 by default to save memory; can be added if needed
)
)
return platform_message.MessageChain(lb_msg_list)
@@ -384,6 +479,7 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
),
message_chain=message_chain,
time=event.event.message.create_time,
source_platform_object=event,
)
elif event.event.message.chat_type == 'group':
return platform_events.GroupMessage(
@@ -400,6 +496,7 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
),
message_chain=message_chain,
time=event.event.message.create_time,
source_platform_object=event,
)
@@ -429,6 +526,10 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
seq: int # 用于在发送卡片消息中识别消息顺序直接以seq作为标识
bot_uuid: str = None # 机器人UUID
app_ticket: str = None # 商店应用用到
app_access_token: str = None # 商店应用用到
app_access_token_expire_at: int = None
tenant_access_tokens: dict[str, dict[str, str]] = {} # 租户access_token映射
def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs):
quart_app = quart.Quart(__name__)
@@ -448,8 +549,9 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
bot_account_id = config['bot_name']
bot = lark_oapi.ws.Client(config['app_id'], config['app_secret'], event_handler=event_handler)
api_client = lark_oapi.Client.builder().app_id(config['app_id']).app_secret(config['app_secret']).build()
api_client = self.build_api_client(config)
cipher = AESCipher(config.get('encrypt-key', ''))
self.request_app_ticket(api_client, config)
super().__init__(
config=config,
@@ -466,6 +568,101 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
**kwargs,
)
def request_app_ticket(self, api_client, config):
app_id = config['app_id']
app_secret = config['app_secret']
print(f'Requesting app ticket for app_id: {app_id[:3]}***{app_id[-3:]}')
if 'isv' == config.get('app_type', 'self'):
request: ResendAppTicketRequest = (
ResendAppTicketRequest.builder()
.request_body(ResendAppTicketRequestBody.builder().app_id(app_id).app_secret(app_secret).build())
.build()
)
response: ResendAppTicketResponse = api_client.auth.v3.app_ticket.resend(request)
if not response.success():
raise Exception(
f'client.auth.v3.auth.app_ticket_resend failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
)
def request_app_access_token(self):
app_id = self.config['app_id']
app_secret = self.config['app_secret']
if 'isv' == self.config.get('app_type', 'self'):
request: CreateAppAccessTokenRequest = (
CreateAppAccessTokenRequest.builder()
.request_body(
CreateAppAccessTokenRequestBody.builder()
.app_id(app_id)
.app_secret(app_secret)
.app_ticket(self.app_ticket)
.build()
)
.build()
)
response: CreateAppAccessTokenResponse = self.api_client.auth.v3.app_access_token.create(request)
if not response.success():
raise Exception(
f'client.auth.v3.auth.app_access_token failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
)
content = json.loads(response.raw.content)
self.app_access_token = content['app_access_token']
self.app_access_token_expire_at = int(time.time()) + content['expire'] - 300
def get_app_access_token(self):
if 'isv' != self.config.get('app_type', 'self'):
return None
if (
self.app_access_token is None
or self.app_access_token_expire_at is None
or int(time.time()) >= self.app_access_token_expire_at
):
self.request_app_access_token()
return self.app_access_token
def request_tenant_access_token(self, tenant_key: str):
app_access_token = self.get_app_access_token()
if 'isv' == self.config.get('app_type', 'self'):
request: CreateTenantAccessTokenRequest = (
CreateTenantAccessTokenRequest.builder()
.request_body(
CreateTenantAccessTokenRequestBody.builder()
.app_access_token(app_access_token)
.tenant_key(tenant_key)
.build()
)
.build()
)
response: CreateTenantAccessTokenResponse = self.api_client.auth.v3.tenant_access_token.create(request)
if not response.success():
raise Exception(
f'client.auth.v3.auth.tenant_access_token failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
)
content = json.loads(response.raw.content)
tenant_access_token = content['tenant_access_token']
expire = content['expire']
self.tenant_access_tokens[tenant_key] = {
'token': tenant_access_token,
'expire_at': int(time.time()) + expire - 300,
}
def get_tenant_access_token(self, tenant_key: str):
if tenant_key is None or 'isv' != self.config.get('app_type', 'self'):
return None
tenant_access_token = self.tenant_access_tokens.get(tenant_key)
if tenant_access_token is None or int(time.time()) >= tenant_access_token['expire_at']:
self.request_tenant_access_token(tenant_key)
return self.tenant_access_tokens.get(tenant_key)['token'] if self.tenant_access_tokens.get(tenant_key) else None
def build_api_client(self, config):
app_id = config['app_id']
app_secret = config['app_secret']
api_client = lark_oapi.Client.builder().app_id(app_id).app_secret(app_secret).build()
if 'isv' == config.get('app_type', 'self'):
api_client = (
lark_oapi.Client.builder().app_id(app_id).app_secret(app_secret).app_type(lark_oapi.AppType.ISV).build()
)
return api_client
async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
pass
@@ -693,9 +890,19 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
)
.build()
)
tenant_key = event.source_platform_object.header.tenant_key if event.source_platform_object else None
app_access_token = self.get_app_access_token()
tenant_access_token = self.get_tenant_access_token(tenant_key)
req_opt: RequestOption = (
RequestOption.builder()
.app_ticket(self.app_ticket)
.tenant_key(tenant_key)
.app_access_token(app_access_token)
.tenant_access_token(tenant_access_token)
.build()
)
# 发起请求
response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request)
response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request, req_opt)
# 处理失败返回
if not response.success():
@@ -722,7 +929,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
'content': text_elements,
},
}
request: ReplyMessageRequest = (
ReplyMessageRequest.builder()
.message_id(message_source.message_chain.message_id)
@@ -737,7 +943,22 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
.build()
)
response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request)
tenant_key = (
message_source.source_platform_object.header.tenant_key
if message_source.source_platform_object
else None
)
app_access_token = self.get_app_access_token()
tenant_access_token = self.get_tenant_access_token(tenant_key)
req_opt: RequestOption = (
RequestOption.builder()
.app_ticket(self.app_ticket)
.tenant_key(tenant_key)
.app_access_token(app_access_token)
.tenant_access_token(tenant_access_token)
.build()
)
response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request, req_opt)
if not response.success():
raise Exception(
@@ -762,7 +983,22 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
.build()
)
response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request)
tenant_key = (
message_source.source_platform_object.header.tenant_key
if message_source.source_platform_object
else None
)
app_access_token = self.get_app_access_token()
tenant_access_token = self.get_tenant_access_token(tenant_key)
req_opt: RequestOption = (
RequestOption.builder()
.app_ticket(self.app_ticket)
.tenant_key(tenant_key)
.app_access_token(app_access_token)
.tenant_access_token(tenant_access_token)
.build()
)
response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request, req_opt)
if not response.success():
raise Exception(
@@ -816,8 +1052,24 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
if is_final and bot_message.tool_calls is None:
# self.seq = 1 # 消息回复结束之后重置seq
self.card_id_dict.pop(message_id) # 清理已经使用过的卡片
tenant_key = (
message_source.source_platform_object.header.tenant_key
if message_source.source_platform_object
else None
)
app_access_token = self.get_app_access_token()
tenant_access_token = self.get_tenant_access_token(tenant_key)
req_opt: RequestOption = (
RequestOption.builder()
.app_ticket(self.app_ticket)
.tenant_key(tenant_key)
.app_access_token(app_access_token)
.tenant_access_token(tenant_access_token)
.build()
)
# 发起请求
response: ContentCardElementResponse = self.api_client.cardkit.v1.card_element.content(request)
response: ContentCardElementResponse = self.api_client.cardkit.v1.card_element.content(request, req_opt)
# 处理失败返回
if not response.success():
@@ -851,6 +1103,17 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
"""设置 bot UUID用于生成 webhook URL"""
self.bot_uuid = bot_uuid
def get_event_type(self, data):
schema = '1.0'
if 'schema' in data:
schema = data['schema']
if '2.0' == schema:
return data['header']['event_type']
elif 'event' in data:
return data['event']['type']
else:
return data['type']
async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
"""处理统一 webhook 请求。
Args:
@@ -866,21 +1129,18 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
if 'encrypt' in data:
data = self.cipher.decrypt_string(data['encrypt'])
data = json.loads(data)
type = data.get('type')
if type is None:
context = EventContext(data)
type = context.header.event_type
type = self.get_event_type(data)
context = EventContext(data)
if 'url_verification' == type:
# todo 验证verification token
return {'challenge': data.get('challenge')}
context = EventContext(data)
type = context.header.event_type
p2v1 = P2ImMessageReceiveV1()
p2v1.header = context.header
event = P2ImMessageReceiveV1Data()
if 'im.message.receive_v1' == type:
elif 'app_ticket' == type:
self.app_ticket = context.event['app_ticket']
elif 'im.message.receive_v1' == type:
try:
p2v1 = P2ImMessageReceiveV1()
p2v1.header = context.header
event = P2ImMessageReceiveV1Data()
event.message = EventMessage(context.event['message'])
event.sender = EventSender(context.event['sender'])
p2v1.event = event
@@ -898,7 +1158,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
final_content = {
'zh_Hans': {
'title': '',
'content': bot_added_welcome_msg,
'content': [[{'tag': 'md', 'text': bot_added_welcome_msg}]],
},
}
chat_id = context.event['chat_id']
@@ -915,17 +1175,30 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
)
.build()
)
response: CreateMessageResponse = self.api_client.im.v1.message.create(request)
tenant_key = context.header.tenant_key if context.header else None
app_access_token = self.get_app_access_token()
tenant_access_token = self.get_tenant_access_token(tenant_key)
req_opt: RequestOption = (
RequestOption.builder()
.app_ticket(self.app_ticket)
.tenant_key(tenant_key)
.app_access_token(app_access_token)
.tenant_access_token(tenant_access_token)
.build()
)
response: CreateMessageResponse = self.api_client.im.v1.message.create(request, req_opt)
if not response.success():
raise Exception(
f'client.im.v1.message.create failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
)
except Exception:
except Exception as e:
print(f'im.chat.member.bot.added_v1: {e}')
await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
return {'code': 200, 'message': 'ok'}
except Exception:
except Exception as e:
print(f'Error in lark callback: {e}')
await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
return {'code': 500, 'message': 'error'}

View File

@@ -65,6 +65,25 @@ spec:
type: boolean
required: true
default: false
- name: app_type
label:
en_US: App Type
zh_Hans: 应用类型
description:
en_US: Default to self-built application, refer to https://open.feishu.cn/document/platform-overveiw/overview
zh_Hans: 默认为企业自建应用,参考 https://open.feishu.cn/document/platform-overveiw/overview
type: select
options:
- name: self
label:
en_US: Self-built Application
zh_Hans: 自建应用
- name: isv
label:
en_US: Store Application
zh_Hans: 商店应用
required: false
default: self
- name: bot_added_welcome
label:
en_US: Bot Welcome Message

View File

@@ -65,6 +65,10 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
outbound_message_queue: asyncio.Queue = pydantic.Field(default_factory=asyncio.Queue, exclude=True)
"""后端主动推送消息的队列"""
# 流式输出开关
stream_enabled: bool = pydantic.Field(default=True, exclude=True)
"""是否启用流式输出"""
def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs):
super().__init__(
config=config,
@@ -77,6 +81,7 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
self.bot_account_id = 'websocketbot'
self.outbound_message_queue = asyncio.Queue()
self.stream_enabled = True
async def send_message(
self,
@@ -212,8 +217,8 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
return message_data.model_dump()
async def is_stream_output_supported(self) -> bool:
"""WebSocket始终支持流式输出"""
return True
"""根据stream_enabled标志返回是否支持流式输出"""
return self.stream_enabled
def register_listener(
self,
@@ -314,11 +319,16 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
Args:
connection: WebSocket连接对象
message_data: 消息数据
message_data: 消息数据,包含:
- message: 消息链
- stream: 是否启用流式输出 (可选默认True)
"""
pipeline_uuid = connection.pipeline_uuid
session_type = connection.session_type
# 获取stream参数默认为True
self.stream_enabled = message_data.get('stream', True)
# 选择会话
use_session = self.websocket_group_session if session_type == 'group' else self.websocket_person_session

View File

@@ -0,0 +1,8 @@
<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
<rect width="24" height="24" rx="5" fill="#1E3A5F"/>
<path d="M6 12C6 8.68629 8.68629 6 12 6C15.3137 6 18 8.68629 18 12" stroke="#4FC3F7" stroke-width="2" stroke-linecap="round"/>
<path d="M18 12C18 15.3137 15.3137 18 12 18C8.68629 18 6 15.3137 6 12" stroke="#81D4FA" stroke-width="2" stroke-linecap="round"/>
<circle cx="12" cy="12" r="2" fill="#4FC3F7"/>
<circle cx="6" cy="12" r="1.5" fill="#81D4FA"/>
<circle cx="18" cy="12" r="1.5" fill="#4FC3F7"/>
</svg>

After

Width:  |  Height:  |  Size: 569 B

View File

@@ -0,0 +1,59 @@
from __future__ import annotations
import typing
from .. import requester
REQUESTER_NAME: str = 'seekdb-embedding'
class SeekDBEmbedding(requester.ProviderAPIRequester):
"""SeekDB built-in embedding requester.
Uses pyseekdb's local embedding function (all-MiniLM-L6-v2).
The base_url config is reserved for future remote embedding support.
"""
default_config: dict[str, typing.Any] = {
'base_url': '',
}
_embedding_function = None
async def initialize(self):
try:
import pyseekdb
except ImportError:
raise ImportError('pyseekdb is not installed. Install it with: pip install pyseekdb')
self._embedding_function = pyseekdb.get_default_embedding_function()
async def invoke_llm(
self,
query,
model: requester.RuntimeLLMModel,
messages: typing.List,
funcs: typing.List = None,
extra_args: dict[str, typing.Any] = {},
remove_think: bool = False,
):
raise NotImplementedError('SeekDB embedding does not support LLM inference')
async def invoke_embedding(
self,
model: requester.RuntimeEmbeddingModel,
input_text: typing.List[str],
extra_args: dict[str, typing.Any] = {},
) -> typing.List[typing.List[float]]:
"""Generate embeddings using SeekDB's built-in embedding function."""
try:
if self._embedding_function is None:
await self.initialize()
if self._embedding_function is None:
raise RuntimeError("SeekDB embedding function initialization failed")
return self._embedding_function(input_text)
except Exception as e:
from .. import errors
raise errors.RequesterError(f'SeekDB embedding failed: {str(e)}')

View File

@@ -0,0 +1,21 @@
apiVersion: v1
kind: LLMAPIRequester
metadata:
name: seekdb-embedding
label:
en_US: SeekDB Embedding
zh_Hans: SeekDB 嵌入
description:
en_US: SeekDB Python library built-in embedding model (all-MiniLM-L6-v2), it will take time to download the model file for the first time
zh_Hans: 使用来自 SeekDB Python 库的内置嵌入模型 (all-MiniLM-L6-v2),首次使用时将会花费时间自动下载模型文件
ja_JP: SeekDB Python ライブラリの組み込み埋め込みモデル (all-MiniLM-L6-v2) を使用します。初回使用時にモデルファイルのダウンロードに時間がかかります。
icon: seekdb.svg
spec:
config: []
support_type:
- text-embedding
provider_category: builtin
execution:
python:
path: ./seekdbembed.py
attr: SeekDBEmbedding

View File

@@ -152,7 +152,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.Message, None]:
"""调用聊天助手"""
cov_id = query.session.using_conversation.uuid or ''
cov_id = query.session.using_conversation.uuid or None
query.variables['conversation_id'] = cov_id
plain_text, upload_files = await self._preprocess_user_message(query)
@@ -218,7 +218,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.Message, None]:
"""调用聊天助手"""
cov_id = query.session.using_conversation.uuid or ''
cov_id = query.session.using_conversation.uuid or None
query.variables['conversation_id'] = cov_id
plain_text, upload_files = await self._preprocess_user_message(query)
@@ -387,7 +387,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
"""调用聊天助手"""
cov_id = query.session.using_conversation.uuid or ''
cov_id = query.session.using_conversation.uuid or None
query.variables['conversation_id'] = cov_id
plain_text, upload_files = await self._preprocess_user_message(query)
@@ -471,7 +471,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
"""调用聊天助手"""
cov_id = query.session.using_conversation.uuid or ''
cov_id = query.session.using_conversation.uuid or None
query.variables['conversation_id'] = cov_id
plain_text, upload_files = await self._preprocess_user_message(query)

View File

@@ -70,30 +70,88 @@ class N8nServiceAPIRunner(runner.RequestRunner):
async def _process_stream_response(self, response: aiohttp.ClientResponse) -> typing.AsyncGenerator[
provider_message.Message, None]:
"""处理流式响应"""
"""处理流式响应——支持部分 JSON 和多个 JSON 对象在同一 chunk 的情况"""
full_content = ""
message_idx = 0
chunk_idx = 0
is_final = False
async for chunk in response.content.iter_chunked(1024):
if not chunk:
message_idx = 0
buffer = ""
decoder = json.JSONDecoder()
async for raw_chunk in response.content.iter_chunked(1024):
if not raw_chunk:
continue
try:
data = json.loads(chunk)
if data.get('type') == 'item' and 'content' in data:
# 将 bytes 解码为字符串(容忍错误)
if isinstance(raw_chunk, (bytes, bytearray)):
chunk_str = raw_chunk.decode('utf-8', errors='replace')
else:
chunk_str = str(raw_chunk)
buffer += chunk_str
# 尝试从 buffer 中循环解析出 JSON 对象(处理多个对象或部分对象)
while buffer:
buffer = buffer.lstrip()
if not buffer:
break
try:
obj, idx = decoder.raw_decode(buffer)
buffer = buffer[idx:]
if not isinstance(obj, dict):
# 忽略非字典类型的顶级 JSON
continue
if obj.get('type') == 'item' and 'content' in obj:
chunk_idx += 1
content = obj['content']
full_content += content
elif obj.get('type') == 'end':
is_final = True
if is_final or chunk_idx % 8 == 0:
message_idx += 1
yield provider_message.MessageChunk(
role='assistant',
content=full_content,
is_final=is_final,
msg_sequence=message_idx,
)
except json.JSONDecodeError:
# buffer 末尾可能是一个不完整的 JSON等待更多数据
break
except Exception as e:
# 记录解析失败并继续接收后续 chunk
try:
preview = chunk_str[:200]
except Exception:
preview = '<unavailable>'
self.ap.logger.warning(f"Failed to process chunk: {e}; chunk preview: {preview}")
# 流结束后,尝试解析残余 buffer
if buffer:
try:
buffer = buffer.strip()
if buffer:
obj, _ = decoder.raw_decode(buffer)
if isinstance(obj, dict):
if obj.get('type') == 'item' and 'content' in obj:
full_content += obj['content']
elif obj.get('type') == 'end':
is_final = True
message_idx += 1
content = data['content']
full_content += content
elif data.get('type') == 'end':
is_final = True
if is_final or message_idx % 8 == 0:
yield provider_message.MessageChunk(
role='assistant',
content=full_content,
is_final=is_final,
msg_sequence=message_idx,
)
except json.JSONDecodeError:
self.ap.logger.warning(f"Failed to parse final JSON line: {response.text()}")
except Exception as e:
preview = buffer[:200]
self.ap.logger.warning(f"Failed to parse remaining buffer: {e}; buffer preview: {preview}")
async def _call_webhook(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
"""调用n8n webhook"""

View File

@@ -153,7 +153,9 @@ async def get_qq_image_bytes(image_url: str, query: dict = {}) -> tuple[bytes, s
ssl_context.check_hostname = False
ssl_context.verify_mode = ssl.CERT_NONE
async with aiohttp.ClientSession(trust_env=False) as session:
async with session.get(image_url, params=query, ssl=ssl_context) as resp:
async with session.get(
image_url, params=query, ssl=ssl_context, timeout=aiohttp.ClientTimeout(total=30.0)
) as resp:
resp.raise_for_status()
file_bytes = await resp.read()
content_type = resp.headers.get('Content-Type')

View File

@@ -4,6 +4,7 @@ from ..core import app
from .vdb import VectorDatabase
from .vdbs.chroma import ChromaVectorDatabase
from .vdbs.qdrant import QdrantVectorDatabase
from .vdbs.seekdb import SeekDBVectorDatabase
from .vdbs.milvus import MilvusVectorDatabase
from .vdbs.pgvector_db import PgVectorDatabase
@@ -27,6 +28,9 @@ class VectorDBManager:
elif vdb_type == 'qdrant':
self.vector_db = QdrantVectorDatabase(self.ap)
self.ap.logger.info('Initialized Qdrant vector database backend.')
elif vdb_type == 'seekdb':
self.vector_db = SeekDBVectorDatabase(self.ap)
self.ap.logger.info('Initialized SeekDB vector database backend.')
elif vdb_type == 'milvus':
# Get Milvus configuration

View File

@@ -0,0 +1,7 @@
"""Vector database implementations for LangBot."""
from .chroma import ChromaVectorDatabase
from .qdrant import QdrantVectorDatabase
from .seekdb import SeekDBVectorDatabase
__all__ = ['ChromaVectorDatabase', 'QdrantVectorDatabase', 'SeekDBVectorDatabase']

View File

@@ -0,0 +1,252 @@
from __future__ import annotations
import asyncio
from typing import Any, Dict, List
import sqlalchemy
from langbot.pkg.core import app
from langbot.pkg.entity.persistence import model as persistence_model
from langbot.pkg.vector.vdb import VectorDatabase
try:
import pyseekdb
from pyseekdb import HNSWConfiguration
SEEKDB_AVAILABLE = True
except ImportError:
SEEKDB_AVAILABLE = False
SEEKDB_EMBEDDING_MODEL_UUID = 'seekdb-builtin-embedding'
SEEKDB_EMBEDDING_REQUESTER = 'seekdb-embedding'
class SeekDBVectorDatabase(VectorDatabase):
"""SeekDB vector database adapter for LangBot.
SeekDB is an AI-native search database by OceanBase that unifies
relational, vector, text, JSON and GIS in a single engine.
Supports both embedded mode and remote server mode.
"""
def __init__(self, ap: app.Application):
if not SEEKDB_AVAILABLE:
raise ImportError('pyseekdb is not installed. Install it with: pip install pyseekdb')
self.ap = ap
config = self.ap.instance_config.data['vdb']['seekdb']
# Determine connection mode based on config
mode = config.get('mode', 'embedded') # 'embedded' or 'server'
if mode == 'embedded':
# Embedded mode: local database
path = config.get('path', './data/seekdb')
database = config.get('database', 'langbot')
# Use AdminClient for database management operations
admin_client = pyseekdb.AdminClient(path=path)
# Check if database exists using public API
existing_dbs = [db.name for db in admin_client.list_databases()]
if database not in existing_dbs:
# Use public API to create database
admin_client.create_database(database)
self.ap.logger.info(f"Created SeekDB database '{database}'")
self.client = pyseekdb.Client(path=path, database=database)
self.ap.logger.info(f"Initialized SeekDB in embedded mode at '{path}', database '{database}'")
elif mode == 'server':
# Server mode: remote SeekDB or OceanBase server
host = config.get('host', 'localhost')
port = config.get('port', 2881)
database = config.get('database', 'langbot')
user = config.get('user', 'root')
password = config.get('password', '')
tenant = config.get('tenant', None) # Optional, for OceanBase
connection_params = {
'host': host,
'port': int(port),
'database': database,
'user': user,
'password': password,
}
if tenant:
connection_params['tenant'] = tenant
self.client = pyseekdb.Client(**connection_params)
self.ap.logger.info(
f"Initialized SeekDB in server mode: {host}:{port}, database '{database}'"
+ (f", tenant '{tenant}'" if tenant else '')
)
else:
raise ValueError(f"Invalid SeekDB mode: {mode}. Must be 'embedded' or 'server'")
self._collections: Dict[str, Any] = {}
self._collection_configs: Dict[str, HNSWConfiguration] = {}
self._escape_table = str.maketrans({
'\x00': '',
'\\': '\\\\',
'"': '\\"',
'\n': '\\n',
'\r': '\\r',
'\t': '\\t',
})
async def _get_or_create_collection_internal(self, collection: str, vector_size: int = None) -> Any:
"""Internal method to get or create a collection with proper configuration."""
if collection in self._collections:
return self._collections[collection]
# Check if collection exists
if await asyncio.to_thread(self.client.has_collection, collection):
# Collection exists, get it
coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
self._collections[collection] = coll
self.ap.logger.info(f"SeekDB collection '{collection}' retrieved.")
return coll
# Collection doesn't exist, create it
if vector_size is None:
# Default dimension if not specified
vector_size = 384
# Create HNSW configuration
config = HNSWConfiguration(dimension=vector_size, distance='cosine')
self._collection_configs[collection] = config
# Create collection without embedding function (we manage embeddings externally)
coll = await asyncio.to_thread(
self.client.create_collection,
name=collection,
configuration=config,
embedding_function=None, # Disable automatic embedding
)
self._collections[collection] = coll
self.ap.logger.info(f"SeekDB collection '{collection}' created with dimension={vector_size}, distance='cosine'")
return coll
def _clean_metadata(self, meta: Dict[str, Any]) -> Dict[str, Any]:
"""SeekDB metadata doesn't support \\ and ", insert will error 3104"""
return {
k: v.translate(self._escape_table) if isinstance(v, str)
else v if v is None or isinstance(v, (int, float, bool))
else str(v)
for k, v in meta.items()
if v is not None
}
async def get_or_create_collection(self, collection: str):
"""Get or create collection (without vector size - will use default)."""
return await self._get_or_create_collection_internal(collection)
async def add_embeddings(
self,
collection: str,
ids: List[str],
embeddings_list: List[List[float]],
metadatas: List[Dict[str, Any]]
) -> None:
"""Add vector embeddings to the specified collection.
Args:
collection: Collection name
ids: List of document IDs
embeddings_list: List of embedding vectors
metadatas: List of metadata dictionaries
"""
if not embeddings_list:
return
# Ensure collection exists with correct dimension
vector_size = len(embeddings_list[0])
coll = await self._get_or_create_collection_internal(collection, vector_size)
cleaned_metadatas = [self._clean_metadata(meta) for meta in metadatas]
await asyncio.to_thread(coll.add, ids=ids, embeddings=embeddings_list, metadatas=cleaned_metadatas)
self.ap.logger.info(f"Added {len(ids)} embeddings to SeekDB collection '{collection}'")
async def search(self, collection: str, query_embedding: List[float], k: int = 5) -> Dict[str, Any]:
"""Search for the most similar vectors in the specified collection.
Args:
collection: Collection name
query_embedding: Query vector
k: Number of results to return
Returns:
Dictionary with 'ids', 'metadatas', 'distances' keys
"""
# Check if collection exists
exists = await asyncio.to_thread(self.client.has_collection, collection)
if not exists:
return {'ids': [[]], 'metadatas': [[]], 'distances': [[]]}
# Get collection
if collection not in self._collections:
coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
self._collections[collection] = coll
else:
coll = self._collections[collection]
# Perform query
# SeekDB's query() returns: {'ids': [[...]], 'metadatas': [[...]], 'distances': [[...]]}
results = await asyncio.to_thread(coll.query, query_embeddings=query_embedding, n_results=k)
self.ap.logger.info(f"SeekDB search in '{collection}' returned {len(results.get('ids', [[]])[0])} results")
return results
async def delete_by_file_id(self, collection: str, file_id: str) -> None:
"""Delete vectors from the collection by file_id metadata.
Args:
collection: Collection name
file_id: File ID to delete
"""
# Check if collection exists
exists = await asyncio.to_thread(self.client.has_collection, collection)
if not exists:
self.ap.logger.warning(f"SeekDB collection '{collection}' not found for deletion")
return
# Get collection
if collection not in self._collections:
coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
self._collections[collection] = coll
else:
coll = self._collections[collection]
# SeekDB's delete() expects a where clause for filtering
# Delete all records where metadata['file_id'] == file_id
await asyncio.to_thread(coll.delete, where={'file_id': file_id})
self.ap.logger.info(f"Deleted embeddings from SeekDB collection '{collection}' with file_id: {file_id}")
async def delete_collection(self, collection: str):
"""Delete the entire collection.
Args:
collection: Collection name
"""
# Remove from cache
if collection in self._collections:
del self._collections[collection]
if collection in self._collection_configs:
del self._collection_configs[collection]
# Check if collection exists
exists = await asyncio.to_thread(self.client.has_collection, collection)
if not exists:
self.ap.logger.warning(f"SeekDB collection '{collection}' not found for deletion")
return
# Delete collection
await asyncio.to_thread(self.client.delete_collection, collection)
self.ap.logger.info(f"SeekDB collection '{collection}' deleted")

View File

@@ -16,6 +16,7 @@ proxy:
https: ''
system:
recovery_key: ''
allow_change_password: true
jwt:
expire: 604800
secret: ''
@@ -36,6 +37,17 @@ vdb:
host: localhost
port: 6333
api_key: ''
seekdb:
mode: embedded # 'embedded' or 'server'
# Embedded mode options:
path: './data/seekdb'
database: 'langbot'
# Server mode options (used when mode='server'):
host: 'localhost'
port: 2881
user: 'root'
password: ''
tenant: '' # Optional, for OceanBase server
milvus:
uri: 'http://127.0.0.1:19530'
token: ''

View File

@@ -51,7 +51,7 @@
"input-otp": "^1.4.2",
"lodash": "^4.17.21",
"lucide-react": "^0.507.0",
"next": "~15.5.7",
"next": "~15.5.9",
"next-themes": "^0.4.6",
"postcss": "^8.5.3",
"react": "19.2.1",

9365
web/pnpm-lock.yaml generated

File diff suppressed because it is too large Load Diff

View File

@@ -310,6 +310,7 @@ export default function BotForm({
name: item.name,
required: item.required,
type: parseDynamicFormItemType(item.type),
options: item.options,
}),
),
);

View File

@@ -12,7 +12,16 @@ import langbotIcon from '@/app/assets/langbot-logo.webp';
import { systemInfo } from '@/app/infra/http/HttpClient';
import { getCloudServiceClientSync } from '@/app/infra/http';
import { useTranslation } from 'react-i18next';
import { Moon, Sun, Monitor } from 'lucide-react';
import {
Moon,
Sun,
Monitor,
CircleHelp,
Lightbulb,
Lock,
LogOut,
KeyRound,
} from 'lucide-react';
import { useTheme } from 'next-themes';
import {
@@ -184,23 +193,6 @@ export default function HomeSidebar({
</div>
)}
<SidebarChild
onClick={() => {
setApiKeyDialogOpen(true);
}}
isSelected={false}
icon={
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 24 24"
fill="currentColor"
>
<path d="M10.7577 11.8281L18.6066 3.97919L20.0208 5.3934L18.6066 6.80761L21.0815 9.28249L19.6673 10.6967L17.1924 8.22183L15.7782 9.63604L17.8995 11.7574L16.4853 13.1716L14.364 11.0503L12.1719 13.2423C13.4581 15.1837 13.246 17.8251 11.5355 19.5355C9.58291 21.4882 6.41709 21.4882 4.46447 19.5355C2.51184 17.5829 2.51184 14.4171 4.46447 12.4645C6.17493 10.754 8.81633 10.5419 10.7577 11.8281ZM10.1213 18.1213C11.2929 16.9497 11.2929 15.0503 10.1213 13.8787C8.94975 12.7071 7.05025 12.7071 5.87868 13.8787C4.70711 15.0503 4.70711 16.9497 5.87868 18.1213C7.05025 19.2929 8.94975 19.2929 10.1213 18.1213Z"></path>
</svg>
}
name={t('common.apiIntegration')}
/>
<Popover
open={popoverOpen}
onOpenChange={(open) => {
@@ -262,6 +254,23 @@ export default function HomeSidebar({
/>
</div>
<div className="flex flex-col gap-2 w-full">
<span className="text-sm font-medium">
{t('common.integration')}
</span>
<Button
variant="ghost"
className="w-full justify-start font-normal"
onClick={() => {
setApiKeyDialogOpen(true);
setPopoverOpen(false);
}}
>
<KeyRound className="w-4 h-4 mr-2" />
{t('common.apiIntegration')}
</Button>
</div>
<div className="flex flex-col gap-2 w-full">
<span className="text-sm font-medium">{t('common.account')}</span>
<Button
@@ -289,34 +298,36 @@ export default function HomeSidebar({
setPopoverOpen(false);
}}
>
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 24 24"
fill="currentColor"
className="w-4 h-4 mr-2"
>
<path d="M12 22C6.47715 22 2 17.5228 2 12C2 6.47715 6.47715 2 12 2C17.5228 2 22 6.47715 22 12C22 17.5228 17.5228 22 12 22ZM12 20C16.4183 20 20 16.4183 20 12C20 7.58172 16.4183 4 12 4C7.58172 4 4 7.58172 4 12C4 16.4183 7.58172 20 12 20ZM11 15H13V17H11V15ZM13 13.3551V14H11V12.5C11 11.9477 11.4477 11.5 12 11.5C12.8284 11.5 13.5 10.8284 13.5 10C13.5 9.17157 12.8284 8.5 12 8.5C11.2723 8.5 10.6656 9.01823 10.5288 9.70577L8.56731 9.31346C8.88637 7.70919 10.302 6.5 12 6.5C13.933 6.5 15.5 8.067 15.5 10C15.5 11.5855 14.4457 12.9248 13 13.3551Z"></path>
</svg>
<CircleHelp className="w-4 h-4 mr-2" />
{t('common.helpDocs')}
</Button>
<Button
variant="ghost"
className="w-full justify-start font-normal"
onClick={() => {
setPasswordChangeOpen(true);
window.open(
'https://github.com/langbot-app/LangBot/issues',
'_blank',
);
setPopoverOpen(false);
}}
>
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 24 24"
fill="currentColor"
className="w-4 h-4 mr-2"
>
<path d="M6 8V7C6 3.68629 8.68629 1 12 1C15.3137 1 18 3.68629 18 7V8H20C20.5523 8 21 8.44772 21 9V21C21 21.5523 20.5523 22 20 22H4C3.44772 22 3 21.5523 3 21V9C3 8.44772 3.44772 8 4 8H6ZM19 10H5V20H19V10ZM11 15.7324C10.4022 15.3866 10 14.7403 10 14C10 12.8954 10.8954 12 12 12C13.1046 12 14 12.8954 14 14C14 14.7403 13.5978 15.3866 13 15.7324V18H11V15.7324ZM8 8H16V7C16 4.79086 14.2091 3 12 3C9.79086 3 8 4.79086 8 7V8Z"></path>
</svg>
{t('common.changePassword')}
<Lightbulb className="w-4 h-4 mr-2" />
{t('common.featureRequest')}
</Button>
{systemInfo?.allow_change_password && (
<Button
variant="ghost"
className="w-full justify-start font-normal"
onClick={() => {
setPasswordChangeOpen(true);
setPopoverOpen(false);
}}
>
<Lock className="w-4 h-4 mr-2" />
{t('common.changePassword')}
</Button>
)}
<Button
variant="ghost"
className="w-full justify-start font-normal"
@@ -324,14 +335,7 @@ export default function HomeSidebar({
handleLogout();
}}
>
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 24 24"
fill="currentColor"
className="w-4 h-4 mr-2"
>
<path d="M4 18H6V20H18V4H6V6H4V3C4 2.44772 4.44772 2 5 2H19C19.5523 2 20 2.44772 20 3V21C20 21.5523 19.5523 22 19 22H5C4.44772 22 4 21.5523 4 21V18ZM6 11H13V13H6V16L1 12L6 8V11Z"></path>
</svg>
<LogOut className="w-4 h-4 mr-2" />
{t('common.logout')}
</Button>
</div>

View File

@@ -2,4 +2,5 @@ export interface IChooseRequesterEntity {
label: string;
value: string;
provider_category?: string;
description?: string;
}

View File

@@ -33,19 +33,21 @@ export default function EmbeddingCard({ cardVO }: { cardVO: EmbeddingCardVO }) {
</span>
</div>
{/* baseURL */}
<div className={`${styles.baseURLContainer}`}>
<svg
className={`${styles.baseURLIcon}`}
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 24 24"
width="36"
height="36"
fill="rgba(98,98,98,1)"
>
<path d="M13.0607 8.11097L14.4749 9.52518C17.2086 12.2589 17.2086 16.691 14.4749 19.4247L14.1214 19.7782C11.3877 22.5119 6.95555 22.5119 4.22188 19.7782C1.48821 17.0446 1.48821 12.6124 4.22188 9.87874L5.6361 11.293C3.68348 13.2456 3.68348 16.4114 5.6361 18.364C7.58872 20.3166 10.7545 20.3166 12.7072 18.364L13.0607 18.0105C15.0133 16.0578 15.0133 12.892 13.0607 10.9394L11.6465 9.52518L13.0607 8.11097ZM19.7782 14.1214L18.364 12.7072C20.3166 10.7545 20.3166 7.58872 18.364 5.6361C16.4114 3.68348 13.2456 3.68348 11.293 5.6361L10.9394 5.98965C8.98678 7.94227 8.98678 11.1081 10.9394 13.0607L12.3536 14.4749L10.9394 15.8891L9.52518 14.4749C6.79151 11.7413 6.79151 7.30911 9.52518 4.57544L9.87874 4.22188C12.6124 1.48821 17.0446 1.48821 19.7782 4.22188C22.5119 6.95555 22.5119 11.3877 19.7782 14.1214Z"></path>
</svg>
<span className={`${styles.baseURLText}`}>{cardVO.baseURL}</span>
</div>
{cardVO.baseURL && (
<div className={`${styles.baseURLContainer}`}>
<svg
className={`${styles.baseURLIcon}`}
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 24 24"
width="36"
height="36"
fill="rgba(98,98,98,1)"
>
<path d="M13.0607 8.11097L14.4749 9.52518C17.2086 12.2589 17.2086 16.691 14.4749 19.4247L14.1214 19.7782C11.3877 22.5119 6.95555 22.5119 4.22188 19.7782C1.48821 17.0446 1.48821 12.6124 4.22188 9.87874L5.6361 11.293C3.68348 13.2456 3.68348 16.4114 5.6361 18.364C7.58872 20.3166 10.7545 20.3166 12.7072 18.364L13.0607 18.0105C15.0133 16.0578 15.0133 12.892 13.0607 10.9394L11.6465 9.52518L13.0607 8.11097ZM19.7782 14.1214L18.364 12.7072C20.3166 10.7545 20.3166 7.58872 18.364 5.6361C16.4114 3.68348 13.2456 3.68348 11.293 5.6361L10.9394 5.98965C8.98678 7.94227 8.98678 11.1081 10.9394 13.0607L12.3536 14.4749L10.9394 15.8891L9.52518 14.4749C6.79151 11.7413 6.79151 7.30911 9.52518 4.57544L9.87874 4.22188C12.6124 1.48821 17.0446 1.48821 19.7782 4.22188C22.5119 6.95555 22.5119 11.3877 19.7782 14.1214Z"></path>
</svg>
<span className={`${styles.baseURLText}`}>{cardVO.baseURL}</span>
</div>
)}
</div>
</div>
</div>

View File

@@ -75,7 +75,7 @@ const getFormSchema = (t: (key: string) => string) =>
model_provider: z
.string()
.min(1, { message: t('models.modelProviderRequired') }),
url: z.string().min(1, { message: t('models.requestURLRequired') }),
url: z.string().optional(),
api_key: z.string().optional(),
extra_args: z.array(getExtraArgSchema(t)).optional(),
});
@@ -188,6 +188,7 @@ export default function EmbeddingForm({
label: extractI18nObject(item.label),
value: item.name,
provider_category: item.spec.provider_category || 'manufacturer',
description: extractI18nObject(item.description) || undefined,
};
}),
);
@@ -243,7 +244,7 @@ export default function EmbeddingForm({
description: '',
requester: value.model_provider,
requester_config: {
base_url: value.url,
base_url: value.url || '',
timeout: 120,
},
extra_args: extraArgsObj,
@@ -320,7 +321,7 @@ export default function EmbeddingForm({
description: '',
requester: form.getValues('model_provider'),
requester_config: {
base_url: form.getValues('url'),
base_url: form.getValues('url') ?? '',
timeout: 120,
},
api_keys: apiKey ? [apiKey] : [],
@@ -425,6 +426,18 @@ export default function EmbeddingForm({
/>
</SelectTrigger>
<SelectContent>
<SelectGroup>
<SelectLabel>{t('models.builtin')}</SelectLabel>
{requesterNameList
.filter(
(item) => item.provider_category === 'builtin',
)
.map((item) => (
<SelectItem key={item.value} value={item.value}>
{item.label}
</SelectItem>
))}
</SelectGroup>
<SelectGroup>
<SelectLabel>
{t('models.modelManufacturer')}
@@ -468,29 +481,42 @@ export default function EmbeddingForm({
</SelectContent>
</Select>
</FormControl>
{currentModelProvider &&
requesterNameList.find(
(item) => item.value === currentModelProvider,
)?.description && (
<FormDescription>
{
requesterNameList.find(
(item) => item.value === currentModelProvider,
)?.description
}
</FormDescription>
)}
<FormMessage />
</FormItem>
)}
/>
<FormField
control={form.control}
name="url"
render={({ field }) => (
<FormItem>
<FormLabel>
{t('models.requestURL')}
<span className="text-red-500">*</span>
</FormLabel>
<FormControl>
<Input {...field} />
</FormControl>
<FormMessage />
</FormItem>
)}
/>
{!['seekdb-embedding'].includes(currentModelProvider) && (
<FormField
control={form.control}
name="url"
render={({ field }) => (
<FormItem>
<FormLabel>{t('models.requestURL')}</FormLabel>
<FormControl>
<Input {...field} />
</FormControl>
<FormMessage />
</FormItem>
)}
/>
)}
{!['ollama-chat'].includes(currentModelProvider) && (
{!['ollama-chat', 'seekdb-embedding'].includes(
currentModelProvider,
) && (
<FormField
control={form.control}
name="api_key"

View File

@@ -5,6 +5,7 @@ import { DialogContent } from '@/components/ui/dialog';
import { Button } from '@/components/ui/button';
import { Input } from '@/components/ui/input';
import { ScrollArea } from '@/components/ui/scroll-area';
import { Switch } from '@/components/ui/switch';
import { cn } from '@/lib/utils';
import {
Message,
@@ -60,6 +61,7 @@ export default function DebugDialog({
const [rawModeMessages, setRawModeMessages] = useState<Set<string>>(
new Set(),
);
const [streamOutput, setStreamOutput] = useState(true);
const messagesEndRef = useRef<HTMLDivElement>(null);
const inputRef = useRef<HTMLInputElement>(null);
const popoverRef = useRef<HTMLDivElement>(null);
@@ -384,7 +386,7 @@ export default function DebugDialog({
// 通过WebSocket发送消息
// 不在本地添加消息等待后端广播回来带有正确的ID
wsClientRef.current.sendMessage(messageChain);
wsClientRef.current.sendMessage(messageChain, streamOutput);
} catch (error) {
console.error('Failed to send message:', error);
toast.error(t('pipelines.debugDialog.sendFailed'));
@@ -897,7 +899,18 @@ export default function DebugDialog({
)}
<div className="p-4 pb-0 bg-white dark:bg-black flex gap-2">
<div className="flex gap-2">
<div className="flex gap-2 items-center">
<div className="flex items-center gap-1">
<span className="text-xs text-gray-500 dark:text-gray-400">
{t('pipelines.debugDialog.streamOutput')}
</span>
<Switch
checked={streamOutput}
onCheckedChange={setStreamOutput}
disabled={!isConnected}
className="data-[state=checked]:bg-[#2288ee]"
/>
</div>
<input
ref={fileInputRef}
type="file"

View File

@@ -52,6 +52,7 @@ export default function PipelineFormComponent({
}) {
const { t } = useTranslation();
const [showDeleteConfirm, setShowDeleteConfirm] = useState(false);
const [showCopyConfirm, setShowCopyConfirm] = useState(false);
const [isDefaultPipeline, setIsDefaultPipeline] = useState<boolean>(false);
const formSchema = isEditMode
@@ -345,25 +346,17 @@ export default function PipelineFormComponent({
};
const handleCopy = () => {
setShowCopyConfirm(true);
};
const confirmCopy = () => {
if (pipelineId) {
let newPipelineName = '';
httpClient
.getPipeline(pipelineId)
.then((resp) => {
const originalPipeline = resp.pipeline;
newPipelineName = `${originalPipeline.name}${t(
'pipelines.copySuffix',
)}`;
const newPipeline: Pipeline = {
name: newPipelineName,
description: originalPipeline.description,
config: originalPipeline.config,
};
return httpClient.createPipeline(newPipeline);
})
.copyPipeline(pipelineId)
.then(() => {
onFinish();
toast.success(`${t('common.copySuccess')}: ${newPipelineName}`);
toast.success(t('common.copySuccess'));
setShowCopyConfirm(false);
onCancel();
})
.catch((err) => {
@@ -547,6 +540,22 @@ export default function PipelineFormComponent({
</DialogFooter>
</DialogContent>
</Dialog>
{/* 复制确认对话框 */}
<Dialog open={showCopyConfirm} onOpenChange={setShowCopyConfirm}>
<DialogContent>
<DialogHeader>
<DialogTitle>{t('pipelines.copyConfirmTitle')}</DialogTitle>
</DialogHeader>
<div className="py-4">{t('pipelines.copyConfirmation')}</div>
<DialogFooter>
<Button variant="outline" onClick={() => setShowCopyConfirm(false)}>
{t('common.cancel')}
</Button>
<Button onClick={confirmCopy}>{t('common.confirm')}</Button>
</DialogFooter>
</DialogContent>
</Dialog>
</>
);
}

View File

@@ -13,6 +13,7 @@ export interface IPluginCardVO {
status: string;
components: PluginComponent[];
debug: boolean;
hasUpdate?: boolean;
}
export class PluginCardVO implements IPluginCardVO {
@@ -28,6 +29,7 @@ export class PluginCardVO implements IPluginCardVO {
install_info: Record<string, any>; // eslint-disable-line @typescript-eslint/no-explicit-any
status: string;
components: PluginComponent[];
hasUpdate?: boolean;
constructor(prop: IPluginCardVO) {
this.author = prop.author;
@@ -42,5 +44,6 @@ export class PluginCardVO implements IPluginCardVO {
this.debug = prop.debug;
this.install_source = prop.install_source;
this.install_info = prop.install_info;
this.hasUpdate = prop.hasUpdate;
}
}

View File

@@ -7,6 +7,8 @@ import PluginForm from '@/app/home/plugins/components/plugin-installed/plugin-fo
import PluginReadme from '@/app/home/plugins/components/plugin-installed/plugin-readme/PluginReadme';
import styles from '@/app/home/plugins/plugins.module.css';
import { httpClient } from '@/app/infra/http/HttpClient';
import { getCloudServiceClientSync } from '@/app/infra/http';
import { isNewerVersion } from '@/app/utils/versionCompare';
import {
Dialog,
DialogContent,
@@ -72,10 +74,68 @@ const PluginInstalledComponent = forwardRef<PluginInstalledComponentRef>(
getPluginList();
}
function getPluginList() {
httpClient.getPlugins().then((value) => {
async function getPluginList() {
try {
// 获取已安装插件列表
const installedPluginsResp = await httpClient.getPlugins();
const installedPlugins = installedPluginsResp.plugins;
// 获取市场插件列表
const client = getCloudServiceClientSync();
const marketplaceResp = await client.getMarketplacePlugins(1, 100);
const marketplacePlugins = marketplaceResp.plugins;
// 创建市场插件映射,便于快速查找
const marketplacePluginMap = new Map();
marketplacePlugins.forEach((plugin) => {
const key = `${plugin.author}/${plugin.name}`;
marketplacePluginMap.set(key, plugin);
});
// 转换并比较版本号
const pluginCards = installedPlugins.map((plugin) => {
const cardVO = new PluginCardVO({
author: plugin.manifest.manifest.metadata.author ?? '',
label: extractI18nObject(plugin.manifest.manifest.metadata.label),
description: extractI18nObject(
plugin.manifest.manifest.metadata.description ?? {
en_US: '',
zh_Hans: '',
},
),
debug: plugin.debug,
enabled: plugin.enabled,
name: plugin.manifest.manifest.metadata.name,
version: plugin.manifest.manifest.metadata.version ?? '',
status: plugin.status,
components: plugin.components,
priority: plugin.priority,
install_source: plugin.install_source,
install_info: plugin.install_info,
});
// 检查是否来自市场且有更新
if (cardVO.install_source === 'marketplace') {
const marketplaceKey = `${cardVO.author}/${cardVO.name}`;
const marketplacePlugin = marketplacePluginMap.get(marketplaceKey);
if (marketplacePlugin && marketplacePlugin.latest_version) {
cardVO.hasUpdate = isNewerVersion(
marketplacePlugin.latest_version,
cardVO.version,
);
}
}
return cardVO;
});
setPluginList(pluginCards);
} catch (error) {
console.error('获取插件列表失败:', error);
// 失败时仍显示已安装插件,不影响用户体验
const installedPluginsResp = await httpClient.getPlugins();
setPluginList(
value.plugins.map((plugin) => {
installedPluginsResp.plugins.map((plugin) => {
return new PluginCardVO({
author: plugin.manifest.manifest.metadata.author ?? '',
label: extractI18nObject(plugin.manifest.manifest.metadata.label),
@@ -97,7 +157,7 @@ const PluginInstalledComponent = forwardRef<PluginInstalledComponentRef>(
});
}),
);
});
}
}
useImperativeHandle(ref, () => ({

View File

@@ -159,12 +159,17 @@ export default function PluginCardComponent({
}}
>
<DropdownMenuTrigger asChild>
<Button
variant="ghost"
className="bg-white dark:bg-[#1f1f22] hover:bg-gray-100 dark:hover:bg-[#2a2a2d]"
>
<Ellipsis className="w-4 h-4" />
</Button>
<div className="relative">
<Button
variant="ghost"
className="bg-white dark:bg-[#1f1f22] hover:bg-gray-100 dark:hover:bg-[#2a2a2d]"
>
<Ellipsis className="w-4 h-4" />
</Button>
{cardVO.hasUpdate && (
<div className="absolute -top-0.5 -right-0.5 w-2.5 h-2.5 bg-red-500 rounded-full border-2 border-white dark:border-[#1f1f22]"></div>
)}
</div>
</DropdownMenuTrigger>
<DropdownMenuContent>
{/**upgrade */}
@@ -179,6 +184,11 @@ export default function PluginCardComponent({
>
<ArrowUp className="w-4 h-4" />
<span>{t('plugins.update')}</span>
{cardVO.hasUpdate && (
<Badge className="ml-auto bg-red-500 hover:bg-red-500 text-white text-[0.6rem] px-1.5 py-0 h-4">
{t('plugins.new')}
</Badge>
)}
</DropdownMenuItem>
)}
{/**view source */}

View File

@@ -235,6 +235,7 @@ export interface ApiRespSystemInfo {
version: string;
cloud_service_url: string;
enable_marketplace: boolean;
allow_change_password: boolean;
}
export interface ApiRespPluginSystemStatus {

View File

@@ -172,6 +172,10 @@ export class BackendClient extends BaseHttpClient {
return this.delete(`/api/v1/pipelines/${uuid}`);
}
public copyPipeline(uuid: string): Promise<{ uuid: string }> {
return this.post(`/api/v1/pipelines/${uuid}/copy`);
}
public getPipelineExtensions(uuid: string): Promise<{
enable_all_plugins: boolean;
enable_all_mcp_servers: boolean;

View File

@@ -8,6 +8,7 @@ export let systemInfo: ApiRespSystemInfo = {
version: '',
enable_marketplace: true,
cloud_service_url: '',
allow_change_password: true,
};
/**

View File

@@ -204,6 +204,7 @@ export class WebSocketClient {
*/
public sendMessage(
messageChain: Array<{ type: string; text?: string; target?: string }>,
stream: boolean = true,
) {
if (!this.ws || this.ws.readyState !== WebSocket.OPEN) {
throw new Error('WebSocket未连接');
@@ -212,6 +213,7 @@ export class WebSocketClient {
const message = {
type: 'message',
message: messageChain,
stream: stream,
};
this.ws.send(JSON.stringify(message));

View File

@@ -0,0 +1,45 @@
/**
* Compare two version strings and determine if the first is newer than the second.
* Supports semantic versioning format (e.g., "1.2.3", "1.0.0-beta.1").
*
* @param version1 - The version to compare (potentially newer)
* @param version2 - The version to compare against (base version)
* @returns true if version1 is newer than version2, false otherwise
*/
export function isNewerVersion(version1: string, version2: string): boolean {
if (!version1 || !version2) {
return false;
}
// Remove any leading 'v' prefix
const v1 = version1.replace(/^v/, '');
const v2 = version2.replace(/^v/, '');
// Split into main version and pre-release parts
const [main1, pre1] = v1.split('-');
const [main2, pre2] = v2.split('-');
// Split main version into numeric parts
const parts1 = main1.split('.').map((p) => parseInt(p, 10) || 0);
const parts2 = main2.split('.').map((p) => parseInt(p, 10) || 0);
// Normalize length
const maxLen = Math.max(parts1.length, parts2.length);
while (parts1.length < maxLen) parts1.push(0);
while (parts2.length < maxLen) parts2.push(0);
// Compare main version parts
for (let i = 0; i < maxLen; i++) {
if (parts1[i] > parts2[i]) return true;
if (parts1[i] < parts2[i]) return false;
}
// Main versions are equal, compare pre-release
// A version without pre-release is newer than one with pre-release
if (!pre1 && pre2) return true;
if (pre1 && !pre2) return false;
if (!pre1 && !pre2) return false;
// Both have pre-release, compare lexicographically
return pre1! > pre2!;
}

View File

@@ -2,8 +2,9 @@ const enUS = {
common: {
login: 'Login',
logout: 'Logout',
accountOptions: 'Account',
accountOptions: 'Settings',
account: 'Account',
integration: 'Integration',
email: 'Email',
password: 'Password',
welcome: 'Welcome back to LangBot 👋',
@@ -16,6 +17,7 @@ const enUS = {
emptyPassword: 'Please enter your password',
language: 'Language',
helpDocs: 'Get Help',
featureRequest: 'Feature Request',
create: 'Create',
edit: 'Edit',
delete: 'Delete',
@@ -141,10 +143,11 @@ const enUS = {
boolean: 'Boolean',
selectModelProvider: 'Select Model Provider',
modelProviderDescription:
'Please fill in the model name provided by the supplier',
'Please fill in the model name provided by the provider',
modelManufacturer: 'Model Manufacturer',
aggregationPlatform: 'Aggregation Platform',
selfDeployed: 'Self-deployed',
builtin: 'Built-in',
selectModel: 'Select Model',
testSuccess: 'Test successful',
testError: 'Test failed, please check your model configuration',
@@ -288,6 +291,7 @@ const enUS = {
noComponents: 'No components',
delete: 'Delete Plugin',
update: 'Update Plugin',
new: 'New',
updateConfirm: 'Update Confirmation',
confirmUpdatePlugin:
'Are you sure you want to update the plugin ({{author}}/{{name}})?',
@@ -492,6 +496,9 @@ const enUS = {
defaultPipelineCannotDelete: 'Default pipeline cannot be deleted',
deleteSuccess: 'Deleted successfully',
deleteError: 'Delete failed: ',
copyConfirmTitle: 'Confirm Copy',
copyConfirmation:
'Are you sure you want to copy this pipeline? This will create a new pipeline with all configurations.',
extensions: {
title: 'Extensions',
loadError: 'Failed to load plugins',
@@ -535,6 +542,7 @@ const enUS = {
loadPipelinesFailed: 'Failed to load pipelines',
atTips: 'Mention the bot',
streaming: 'Streaming',
streamOutput: 'Stream',
connected: 'WebSocket connected',
disconnected: 'WebSocket disconnected',
connectionError: 'WebSocket connection error',

View File

@@ -2,8 +2,9 @@ const jaJP = {
common: {
login: 'ログイン',
logout: 'ログアウト',
accountOptions: 'アカウントオプション',
accountOptions: 'システム設定',
account: 'アカウント',
integration: '連携',
email: 'メールアドレス',
password: 'パスワード',
welcome: 'LangBot へおかえりなさい 👋',
@@ -17,6 +18,7 @@ const jaJP = {
emptyPassword: 'パスワードを入力してください',
language: '言語',
helpDocs: 'ヘルプドキュメント',
featureRequest: '機能リクエスト',
create: '作成',
edit: '編集',
delete: '削除',
@@ -148,6 +150,7 @@ const jaJP = {
modelManufacturer: 'モデルメーカー',
aggregationPlatform: 'アグリゲーションプラットフォーム',
selfDeployed: 'セルフデプロイ',
builtin: 'ビルトイン',
selectModel: 'モデルを選択してください',
testSuccess: 'テストに成功しました',
testError: 'テストに失敗しました。モデル設定を確認してください',
@@ -289,6 +292,7 @@ const jaJP = {
noComponents: '部品がありません',
delete: 'プラグインを削除',
update: 'プラグインを更新',
new: 'New',
updateConfirm: '更新の確認',
confirmUpdatePlugin:
'プラグイン「{{author}}/{{name}}」を更新してもよろしいですか?',
@@ -495,6 +499,9 @@ const jaJP = {
defaultPipelineCannotDelete: 'デフォルトパイプラインは削除できません',
deleteSuccess: '削除に成功しました',
deleteError: '削除に失敗しました:',
copyConfirmTitle: 'コピーの確認',
copyConfirmation:
'このパイプラインをコピーしますか?すべての設定を含む新しいパイプラインが作成されます。',
extensions: {
title: 'プラグイン統合',
loadError: 'プラグインリストの読み込みに失敗しました',
@@ -538,6 +545,7 @@ const jaJP = {
loadPipelinesFailed: 'パイプラインの読み込みに失敗しました',
atTips: 'ボットをメンション',
streaming: 'ストリーミング',
streamOutput: 'ストリーム',
connected: 'WebSocket接続済み',
disconnected: 'WebSocket未接続',
connectionError: 'WebSocket接続エラー',

View File

@@ -2,8 +2,9 @@ const zhHans = {
common: {
login: '登录',
logout: '退出登录',
accountOptions: '账户选项',
accountOptions: '系统设置',
account: '账户',
integration: '连接',
email: '邮箱',
password: '密码',
welcome: '欢迎回到 LangBot 👋',
@@ -16,6 +17,7 @@ const zhHans = {
emptyPassword: '请输入密码',
language: '语言',
helpDocs: '帮助文档',
featureRequest: '需求建议',
create: '创建',
edit: '编辑',
delete: '删除',
@@ -142,6 +144,7 @@ const zhHans = {
modelManufacturer: '模型厂商',
aggregationPlatform: '中转平台',
selfDeployed: '自部署',
builtin: '内置',
selectModel: '请选择模型',
testSuccess: '测试成功',
testError: '测试失败,请检查模型配置',
@@ -275,6 +278,7 @@ const zhHans = {
noComponents: '无组件',
delete: '删除插件',
update: '更新插件',
new: '新',
updateConfirm: '更新确认',
confirmUpdatePlugin: '你确定要更新插件({{author}}/{{name}})吗?',
confirmUpdate: '确认更新',
@@ -474,6 +478,9 @@ const zhHans = {
defaultPipelineCannotDelete: '默认流水线不可删除',
deleteSuccess: '删除成功',
deleteError: '删除失败:',
copyConfirmTitle: '确认复制',
copyConfirmation:
'确定要复制这个流水线吗?复制将创建一个包含完整配置的新流水线。',
extensions: {
title: '扩展集成',
loadError: '加载插件列表失败',
@@ -517,6 +524,7 @@ const zhHans = {
loadPipelinesFailed: '加载流水线失败',
atTips: '提及机器人',
streaming: '流式传输',
streamOutput: '流式',
connected: 'WebSocket已连接',
disconnected: 'WebSocket未连接',
connectionError: 'WebSocket连接错误',

View File

@@ -2,8 +2,9 @@ const zhHant = {
common: {
login: '登入',
logout: '登出',
accountOptions: '帳戶選項',
accountOptions: '系統設定',
account: '帳戶',
integration: '連接',
email: '電子郵件',
password: '密碼',
welcome: '歡迎回到 LangBot 👋',
@@ -16,6 +17,7 @@ const zhHant = {
emptyPassword: '請輸入密碼',
language: '語言',
helpDocs: '輔助說明',
featureRequest: '需求建議',
create: '建立',
edit: '編輯',
delete: '刪除',
@@ -142,6 +144,7 @@ const zhHant = {
modelManufacturer: '模型廠商',
aggregationPlatform: '中轉平台',
selfDeployed: '自部署',
builtin: '內建',
selectModel: '請選擇模型',
testSuccess: '測試成功',
testError: '測試失敗,請檢查模型設定',
@@ -274,6 +277,7 @@ const zhHant = {
noComponents: '無組件',
delete: '刪除插件',
update: '更新插件',
new: '新',
updateConfirm: '更新確認',
confirmUpdatePlugin: '您確定要更新插件({{author}}/{{name}})嗎?',
confirmUpdate: '確認更新',
@@ -472,6 +476,9 @@ const zhHant = {
defaultPipelineCannotDelete: '預設流程線不可刪除',
deleteSuccess: '刪除成功',
deleteError: '刪除失敗:',
copyConfirmTitle: '確認複製',
copyConfirmation:
'確定要複製這個流程線嗎?複製將創建一個包含完整配置的新流程線。',
extensions: {
title: '擴展集成',
loadError: '載入插件清單失敗',
@@ -515,6 +522,7 @@ const zhHant = {
loadPipelinesFailed: '載入流程線失敗',
atTips: '提及機器人',
streaming: '串流傳輸',
streamOutput: '串流',
connected: 'WebSocket已連接',
disconnected: 'WebSocket未連接',
connectionError: 'WebSocket連接錯誤',