Compare commits

...

20 Commits

Author SHA1 Message Date
Junyan Qin
20f5ebd9b8 chore: bump version 4.9.1 2026-03-12 23:24:33 +08:00
Junyan Qin
d2c75329cf fix: kbform react error 2026-03-12 23:20:51 +08:00
Junyan Qin
7e2fe082f0 chore: bump langbot-plugin to 0.3.1 2026-03-12 23:16:09 +08:00
fdc310
d451b059fd feat: Implement WebSocket long connection client for WeChat Work AI Bot (#2054)
* feat: Implement WebSocket long connection client for WeChat Work AI Bot

- Added WecomBotWsClient to handle WebSocket connections for receiving messages and sending replies.
- Introduced a new migration (dbm022) to add 'enable-webhook' field to existing wecombot adapter configs, ensuring backward compatibility.
- Updated WecomBotAdapter to support both WebSocket and webhook modes based on the new configuration.
- Enhanced YAML configuration for WecomBot to include 'enable-webhook' and 'Secret' fields, adjusting requirements accordingly.
- Incremented database version to 22 to reflect schema changes.

* fix:db enable-webhook is false

* fix:add logic

* fix:Removed an unnecessary configuration check

* fix: migration

* fix: update migration

* fix:migration
2026-03-12 22:31:14 +08:00
marun
93c52fcd4c Enhance Lark Bot Ability to Reply to Quoted Messages (#2043)
* fix(database): Update database version requirement to 20

- Increase required_database_version from 19 to 20
- Add documentation on database schema version check

* feat(lark): Added support for message references and topic message grouping

- Implemented the function to extract reference message IDs from messages, supporting parent message identification

- Added a method to construct event messages from SDK message items

- Implemented the function to asynchronously obtain reference messages and convert them into message chains

- Integrated reference message injection logic into the message processing flow

- Added a mechanism to filter source components while retaining reference content

- Implemented a method to obtain the starter ID with topic awareness

- Provided session isolation support for topic range in group thread messages

- Supported stable maintenance of conversation context in group thread discussions

- Handled cases where topic messages cannot reliably detect reference targets

* feat(lark): Implement a duplicate prevention mechanism for Feishu topic message references

- Add class-level cache to store processed topic IDs and timestamps

- Implement a timed cleanup mechanism to remove expired topic records

- Add cache size limit to prevent memory from growing indefinitely

- Return the parent message ID and mark it as processed when the first reply is made to a topic

- Return None in subsequent replies to the same topic to avoid duplicate references

- Implement automatic cache trimming to ensure stable performance
2026-03-12 21:48:30 +08:00
huanghuoguoguo
f1608682e6 Feat/agentic rag and parser invoke api (#2052)
* feat: add pipeline api

* feat: add list parser

* ruff lint

* fix: add filter but agentic rag not to use

* feat: add bot uuid for memory..
2026-03-12 21:47:27 +08:00
youhuanghe
077e631c13 fix(rag): normalize vector search to distance semantics 2026-03-12 12:33:09 +00:00
Junyan Chin
d7df1f05d1 fix: resolve security vulnerabilities in dependencies (#2059)
Python (uv.lock):
- langchain-core 1.2.7 → 1.2.18 (SSRF via image_url token counting)
- langgraph 1.0.7 → 1.1.1 (unsafe msgpack deserialization)
- flask 3.1.2 → 3.1.3 (missing Vary: Cookie header)
- werkzeug 3.1.5 → 3.1.6 (Windows special device name in safe_join)

npm (web/pnpm-lock.yaml):
- minimatch updated to fix ReDoS vulnerabilities
2026-03-12 20:09:19 +08:00
Junyan Chin
8b8cfb76de fix(market): sync plugin market UI improvements from Space (#2056)
* fix(market): sync plugin market UI from space - page size 12, full list display, fix double separator, adaptive tag display

* fix: lint and prettier formatting

* fix: prettier formatting for remaining files
2026-03-12 15:06:11 +08:00
Junyan Chin
79311ccde3 feat: model fallback chain (#2017) (#2018) 2026-03-12 03:33:05 +08:00
Guanchao Wang
89064a9d5b feat: add support for username (#2047)
* feat: add support for username

* fix: lint

* fix: migerations

* fix: change to version 21

* fix: remove duplicate dbm021 migration and rename dbm022

* feat: add user_id and user_name display with copy functionality in BotSessionMonitor

---------

Co-authored-by: wangcham <wangcham@gmail.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2026-03-12 01:27:22 +08:00
RockChinQ
8c2aef3734 fix: prettier formatting for long URL strings 2026-03-11 07:05:45 -04:00
RockChinQ
3fb9e542b6 fix(web): use locale-aware data collection policy URL 2026-03-11 07:03:52 -04:00
RockChinQ
01844d8687 feat(web): add privacy & data collection policy consent to login/register pages 2026-03-11 06:50:54 -04:00
Copilot
2655425fbe fix: deduplicate final chunk yield in Dify chatflow streaming (#2049)
* Initial plan

* fix: prevent duplicate messages when Dify chatflow sends both workflow_finished and message_end events

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

* style: apply ruff formatting to difysvapi.py

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>
2026-03-11 14:45:55 +08:00
youhuanghe
bd15b630b0 fix: chroma ruff lint 2026-03-11 04:07:21 +00:00
youhuanghe
fe5ce68436 feat(vector): add full-text and hybrid search support for Chroma backend
- Implement full-text search via Chroma's $contains filter
  - Implement hybrid search with RRF (Reciprocal Rank Fusion) combining
    vector and full-text results, with min-max normalized distances
  - Fix add_embeddings to use col.upsert instead of col.add for idempotency
  - Bump chromadb dependency to >=1.0.0,<2.0.0
  - Re-lock uv.lock with official PyPI source
2026-03-11 03:59:14 +00:00
Typer_Body
0541b05966 refactor: optimized error handling (#2020)
* Update output.yaml

* Update default-pipeline-config.json

* Update chat.py

* Add files via upload

* Update chat.py

* Update default-pipeline-config.json

* Update output.yaml

* Update constants.py

* feat: update logic

* fix: update required database version to 21

---------

Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2026-03-10 22:01:23 +08:00
youhuanghe
13cb0aa9be bugfix: rollback filter, add to retrive settings 2026-03-10 12:49:24 +00:00
youhuanghe
a048369b38 feat: Pass session context (session_name) to knowledge engine retrieval filters.
Allow KnowledgeEngine plugins to filter retrieval results by session,enabling per-session memory isolation in plugin-based knowledge bases
2026-03-10 12:27:50 +00:00
49 changed files with 2540 additions and 538 deletions

View File

@@ -1,6 +1,6 @@
[project]
name = "langbot"
version = "4.9.0"
version = "4.9.1"
description = "Production-grade platform for building agentic IM bots"
readme = "README.md"
license-files = ["LICENSE"]
@@ -61,10 +61,10 @@ dependencies = [
"html2text>=2024.2.26",
"langchain>=0.2.0",
"langchain-text-splitters>=0.0.1",
"chromadb>=0.4.24",
"chromadb>=1.0.0,<2.0.0",
"qdrant-client (>=1.15.1,<2.0.0)",
"pyseekdb==1.1.0.post3",
"langbot-plugin==0.3.0",
"langbot-plugin==0.3.1",
"asyncpg>=0.30.0",
"line-bot-sdk>=3.19.0",
"tboxsdk>=0.0.10",

View File

@@ -1,3 +1,3 @@
"""LangBot - Production-grade platform for building agentic IM bots"""
__version__ = '4.9.0'
__version__ = '4.9.1'

View File

@@ -199,6 +199,253 @@ class StreamSessionManager:
self._msg_index.pop(msg_id, None)
async def download_encrypted_file(download_url: str, encoding_aes_key: str, logger: EventLogger) -> Optional[str]:
"""Download an AES-encrypted file from WeChat Work and return as data URI.
Args:
download_url: The encrypted file download URL.
encoding_aes_key: The AES key used for decryption (base64-encoded, without trailing '=').
logger: Logger instance.
Returns:
A data URI string (e.g. 'data:image/jpeg;base64,...') or None on failure.
"""
if not download_url:
return None
async with httpx.AsyncClient() as client:
response = await client.get(download_url)
if response.status_code != 200:
await logger.error(f'failed to get file: {response.text}')
return None
encrypted_bytes = response.content
aes_key = base64.b64decode(encoding_aes_key + '=')
iv = aes_key[:16]
cipher = AES.new(aes_key, AES.MODE_CBC, iv)
decrypted = cipher.decrypt(encrypted_bytes)
pad_len = decrypted[-1]
decrypted = decrypted[:-pad_len]
if decrypted.startswith(b'\xff\xd8'):
mime_type = 'image/jpeg'
elif decrypted.startswith(b'\x89PNG'):
mime_type = 'image/png'
elif decrypted.startswith((b'GIF87a', b'GIF89a')):
mime_type = 'image/gif'
elif decrypted.startswith(b'BM'):
mime_type = 'image/bmp'
elif decrypted.startswith(b'II*\x00') or decrypted.startswith(b'MM\x00*'):
mime_type = 'image/tiff'
else:
mime_type = 'application/octet-stream'
base64_str = base64.b64encode(decrypted).decode('utf-8')
return f'data:{mime_type};base64,{base64_str}'
async def parse_wecom_bot_message(
msg_json: dict[str, Any], encoding_aes_key: str, logger: EventLogger
) -> dict[str, Any]:
"""Parse a decrypted WeChat Work AI Bot message JSON into a unified message dict.
This is the shared message parsing logic used by both webhook and WebSocket modes.
Args:
msg_json: The decrypted message JSON from WeChat Work.
encoding_aes_key: AES key for file decryption.
logger: Logger instance.
Returns:
A dict suitable for constructing a WecomBotEvent.
"""
message_data: dict[str, Any] = {}
msg_type = msg_json.get('msgtype', '')
if msg_type:
message_data['msgtype'] = msg_type
if msg_json.get('chattype', '') == 'single':
message_data['type'] = 'single'
elif msg_json.get('chattype', '') == 'group':
message_data['type'] = 'group'
max_inline_file_size = 5 * 1024 * 1024
async def _safe_download(url: str):
if not url:
return None
return await download_encrypted_file(url, encoding_aes_key, logger)
if msg_type == 'text':
message_data['content'] = msg_json.get('text', {}).get('content')
elif msg_type == 'markdown':
message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
'content', ''
)
elif msg_type == 'image':
picurl = msg_json.get('image', {}).get('url', '')
base64_data = await _safe_download(picurl)
if base64_data:
message_data['picurl'] = base64_data
message_data['images'] = [base64_data]
elif msg_type == 'voice':
voice_info = msg_json.get('voice', {}) or {}
download_url = voice_info.get('url')
message_data['voice'] = {
'url': download_url,
'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
'filesize': voice_info.get('filesize') or voice_info.get('size'),
'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
}
if voice_info.get('content'):
message_data['content'] = voice_info.get('content')
if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
voice_base64 = await _safe_download(download_url)
if voice_base64:
message_data['voice']['base64'] = voice_base64
elif msg_type == 'video':
video_info = msg_json.get('video', {}) or {}
download_url = video_info.get('url')
video_data = {
'url': download_url,
'filesize': video_info.get('filesize') or video_info.get('size'),
'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
'md5sum': video_info.get('md5sum') or video_info.get('md5'),
'filename': video_info.get('filename') or video_info.get('name'),
}
if (video_data.get('filesize') or 0) <= max_inline_file_size:
video_base64 = await _safe_download(download_url)
if video_base64:
video_data['base64'] = video_base64
message_data['video'] = video_data
elif msg_type == 'file':
file_info = msg_json.get('file', {}) or {}
download_url = file_info.get('url') or file_info.get('fileurl')
file_data = {
'filename': file_info.get('filename') or file_info.get('name'),
'filesize': file_info.get('filesize') or file_info.get('size'),
'md5sum': file_info.get('md5sum') or file_info.get('md5'),
'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
'download_url': download_url,
'extra': file_info,
}
if (file_data.get('filesize') or 0) <= max_inline_file_size:
file_base64 = await _safe_download(download_url)
if file_base64:
file_data['base64'] = file_base64
message_data['file'] = file_data
elif msg_type == 'link':
message_data['link'] = msg_json.get('link', {})
if not message_data.get('content'):
title = message_data['link'].get('title', '')
desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
message_data['content'] = '\n'.join(filter(None, [title, desc]))
elif msg_type == 'mixed':
items = msg_json.get('mixed', {}).get('msg_item', [])
texts = []
images = []
files = []
voices = []
videos = []
links = []
for item in items:
item_type = item.get('msgtype')
if item_type == 'text':
texts.append(item.get('text', {}).get('content', ''))
elif item_type == 'image':
img_url = item.get('image', {}).get('url')
base64_data = await _safe_download(img_url)
if base64_data:
images.append(base64_data)
elif item_type == 'file':
file_info = item.get('file', {}) or {}
download_url = file_info.get('url') or file_info.get('fileurl')
file_data = {
'filename': file_info.get('filename') or file_info.get('name'),
'filesize': file_info.get('filesize') or file_info.get('size'),
'md5sum': file_info.get('md5sum') or file_info.get('md5'),
'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
'download_url': download_url,
'extra': file_info,
}
if (file_data.get('filesize') or 0) <= max_inline_file_size:
file_base64 = await _safe_download(download_url)
if file_base64:
file_data['base64'] = file_base64
files.append(file_data)
elif item_type == 'voice':
voice_info = item.get('voice', {}) or {}
download_url = voice_info.get('url')
voice_data = {
'url': download_url,
'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
'filesize': voice_info.get('filesize') or voice_info.get('size'),
'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
}
if voice_info.get('content'):
texts.append(voice_info.get('content'))
if (voice_data.get('filesize') or 0) <= max_inline_file_size:
voice_base64 = await _safe_download(download_url)
if voice_base64:
voice_data['base64'] = voice_base64
voices.append(voice_data)
elif item_type == 'video':
video_info = item.get('video', {}) or {}
download_url = video_info.get('url')
video_data = {
'url': download_url,
'filesize': video_info.get('filesize') or video_info.get('size'),
'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
'md5sum': video_info.get('md5sum') or video_info.get('md5'),
'filename': video_info.get('filename') or video_info.get('name'),
}
if (video_data.get('filesize') or 0) <= max_inline_file_size:
video_base64 = await _safe_download(download_url)
if video_base64:
video_data['base64'] = video_base64
videos.append(video_data)
elif item_type == 'link':
links.append(item.get('link', {}))
if texts:
message_data['content'] = ' '.join(texts)
if images:
message_data['images'] = images
message_data['picurl'] = images[0]
if files:
message_data['files'] = files
message_data['file'] = files[0]
if voices:
message_data['voices'] = voices
message_data['voice'] = voices[0]
if videos:
message_data['videos'] = videos
message_data['video'] = videos[0]
if links:
message_data['link'] = links[0]
if items:
message_data['attachments'] = items
else:
message_data['raw_msg'] = msg_json
from_info = msg_json.get('from', {})
message_data['userid'] = from_info.get('userid', '')
message_data['username'] = from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
if msg_json.get('chattype', '') == 'group':
message_data['chatid'] = msg_json.get('chatid', '')
message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
message_data['msgid'] = msg_json.get('msgid', '')
if msg_json.get('aibotid'):
message_data['aibotid'] = msg_json.get('aibotid', '')
return message_data
class WecomBotClient:
def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger, unified_mode: bool = False):
"""企业微信智能机器人客户端。
@@ -455,196 +702,7 @@ class WecomBotClient:
return await self._handle_post_initial_response(msg_json, nonce)
async def get_message(self, msg_json):
message_data = {}
msg_type = msg_json.get('msgtype', '')
if msg_type:
message_data['msgtype'] = msg_type
if msg_json.get('chattype', '') == 'single':
message_data['type'] = 'single'
elif msg_json.get('chattype', '') == 'group':
message_data['type'] = 'group'
max_inline_file_size = 5 * 1024 * 1024 # avoid decoding very large payloads by default
async def _safe_download(url: str):
if not url:
return None
return await self.download_url_to_base64(url, self.EnCodingAESKey)
if msg_type == 'text':
message_data['content'] = msg_json.get('text', {}).get('content')
elif msg_type == 'markdown':
message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
'content', ''
)
elif msg_type == 'image':
picurl = msg_json.get('image', {}).get('url', '')
base64_data = await _safe_download(picurl)
if base64_data:
message_data['picurl'] = base64_data
message_data['images'] = [base64_data]
elif msg_type == 'voice':
voice_info = msg_json.get('voice', {}) or {}
download_url = voice_info.get('url')
message_data['voice'] = {
'url': download_url,
'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
'filesize': voice_info.get('filesize') or voice_info.get('size'),
'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
}
# 企业微信智能转写文本(如果已有)直接复用,避免重复转写
if voice_info.get('content'):
message_data['content'] = voice_info.get('content')
if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
voice_base64 = await _safe_download(download_url)
if voice_base64:
message_data['voice']['base64'] = voice_base64
elif msg_type == 'video':
video_info = msg_json.get('video', {}) or {}
download_url = video_info.get('url')
video_data = {
'url': download_url,
'filesize': video_info.get('filesize') or video_info.get('size'),
'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
'md5sum': video_info.get('md5sum') or video_info.get('md5'),
'filename': video_info.get('filename') or video_info.get('name'),
}
if (video_data.get('filesize') or 0) <= max_inline_file_size:
video_base64 = await _safe_download(download_url)
if video_base64:
video_data['base64'] = video_base64
message_data['video'] = video_data
elif msg_type == 'file':
file_info = msg_json.get('file', {}) or {}
download_url = file_info.get('url') or file_info.get('fileurl')
file_data = {
'filename': file_info.get('filename') or file_info.get('name'),
'filesize': file_info.get('filesize') or file_info.get('size'),
'md5sum': file_info.get('md5sum') or file_info.get('md5'),
'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
'download_url': download_url,
'extra': file_info,
}
if (file_data.get('filesize') or 0) <= max_inline_file_size:
file_base64 = await _safe_download(download_url)
if file_base64:
file_data['base64'] = file_base64
message_data['file'] = file_data
elif msg_type == 'link':
message_data['link'] = msg_json.get('link', {})
if not message_data.get('content'):
title = message_data['link'].get('title', '')
desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
message_data['content'] = '\n'.join(filter(None, [title, desc]))
elif msg_type == 'mixed':
items = msg_json.get('mixed', {}).get('msg_item', [])
texts = []
images = []
files = []
voices = []
videos = []
links = []
for item in items:
item_type = item.get('msgtype')
if item_type == 'text':
texts.append(item.get('text', {}).get('content', ''))
elif item_type == 'image':
img_url = item.get('image', {}).get('url')
base64_data = await _safe_download(img_url)
if base64_data:
images.append(base64_data)
elif item_type == 'file':
file_info = item.get('file', {}) or {}
download_url = file_info.get('url') or file_info.get('fileurl')
file_data = {
'filename': file_info.get('filename') or file_info.get('name'),
'filesize': file_info.get('filesize') or file_info.get('size'),
'md5sum': file_info.get('md5sum') or file_info.get('md5'),
'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
'download_url': download_url,
'extra': file_info,
}
if (file_data.get('filesize') or 0) <= max_inline_file_size:
file_base64 = await _safe_download(download_url)
if file_base64:
file_data['base64'] = file_base64
files.append(file_data)
elif item_type == 'voice':
voice_info = item.get('voice', {}) or {}
download_url = voice_info.get('url')
voice_data = {
'url': download_url,
'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
'filesize': voice_info.get('filesize') or voice_info.get('size'),
'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
}
if voice_info.get('content'):
texts.append(voice_info.get('content'))
if (voice_data.get('filesize') or 0) <= max_inline_file_size:
voice_base64 = await _safe_download(download_url)
if voice_base64:
voice_data['base64'] = voice_base64
voices.append(voice_data)
elif item_type == 'video':
video_info = item.get('video', {}) or {}
download_url = video_info.get('url')
video_data = {
'url': download_url,
'filesize': video_info.get('filesize') or video_info.get('size'),
'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
'md5sum': video_info.get('md5sum') or video_info.get('md5'),
'filename': video_info.get('filename') or video_info.get('name'),
}
if (video_data.get('filesize') or 0) <= max_inline_file_size:
video_base64 = await _safe_download(download_url)
if video_base64:
video_data['base64'] = video_base64
videos.append(video_data)
elif item_type == 'link':
links.append(item.get('link', {}))
if texts:
message_data['content'] = ' '.join(texts) # 拼接所有 text
if images:
message_data['images'] = images
message_data['picurl'] = images[0] # 只保留第一个 image
if files:
message_data['files'] = files
message_data['file'] = files[0]
if voices:
message_data['voices'] = voices
message_data['voice'] = voices[0]
if videos:
message_data['videos'] = videos
message_data['video'] = videos[0]
if links:
message_data['link'] = links[0]
if items:
message_data['attachments'] = items
else:
message_data['raw_msg'] = msg_json
# Extract user information
from_info = msg_json.get('from', {})
message_data['userid'] = from_info.get('userid', '')
message_data['username'] = (
from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
)
# Extract chat/group information
if msg_json.get('chattype', '') == 'group':
message_data['chatid'] = msg_json.get('chatid', '')
# Try to get group name if available
message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
message_data['msgid'] = msg_json.get('msgid', '')
if msg_json.get('aibotid'):
message_data['aibotid'] = msg_json.get('aibotid', '')
return message_data
return await parse_wecom_bot_message(msg_json, self.EnCodingAESKey, self.logger)
async def _handle_message(self, event: wecombotevent.WecomBotEvent):
"""
@@ -712,39 +770,7 @@ class WecomBotClient:
return decorator
async def download_url_to_base64(self, download_url, encoding_aes_key):
async with httpx.AsyncClient() as client:
response = await client.get(download_url)
if response.status_code != 200:
await self.logger.error(f'failed to get file: {response.text}')
return None
encrypted_bytes = response.content
aes_key = base64.b64decode(encoding_aes_key + '=') # base64 补齐
iv = aes_key[:16]
cipher = AES.new(aes_key, AES.MODE_CBC, iv)
decrypted = cipher.decrypt(encrypted_bytes)
pad_len = decrypted[-1]
decrypted = decrypted[:-pad_len]
if decrypted.startswith(b'\xff\xd8'): # JPEG
mime_type = 'image/jpeg'
elif decrypted.startswith(b'\x89PNG'): # PNG
mime_type = 'image/png'
elif decrypted.startswith((b'GIF87a', b'GIF89a')): # GIF
mime_type = 'image/gif'
elif decrypted.startswith(b'BM'): # BMP
mime_type = 'image/bmp'
elif decrypted.startswith(b'II*\x00') or decrypted.startswith(b'MM\x00*'): # TIFF
mime_type = 'image/tiff'
else:
mime_type = 'application/octet-stream'
# 转 base64
base64_str = base64.b64encode(decrypted).decode('utf-8')
return f'data:{mime_type};base64,{base64_str}'
return await download_encrypted_file(download_url, encoding_aes_key, self.logger)
async def run_task(self, host: str, port: int, *args, **kwargs):
"""

View File

@@ -0,0 +1,596 @@
"""WeChat Work AI Bot WebSocket long connection client.
Implements the WebSocket protocol for receiving messages and sending replies
via a persistent connection to wss://openws.work.weixin.qq.com, as an
alternative to the HTTP callback (webhook) mode.
Protocol reference: https://developer.work.weixin.qq.com/document/path/101463
Official Node.js SDK: https://github.com/WecomTeam/aibot-node-sdk
"""
from __future__ import annotations
import asyncio
import json
import secrets
import time
import traceback
from typing import Any, Callable, Optional
import aiohttp
from langbot.libs.wecom_ai_bot_api import wecombotevent
from langbot.libs.wecom_ai_bot_api.api import parse_wecom_bot_message
from langbot.pkg.platform.logger import EventLogger
DEFAULT_WS_URL = 'wss://openws.work.weixin.qq.com'
# WebSocket frame command constants
CMD_SUBSCRIBE = 'aibot_subscribe'
CMD_HEARTBEAT = 'ping'
CMD_MSG_CALLBACK = 'aibot_msg_callback'
CMD_EVENT_CALLBACK = 'aibot_event_callback'
CMD_RESPOND_MSG = 'aibot_respond_msg'
CMD_RESPOND_WELCOME = 'aibot_respond_welcome_msg'
CMD_RESPOND_UPDATE = 'aibot_respond_update_msg'
CMD_SEND_MSG = 'aibot_send_msg'
def _generate_req_id(prefix: str) -> str:
"""Generate a unique request ID in the format: {prefix}_{timestamp}_{random}."""
ts = int(time.time() * 1000)
rand = secrets.token_hex(4)
return f'{prefix}_{ts}_{rand}'
class WecomBotWsClient:
"""WeChat Work AI Bot WebSocket long connection client.
Provides message receiving, streaming reply, proactive message sending,
and event callback handling over a persistent WebSocket connection.
"""
def __init__(
self,
bot_id: str,
secret: str,
logger: EventLogger,
encoding_aes_key: str = '',
ws_url: str = DEFAULT_WS_URL,
heartbeat_interval: float = 30.0,
max_reconnect_attempts: int = -1,
reconnect_base_delay: float = 1.0,
reconnect_max_delay: float = 30.0,
):
self.bot_id = bot_id
self.secret = secret
self.logger = logger
self.encoding_aes_key = encoding_aes_key
self.ws_url = ws_url
self.heartbeat_interval = heartbeat_interval
self.max_reconnect_attempts = max_reconnect_attempts
self.reconnect_base_delay = reconnect_base_delay
self.reconnect_max_delay = reconnect_max_delay
self._ws: Optional[aiohttp.ClientWebSocketResponse] = None
self._session: Optional[aiohttp.ClientSession] = None
self._running = False
self._heartbeat_task: Optional[asyncio.Task] = None
self._missed_pong_count = 0
self._max_missed_pong = 2
self._reconnect_attempts = 0
# Message handler registry (same pattern as WecomBotClient)
self._message_handlers: dict[str, list[Callable]] = {}
# Message deduplication
self._msg_id_map: dict[str, int] = {}
# Pending ACK futures: req_id -> Future[dict]
self._pending_acks: dict[str, asyncio.Future] = {}
# Per-req_id serial reply queues
self._reply_queues: dict[str, asyncio.Queue] = {}
self._reply_workers: dict[str, asyncio.Task] = {}
self._reply_ack_timeout = 5.0
# Stream ID tracking for WebSocket mode
self._stream_ids: dict[str, str] = {} # msg_id -> req_id|stream_id
# Dedup: skip sending when content hasn't changed
self._stream_last_content: dict[str, str] = {} # msg_id -> last content sent
# ── Public API ──────────────────────────────────────────────────
async def connect(self):
"""Connect to WebSocket server with automatic reconnection.
This method blocks until disconnect() is called or max reconnect
attempts are exhausted.
"""
self._running = True
self._reconnect_attempts = 0
while self._running:
try:
await self._connect_once()
except Exception:
if not self._running:
break
await self.logger.error(f'WebSocket connection error: {traceback.format_exc()}')
if not self._running:
break
# Reconnect with exponential backoff
if self.max_reconnect_attempts != -1 and self._reconnect_attempts >= self.max_reconnect_attempts:
await self.logger.error(f'Max reconnect attempts reached ({self.max_reconnect_attempts}), giving up')
break
self._reconnect_attempts += 1
delay = min(
self.reconnect_base_delay * (2 ** (self._reconnect_attempts - 1)),
self.reconnect_max_delay,
)
await self.logger.info(f'Reconnecting in {delay:.1f}s (attempt {self._reconnect_attempts})...')
await asyncio.sleep(delay)
async def disconnect(self):
"""Gracefully disconnect from the WebSocket server."""
self._running = False
if self._heartbeat_task and not self._heartbeat_task.done():
self._heartbeat_task.cancel()
for task in self._reply_workers.values():
if not task.done():
task.cancel()
if self._ws and not self._ws.closed:
await self._ws.close()
self._ws = None
if self._session and not self._session.closed:
await self._session.close()
self._session = None
def on_message(self, msg_type: str) -> Callable:
"""Decorator to register a message handler.
Same interface as WecomBotClient.on_message for compatibility.
Args:
msg_type: 'single', 'group', or specific message type.
"""
def decorator(func: Callable[[wecombotevent.WecomBotEvent], Any]):
if msg_type not in self._message_handlers:
self._message_handlers[msg_type] = []
self._message_handlers[msg_type].append(func)
return func
return decorator
async def reply_stream(
self,
req_id: str,
stream_id: str,
content: str,
finish: bool = False,
) -> Optional[dict]:
"""Send a streaming reply frame.
Args:
req_id: The req_id from the original message frame (must be passed through).
stream_id: The stream ID for this streaming session.
content: The content to send (supports Markdown).
finish: Whether this is the final chunk.
Returns:
The ACK frame dict, or None on failure.
"""
body = {
'msgtype': 'stream',
'stream': {
'id': stream_id,
'finish': finish,
'content': content,
},
}
return await self._send_reply(req_id, body)
async def reply_text(self, req_id: str, content: str) -> Optional[dict]:
"""Send a non-streaming text reply.
Args:
req_id: The req_id from the original message frame.
content: The text content to reply.
Returns:
The ACK frame dict, or None on failure.
"""
body = {
'msgtype': 'markdown',
'markdown': {
'content': content,
},
}
return await self._send_reply(req_id, body)
async def send_message(self, chat_id: str, content: str, msgtype: str = 'markdown') -> Optional[dict]:
"""Proactively send a message to a specified chat.
Args:
chat_id: The chat ID (userid for single chat, chatid for group chat).
content: The message content.
msgtype: Message type, 'markdown' by default.
Returns:
The ACK frame dict, or None on failure.
"""
req_id = _generate_req_id(CMD_SEND_MSG)
body: dict[str, Any] = {
'chatid': chat_id,
'msgtype': msgtype,
}
if msgtype == 'markdown':
body['markdown'] = {'content': content}
elif msgtype == 'text':
body['text'] = {'content': content}
return await self._send_reply(req_id, body, cmd=CMD_SEND_MSG)
async def push_stream_chunk(self, msg_id: str, content: str, is_final: bool = False) -> bool:
"""Push a streaming chunk for a given message ID.
Compatible interface with WecomBotClient.push_stream_chunk.
Args:
msg_id: The original message ID.
content: The cumulative content from the pipeline.
is_final: Whether this is the final chunk.
Returns:
True if the stream session exists and chunk was sent.
"""
key = self._stream_ids.get(msg_id)
if not key:
return False
req_id, stream_id = key.split('|', 1)
try:
# Skip sending if content hasn't changed (e.g. during tool call argument streaming)
if not is_final and content == self._stream_last_content.get(msg_id):
return True
await self.reply_stream(req_id, stream_id, content, finish=is_final)
self._stream_last_content[msg_id] = content
if is_final:
self._stream_ids.pop(msg_id, None)
self._stream_last_content.pop(msg_id, None)
return True
except Exception:
await self.logger.error(f'Failed to push stream chunk: {traceback.format_exc()}')
return False
async def set_message(self, msg_id: str, content: str):
"""Fallback: send content as a final stream chunk or direct reply.
Compatible interface with WecomBotClient.set_message.
"""
handled = await self.push_stream_chunk(msg_id, content, is_final=True)
if not handled:
await self.logger.warning(f'No active stream for msg_id={msg_id}, message dropped')
# ── Connection lifecycle ────────────────────────────────────────
async def _connect_once(self):
"""Establish a single WebSocket connection, authenticate, and listen."""
await self.logger.info(f'Connecting to {self.ws_url}...')
self._session = aiohttp.ClientSession()
try:
self._ws = await self._session.ws_connect(self.ws_url)
self._missed_pong_count = 0
self._reconnect_attempts = 0
await self.logger.info('WebSocket connected, sending auth...')
await self._send_auth()
# Wait for auth response
auth_ok = await self._wait_for_auth()
if not auth_ok:
await self.logger.error('Authentication failed')
return
await self.logger.info('Authenticated successfully')
# Start heartbeat
self._heartbeat_task = asyncio.create_task(self._heartbeat_loop())
try:
await self._listen_loop()
finally:
if self._heartbeat_task and not self._heartbeat_task.done():
self._heartbeat_task.cancel()
self._clear_pending_acks('Connection closed')
finally:
if self._ws and not self._ws.closed:
await self._ws.close()
self._ws = None
if self._session and not self._session.closed:
await self._session.close()
self._session = None
async def _send_auth(self):
"""Send the authentication frame."""
frame = {
'cmd': CMD_SUBSCRIBE,
'headers': {'req_id': _generate_req_id(CMD_SUBSCRIBE)},
'body': {
'bot_id': self.bot_id,
'secret': self.secret,
},
}
await self._send_frame(frame)
async def _wait_for_auth(self) -> bool:
"""Wait for and validate the authentication response."""
try:
msg = await asyncio.wait_for(self._ws.receive(), timeout=10.0)
if msg.type in (aiohttp.WSMsgType.TEXT,):
frame = json.loads(msg.data)
req_id = frame.get('headers', {}).get('req_id', '')
if req_id.startswith(CMD_SUBSCRIBE) and frame.get('errcode') == 0:
return True
await self.logger.error(f'Auth response: errcode={frame.get("errcode")}, errmsg={frame.get("errmsg")}')
return False
elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
await self.logger.error(f'WebSocket closed during auth: {msg.type}')
return False
await self.logger.error(f'Unexpected message type during auth: {msg.type}')
return False
except asyncio.TimeoutError:
await self.logger.error('Auth response timeout')
return False
async def _heartbeat_loop(self):
"""Periodically send heartbeat pings."""
try:
while self._running and self._ws and not self._ws.closed:
await asyncio.sleep(self.heartbeat_interval)
if not self._running or not self._ws or self._ws.closed:
break
if self._missed_pong_count >= self._max_missed_pong:
await self.logger.warning(
f'No heartbeat ack for {self._missed_pong_count} consecutive pings, connection considered dead'
)
await self._ws.close()
break
self._missed_pong_count += 1
frame = {
'cmd': CMD_HEARTBEAT,
'headers': {'req_id': _generate_req_id(CMD_HEARTBEAT)},
}
try:
await self._send_frame(frame)
except Exception:
break
except asyncio.CancelledError:
pass
async def _listen_loop(self):
"""Listen for incoming WebSocket frames and dispatch them."""
async for msg in self._ws:
if not self._running:
break
if msg.type == aiohttp.WSMsgType.TEXT:
try:
frame = json.loads(msg.data)
await self._handle_frame(frame)
except json.JSONDecodeError:
await self.logger.error(f'Failed to parse WebSocket message: {str(msg.data)[:200]}')
except Exception:
await self.logger.error(f'Error handling frame: {traceback.format_exc()}')
elif msg.type == aiohttp.WSMsgType.BINARY:
try:
frame = json.loads(msg.data)
await self._handle_frame(frame)
except Exception:
await self.logger.error(f'Error handling binary frame: {traceback.format_exc()}')
elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
await self.logger.warning(f'WebSocket connection closed: {msg.type}')
break
# ── Frame handling ──────────────────────────────────────────────
async def _handle_frame(self, frame: dict):
"""Route an incoming frame to the appropriate handler."""
cmd = frame.get('cmd', '')
# Message push
if cmd == CMD_MSG_CALLBACK:
asyncio.create_task(self._handle_message_callback(frame))
return
# Event push
if cmd == CMD_EVENT_CALLBACK:
asyncio.create_task(self._handle_event_callback(frame))
return
# No cmd → response/ACK frame, dispatch by req_id prefix
req_id = frame.get('headers', {}).get('req_id', '')
# Check pending ACKs first
if req_id in self._pending_acks:
future = self._pending_acks.pop(req_id)
if not future.done():
future.set_result(frame)
return
# Heartbeat response
if req_id.startswith(CMD_HEARTBEAT):
if frame.get('errcode') == 0:
self._missed_pong_count = 0
return
# Unknown frame
await self.logger.warning(f'Unknown frame: {json.dumps(frame, ensure_ascii=False)[:200]}')
async def _handle_message_callback(self, frame: dict):
"""Handle an incoming message callback frame."""
try:
body = frame.get('body', {})
req_id = frame.get('headers', {}).get('req_id', '')
# Parse message using shared logic
message_data = await parse_wecom_bot_message(body, self.encoding_aes_key, self.logger)
if not message_data:
return
# Generate stream_id for this message and store the mapping
stream_id = _generate_req_id('stream')
msg_id = message_data.get('msgid', '')
if msg_id:
self._stream_ids[msg_id] = f'{req_id}|{stream_id}'
message_data['stream_id'] = stream_id
message_data['req_id'] = req_id
event = wecombotevent.WecomBotEvent(message_data)
await self._dispatch_event(event)
except Exception:
await self.logger.error(f'Error in message callback: {traceback.format_exc()}')
async def _handle_event_callback(self, frame: dict):
"""Handle an incoming event callback frame (enter_chat, template_card_event, etc.)."""
try:
body = frame.get('body', {})
req_id = frame.get('headers', {}).get('req_id', '')
event_info = body.get('event', {})
event_type = event_info.get('eventtype', '')
message_data = {
'msgtype': 'event',
'type': body.get('chattype', 'single'),
'event': event_info,
'eventtype': event_type,
'msgid': body.get('msgid', ''),
'aibotid': body.get('aibotid', ''),
'req_id': req_id,
}
from_info = body.get('from', {})
message_data['userid'] = from_info.get('userid', '')
message_data['username'] = from_info.get('alias', '') or from_info.get('userid', '')
if body.get('chatid'):
message_data['chatid'] = body.get('chatid', '')
event = wecombotevent.WecomBotEvent(message_data)
# Dispatch to event-specific handlers
if event_type in self._message_handlers:
for handler in self._message_handlers[event_type]:
await handler(event)
# Also dispatch to generic 'event' handlers
if 'event' in self._message_handlers:
for handler in self._message_handlers['event']:
await handler(event)
except Exception:
await self.logger.error(f'Error in event callback: {traceback.format_exc()}')
async def _dispatch_event(self, event: wecombotevent.WecomBotEvent):
"""Dispatch a message event to registered handlers with deduplication."""
try:
message_id = event.message_id
if message_id in self._msg_id_map:
self._msg_id_map[message_id] += 1
return
self._msg_id_map[message_id] = 1
msg_type = event.type
if msg_type in self._message_handlers:
for handler in self._message_handlers[msg_type]:
await handler(event)
except Exception:
await self.logger.error(f'Error dispatching event: {traceback.format_exc()}')
# ── Reply sending with serial queue ─────────────────────────────
async def _send_reply(
self,
req_id: str,
body: dict,
cmd: str = CMD_RESPOND_MSG,
) -> Optional[dict]:
"""Send a reply frame and wait for ACK.
Replies with the same req_id are serialized to maintain ordering.
"""
if not self._ws or self._ws.closed:
return None
frame = {
'cmd': cmd,
'headers': {'req_id': req_id},
'body': body,
}
# Ensure serial delivery per req_id
if req_id not in self._reply_queues:
self._reply_queues[req_id] = asyncio.Queue()
self._reply_workers[req_id] = asyncio.create_task(self._reply_queue_worker(req_id))
future: asyncio.Future = asyncio.get_event_loop().create_future()
await self._reply_queues[req_id].put((frame, future))
return await future
async def _reply_queue_worker(self, req_id: str):
"""Process reply queue items serially for a given req_id."""
queue = self._reply_queues[req_id]
try:
while self._running:
try:
frame, future = await asyncio.wait_for(queue.get(), timeout=60.0)
except asyncio.TimeoutError:
# Queue idle, clean up worker
break
try:
ack = await self._send_and_wait_ack(frame)
if not future.done():
future.set_result(ack)
except Exception as e:
if not future.done():
future.set_exception(e)
except asyncio.CancelledError:
pass
finally:
self._reply_queues.pop(req_id, None)
self._reply_workers.pop(req_id, None)
async def _send_and_wait_ack(self, frame: dict) -> Optional[dict]:
"""Send a frame and wait for the corresponding ACK."""
req_id = frame['headers']['req_id']
ack_future: asyncio.Future = asyncio.get_event_loop().create_future()
self._pending_acks[req_id] = ack_future
try:
await self._send_frame(frame)
result = await asyncio.wait_for(ack_future, timeout=self._reply_ack_timeout)
if result.get('errcode', 0) != 0:
await self.logger.warning(
f'Reply ACK error: errcode={result.get("errcode")}, errmsg={result.get("errmsg")}'
)
return result
except asyncio.TimeoutError:
self._pending_acks.pop(req_id, None)
await self.logger.warning(f'Reply ACK timeout ({self._reply_ack_timeout}s) for req_id={req_id}')
return None
async def _send_frame(self, frame: dict):
"""Send a JSON frame over the WebSocket connection."""
if self._ws and not self._ws.closed:
await self._ws.send_str(json.dumps(frame, ensure_ascii=False))
def _clear_pending_acks(self, reason: str):
"""Reject all pending ACK futures on disconnection."""
for req_id, future in self._pending_acks.items():
if not future.done():
future.set_exception(ConnectionError(reason))
self._pending_acks.clear()

View File

@@ -10,6 +10,7 @@ from typing import Callable
from .wecomcsevent import WecomCSEvent
import langbot_plugin.api.entities.builtin.platform.message as platform_message
import aiofiles
import time
class WecomCSClient:
@@ -34,6 +35,10 @@ class WecomCSClient:
self.unified_mode = unified_mode
self.app = Quart(__name__)
# Customer info cache: {external_userid: (info_dict, timestamp)}
self._customer_cache: dict[str, tuple[dict, float]] = {}
self._cache_ttl = 60 # Cache TTL in seconds (1 minute)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
@@ -378,3 +383,53 @@ class WecomCSClient:
async def get_media_id(self, image: platform_message.Image):
media_id = await self.upload_to_work(image=image)
return media_id
async def get_customer_info(self, external_userid: str) -> dict | None:
"""
Get customer information by external_userid with caching.
Uses a 1-minute cache to avoid repeated API calls for the same user.
Args:
external_userid: The external user ID of the customer.
Returns:
Customer info dict with 'nickname', 'avatar', etc., or None if not found.
"""
# Check cache first
current_time = time.time()
if external_userid in self._customer_cache:
cached_info, cached_time = self._customer_cache[external_userid]
if current_time - cached_time < self._cache_ttl:
return cached_info
# Cache miss or expired, fetch from API
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = f'{self.base_url}/kf/customer/batchget?access_token={self.access_token}'
payload = {
'external_userid_list': [external_userid],
}
async with httpx.AsyncClient() as client:
response = await client.post(url, json=payload)
data = response.json()
if data.get('errcode') in [40014, 42001]:
self.access_token = await self.get_access_token(self.secret)
return await self.get_customer_info(external_userid)
if data.get('errcode', 0) != 0:
if self.logger:
await self.logger.warning(f'Failed to get customer info: {data}')
return None
customer_list = data.get('customer_list', [])
if customer_list:
customer_info = customer_list[0]
# Store in cache
self._customer_cache[external_userid] = (customer_info, current_time)
return customer_info
return None

View File

@@ -30,6 +30,7 @@ class MonitoringService:
level: str = 'info',
platform: str | None = None,
user_id: str | None = None,
user_name: str | None = None,
runner_name: str | None = None,
variables: str | None = None,
role: str = 'user',
@@ -49,6 +50,7 @@ class MonitoringService:
'level': level,
'platform': platform,
'user_id': user_id,
'user_name': user_name,
'runner_name': runner_name,
'variables': variables,
'role': role,
@@ -152,6 +154,7 @@ class MonitoringService:
pipeline_name: str,
platform: str | None = None,
user_id: str | None = None,
user_name: str | None = None,
) -> None:
"""Record a new session"""
session_data = {
@@ -166,6 +169,7 @@ class MonitoringService:
'is_active': True,
'platform': platform,
'user_id': user_id,
'user_name': user_name,
}
await self.ap.persistence_mgr.execute_async(

View File

@@ -9,6 +9,7 @@ from ..platform import botmgr as im_mgr
from ..platform.webhook_pusher import WebhookPusher
from ..provider.session import sessionmgr as llm_session_mgr
from ..provider.modelmgr import modelmgr as llm_model_mgr
from langbot.pkg.provider.tools import toolmgr as llm_tool_mgr
from ..config import manager as config_mgr
from ..command import cmdmgr
@@ -30,6 +31,7 @@ from ..api.http.service import mcp as mcp_service
from ..api.http.service import apikey as apikey_service
from ..api.http.service import webhook as webhook_service
from ..api.http.service import monitoring as monitoring_service
from ..discover import engine as discover_engine
from ..storage import mgr as storagemgr
from ..utils import logcache

View File

@@ -20,6 +20,7 @@ class MonitoringMessage(Base):
level = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # info, warning, error, debug
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # Runner name for this query
variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # Query variables as JSON string
role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user') # user, assistant
@@ -64,6 +65,7 @@ class MonitoringSession(Base):
is_active = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=True, index=True)
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
class MonitoringError(Base):

View File

@@ -0,0 +1,74 @@
from .. import migration
import sqlalchemy
import json
@migration.migration_class(21)
class DBMigrateMergeExceptionHandling(migration.DBMigration):
"""Merge hide-exception and block-failed-request-output into a single exception-handling select option,
and add failure-hint field.
Conversion logic:
- block-failed-request-output=true -> exception-handling: hide
- hide-exception=true -> exception-handling: show-hint
- hide-exception=false -> exception-handling: show-error
"""
async def upgrade(self):
"""Upgrade"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
current_version = self.ap.ver_mgr.get_current_version()
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
if 'output' not in config:
config['output'] = {}
if 'misc' not in config['output']:
config['output']['misc'] = {}
misc = config['output']['misc']
# Determine new exception-handling value from legacy fields
hide_exception = misc.get('hide-exception', True)
block_failed = misc.get('block-failed-request-output', False)
if block_failed:
exception_handling = 'hide'
elif hide_exception:
exception_handling = 'show-hint'
else:
exception_handling = 'show-error'
misc['exception-handling'] = exception_handling
# Add failure-hint with default value
misc['failure-hint'] = 'Request failed.'
# Remove legacy fields
misc.pop('hide-exception', None)
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -0,0 +1,73 @@
import sqlalchemy
from .. import migration
@migration.migration_class(22)
class DBMigrateMonitoringUserId(migration.DBMigration):
"""Add user_id and user_name columns to monitoring_sessions table
This migration adds the missing user_id column and also ensures user_name
column exists (in case migration 21 failed or was skipped).
"""
async def _table_exists(self, table_name: str) -> bool:
"""Check if a table exists (works for both SQLite and PostgreSQL)."""
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
).bindparams(table_name=table_name)
)
return bool(result.scalar())
else:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
table_name=table_name
)
)
return result.first() is not None
async def _get_table_columns(self, table_name: str) -> list[str]:
"""Get column names from a table (works for both SQLite and PostgreSQL)."""
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'SELECT column_name FROM information_schema.columns WHERE table_name = :table_name;'
).bindparams(table_name=table_name)
)
return [row[0] for row in result.fetchall()]
else:
if not table_name.isidentifier():
raise ValueError(f'Invalid table name: {table_name}')
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
return [row[1] for row in result.fetchall()]
async def _add_column_if_not_exists(self, table_name: str, column_name: str, column_type: str):
"""Add a column to a table if it does not already exist."""
columns = await self._get_table_columns(table_name)
if column_name in columns:
self.ap.logger.debug('%s column already exists in %s.', column_name, table_name)
return
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f'ALTER TABLE {table_name} ADD COLUMN {column_name} {column_type};')
)
self.ap.logger.info('Added %s column to %s table.', column_name, table_name)
async def upgrade(self):
# Check if monitoring_sessions table exists
if not await self._table_exists('monitoring_sessions'):
self.ap.logger.warning('monitoring_sessions table does not exist, skipping migration.')
return
# Add user_id column to monitoring_sessions table
await self._add_column_if_not_exists('monitoring_sessions', 'user_id', 'VARCHAR(255)')
# Add user_name column to monitoring_sessions table (in case migration 21 failed)
await self._add_column_if_not_exists('monitoring_sessions', 'user_name', 'VARCHAR(255)')
# Add user_name column to monitoring_messages table (in case migration 21 failed)
if await self._table_exists('monitoring_messages'):
await self._add_column_if_not_exists('monitoring_messages', 'user_name', 'VARCHAR(255)')
async def downgrade(self):
pass

View File

@@ -0,0 +1,102 @@
from .. import migration
import sqlalchemy
import json
@migration.migration_class(23)
class DBMigrateModelFallbackConfig(migration.DBMigration):
"""Convert model field from plain UUID string to object with primary/fallbacks"""
async def upgrade(self):
"""Upgrade"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
current_version = self.ap.ver_mgr.get_current_version()
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
if 'ai' not in config or 'local-agent' not in config['ai']:
continue
local_agent = config['ai']['local-agent']
changed = False
# Convert model from string to object
model_value = local_agent.get('model', '')
if isinstance(model_value, str):
local_agent['model'] = {
'primary': model_value,
'fallbacks': [],
}
changed = True
# Remove leftover fallback-models field if present
if 'fallback-models' in local_agent:
del local_agent['fallback-models']
changed = True
if not changed:
continue
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
async def downgrade(self):
"""Downgrade"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
current_version = self.ap.ver_mgr.get_current_version()
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
if 'ai' not in config or 'local-agent' not in config['ai']:
continue
local_agent = config['ai']['local-agent']
# Convert model from object back to string
model_value = local_agent.get('model', '')
if isinstance(model_value, dict):
local_agent['model'] = model_value.get('primary', '')
else:
continue
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)

View File

@@ -0,0 +1,49 @@
from .. import migration
import sqlalchemy
import json
@migration.migration_class(24)
class DBMigrateWecomBotWebSocketMode(migration.DBMigration):
"""Add enable-webhook field to existing wecombot adapter configs.
Existing wecombot bots were all using webhook mode, so we set
enable-webhook=true to preserve their behavior after the new
WebSocket long connection mode is introduced as default.
"""
async def upgrade(self):
"""Upgrade"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("SELECT uuid, adapter_config FROM bots WHERE adapter = 'wecombot'")
)
bots = result.fetchall()
for bot_row in bots:
bot_uuid = bot_row[0]
adapter_config = json.loads(bot_row[1]) if isinstance(bot_row[1], str) else bot_row[1]
if 'enable-webhook' in adapter_config:
continue
# Determine mode based on existing config: if webhook fields are present, keep webhook mode
has_webhook_config = bool(
adapter_config.get('Token') and adapter_config.get('EncodingAESKey') and adapter_config.get('Corpid')
)
adapter_config['enable-webhook'] = has_webhook_config
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('UPDATE bots SET adapter_config = :config::jsonb WHERE uuid = :uuid'),
{'config': json.dumps(adapter_config), 'uuid': bot_uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('UPDATE bots SET adapter_config = :config WHERE uuid = :uuid'),
{'config': json.dumps(adapter_config), 'uuid': bot_uuid},
)
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -34,6 +34,15 @@ class MonitoringHelper:
# Check if session exists, if not, record session start
session_id = f'{query.launcher_type}_{query.launcher_id}'
# Get sender name from message event
sender_name = None
if hasattr(query, 'message_event'):
if hasattr(query.message_event, 'sender'):
if hasattr(query.message_event.sender, 'nickname'):
sender_name = query.message_event.sender.nickname
elif hasattr(query.message_event.sender, 'member_name'):
sender_name = query.message_event.sender.member_name
# Try to record message
# Use JSON serialization to preserve message chain structure (including image URLs, etc.)
if hasattr(query, 'message_chain') and hasattr(query.message_chain, 'model_dump'):
@@ -57,6 +66,7 @@ class MonitoringHelper:
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
runner_name=runner_name,
variables=None, # Will be updated in record_query_success
)
@@ -80,6 +90,7 @@ class MonitoringHelper:
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
)
return message_id
@@ -128,6 +139,15 @@ class MonitoringHelper:
try:
session_id = f'{query.launcher_type}_{query.launcher_id}'
# Get sender name from message event
sender_name = None
if hasattr(query, 'message_event'):
if hasattr(query.message_event, 'sender'):
if hasattr(query.message_event.sender, 'nickname'):
sender_name = query.message_event.sender.nickname
elif hasattr(query.message_event.sender, 'member_name'):
sender_name = query.message_event.sender.member_name
# Extract response content from resp_message_chain
if hasattr(query, 'resp_message_chain') and query.resp_message_chain:
# Serialize the last response message chain
@@ -162,6 +182,7 @@ class MonitoringHelper:
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
runner_name=runner_name,
role='assistant',
)
@@ -183,6 +204,15 @@ class MonitoringHelper:
try:
session_id = f'{query.launcher_type}_{query.launcher_id}'
# Get sender name from message event
sender_name = None
if hasattr(query, 'message_event'):
if hasattr(query.message_event, 'sender'):
if hasattr(query.message_event.sender, 'nickname'):
sender_name = query.message_event.sender.nickname
elif hasattr(query.message_event.sender, 'member_name'):
sender_name = query.message_event.sender.member_name
# Record error message
message_id = await ap.monitoring_service.record_message(
bot_id=bot_id,
@@ -197,6 +227,7 @@ class MonitoringHelper:
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
runner_name=runner_name,
)

View File

@@ -36,17 +36,36 @@ class PreProcessor(stage.PipelineStage):
session = await self.ap.sess_mgr.get_session(query)
# When not local-agent, llm_model is None
try:
llm_model = (
await self.ap.model_mgr.get_model_by_uuid(query.pipeline_config['ai']['local-agent']['model'])
if selected_runner == 'local-agent'
else None
)
except ValueError:
self.ap.logger.warning(
f'LLM model {query.pipeline_config["ai"]["local-agent"]["model"] + " "}not found or not configured'
)
llm_model = None
llm_model = None
if selected_runner == 'local-agent':
# Read model config — new format is { primary: str, fallbacks: [str] },
# but handle legacy plain string for backward compatibility
model_config = query.pipeline_config['ai']['local-agent'].get('model', {})
if isinstance(model_config, str):
# Legacy format: plain UUID string
primary_uuid = model_config
fallback_uuids = []
else:
primary_uuid = model_config.get('primary', '')
fallback_uuids = model_config.get('fallbacks', [])
if primary_uuid:
try:
llm_model = await self.ap.model_mgr.get_model_by_uuid(primary_uuid)
except ValueError:
self.ap.logger.warning(f'LLM model {primary_uuid} not found or not configured')
# Resolve fallback model UUIDs
if fallback_uuids:
valid_fallbacks = []
for fb_uuid in fallback_uuids:
try:
await self.ap.model_mgr.get_model_by_uuid(fb_uuid)
valid_fallbacks.append(fb_uuid)
except ValueError:
self.ap.logger.warning(f'Fallback model {fb_uuid} not found, skipping')
if valid_fallbacks:
query.variables['_fallback_model_uuids'] = valid_fallbacks
conversation = await self.ap.sess_mgr.get_conversation(
query,
@@ -61,20 +80,28 @@ class PreProcessor(stage.PipelineStage):
query.prompt = conversation.prompt.copy()
query.messages = conversation.messages.copy()
if selected_runner == 'local-agent' and llm_model:
if selected_runner == 'local-agent':
query.use_funcs = []
query.use_llm_model_uuid = llm_model.model_entity.uuid
if llm_model:
query.use_llm_model_uuid = llm_model.model_entity.uuid
if llm_model.model_entity.abilities.__contains__('func_call'):
# Get bound plugins and MCP servers for filtering tools
if llm_model.model_entity.abilities.__contains__('func_call'):
# Get bound plugins and MCP servers for filtering tools
bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
bound_mcp_servers = query.variables.get('_pipeline_bound_mcp_servers', None)
query.use_funcs = await self.ap.tool_mgr.get_all_tools(bound_plugins, bound_mcp_servers)
self.ap.logger.debug(f'Bound plugins: {bound_plugins}')
self.ap.logger.debug(f'Bound MCP servers: {bound_mcp_servers}')
self.ap.logger.debug(f'Use funcs: {query.use_funcs}')
# If primary model doesn't support func_call but fallback models exist,
# load tools anyway since fallback models may support them
if not query.use_funcs and query.variables.get('_fallback_model_uuids'):
bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
bound_mcp_servers = query.variables.get('_pipeline_bound_mcp_servers', None)
query.use_funcs = await self.ap.tool_mgr.get_all_tools(bound_plugins, bound_mcp_servers)
self.ap.logger.debug(f'Bound plugins: {bound_plugins}')
self.ap.logger.debug(f'Bound MCP servers: {bound_mcp_servers}')
self.ap.logger.debug(f'Use funcs: {query.use_funcs}')
sender_name = ''
if isinstance(query.message_event, platform_events.GroupMessage):

View File

@@ -149,12 +149,19 @@ class ChatMessageHandler(handler.MessageHandler):
self.ap.logger.error(f'Conversation({query.query_id}) Request Failed: {error_info}')
traceback.print_exc()
hide_exception_info = query.pipeline_config['output']['misc']['hide-exception']
exception_handling = query.pipeline_config['output']['misc'].get('exception-handling', 'show-hint')
if exception_handling == 'show-error':
user_notice = f'{e}'
elif exception_handling == 'show-hint':
user_notice = query.pipeline_config['output']['misc'].get('failure-hint', 'Request failed.')
else: # hide
user_notice = None
yield entities.StageProcessResult(
result_type=entities.ResultType.INTERRUPT,
new_query=query,
user_notice='请求失败' if hide_exception_info else f'{e}',
user_notice=user_notice,
error_notice=f'{e}',
debug_notice=traceback.format_exc(),
)

View File

@@ -575,6 +575,127 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
_processed_thread_quote_cache: typing.ClassVar[dict[str, float]] = {}
_processed_thread_quote_cache_max_size: typing.ClassVar[int] = 4096
_processed_thread_quote_cache_ttl_seconds: typing.ClassVar[int] = 86400
@classmethod
def _prune_processed_thread_quote_cache(cls, now: typing.Optional[float] = None) -> None:
if now is None:
now = time.time()
expire_before = now - cls._processed_thread_quote_cache_ttl_seconds
while cls._processed_thread_quote_cache:
oldest_key, oldest_ts = next(iter(cls._processed_thread_quote_cache.items()))
if oldest_ts >= expire_before:
break
cls._processed_thread_quote_cache.pop(oldest_key, None)
while len(cls._processed_thread_quote_cache) > cls._processed_thread_quote_cache_max_size:
oldest_key = next(iter(cls._processed_thread_quote_cache))
cls._processed_thread_quote_cache.pop(oldest_key, None)
@classmethod
def _mark_thread_quote_processed(cls, thread_id: str) -> None:
now = time.time()
cls._prune_processed_thread_quote_cache(now)
cls._processed_thread_quote_cache[thread_id] = now
@classmethod
def _extract_quote_message_id(cls, message: EventMessage) -> typing.Optional[str]:
"""
Extract the message ID to quote from the given message.
Rules:
- First thread reply in a topic: return parent_id and mark topic as processed
- Follow-up thread replies in the same topic: return None
- Non-thread message: return parent_id if valid (non-empty, different from message_id)
Thread reply state is kept in a bounded TTL cache to avoid unbounded memory growth.
"""
parent_id = getattr(message, 'parent_id', None)
if not parent_id:
return None
message_id = getattr(message, 'message_id', None)
if parent_id == message_id:
return None
thread_id = getattr(message, 'thread_id', None)
if thread_id:
cls._prune_processed_thread_quote_cache()
if thread_id in cls._processed_thread_quote_cache:
return None
cls._mark_thread_quote_processed(thread_id)
return parent_id
@staticmethod
def _build_event_message_from_message_item(message_item: Message) -> typing.Optional[EventMessage]:
"""
Build EventMessage from SDK typed Message item.
Returns None if body or content is missing.
"""
body = getattr(message_item, 'body', None)
if not body:
return None
content = getattr(body, 'content', None)
if not content:
return None
event_data = {
'message_id': message_item.message_id,
'message_type': message_item.msg_type,
'content': content,
'create_time': message_item.create_time,
'mentions': getattr(message_item, 'mentions', []) or [],
}
# Preserve thread-related fields
if hasattr(message_item, 'parent_id') and message_item.parent_id:
event_data['parent_id'] = message_item.parent_id
if hasattr(message_item, 'root_id') and message_item.root_id:
event_data['root_id'] = message_item.root_id
if hasattr(message_item, 'thread_id') and message_item.thread_id:
event_data['thread_id'] = message_item.thread_id
if hasattr(message_item, 'chat_id') and message_item.chat_id:
event_data['chat_id'] = message_item.chat_id
return EventMessage(event_data)
@staticmethod
async def _fetch_quoted_message(
quote_message_id: str,
api_client: lark_oapi.Client,
) -> typing.Optional[platform_message.MessageChain]:
"""
Fetch the quoted message and convert to MessageChain.
Returns None if:
- API call fails
- Response items is empty
- Message item normalization fails
"""
request = GetMessageRequest.builder().message_id(quote_message_id).build()
response = await api_client.im.v1.message.aget(request)
if not response.success():
return None
items = getattr(response.data, 'items', None)
if not items:
return None
message_item = items[0]
event_message = LarkEventConverter._build_event_message_from_message_item(message_item)
if event_message is None:
return None
quote_chain = await LarkMessageConverter.target2yiri(event_message, api_client)
return quote_chain
@staticmethod
async def yiri2target(
event: platform_events.MessageEvent,
@@ -587,6 +708,23 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
) -> platform_events.Event:
message_chain = await LarkMessageConverter.target2yiri(event.event.message, api_client)
# Check for quote/reply message
quote_message_id = LarkEventConverter._extract_quote_message_id(event.event.message)
if quote_message_id:
quote_chain = await LarkEventConverter._fetch_quoted_message(quote_message_id, api_client)
if quote_chain:
# Filter out Source component from quoted chain, keep only content
quote_origin = platform_message.MessageChain(
[comp for comp in quote_chain if not isinstance(comp, platform_message.Source)]
)
if quote_origin:
message_chain.append(
platform_message.Quote(
message_id=quote_message_id,
origin=quote_origin,
)
)
if event.event.message.chat_type == 'p2p':
return platform_events.FriendMessage(
sender=platform_entities.Friend(
@@ -770,6 +908,32 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
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 get_launcher_id(self, event: platform_events.MessageEvent) -> str | None:
"""
Get topic-scoped launcher_id for thread-aware session isolation.
For group thread messages, returns "{group_id}_{thread_id}"
to ensure conversation context stays stable per topic.
Returns None for non-thread messages or P2P messages.
"""
source_event = getattr(event.source_platform_object, 'event', None)
if not source_event:
return None
message = getattr(source_event, 'message', None)
if not message:
return None
thread_id = getattr(message, 'thread_id', None)
if not thread_id:
return None
if isinstance(event, platform_events.GroupMessage):
return f'{event.group.id}_{thread_id}'
return None
def build_api_client(self, config):
app_id = config['app_id']
app_secret = config['app_secret']

View File

@@ -11,6 +11,7 @@ import langbot_plugin.api.entities.builtin.platform.entities as platform_entitie
from ..logger import EventLogger
from langbot.libs.wecom_ai_bot_api.wecombotevent import WecomBotEvent
from langbot.libs.wecom_ai_bot_api.api import WecomBotClient
from langbot.libs.wecom_ai_bot_api.ws_client import WecomBotWsClient
class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
@@ -176,27 +177,42 @@ class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
bot: WecomBotClient
bot: typing.Union[WecomBotClient, WecomBotWsClient]
bot_account_id: str
message_converter: WecomBotMessageConverter = WecomBotMessageConverter()
event_converter: WecomBotEventConverter = WecomBotEventConverter()
config: dict
bot_uuid: str = None
_ws_mode: bool = False
def __init__(self, config: dict, logger: EventLogger):
required_keys = ['Token', 'EncodingAESKey', 'Corpid', 'BotId']
missing_keys = [key for key in required_keys if key not in config]
if missing_keys:
raise Exception(f'WecomBot 缺少配置项: {missing_keys}')
enable_webhook = config.get('enable-webhook', False)
bot = WecomBotClient(
Token=config['Token'],
EnCodingAESKey=config['EncodingAESKey'],
Corpid=config['Corpid'],
logger=logger,
unified_mode=True,
)
bot_account_id = config['BotId']
if not enable_webhook:
bot = WecomBotWsClient(
bot_id=config['BotId'],
secret=config['Secret'],
logger=logger,
encoding_aes_key=config.get('EncodingAESKey', ''),
)
ws_mode = True
else:
# Webhook callback mode
required_keys = ['Token', 'EncodingAESKey', 'Corpid']
missing_keys = [key for key in required_keys if key not in config or not config[key]]
if missing_keys:
raise Exception(f'WecomBot webhook mode missing config: {missing_keys}')
bot = WecomBotClient(
Token=config['Token'],
EnCodingAESKey=config['EncodingAESKey'],
Corpid=config['Corpid'],
logger=logger,
unified_mode=True,
)
ws_mode = False
bot_account_id = config.get('BotId', '')
super().__init__(
config=config,
@@ -204,6 +220,7 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
bot=bot,
bot_account_id=bot_account_id,
)
self._ws_mode = ws_mode
async def reply_message(
self,
@@ -212,7 +229,15 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
quote_origin: bool = False,
):
content = await self.message_converter.yiri2target(message)
await self.bot.set_message(message_source.source_platform_object.message_id, content)
if self._ws_mode:
event = message_source.source_platform_object
req_id = event.get('req_id', '')
if req_id:
await self.bot.reply_text(req_id, content)
else:
await self.bot.set_message(event.message_id, content)
else:
await self.bot.set_message(message_source.source_platform_object.message_id, content)
async def reply_message_chunk(
self,
@@ -222,31 +247,22 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
quote_origin: bool = False,
is_final: bool = False,
):
"""将流水线增量输出写入企业微信 stream 会话。
Args:
message_source: 流水线提供的原始消息事件。
bot_message: 当前片段对应的模型元信息(未使用)。
message: 需要回复的消息链。
quote_origin: 是否引用原消息(企业微信暂不支持)。
is_final: 标记当前片段是否为最终回复。
Returns:
dict: 包含 `stream` 键,标识写入是否成功。
Example:
在流水线 `reply_message_chunk` 调用中自动触发,无需手动调用。
"""
# 转换为纯文本(智能机器人当前协议仅支持文本流)
content = await self.message_converter.yiri2target(message)
msg_id = message_source.source_platform_object.message_id
# 将片段推送到 WecomBotClient 中的队列,返回值用于判断是否走降级逻辑
success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
if not success and is_final:
# 未命中流式队列时使用旧有 set_message 兜底
await self.bot.set_message(msg_id, content)
return {'stream': success}
if self._ws_mode:
success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
if not success and is_final:
event = message_source.source_platform_object
req_id = event.get('req_id', '')
if req_id:
await self.bot.reply_text(req_id, content)
return {'stream': success}
else:
success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
if not success and is_final:
await self.bot.set_message(msg_id, content)
return {'stream': success}
async def is_stream_output_supported(self) -> bool:
"""智能机器人侧默认开启流式能力。
@@ -259,7 +275,11 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
return True
async def send_message(self, target_type, target_id, message):
pass
if self._ws_mode:
content = await self.message_converter.yiri2target(message)
await self.bot.send_message(target_id, content)
else:
pass
def register_listener(
self,
@@ -288,29 +308,25 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
self.bot_uuid = bot_uuid
async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
"""处理统一 webhook 请求。
Args:
bot_uuid: Bot 的 UUID
path: 子路径(如果有的话)
request: Quart Request 对象
Returns:
响应数据
"""
if self._ws_mode:
return None
return await self.bot.handle_unified_webhook(request)
async def run_async(self):
# 统一 webhook 模式下,不启动独立的 Quart 应用
# 保持运行但不启动独立端口
if self._ws_mode:
await self.bot.connect()
else:
async def keep_alive():
while True:
await asyncio.sleep(1)
async def keep_alive():
while True:
await asyncio.sleep(1)
await keep_alive()
await keep_alive()
async def kill(self) -> bool:
if self._ws_mode:
await self.bot.disconnect()
return True
return False
async def unregister_listener(

View File

@@ -11,35 +11,64 @@ metadata:
icon: wecombot.png
spec:
config:
- name: BotId
label:
en_US: BotId
zh_Hans: 机器人ID (BotId)
type: string
required: true
default: ""
- name: enable-webhook
label:
en_US: Enable Webhook Mode
zh_Hans: 启用Webhook模式
description:
en_US: If enabled, the bot will use webhook mode to receive messages. Otherwise, it will use WS long connection mode
zh_Hans: 如果启用,机器人将使用 Webhook 模式接收消息。否则,将使用 WS 长连接模式
type: boolean
required: true
default: false
- name: Secret
label:
en_US: Secret
zh_Hans: 机器人密钥 (Secret)
description:
en_US: Required for WebSocket long connection mode
zh_Hans: 使用 WS 长连接模式时必填
type: string
required: false
default: ""
- name: Corpid
label:
en_US: Corpid
zh_Hans: 企业ID
description:
en_US: Required for Webhook mode
zh_Hans: 使用 Webhook 模式时必填
type: string
required: true
required: false
default: ""
- name: Token
label:
en_US: Token
zh_Hans: 令牌 (Token)
description:
en_US: Required for Webhook mode
zh_Hans: 使用 Webhook 模式时必填
type: string
required: true
required: false
default: ""
- name: EncodingAESKey
label:
en_US: EncodingAESKey
zh_Hans: 消息加解密密钥 (EncodingAESKey)
type: string
required: true
default: ""
- name: BotId
label:
en_US: BotId
zh_Hans: 机器人ID
description:
en_US: Required for Webhook mode. Optional for WebSocket mode (used for file decryption)
zh_Hans: 使用 Webhook 模式时必填。WebSocket 模式下可选(用于文件解密)
type: string
required: false
default: ""
execution:
python:
path: ./wecombot.py
attr: WecomBotAdapter
attr: WecomBotAdapter

View File

@@ -81,22 +81,33 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
return event.source_platform_object
@staticmethod
async def target2yiri(event: WecomCSEvent):
async def target2yiri(event: WecomCSEvent, bot: WecomCSClient = None):
"""
将 WecomEvent 转换为平台的 FriendMessage 对象。
Args:
event (WecomEvent): 企业微信客服事件。
bot (WecomCSClient): 企业微信客服客户端,用于获取用户信息。
Returns:
platform_events.FriendMessage: 转换后的 FriendMessage 对象。
"""
# Try to get customer nickname from WeChat API
nickname = str(event.user_id)
if bot and event.user_id:
try:
customer_info = await bot.get_customer_info(event.user_id)
if customer_info and customer_info.get('nickname'):
nickname = customer_info.get('nickname')
except Exception:
pass # Fall back to user_id as nickname
# 转换消息链
if event.type == 'text':
yiri_chain = await WecomMessageConverter.target2yiri(event.message, event.message_id)
friend = platform_entities.Friend(
id=f'u{event.user_id}',
nickname=str(event.user_id),
nickname=nickname,
remark='',
)
@@ -106,7 +117,7 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
elif event.type == 'image':
friend = platform_entities.Friend(
id=f'u{event.user_id}',
nickname=str(event.user_id),
nickname=nickname,
remark='',
)
@@ -187,7 +198,7 @@ class WecomCSAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
async def on_message(event: WecomCSEvent):
self.bot_account_id = event.receiver_id
try:
return await callback(await self.event_converter.target2yiri(event), self)
return await callback(await self.event_converter.target2yiri(event, self.bot), self)
except Exception:
await self.logger.error(f'Error in wecomcs callback: {traceback.format_exc()}')

View File

@@ -565,6 +565,16 @@ class RuntimeConnectionHandler(handler.Handler):
except Exception as e:
return _make_rag_error_response(e, 'FileServiceError', storage_path=storage_path)
@self.action(PluginToRuntimeAction.LIST_PARSERS)
async def list_parsers(data: dict[str, Any]) -> handler.ActionResponse:
"""Plugin requests host to list available parser plugins."""
mime_type = data.get('mime_type')
try:
parsers = await self.ap.knowledge_service.list_parsers(mime_type)
return handler.ActionResponse.success(data={'parsers': parsers})
except Exception as e:
return _make_rag_error_response(e, 'ParserDiscoveryError', mime_type=mime_type)
@self.action(PluginToRuntimeAction.INVOKE_PARSER)
async def invoke_parser(data: dict[str, Any]) -> handler.ActionResponse:
"""Plugin requests host to invoke a parser plugin."""
@@ -589,6 +599,94 @@ class RuntimeConnectionHandler(handler.Handler):
except Exception as e:
return _make_rag_error_response(e, 'ParserError')
# ================= Knowledge Base Query APIs =================
@self.action(PluginToRuntimeAction.LIST_PIPELINE_KNOWLEDGE_BASES)
async def list_pipeline_knowledge_bases(data: dict[str, Any]) -> handler.ActionResponse:
"""List knowledge bases configured for the current query's pipeline."""
query_id = data['query_id']
if query_id not in self.ap.query_pool.cached_queries:
return handler.ActionResponse.error(
message=f'Query with query_id {query_id} not found',
)
query = self.ap.query_pool.cached_queries[query_id]
kb_uuids = []
if query.pipeline_config:
local_agent_config = query.pipeline_config.get('ai', {}).get('local-agent', {})
kb_uuids = local_agent_config.get('knowledge-bases', [])
# Backward compatibility
if not kb_uuids:
old_kb_uuid = local_agent_config.get('knowledge-base', '')
if old_kb_uuid and old_kb_uuid != '__none__':
kb_uuids = [old_kb_uuid]
knowledge_bases = []
for kb_uuid in kb_uuids:
kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
if kb:
knowledge_bases.append(
{
'uuid': kb.get_uuid(),
'name': kb.get_name(),
'description': kb.knowledge_base_entity.description or '',
}
)
return handler.ActionResponse.success(data={'knowledge_bases': knowledge_bases})
@self.action(PluginToRuntimeAction.RETRIEVE_KNOWLEDGE_BASE)
async def retrieve_knowledge_base(data: dict[str, Any]) -> handler.ActionResponse:
"""Retrieve documents from a knowledge base within the pipeline's scope."""
query_id = data['query_id']
kb_id = data['kb_id']
query_text = data['query_text']
top_k = data.get('top_k', 5)
filters = data.get('filters', {})
if query_id not in self.ap.query_pool.cached_queries:
return handler.ActionResponse.error(
message=f'Query with query_id {query_id} not found',
)
query = self.ap.query_pool.cached_queries[query_id]
# Validate kb_id is in pipeline's allowed list
allowed_kb_uuids = []
if query.pipeline_config:
local_agent_config = query.pipeline_config.get('ai', {}).get('local-agent', {})
allowed_kb_uuids = local_agent_config.get('knowledge-bases', [])
if not allowed_kb_uuids:
old_kb_uuid = local_agent_config.get('knowledge-base', '')
if old_kb_uuid and old_kb_uuid != '__none__':
allowed_kb_uuids = [old_kb_uuid]
if kb_id not in allowed_kb_uuids:
return handler.ActionResponse.error(
message=f'Knowledge base {kb_id} is not configured for this pipeline',
)
kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_id)
if not kb:
return handler.ActionResponse.error(
message=f'Knowledge base {kb_id} not found',
)
try:
entries = await kb.retrieve(
query_text,
settings={
'top_k': top_k,
'filters': filters,
},
)
results = [entry.model_dump(mode='json') for entry in entries]
return handler.ActionResponse.success(data={'results': results})
except Exception as e:
return _make_rag_error_response(e, 'RetrievalError', kb_id=kb_id)
@self.action(CommonAction.PING)
async def ping(data: dict[str, Any]) -> handler.ActionResponse:
"""Ping"""

View File

@@ -441,6 +441,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
is_final = False
think_start = False
think_end = False
yielded_final = False
remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think')
@@ -493,13 +494,19 @@ class DifyServiceAPIRunner(runner.RequestRunner):
if answer:
basic_mode_pending_chunk = answer
if (is_final or message_idx % 8 == 0) and (basic_mode_pending_chunk != '' or is_final):
if (
not yielded_final
and (is_final or message_idx % 8 == 0)
and (basic_mode_pending_chunk != '' or is_final)
):
# content, _ = self._process_thinking_content(basic_mode_pending_chunk)
yield provider_message.MessageChunk(
role='assistant',
content=basic_mode_pending_chunk,
is_final=is_final,
)
if is_final:
yielded_final = True
if chunk is None:
raise errors.DifyAPIError('Dify API 没有返回任何响应请检查网络连接和API配置')

View File

@@ -4,6 +4,7 @@ import json
import copy
import typing
from .. import runner
from ..modelmgr import requester as modelmgr_requester
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
import langbot_plugin.api.entities.builtin.provider.message as provider_message
import langbot_plugin.api.entities.builtin.rag.context as rag_context
@@ -26,19 +27,109 @@ Respond in the same language as the user's input.
@runner.runner_class('local-agent')
class LocalAgentRunner(runner.RequestRunner):
"""本地Agent请求运行器"""
"""Local agent request runner"""
class ToolCallTracker:
"""工具调用追踪器"""
async def _get_model_candidates(
self,
query: pipeline_query.Query,
) -> list[modelmgr_requester.RuntimeLLMModel]:
"""Build ordered list of models to try: primary model + fallback models."""
candidates = []
def __init__(self):
self.active_calls: dict[str, dict] = {}
self.completed_calls: list[provider_message.ToolCall] = []
# Primary model
if query.use_llm_model_uuid:
try:
primary = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
candidates.append(primary)
except ValueError:
self.ap.logger.warning(f'Primary model {query.use_llm_model_uuid} not found')
# Fallback models
fallback_uuids = (query.variables or {}).get('_fallback_model_uuids', [])
for fb_uuid in fallback_uuids:
try:
fb_model = await self.ap.model_mgr.get_model_by_uuid(fb_uuid)
candidates.append(fb_model)
except ValueError:
self.ap.logger.warning(f'Fallback model {fb_uuid} not found, skipping')
return candidates
async def _invoke_with_fallback(
self,
query: pipeline_query.Query,
candidates: list[modelmgr_requester.RuntimeLLMModel],
messages: list,
funcs: list,
remove_think: bool,
) -> tuple[provider_message.Message, modelmgr_requester.RuntimeLLMModel]:
"""Try non-streaming invocation with sequential fallback. Returns (message, model_used)."""
last_error = None
for model in candidates:
try:
msg = await model.provider.invoke_llm(
query,
model,
messages,
funcs if model.model_entity.abilities.__contains__('func_call') else [],
extra_args=model.model_entity.extra_args,
remove_think=remove_think,
)
return msg, model
except Exception as e:
last_error = e
self.ap.logger.warning(f'Model {model.model_entity.name} failed: {e}, trying next fallback...')
raise last_error or RuntimeError('No model candidates available')
async def _invoke_stream_with_fallback(
self,
query: pipeline_query.Query,
candidates: list[modelmgr_requester.RuntimeLLMModel],
messages: list,
funcs: list,
remove_think: bool,
) -> tuple[typing.AsyncGenerator, modelmgr_requester.RuntimeLLMModel]:
"""Try streaming invocation with sequential fallback. Returns (stream_generator, model_used).
Fallback is only possible before any chunks have been yielded to the client.
Once streaming starts, the model is committed.
"""
last_error = None
for model in candidates:
try:
stream = model.provider.invoke_llm_stream(
query,
model,
messages,
funcs if model.model_entity.abilities.__contains__('func_call') else [],
extra_args=model.model_entity.extra_args,
remove_think=remove_think,
)
# Attempt to get the first chunk to verify the stream works
first_chunk = await stream.__anext__()
async def _chain_stream(first, rest):
yield first
async for chunk in rest:
yield chunk
return _chain_stream(first_chunk, stream), model
except StopAsyncIteration:
# Empty stream — treat as success (model returned nothing)
async def _empty_stream():
return
yield # make it a generator
return _empty_stream(), model
except Exception as e:
last_error = e
self.ap.logger.warning(f'Model {model.model_entity.name} stream failed: {e}, trying next fallback...')
raise last_error or RuntimeError('No model candidates available')
async def run(
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]:
"""运行请求"""
"""Run request"""
pending_tool_calls = []
# Get knowledge bases list (new field)
@@ -74,7 +165,14 @@ class LocalAgentRunner(runner.RequestRunner):
self.ap.logger.warning(f'Knowledge base {kb_uuid} not found, skipping')
continue
result = await kb.retrieve(user_message_text)
result = await kb.retrieve(
user_message_text,
settings={
'bot_uuid': query.bot_uuid or '',
'sender_id': str(query.sender_id),
'session_name': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
},
)
if result:
all_results.extend(result)
@@ -113,51 +211,51 @@ class LocalAgentRunner(runner.RequestRunner):
remove_think = query.pipeline_config['output'].get('misc', '').get('remove-think')
use_llm_model = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
# Build ordered candidate list (primary + fallbacks)
candidates = await self._get_model_candidates(query)
if not candidates:
raise RuntimeError('No LLM model configured for local-agent runner')
self.ap.logger.debug(
f'localagent req: query={query.query_id} req_messages={req_messages} use_llm_model={query.use_llm_model_uuid}'
f'localagent req: query={query.query_id} req_messages={req_messages} '
f'candidates={[m.model_entity.name for m in candidates]}'
)
if not is_stream:
# 非流式输出,直接请求
msg = await use_llm_model.provider.invoke_llm(
# Non-streaming: invoke with fallback
msg, use_llm_model = await self._invoke_with_fallback(
query,
use_llm_model,
candidates,
req_messages,
query.use_funcs,
extra_args=use_llm_model.model_entity.extra_args,
remove_think=remove_think,
remove_think,
)
yield msg
final_msg = msg
else:
# 流式输出,需要处理工具调用
# Streaming: invoke with fallback
tool_calls_map: dict[str, provider_message.ToolCall] = {}
msg_idx = 0
accumulated_content = '' # 从开始累积的所有内容
accumulated_content = ''
last_role = 'assistant'
msg_sequence = 1
async for msg in use_llm_model.provider.invoke_llm_stream(
stream_src, use_llm_model = await self._invoke_stream_with_fallback(
query,
use_llm_model,
candidates,
req_messages,
query.use_funcs,
extra_args=use_llm_model.model_entity.extra_args,
remove_think=remove_think,
):
remove_think,
)
async for msg in stream_src:
msg_idx = msg_idx + 1
# 记录角色
if msg.role:
last_role = msg.role
# 累积内容
if msg.content:
accumulated_content += msg.content
# 处理工具调用
if msg.tool_calls:
for tool_call in msg.tool_calls:
if tool_call.id not in tool_calls_map:
@@ -169,21 +267,18 @@ class LocalAgentRunner(runner.RequestRunner):
),
)
if tool_call.function and tool_call.function.arguments:
# 流式处理中工具调用参数可能分多个chunk返回需要追加而不是覆盖
tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
# continue
# 每8个chunk或最后一个chunk时输出所有累积的内容
if msg_idx % 8 == 0 or msg.is_final:
msg_sequence += 1
yield provider_message.MessageChunk(
role=last_role,
content=accumulated_content, # 输出所有累积内容
content=accumulated_content,
tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None,
is_final=msg.is_final,
msg_sequence=msg_sequence,
)
# 创建最终消息用于后续处理
final_msg = provider_message.MessageChunk(
role=last_role,
content=accumulated_content,
@@ -198,7 +293,8 @@ class LocalAgentRunner(runner.RequestRunner):
req_messages.append(final_msg)
# 持续请求,只要还有待处理的工具调用就继续处理调用
# Once a model succeeds, commit to it for the tool call loop
# (no fallback mid-conversation — different models may interpret tool results differently)
while pending_tool_calls:
for tool_call in pending_tool_calls:
try:
@@ -239,7 +335,6 @@ class LocalAgentRunner(runner.RequestRunner):
req_messages.append(msg)
except Exception as e:
# 工具调用出错,添加一个报错信息到 req_messages
err_msg = provider_message.Message(role='tool', content=f'err: {e}', tool_call_id=tool_call.id)
yield err_msg
@@ -247,39 +342,38 @@ class LocalAgentRunner(runner.RequestRunner):
req_messages.append(err_msg)
self.ap.logger.debug(
f'localagent req: query={query.query_id} req_messages={req_messages} use_llm_model={query.use_llm_model_uuid}'
f'localagent req: query={query.query_id} req_messages={req_messages} '
f'use_llm_model={use_llm_model.model_entity.name}'
)
if is_stream:
tool_calls_map = {}
msg_idx = 0
accumulated_content = '' # 从开始累积的所有内容
accumulated_content = ''
last_role = 'assistant'
msg_sequence = first_end_sequence
async for msg in use_llm_model.provider.invoke_llm_stream(
tool_stream_src = use_llm_model.provider.invoke_llm_stream(
query,
use_llm_model,
req_messages,
query.use_funcs,
query.use_funcs if use_llm_model.model_entity.abilities.__contains__('func_call') else [],
extra_args=use_llm_model.model_entity.extra_args,
remove_think=remove_think,
):
)
async for msg in tool_stream_src:
msg_idx += 1
# 记录角色
if msg.role:
last_role = msg.role
# 第一次请求工具调用时的内容
# Prepend first-round content on first chunk of tool-call round
if msg_idx == 1:
accumulated_content = first_content if first_content is not None else accumulated_content
# 累积内容
if msg.content:
accumulated_content += msg.content
# 处理工具调用
if msg.tool_calls:
for tool_call in msg.tool_calls:
if tool_call.id not in tool_calls_map:
@@ -291,15 +385,13 @@ class LocalAgentRunner(runner.RequestRunner):
),
)
if tool_call.function and tool_call.function.arguments:
# 流式处理中工具调用参数可能分多个chunk返回需要追加而不是覆盖
tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
# 每8个chunk或最后一个chunk时输出所有累积的内容
if msg_idx % 8 == 0 or msg.is_final:
msg_sequence += 1
yield provider_message.MessageChunk(
role=last_role,
content=accumulated_content, # 输出所有累积内容
content=accumulated_content,
tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None,
is_final=msg.is_final,
msg_sequence=msg_sequence,
@@ -312,12 +404,12 @@ class LocalAgentRunner(runner.RequestRunner):
msg_sequence=msg_sequence,
)
else:
# 处理完所有调用,再次请求
# Non-streaming: use committed model directly (no fallback in tool loop)
msg = await use_llm_model.provider.invoke_llm(
query,
use_llm_model,
req_messages,
query.use_funcs,
query.use_funcs if use_llm_model.model_entity.abilities.__contains__('func_call') else [],
extra_args=use_llm_model.model_entity.extra_args,
remove_think=remove_think,
)

View File

@@ -321,13 +321,19 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
if not plugin_id:
raise ValueError(f'No RAG plugin ID configured for KB {kb.uuid}. Retrieval failed.')
# Session context (e.g. session_name) stays in retrieval_settings
# for plugins that need it. Do NOT move them into filters, as filters
# are passed directly to vector_search by some plugins (e.g. LangRAG)
# and would cause empty results when the metadata field doesn't exist.
filters = settings.pop('filters', {})
retrieval_context = {
'query': query,
'knowledge_base_id': kb.uuid,
'collection_id': kb.collection_id or kb.uuid,
'retrieval_settings': settings,
'creation_settings': kb.creation_settings or {},
'filters': settings.pop('filters', {}),
'filters': filters,
}
result = await self.ap.plugin_connector.call_rag_retrieve(

View File

@@ -2,7 +2,7 @@ import langbot
semantic_version = f'v{langbot.__version__}'
required_database_version = 20
required_database_version = 24
"""Tag the version of the database schema, used to check if the database needs to be migrated"""
debug_mode = False

View File

@@ -100,7 +100,7 @@ class VectorDBManager:
) -> list[dict]:
"""Proxy: Search vectors.
Returns a list of dicts with keys: 'id', 'score', 'metadata'.
Returns a list of dicts with keys: 'id', 'distance', 'metadata'.
The underlying VectorDatabase.search returns Chroma-style format:
{ 'ids': [['id1']], 'distances': [[0.1]], 'metadatas': [[{}]] }
"""
@@ -130,7 +130,7 @@ class VectorDBManager:
parsed_results.append(
{
'id': id_val,
'score': r_dists[i] if r_dists and i < len(r_dists) else 0.0,
'distance': r_dists[i] if r_dists and i < len(r_dists) else 0.0,
'metadata': r_metas[i] if r_metas and i < len(r_metas) else {},
}
)

View File

@@ -2,11 +2,14 @@ from __future__ import annotations
import asyncio
from typing import Any
from chromadb import PersistentClient
from langbot.pkg.vector.vdb import VectorDatabase
from langbot.pkg.vector.vdb import VectorDatabase, SearchType
from langbot.pkg.core import app
import chromadb
import chromadb.errors
# RRF smoothing constant (standard value from the literature)
_RRF_K = 60
class ChromaVectorDatabase(VectorDatabase):
def __init__(self, ap: app.Application, base_path: str = './data/chroma'):
@@ -14,6 +17,10 @@ class ChromaVectorDatabase(VectorDatabase):
self.client = PersistentClient(path=base_path)
self._collections = {}
@classmethod
def supported_search_types(cls) -> list[SearchType]:
return [SearchType.VECTOR, SearchType.FULL_TEXT, SearchType.HYBRID]
async def get_or_create_collection(self, collection: str) -> chromadb.Collection:
if collection not in self._collections:
self._collections[collection] = await asyncio.to_thread(
@@ -34,8 +41,8 @@ class ChromaVectorDatabase(VectorDatabase):
kwargs: dict[str, Any] = dict(embeddings=embeddings_list, ids=ids, metadatas=metadatas)
if documents is not None:
kwargs['documents'] = documents
await asyncio.to_thread(col.add, **kwargs)
self.ap.logger.info(f"Added {len(ids)} embeddings to Chroma collection '{collection}'.")
await asyncio.to_thread(col.upsert, **kwargs)
self.ap.logger.info(f"Upserted {len(ids)} embeddings to Chroma collection '{collection}'.")
async def search(
self,
@@ -47,6 +54,23 @@ class ChromaVectorDatabase(VectorDatabase):
filter: dict[str, Any] | None = None,
) -> dict[str, Any]:
col = await self.get_or_create_collection(collection)
if search_type == SearchType.FULL_TEXT:
return await self._full_text_search(col, collection, k, query_text, filter)
elif search_type == SearchType.HYBRID:
return await self._hybrid_search(col, collection, query_embedding, k, query_text, filter)
# Default: vector search
return await self._vector_search(col, collection, query_embedding, k, filter)
async def _vector_search(
self,
col: chromadb.Collection,
collection: str,
query_embedding: list[float],
k: int,
filter: dict[str, Any] | None,
) -> dict[str, Any]:
query_kwargs: dict[str, Any] = dict(
query_embeddings=query_embedding,
n_results=k,
@@ -55,9 +79,137 @@ class ChromaVectorDatabase(VectorDatabase):
if filter:
query_kwargs['where'] = filter
results = await asyncio.to_thread(col.query, **query_kwargs)
self.ap.logger.info(f"Chroma search in '{collection}' returned {len(results.get('ids', [[]])[0])} results.")
self.ap.logger.info(
f"Chroma vector search in '{collection}' returned {len(results.get('ids', [[]])[0])} results."
)
return results
async def _full_text_search(
self,
col: chromadb.Collection,
collection: str,
k: int,
query_text: str,
filter: dict[str, Any] | None,
) -> dict[str, Any]:
if not query_text:
return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
get_kwargs: dict[str, Any] = dict(
where_document={'$contains': query_text},
include=['metadatas', 'documents'],
limit=k,
)
if filter:
get_kwargs['where'] = filter
results = await asyncio.to_thread(col.get, **get_kwargs)
# col.get returns flat lists; wrap into column-major format.
# Distances are all 0.0 because Chroma's local $contains is a boolean
# filter with no relevance scoring. Chroma's BM25 sparse embedding
# function (ChromaBm25EmbeddingFunction) can generate scored sparse
# vectors, but sparse vector *indexing* is only available on Chroma
# Cloud, not locally. For ranked results, use hybrid mode or apply a
# reranker in a downstream stage.
ids = results.get('ids', [])
metadatas = results.get('metadatas', []) or [None] * len(ids)
documents = results.get('documents', []) or [None] * len(ids)
distances = [0.0] * len(ids)
self.ap.logger.info(f"Chroma full-text search in '{collection}' returned {len(ids)} results.")
return {'ids': [ids], 'metadatas': [metadatas], 'distances': [distances], 'documents': [documents]}
async def _hybrid_search(
self,
col: chromadb.Collection,
collection: str,
query_embedding: list[float],
k: int,
query_text: str,
filter: dict[str, Any] | None,
) -> dict[str, Any]:
# Fall back to pure vector search when no text is provided
if not query_text:
return await self._vector_search(col, collection, query_embedding, k, filter)
# Run vector search and full-text search in parallel
vector_task = self._vector_search(col, collection, query_embedding, k, filter)
text_task = self._full_text_search(col, collection, k, query_text, filter)
vector_results, text_results = await asyncio.gather(vector_task, text_task)
vector_ids = vector_results.get('ids', [[]])[0]
text_ids = text_results.get('ids', [[]])[0]
if not vector_ids and not text_ids:
return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
# RRF fusion
fused = self._rrf_fuse([vector_ids, text_ids], k)
if not fused:
return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
fused_ids = [doc_id for doc_id, _ in fused]
# Fetch full metadata and documents for fused results
fetched = await asyncio.to_thread(col.get, ids=fused_ids, include=['metadatas', 'documents'])
# col.get returns results in arbitrary order; re-order to match fused ranking
fetched_map: dict[str, tuple] = {}
for i, fid in enumerate(fetched.get('ids', [])):
meta = (fetched.get('metadatas') or [None] * len(fetched['ids']))[i]
doc = (fetched.get('documents') or [None] * len(fetched['ids']))[i]
fetched_map[fid] = (meta, doc)
ordered_ids = []
ordered_metas = []
ordered_docs = []
ordered_dists = []
# Normalize RRF scores to 0~1 distances via min-max scaling.
# Raw RRF scores are tiny (e.g. 0.016~0.033 with k=60) so a naive
# ``1 - score`` would compress all distances into a narrow 0.96~0.98
# band with almost no discriminative power. Min-max normalization
# spreads them across the full 0~1 range (0.0 = best match).
max_score = fused[0][1]
min_score = fused[-1][1]
score_range = max_score - min_score
for doc_id, score in fused:
if doc_id in fetched_map:
meta, doc = fetched_map[doc_id]
ordered_ids.append(doc_id)
ordered_metas.append(meta)
ordered_docs.append(doc)
if score_range > 0:
ordered_dists.append(1.0 - (score - min_score) / score_range)
else:
ordered_dists.append(0.0)
self.ap.logger.info(
f"Chroma hybrid search in '{collection}' returned {len(ordered_ids)} results "
f'(vector={len(vector_ids)}, text={len(text_ids)}).'
)
return {
'ids': [ordered_ids],
'metadatas': [ordered_metas],
'distances': [ordered_dists],
'documents': [ordered_docs],
}
@staticmethod
def _rrf_fuse(result_lists: list[list[str]], k: int) -> list[tuple[str, float]]:
"""Reciprocal Rank Fusion over multiple ranked ID lists.
Returns a list of (doc_id, rrf_score) sorted by descending score,
truncated to *k* entries.
"""
scores: dict[str, float] = {}
for ranked_ids in result_lists:
for rank, doc_id in enumerate(ranked_ids):
scores[doc_id] = scores.get(doc_id, 0.0) + 1.0 / (_RRF_K + rank + 1)
sorted_results = sorted(scores.items(), key=lambda x: x[1], reverse=True)
return sorted_results[:k]
async def delete_by_file_id(self, collection: str, file_id: str) -> None:
col = await self.get_or_create_collection(collection)
await asyncio.to_thread(col.delete, where={'file_id': file_id})

View File

@@ -95,11 +95,12 @@
"max": 0
},
"misc": {
"hide-exception": true,
"exception-handling": "show-hint",
"failure-hint": "Request failed.",
"at-sender": true,
"quote-origin": true,
"track-function-calls": false,
"remove-think": false
}
}
}
}

View File

@@ -59,8 +59,11 @@ stages:
label:
en_US: Model
zh_Hans: 模型
type: llm-model-selector
type: model-fallback-selector
required: true
default:
primary: ''
fallbacks: []
- name: max-round
label:
en_US: Max Round

View File

@@ -78,13 +78,39 @@ stages:
en_US: Misc
zh_Hans: 杂项
config:
- name: hide-exception
- name: exception-handling
label:
en_US: Hide Exception
zh_Hans: 不输出异常信息给用户
type: boolean
en_US: Exception Handling Strategy
zh_Hans: 异常处理策略
description:
en_US: Controls how error messages are displayed to the user when an AI request fails
zh_Hans: 控制 AI 请求失败时向用户展示错误信息的方式
type: select
required: true
default: true
default: show-hint
options:
- name: show-error
label:
en_US: Show Full Error
zh_Hans: 显示完整报错信息
- name: show-hint
label:
en_US: Show Failure Hint
zh_Hans: 仅文字提示
- name: hide
label:
en_US: Hide All
zh_Hans: 不显示任何异常信息
- name: failure-hint
label:
en_US: Failure Hint Text
zh_Hans: 失败提示文本
description:
en_US: The text to display when a request fails. Only effective when Exception Handling Strategy is set to "Show Failure Hint"
zh_Hans: 请求失败时显示的提示文本,仅在异常处理策略设置为"仅文字提示"时生效
type: string
required: false
default: 'Request failed.'
- name: at-sender
label:
en_US: At Sender
@@ -119,3 +145,4 @@ stages:
type: boolean
required: true
default: false

54
uv.lock generated
View File

@@ -1112,7 +1112,7 @@ wheels = [
[[package]]
name = "flask"
version = "3.1.2"
version = "3.1.3"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "blinker" },
@@ -1122,9 +1122,9 @@ dependencies = [
{ name = "markupsafe" },
{ name = "werkzeug" },
]
sdist = { url = "https://files.pythonhosted.org/packages/dc/6d/cfe3c0fcc5e477df242b98bfe186a4c34357b4847e87ecaef04507332dab/flask-3.1.2.tar.gz", hash = "sha256:bf656c15c80190ed628ad08cdfd3aaa35beb087855e2f494910aa3774cc4fd87", size = 720160, upload-time = "2025-08-19T21:03:21.205Z" }
sdist = { url = "https://files.pythonhosted.org/packages/26/00/35d85dcce6c57fdc871f3867d465d780f302a175ea360f62533f12b27e2b/flask-3.1.3.tar.gz", hash = "sha256:0ef0e52b8a9cd932855379197dd8f94047b359ca0a78695144304cb45f87c9eb", size = 759004, upload-time = "2026-02-19T05:00:57.678Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/ec/f9/7f9263c5695f4bd0023734af91bedb2ff8209e8de6ead162f35d8dc762fd/flask-3.1.2-py3-none-any.whl", hash = "sha256:ca1d8112ec8a6158cc29ea4858963350011b5c846a414cdb7a954aa9e967d03c", size = 103308, upload-time = "2025-08-19T21:03:19.499Z" },
{ url = "https://files.pythonhosted.org/packages/7f/9c/34f6962f9b9e9c71f6e5ed806e0d0ff03c9d1b0b2340088a0cf4bce09b18/flask-3.1.3-py3-none-any.whl", hash = "sha256:f4bcbefc124291925f1a26446da31a5178f9483862233b23c0c96a20701f670c", size = 103424, upload-time = "2026-02-19T05:00:56.027Z" },
]
[[package]]
@@ -1832,7 +1832,7 @@ wheels = [
[[package]]
name = "langbot"
version = "4.9.0"
version = "4.9.1"
source = { editable = "." }
dependencies = [
{ name = "aiocqhttp" },
@@ -1928,7 +1928,7 @@ requires-dist = [
{ name = "botocore", specifier = ">=1.42.39" },
{ name = "certifi", specifier = ">=2025.4.26" },
{ name = "chardet", specifier = ">=5.2.0" },
{ name = "chromadb", specifier = ">=0.4.24" },
{ name = "chromadb", specifier = ">=1.0.0,<2.0.0" },
{ name = "colorlog", specifier = "~=6.6.0" },
{ name = "cryptography", specifier = ">=44.0.3" },
{ name = "dashscope", specifier = ">=1.25.10" },
@@ -1937,7 +1937,7 @@ requires-dist = [
{ name = "ebooklib", specifier = ">=0.18" },
{ name = "gewechat-client", specifier = ">=0.1.5" },
{ name = "html2text", specifier = ">=2024.2.26" },
{ name = "langbot-plugin", specifier = "==0.3.0" },
{ name = "langbot-plugin", specifier = "==0.3.1" },
{ name = "langchain", specifier = ">=0.2.0" },
{ name = "langchain-text-splitters", specifier = ">=0.0.1" },
{ name = "lark-oapi", specifier = ">=1.4.15" },
@@ -1993,7 +1993,7 @@ dev = [
[[package]]
name = "langbot-plugin"
version = "0.3.0"
version = "0.3.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiofiles" },
@@ -2011,28 +2011,28 @@ dependencies = [
{ name = "watchdog" },
{ name = "websockets" },
]
sdist = { url = "https://files.pythonhosted.org/packages/8d/e5/3686b3225e5f2ee6e19a6050bb981b49a91f2450dff83deb5dfba13b3a2a/langbot_plugin-0.3.0.tar.gz", hash = "sha256:9add2d6e81c8cc7281863e4a92a33ed6228dcc0243f4327ac4062edc962dbf98", size = 169751, upload-time = "2026-03-08T09:54:27.102Z" }
sdist = { url = "https://files.pythonhosted.org/packages/4e/ed/b440e26ebc40983abf00dd343338101ada3381065fb3347401ba75f873fe/langbot_plugin-0.3.1.tar.gz", hash = "sha256:0839dcb4cfe689fc670d0ded29b57e6a3f683d8f7326eaa771a5b753675459ac", size = 170285, upload-time = "2026-03-12T15:07:01.918Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/72/51/18f0c1446bcb6712ff3d31d81ea708e3f0e671fde5da69598204a1df977d/langbot_plugin-0.3.0-py3-none-any.whl", hash = "sha256:37bfd3ce507448a6ec4444bec1bc6da1c9911c9df144dfd428febb71122077a6", size = 144096, upload-time = "2026-03-08T09:54:25.581Z" },
{ url = "https://files.pythonhosted.org/packages/13/81/d3c4142911792838b90384a28f7dd1540d0862303293c53ba77e69fc0e15/langbot_plugin-0.3.1-py3-none-any.whl", hash = "sha256:8139796926fe8385b7b546ef865e29b1b8d8e28249e20f3b5417d42d3181ec62", size = 144813, upload-time = "2026-03-12T15:07:03.69Z" },
]
[[package]]
name = "langchain"
version = "1.2.7"
version = "1.2.12"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "langchain-core" },
{ name = "langgraph" },
{ name = "pydantic" },
]
sdist = { url = "https://files.pythonhosted.org/packages/47/f2/478ca9f3455b5d66402066d287eae7e8d6c722acfb8553937e06af708334/langchain-1.2.7.tar.gz", hash = "sha256:ba40e8d5b069a22f7085f54f405973da3d87cfdebf116282e77c692271432ecb", size = 556837, upload-time = "2026-01-23T15:22:10.817Z" }
sdist = { url = "https://files.pythonhosted.org/packages/d8/1d/1af2fc0ac084d4781778b7846b1aed62e05006bf2d73fdf84ac3a8f5225c/langchain-1.2.12.tar.gz", hash = "sha256:ed705b5b293799f7e3e394387f398a1b71707542758283206c8c21415759d991", size = 566444, upload-time = "2026-03-11T22:21:00.712Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/dd/c8/9ce37ae34870834c7d00bb14ff4876b700db31b928635e3307804dc41d74/langchain-1.2.7-py3-none-any.whl", hash = "sha256:1d643c8ca569bcde2470b853807f74f0768b3982d25d66d57db21a166aabda72", size = 108827, upload-time = "2026-01-23T15:22:09.771Z" },
{ url = "https://files.pythonhosted.org/packages/ca/51/09bb1cfb0b57ae9440ca56cc576e4dc792f83d030eef7637d2c516dcb0a0/langchain-1.2.12-py3-none-any.whl", hash = "sha256:60eff184b8f92c2610f5a4c9a97ad339a891adb01901e83e4df8e6c9c69cf852", size = 112373, upload-time = "2026-03-11T22:20:59.508Z" },
]
[[package]]
name = "langchain-core"
version = "1.2.7"
version = "1.2.18"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "jsonpatch" },
@@ -2044,9 +2044,9 @@ dependencies = [
{ name = "typing-extensions" },
{ name = "uuid-utils" },
]
sdist = { url = "https://files.pythonhosted.org/packages/a2/0e/664d8d81b3493e09cbab72448d2f9d693d1fa5aa2bcc488602203a9b6da0/langchain_core-1.2.7.tar.gz", hash = "sha256:e1460639f96c352b4a41c375f25aeb8d16ffc1769499fb1c20503aad59305ced", size = 837039, upload-time = "2026-01-09T17:44:25.505Z" }
sdist = { url = "https://files.pythonhosted.org/packages/18/b7/8bbd0d99a6441b35d891e4b79e7d24c67722cdd363893ae650f24808cf5a/langchain_core-1.2.18.tar.gz", hash = "sha256:ffe53eec44636d092895b9fe25d28af3aaf79060e293fa7cda2a5aaa50c80d21", size = 836725, upload-time = "2026-03-09T20:40:07.229Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/6e/6f/34a9fba14d191a67f7e2ee3dbce3e9b86d2fa7310e2c7f2c713583481bd2/langchain_core-1.2.7-py3-none-any.whl", hash = "sha256:452f4fef7a3d883357b22600788d37e3d8854ef29da345b7ac7099f33c31828b", size = 490232, upload-time = "2026-01-09T17:44:24.236Z" },
{ url = "https://files.pythonhosted.org/packages/1f/d8/9418564ed4ab4f150668b25cf8c188266267d829362e9c9106946afa628b/langchain_core-1.2.18-py3-none-any.whl", hash = "sha256:cccb79523e0045174ab826054e555fddc973266770e427588c8f1ec9d9d6212b", size = 503048, upload-time = "2026-03-09T20:40:06.115Z" },
]
[[package]]
@@ -2063,7 +2063,7 @@ wheels = [
[[package]]
name = "langgraph"
version = "1.0.7"
version = "1.1.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "langchain-core" },
@@ -2073,9 +2073,9 @@ dependencies = [
{ name = "pydantic" },
{ name = "xxhash" },
]
sdist = { url = "https://files.pythonhosted.org/packages/72/5b/f72655717c04e33d3b62f21b166dc063d192b53980e9e3be0e2a117f1c9f/langgraph-1.0.7.tar.gz", hash = "sha256:0cfdfee51e6e8cfe503ecc7367c73933437c505b03fa10a85c710975c8182d9a", size = 497098, upload-time = "2026-01-22T16:57:47.303Z" }
sdist = { url = "https://files.pythonhosted.org/packages/6d/1a/6dbad0c87fb39a58e5ced85297511cc4bcad06cc420b20898eecafece2a2/langgraph-1.1.1.tar.gz", hash = "sha256:cd6282efc657c955b41bff6bd9693de58137ad18f7e7f16b4d17c7d2118d53e1", size = 544040, upload-time = "2026-03-11T22:14:47.845Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/7e/0e/fe80144e3e4048e5d19ccdb91ac547c1a7dc3da8dbd1443e210048194c14/langgraph-1.0.7-py3-none-any.whl", hash = "sha256:9d68e8f8dd8f3de2fec45f9a06de05766d9b075b78fb03171779893b7a52c4d2", size = 157353, upload-time = "2026-01-22T16:57:45.997Z" },
{ url = "https://files.pythonhosted.org/packages/dc/c1/572187bb61a534050ef2d5030e7abe46b19694ec106604fe12ddcb8672c7/langgraph-1.1.1-py3-none-any.whl", hash = "sha256:d0cc8d347131cbfc010e65aad9b0f1afbd0e151f470c288bec1f3df8336c50c6", size = 167502, upload-time = "2026-03-11T22:14:46.121Z" },
]
[[package]]
@@ -2093,15 +2093,15 @@ wheels = [
[[package]]
name = "langgraph-prebuilt"
version = "1.0.7"
version = "1.0.8"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "langchain-core" },
{ name = "langgraph-checkpoint" },
]
sdist = { url = "https://files.pythonhosted.org/packages/a7/59/711aecd1a50999456850dc328f3cad72b4372d8218838d8d5326f80cb76f/langgraph_prebuilt-1.0.7.tar.gz", hash = "sha256:38e097e06de810de4d0e028ffc0e432bb56d1fb417620fb1dfdc76c5e03e4bf9", size = 163692, upload-time = "2026-01-22T16:45:22.801Z" }
sdist = { url = "https://files.pythonhosted.org/packages/0d/06/dd61a5c2dce009d1b03b1d56f2a85b3127659fdddf5b3be5d8f1d60820fb/langgraph_prebuilt-1.0.8.tar.gz", hash = "sha256:0cd3cf5473ced8a6cd687cc5294e08d3de57529d8dd14fdc6ae4899549efcf69", size = 164442, upload-time = "2026-02-19T18:14:39.083Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/47/49/5e37abb3f38a17a3487634abc2a5da87c208cc1d14577eb8d7184b25c886/langgraph_prebuilt-1.0.7-py3-none-any.whl", hash = "sha256:e14923516504405bb5edc3977085bc9622c35476b50c1808544490e13871fe7c", size = 35324, upload-time = "2026-01-22T16:45:21.784Z" },
{ url = "https://files.pythonhosted.org/packages/dc/41/ec966424ad3f2ed3996d24079d3342c8cd6c0bd0653c12b2a917a685ec6c/langgraph_prebuilt-1.0.8-py3-none-any.whl", hash = "sha256:d16a731e591ba4470f3e313a319c7eee7dbc40895bcf15c821f985a3522a7ce0", size = 35648, upload-time = "2026-02-19T18:14:37.611Z" },
]
[[package]]
@@ -5374,6 +5374,12 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/0f/8b/4b61d6e13f7108f36910df9ab4b58fd389cc2520d54d81b88660804aad99/torch-2.10.0-2-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:418997cb02d0a0f1497cf6a09f63166f9f5df9f3e16c8a716ab76a72127c714f", size = 79423467, upload-time = "2026-02-10T21:44:48.711Z" },
{ url = "https://files.pythonhosted.org/packages/d3/54/a2ba279afcca44bbd320d4e73675b282fcee3d81400ea1b53934efca6462/torch-2.10.0-2-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:13ec4add8c3faaed8d13e0574f5cd4a323c11655546f91fbe6afa77b57423574", size = 79498202, upload-time = "2026-02-10T21:44:52.603Z" },
{ url = "https://files.pythonhosted.org/packages/ec/23/2c9fe0c9c27f7f6cb865abcea8a4568f29f00acaeadfc6a37f6801f84cb4/torch-2.10.0-2-cp313-none-macosx_11_0_arm64.whl", hash = "sha256:e521c9f030a3774ed770a9c011751fb47c4d12029a3d6522116e48431f2ff89e", size = 79498254, upload-time = "2026-02-10T21:44:44.095Z" },
{ url = "https://files.pythonhosted.org/packages/36/ab/7b562f1808d3f65414cd80a4f7d4bb00979d9355616c034c171249e1a303/torch-2.10.0-3-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:ac5bdcbb074384c66fa160c15b1ead77839e3fe7ed117d667249afce0acabfac", size = 915518691, upload-time = "2026-03-11T14:15:43.147Z" },
{ url = "https://files.pythonhosted.org/packages/b3/7a/abada41517ce0011775f0f4eacc79659bc9bc6c361e6bfe6f7052a6b9363/torch-2.10.0-3-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:98c01b8bb5e3240426dcde1446eed6f40c778091c8544767ef1168fc663a05a6", size = 915622781, upload-time = "2026-03-11T14:17:11.354Z" },
{ url = "https://files.pythonhosted.org/packages/ab/c6/4dfe238342ffdcec5aef1c96c457548762d33c40b45a1ab7033bb26d2ff2/torch-2.10.0-3-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:80b1b5bfe38eb0e9f5ff09f206dcac0a87aadd084230d4a36eea5ec5232c115b", size = 915627275, upload-time = "2026-03-11T14:16:11.325Z" },
{ url = "https://files.pythonhosted.org/packages/d8/f0/72bf18847f58f877a6a8acf60614b14935e2f156d942483af1ffc081aea0/torch-2.10.0-3-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:46b3574d93a2a8134b3f5475cfb98e2eb46771794c57015f6ad1fb795ec25e49", size = 915523474, upload-time = "2026-03-11T14:17:44.422Z" },
{ url = "https://files.pythonhosted.org/packages/f4/39/590742415c3030551944edc2ddc273ea1fdfe8ffb2780992e824f1ebee98/torch-2.10.0-3-cp314-cp314-manylinux_2_28_x86_64.whl", hash = "sha256:b1d5e2aba4eb7f8e87fbe04f86442887f9167a35f092afe4c237dfcaaef6e328", size = 915632474, upload-time = "2026-03-11T14:15:13.666Z" },
{ url = "https://files.pythonhosted.org/packages/b6/8e/34949484f764dde5b222b7fe3fede43e4a6f0da9d7f8c370bb617d629ee2/torch-2.10.0-3-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:0228d20b06701c05a8f978357f657817a4a63984b0c90745def81c18aedfa591", size = 915523882, upload-time = "2026-03-11T14:14:46.311Z" },
{ url = "https://files.pythonhosted.org/packages/78/89/f5554b13ebd71e05c0b002f95148033e730d3f7067f67423026cc9c69410/torch-2.10.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:3282d9febd1e4e476630a099692b44fdc214ee9bf8ee5377732d9d9dfe5712e4", size = 145992610, upload-time = "2026-01-21T16:25:26.327Z" },
{ url = "https://files.pythonhosted.org/packages/ae/30/a3a2120621bf9c17779b169fc17e3dc29b230c29d0f8222f499f5e159aa8/torch-2.10.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:a2f9edd8dbc99f62bc4dfb78af7bf89499bca3d753423ac1b4e06592e467b763", size = 915607863, upload-time = "2026-01-21T16:25:06.696Z" },
{ url = "https://files.pythonhosted.org/packages/6f/3d/c87b33c5f260a2a8ad68da7147e105f05868c281c63d65ed85aa4da98c66/torch-2.10.0-cp311-cp311-win_amd64.whl", hash = "sha256:29b7009dba4b7a1c960260fc8ac85022c784250af43af9fb0ebafc9883782ebd", size = 113723116, upload-time = "2026-01-21T16:25:21.916Z" },
@@ -5866,14 +5872,14 @@ wheels = [
[[package]]
name = "werkzeug"
version = "3.1.5"
version = "3.1.6"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "markupsafe" },
]
sdist = { url = "https://files.pythonhosted.org/packages/5a/70/1469ef1d3542ae7c2c7b72bd5e3a4e6ee69d7978fa8a3af05a38eca5becf/werkzeug-3.1.5.tar.gz", hash = "sha256:6a548b0e88955dd07ccb25539d7d0cc97417ee9e179677d22c7041c8f078ce67", size = 864754, upload-time = "2026-01-08T17:49:23.247Z" }
sdist = { url = "https://files.pythonhosted.org/packages/61/f1/ee81806690a87dab5f5653c1f146c92bc066d7f4cebc603ef88eb9e13957/werkzeug-3.1.6.tar.gz", hash = "sha256:210c6bede5a420a913956b4791a7f4d6843a43b6fcee4dfa08a65e93007d0d25", size = 864736, upload-time = "2026-02-19T15:17:18.884Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/ad/e4/8d97cca767bcc1be76d16fb76951608305561c6e056811587f36cb1316a8/werkzeug-3.1.5-py3-none-any.whl", hash = "sha256:5111e36e91086ece91f93268bb39b4a35c1e6f1feac762c9c822ded0a4e322dc", size = 225025, upload-time = "2026-01-08T17:49:21.859Z" },
{ url = "https://files.pythonhosted.org/packages/4d/ec/d58832f89ede95652fd01f4f24236af7d32b70cab2196dfcc2d2fd13c5c2/werkzeug-3.1.6-py3-none-any.whl", hash = "sha256:7ddf3357bb9564e407607f988f683d72038551200c704012bb9a4c523d42f131", size = 225166, upload-time = "2026-02-19T15:17:17.475Z" },
]
[[package]]

View File

@@ -102,5 +102,10 @@
"typescript": "^5.8.3",
"typescript-eslint": "^8.31.1"
},
"packageManager": "pnpm@8.9.2+sha512.b9d35fe91b2a5854dadc43034a3e7b2e675fa4b56e20e8e09ef078fa553c18f8aed44051e7b36e8b8dd435f97eb0c44c4ff3b44fc7c6fa7d21e1fac17bbe661e"
}
"packageManager": "pnpm@8.9.2+sha512.b9d35fe91b2a5854dadc43034a3e7b2e675fa4b56e20e8e09ef078fa553c18f8aed44051e7b36e8b8dd435f97eb0c44c4ff3b44fc7c6fa7d21e1fac17bbe661e",
"pnpm": {
"overrides": {
"minimatch": "3.1.3"
}
}
}

34
web/pnpm-lock.yaml generated
View File

@@ -4,6 +4,9 @@ settings:
autoInstallPeers: true
excludeLinksFromLockfile: false
overrides:
minimatch: 3.1.3
dependencies:
'@dnd-kit/core':
specifier: ^6.3.1
@@ -345,7 +348,7 @@ packages:
dependencies:
'@eslint/object-schema': 2.1.7
debug: 4.4.3
minimatch: 3.1.2
minimatch: 3.1.3
transitivePeerDependencies:
- supports-color
dev: true
@@ -375,7 +378,7 @@ packages:
ignore: 5.3.2
import-fresh: 3.3.1
js-yaml: 4.1.1
minimatch: 3.1.2
minimatch: 3.1.3
strip-json-comments: 3.1.1
transitivePeerDependencies:
- supports-color
@@ -2260,7 +2263,7 @@ packages:
'@typescript-eslint/types': 8.54.0
'@typescript-eslint/visitor-keys': 8.54.0
debug: 4.4.3
minimatch: 9.0.5
minimatch: 3.1.3
semver: 7.7.3
tinyglobby: 0.2.15
ts-api-utils: 2.4.0(typescript@5.9.3)
@@ -2678,12 +2681,6 @@ packages:
concat-map: 0.0.1
dev: true
/brace-expansion@2.0.2:
resolution: {integrity: sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==}
dependencies:
balanced-match: 1.0.2
dev: true
/braces@3.0.3:
resolution: {integrity: sha512-yQbXgO/OSZVD2IsiLlro+7Hf6Q18EJrKSEsdoMzKePKXct3gvD8oLcOQdIzGupr5Fj+EDe8gO/lxc1BzfMpxvA==}
engines: {node: '>=8'}
@@ -3345,7 +3342,7 @@ packages:
hasown: 2.0.2
is-core-module: 2.16.1
is-glob: 4.0.3
minimatch: 3.1.2
minimatch: 3.1.3
object.fromentries: 2.0.8
object.groupby: 1.0.3
object.values: 1.2.1
@@ -3376,7 +3373,7 @@ packages:
hasown: 2.0.2
jsx-ast-utils: 3.3.5
language-tags: 1.0.9
minimatch: 3.1.2
minimatch: 3.1.3
object.fromentries: 2.0.8
safe-regex-test: 1.1.0
string.prototype.includes: 2.0.1
@@ -3428,7 +3425,7 @@ packages:
estraverse: 5.3.0
hasown: 2.0.2
jsx-ast-utils: 3.3.5
minimatch: 3.1.2
minimatch: 3.1.3
object.entries: 1.1.9
object.fromentries: 2.0.8
object.values: 1.2.1
@@ -3498,7 +3495,7 @@ packages:
is-glob: 4.0.3
json-stable-stringify-without-jsonify: 1.0.1
lodash.merge: 4.6.2
minimatch: 3.1.2
minimatch: 3.1.3
natural-compare: 1.4.0
optionator: 0.9.4
transitivePeerDependencies:
@@ -5113,19 +5110,12 @@ packages:
engines: {node: '>=18'}
dev: true
/minimatch@3.1.2:
resolution: {integrity: sha512-J7p63hRiAjw1NDEww1W7i37+ByIrOWO5XQQAzZ3VOcL0PNybwpfmV/N05zFAzwQ9USyEcX6t3UO+K5aqBQOIHw==}
/minimatch@3.1.3:
resolution: {integrity: sha512-M2GCs7Vk83NxkUyQV1bkABc4yxgz9kILhHImZiBPAZ9ybuvCb0/H7lEl5XvIg3g+9d4eNotkZA5IWwYl0tibaA==}
dependencies:
brace-expansion: 1.1.12
dev: true
/minimatch@9.0.5:
resolution: {integrity: sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow==}
engines: {node: '>=16 || 14 >=14.17'}
dependencies:
brace-expansion: 2.0.2
dev: true
/minimist@1.2.8:
resolution: {integrity: sha512-2yyAR8qBkN3YuheJanUpWC5U3bb5osDywNB8RzDVlDwDHbocAJveqqj1u8+SVD7jkWT4yvsHCpWqqWqAxb0zCA==}
dev: true

View File

@@ -124,12 +124,6 @@ export default function BotForm({
const currentAdapter = form.watch('adapter');
const currentAdapterConfig = form.watch('adapter_config');
// Serialize adapter_config to a stable string so it can be used as a
// useEffect dependency without triggering on every render. form.watch()
// returns a new object reference each time, which would otherwise cause
// the filtering effect below to loop indefinitely.
const adapterConfigJson = JSON.stringify(currentAdapterConfig);
useEffect(() => {
setBotFormValues();
}, []);
@@ -153,7 +147,7 @@ export default function BotForm({
// For non-Lark adapters, show all fields
setFilteredDynamicFormConfigList(dynamicFormConfigList);
}
}, [currentAdapter, adapterConfigJson, dynamicFormConfigList]);
}, [currentAdapter, currentAdapterConfig, dynamicFormConfigList]);
// 复制到剪贴板的辅助函数 - 使用页面上的真实input元素
const copyToClipboard = () => {

View File

@@ -6,6 +6,7 @@ import { httpClient } from '@/app/infra/http/HttpClient';
import { ScrollArea } from '@/components/ui/scroll-area';
import { Button } from '@/components/ui/button';
import { cn } from '@/lib/utils';
import { Copy, Check } from 'lucide-react';
import {
MessageChainComponent,
Plain,
@@ -27,6 +28,7 @@ interface SessionInfo {
is_active: boolean;
platform?: string | null;
user_id?: string | null;
user_name?: string | null;
}
interface SessionMessage {
@@ -60,8 +62,29 @@ export default function BotSessionMonitor({ botId }: BotSessionMonitorProps) {
const [messages, setMessages] = useState<SessionMessage[]>([]);
const [loadingSessions, setLoadingSessions] = useState(false);
const [loadingMessages, setLoadingMessages] = useState(false);
const [copiedUserId, setCopiedUserId] = useState(false);
const messagesContainerRef = useRef<HTMLDivElement>(null);
const parseSessionType = (sessionId: string): string | null => {
const idx = sessionId.indexOf('_');
if (idx === -1) return null;
const type = sessionId.slice(0, idx);
if (type === 'person' || type === 'group') return type;
return null;
};
const abbreviateId = (id: string): string => {
if (id.length <= 10) return id;
return `${id.slice(0, 4)}..${id.slice(-4)}`;
};
const copyUserId = (userId: string) => {
navigator.clipboard.writeText(userId).then(() => {
setCopiedUserId(true);
setTimeout(() => setCopiedUserId(false), 2000);
});
};
const loadSessions = useCallback(async () => {
setLoadingSessions(true);
try {
@@ -338,24 +361,36 @@ export default function BotSessionMonitor({ botId }: BotSessionMonitorProps) {
>
<div className="flex items-center justify-between mb-0.5">
<span className="text-sm font-medium truncate mr-2">
{session.user_id || session.session_id.slice(0, 12)}
{session.user_name ||
session.user_id ||
session.session_id.slice(0, 12)}
</span>
<span className="text-[11px] text-muted-foreground tabular-nums flex-shrink-0">
{formatRelativeTime(session.last_activity)}
</span>
</div>
<div className="flex items-center gap-1.5 text-xs text-muted-foreground">
{parseSessionType(session.session_id) && (
<span className="px-1 py-0.5 rounded bg-muted text-[10px]">
{parseSessionType(session.session_id)}
</span>
)}
{session.platform && (
<span className="px-1 py-0.5 rounded bg-muted text-[10px]">
{session.platform}
</span>
)}
{session.user_id && (
<span className="truncate text-[10px]">
{abbreviateId(session.user_id)}
</span>
)}
{session.is_active && (
<span className="flex items-center gap-0.5 text-green-600 dark:text-green-400">
<span className="w-1.5 h-1.5 rounded-full bg-green-500 inline-block" />
</span>
)}
<span>{session.pipeline_name}</span>
<span className="truncate">{session.pipeline_name}</span>
</div>
</button>
);
@@ -377,15 +412,42 @@ export default function BotSessionMonitor({ botId }: BotSessionMonitorProps) {
<div className="px-6 py-3 border-b shrink-0 flex items-center justify-between">
<div className="min-w-0">
<div className="text-sm font-medium truncate">
{selectedSession?.user_id || selectedSessionId.slice(0, 20)}
{selectedSession?.user_name ||
selectedSession?.user_id ||
selectedSessionId.slice(0, 20)}
</div>
<div className="flex items-center gap-2 text-xs text-muted-foreground">
{parseSessionType(selectedSessionId) && (
<span>{parseSessionType(selectedSessionId)}</span>
)}
{selectedSession?.platform && (
<span>{selectedSession.platform}</span>
<>
{parseSessionType(selectedSessionId) && <span>·</span>}
<span>{selectedSession.platform}</span>
</>
)}
{selectedSession?.user_id && (
<>
<span>·</span>
<span className="font-mono">
{selectedSession.user_id}
</span>
<button
onClick={() => copyUserId(selectedSession.user_id!)}
className="inline-flex items-center text-muted-foreground hover:text-foreground transition-colors"
title={t('common.copy')}
>
{copiedUserId ? (
<Check className="w-3 h-3 text-green-600" />
) : (
<Copy className="w-3 h-3" />
)}
</button>
</>
)}
{selectedSession?.pipeline_name && (
<>
{selectedSession?.platform && <span>·</span>}
<span>·</span>
<span>{selectedSession.pipeline_name}</span>
</>
)}

View File

@@ -11,7 +11,7 @@ import {
FormMessage,
} from '@/components/ui/form';
import DynamicFormItemComponent from '@/app/home/components/dynamic-form/DynamicFormItemComponent';
import { useCallback, useEffect, useRef } from 'react';
import { useEffect, useRef } from 'react';
import { extractI18nObject } from '@/i18n/I18nProvider';
import { useTranslation } from 'react-i18next';
@@ -73,6 +73,12 @@ export default function DynamicFormComponent({
case 'bot-selector':
fieldSchema = z.string();
break;
case 'model-fallback-selector':
fieldSchema = z.object({
primary: z.string(),
fallbacks: z.array(z.string()),
});
break;
case 'prompt-editor':
fieldSchema = z.array(
z.object({
@@ -160,39 +166,34 @@ export default function DynamicFormComponent({
const onSubmitRef = useRef(onSubmit);
onSubmitRef.current = onSubmit;
// Track the last emitted values to avoid emitting identical snapshots,
// which would cause the parent to call setValue with an equivalent object,
// triggering a re-render loop.
const lastEmittedRef = useRef<string>('');
const emitValues = useCallback(() => {
// 监听表单值变化
useEffect(() => {
// Emit initial form values immediately so the parent always has a valid snapshot,
// even if the user saves without modifying any field.
// form.watch(callback) only fires on subsequent changes, not on mount.
const formValues = form.getValues();
const finalValues = itemConfigList.reduce(
const initialFinalValues = itemConfigList.reduce(
(acc, item) => {
acc[item.name] = formValues[item.name] ?? item.default;
return acc;
},
{} as Record<string, object>,
);
const serialized = JSON.stringify(finalValues);
if (serialized !== lastEmittedRef.current) {
lastEmittedRef.current = serialized;
onSubmitRef.current?.(finalValues);
}
}, [form, itemConfigList]);
// 监听表单值变化
useEffect(() => {
// Emit initial form values immediately so the parent always has a valid snapshot,
// even if the user saves without modifying any field.
// form.watch(callback) only fires on subsequent changes, not on mount.
emitValues();
onSubmitRef.current?.(initialFinalValues);
const subscription = form.watch(() => {
emitValues();
const formValues = form.getValues();
const finalValues = itemConfigList.reduce(
(acc, item) => {
acc[item.name] = formValues[item.name] ?? item.default;
return acc;
},
{} as Record<string, object>,
);
onSubmitRef.current?.(finalValues);
});
return () => subscription.unsubscribe();
}, [form, itemConfigList, emitValues]);
}, [form, itemConfigList]);
return (
<Form {...form}>
@@ -231,6 +232,7 @@ export default function DynamicFormComponent({
// All fields are disabled when editing (creation_settings are immutable)
const isFieldDisabled = !!isEditing;
return (
<FormField
key={config.id}

View File

@@ -124,6 +124,28 @@ export default function DynamicFormItemComponent({
}
}, [config.type]);
useEffect(() => {
if (config.type === DynamicFormItemType.MODEL_FALLBACK_SELECTOR) {
httpClient
.getProviderLLMModels()
.then((resp) => {
let models = resp.models;
if (
systemInfo.disable_models_service ||
userInfo?.account_type !== 'space'
) {
models = models.filter(
(m) => m.provider?.requester !== 'space-chat-completions',
);
}
setLlmModels(models);
})
.catch((err) => {
toast.error('Failed to get LLM model list: ' + err.msg);
});
}
}, [config.type]);
useEffect(() => {
if (
config.type === DynamicFormItemType.KNOWLEDGE_BASE_SELECTOR ||
@@ -171,12 +193,7 @@ export default function DynamicFormItemComponent({
return <Textarea {...field} className="min-h-[120px]" />;
case DynamicFormItemType.BOOLEAN:
return (
<Switch
checked={field.value ?? false}
onCheckedChange={field.onChange}
/>
);
return <Switch checked={field.value} onCheckedChange={field.onChange} />;
case DynamicFormItemType.STRING_ARRAY:
return (
@@ -227,7 +244,7 @@ export default function DynamicFormItemComponent({
case DynamicFormItemType.SELECT:
return (
<Select value={field.value ?? ''} onValueChange={field.onChange}>
<Select value={field.value} onValueChange={field.onChange}>
<SelectTrigger className="bg-[#ffffff] dark:bg-[#2a2a2e]">
<SelectValue placeholder={t('common.select')} />
</SelectTrigger>
@@ -318,6 +335,172 @@ export default function DynamicFormItemComponent({
</Select>
);
case DynamicFormItemType.MODEL_FALLBACK_SELECTOR: {
// Group models by provider
const groupedModelsForFallback = llmModels.reduce(
(acc, model) => {
const providerName =
model.provider?.name || model.provider?.requester || 'Unknown';
if (!acc[providerName]) acc[providerName] = [];
acc[providerName].push(model);
return acc;
},
{} as Record<string, LLMModel[]>,
);
const modelValue = field.value as {
primary: string;
fallbacks: string[];
};
const renderModelSelect = (
value: string,
onChange: (val: string) => void,
placeholder: string,
) => (
<Select value={value} onValueChange={onChange}>
<SelectTrigger className="bg-[#ffffff] dark:bg-[#2a2a2e]">
<SelectValue placeholder={placeholder} />
</SelectTrigger>
<SelectContent>
{Object.entries(groupedModelsForFallback).map(
([providerName, models]) => (
<SelectGroup key={providerName}>
<SelectLabel>{providerName}</SelectLabel>
{models.map((model) => (
<SelectItem key={model.uuid} value={model.uuid}>
<span className="inline-flex items-center gap-1">
{model.name}
{model.abilities?.includes('vision') && (
<Eye className="h-3 w-3 text-muted-foreground" />
)}
{model.abilities?.includes('func_call') && (
<Wrench className="h-3 w-3 text-muted-foreground" />
)}
</span>
</SelectItem>
))}
</SelectGroup>
),
)}
</SelectContent>
</Select>
);
const updateValue = (patch: Partial<typeof modelValue>) => {
field.onChange({ ...modelValue, ...patch });
};
const addFallbackModel = () => {
updateValue({ fallbacks: [...modelValue.fallbacks, ''] });
};
const updateFallbackModel = (index: number, value: string) => {
const updated = [...modelValue.fallbacks];
updated[index] = value;
updateValue({ fallbacks: updated });
};
const removeFallbackModel = (index: number) => {
const updated = [...modelValue.fallbacks];
updated.splice(index, 1);
updateValue({ fallbacks: updated });
};
const moveFallbackModel = (index: number, direction: 'up' | 'down') => {
const updated = [...modelValue.fallbacks];
const newIndex = direction === 'up' ? index - 1 : index + 1;
if (newIndex < 0 || newIndex >= updated.length) return;
[updated[index], updated[newIndex]] = [
updated[newIndex],
updated[index],
];
updateValue({ fallbacks: updated });
};
return (
<div className="space-y-3">
{/* Primary model selector */}
<div>
<p className="text-xs text-muted-foreground mb-1">
{t('models.fallback.primary')}
</p>
{renderModelSelect(
modelValue.primary,
(val) => updateValue({ primary: val }),
t('models.selectModel'),
)}
</div>
{/* Fallback models */}
{modelValue.fallbacks.length > 0 && (
<div className="space-y-2">
<p className="text-xs text-muted-foreground">
{t('models.fallback.fallbackList')}
</p>
{modelValue.fallbacks.map((fbUuid: string, index: number) => (
<div key={index} className="flex items-center gap-2">
<span className="text-xs text-muted-foreground w-4 shrink-0">
{index + 1}.
</span>
<div className="flex-1">
{renderModelSelect(
fbUuid,
(val) => updateFallbackModel(index, val),
t('models.selectModel'),
)}
</div>
<div className="flex gap-1 shrink-0">
<Button
type="button"
variant="ghost"
size="sm"
className="h-8 w-8 p-0"
onClick={() => moveFallbackModel(index, 'up')}
disabled={index === 0}
>
</Button>
<Button
type="button"
variant="ghost"
size="sm"
className="h-8 w-8 p-0"
onClick={() => moveFallbackModel(index, 'down')}
disabled={index === modelValue.fallbacks.length - 1}
>
</Button>
<Button
type="button"
variant="ghost"
size="sm"
className="h-8 w-8 p-0 text-destructive"
onClick={() => removeFallbackModel(index)}
>
<X className="h-4 w-4" />
</Button>
</div>
</div>
))}
</div>
)}
{/* Add fallback button */}
<Button
type="button"
variant="outline"
size="sm"
className="w-full"
onClick={addFallbackModel}
>
<Plus className="h-4 w-4 mr-1" />
{t('models.fallback.addFallback')}
</Button>
</div>
);
}
case DynamicFormItemType.KNOWLEDGE_BASE_SELECTOR:
// Group KBs by Knowledge Engine name
const kbsByEngine = knowledgeBases.reduce(

View File

@@ -463,14 +463,16 @@ export default function ModelsDialog({
)
: t('models.providerCount', { count: otherProviders.length })}
</span>
<Button
size="sm"
variant="outline"
onClick={handleCreateProvider}
>
<Plus className="h-4 w-4 mr-1" />
{t('models.addProvider')}
</Button>
<div className="flex gap-2">
<Button
size="sm"
variant="outline"
onClick={handleCreateProvider}
>
<Plus className="h-4 w-4 mr-1" />
{t('models.addProvider')}
</Button>
</div>
</div>
{/* Provider List */}

View File

@@ -1,4 +1,4 @@
import { useEffect, useState } from 'react';
import { useEffect, useMemo, useState } from 'react';
import Link from 'next/link';
import { useForm } from 'react-hook-form';
import { zodResolver } from '@hookform/resolvers/zod';
@@ -242,11 +242,17 @@ export default function KBForm({
};
// Convert creation schema to dynamic form items (same as ExternalKBForm)
const configFormItems = parseCreationSchema(selectedEngine?.creation_schema);
// Memoize to avoid regenerating UUIDs on every render, which would cause
// DynamicFormComponent's useEffect to re-fire and trigger an infinite loop.
const configFormItems = useMemo(
() => parseCreationSchema(selectedEngine?.creation_schema),
[selectedEngine?.creation_schema],
);
// Convert retrieval schema to dynamic form items
const retrievalFormItems = parseCreationSchema(
selectedEngine?.retrieval_schema,
const retrievalFormItems = useMemo(
() => parseCreationSchema(selectedEngine?.retrieval_schema),
[selectedEngine?.retrieval_schema],
);
// Show loading state

View File

@@ -1,13 +1,6 @@
'use client';
import {
useState,
useEffect,
useCallback,
useRef,
Suspense,
useMemo,
} from 'react';
import { useState, useEffect, useCallback, useRef, Suspense } from 'react';
import { Input } from '@/components/ui/input';
import {
Select,
@@ -70,7 +63,7 @@ function MarketPageContent({
RecommendationList[]
>([]);
const pageSize = 16; // 每页16个4行x4列
const pageSize = 12; // 每页12个
const searchTimeoutRef = useRef<NodeJS.Timeout | null>(null);
const scrollContainerRef = useRef<HTMLDivElement | null>(null);
@@ -330,38 +323,7 @@ function MarketPageContent({
};
}, []);
// 计算所有推荐插件的 ID 集合
const recommendedPluginIds = useMemo(() => {
const ids = new Set<string>();
recommendationLists.forEach((list) => {
list.plugins.forEach((plugin) => {
ids.add(`${plugin.author} / ${plugin.name}`);
});
});
return ids;
}, [recommendationLists]);
// 过滤掉已在推荐列表中展示的插件
// 仅在显示推荐列表的条件下(无搜索、无筛选、第一页或后续页的累积数据中)进行过滤
// 注意:如果用户翻页,我们希望一直保持去重,否则推荐过的插件会在第二页出现
// 但是推荐列表只在第一页且无筛选时显示。
// 如果用户进行了筛选/搜索,推荐列表不显示,此时不需要去重。
const visiblePlugins = useMemo(() => {
const showRecommendations =
!searchQuery && componentFilter === 'all' && selectedTags.length === 0;
if (!showRecommendations) {
return plugins;
}
return plugins.filter((p) => !recommendedPluginIds.has(p.pluginId));
}, [
plugins,
recommendedPluginIds,
searchQuery,
componentFilter,
selectedTags,
]);
const visiblePlugins = plugins;
// 加载更多
const loadMore = useCallback(() => {

View File

@@ -47,10 +47,12 @@ function RecommendationListRow({
list,
tagNames,
onInstall,
isLast,
}: {
list: RecommendationList;
tagNames: Record<string, string>;
onInstall: (author: string, pluginName: string) => void;
isLast: boolean;
}) {
const { t } = useTranslation();
const [page, setPage] = useState(0);
@@ -143,7 +145,9 @@ function RecommendationListRow({
/>
))}
</div>
{totalPages > 1 && <div className="border-b border-border mt-6" />}
{totalPages > 1 && !isLast && (
<div className="border-b border-border mt-6" />
)}
</div>
);
}
@@ -161,12 +165,13 @@ export function RecommendationLists({
return (
<div className="mt-6">
{lists.map((list) => (
{lists.map((list, index) => (
<RecommendationListRow
key={list.uuid}
list={list}
tagNames={tagNames}
onInstall={onInstall}
isLast={index === lists.length - 1}
/>
))}
<div className="border-b border-border mb-6" />

View File

@@ -17,7 +17,7 @@ import {
FileText,
Info,
} from 'lucide-react';
import { useState } from 'react';
import { useState, useRef, useEffect } from 'react';
import { Button } from '@/components/ui/button';
export default function PluginMarketCardComponent({
@@ -31,6 +31,43 @@ export default function PluginMarketCardComponent({
}) {
const { t } = useTranslation();
const [isHovered, setIsHovered] = useState(false);
const bottomRef = useRef<HTMLDivElement>(null);
const [visibleTags, setVisibleTags] = useState(2);
// Measure how many tags fit in the bottom row
useEffect(() => {
const tags = cardVO.tags;
if (!bottomRef.current || !tags || tags.length === 0) return;
const measure = () => {
const container = bottomRef.current;
if (!container) return;
const width = container.offsetWidth;
const availableForTags = width - 140 - 80;
if (availableForTags <= 0) {
setVisibleTags(0);
return;
}
const tagWidth = 80;
const plusBadgeWidth = 40;
const maxTags = Math.max(
0,
Math.floor((availableForTags - plusBadgeWidth) / tagWidth),
);
if (maxTags >= tags.length) {
setVisibleTags(tags.length);
} else {
setVisibleTags(Math.max(1, maxTags));
}
};
measure();
const observer = new ResizeObserver(measure);
observer.observe(bottomRef.current);
return () => observer.disconnect();
}, [cardVO.tags]);
const remainingTags = cardVO.tags ? cardVO.tags.length - visibleTags : 0;
function handleInstallClick(e: React.MouseEvent) {
e.stopPropagation();
@@ -135,10 +172,13 @@ export default function PluginMarketCardComponent({
</div>
{/* 下部分:下载量、标签和组件列表 */}
<div className="w-full flex flex-row items-center justify-between gap-2 px-0 sm:px-[0.4rem] flex-shrink-0">
<div className="flex flex-row items-center justify-start gap-2 flex-wrap">
<div
ref={bottomRef}
className="w-full flex flex-row items-center justify-between gap-2 px-0 sm:px-[0.4rem] flex-shrink-0 overflow-hidden"
>
<div className="flex flex-row items-center justify-start gap-2 min-w-0 overflow-hidden">
{/* 下载数量 */}
<div className="flex flex-row items-center gap-[0.3rem] sm:gap-[0.4rem]">
<div className="flex flex-row items-center gap-[0.3rem] sm:gap-[0.4rem] flex-shrink-0">
<svg
className="w-4 h-4 sm:w-[1.2rem] sm:h-[1.2rem] text-[#2563eb] dark:text-[#5b8def] flex-shrink-0"
xmlns="http://www.w3.org/2000/svg"
@@ -156,14 +196,14 @@ export default function PluginMarketCardComponent({
</div>
</div>
{/* Tags */}
{cardVO.tags && cardVO.tags.length > 0 && (
<div className="flex flex-wrap gap-1.5">
{cardVO.tags.slice(0, 2).map((tag) => (
{/* Tags - adaptive */}
{cardVO.tags && cardVO.tags.length > 0 && visibleTags > 0 && (
<div className="flex flex-row items-center gap-1.5 overflow-hidden flex-shrink min-w-0">
{cardVO.tags.slice(0, visibleTags).map((tag) => (
<Badge
key={tag}
variant="secondary"
className="text-[0.65rem] sm:text-[0.7rem] px-2 py-0.5 h-5 flex items-center gap-1 flex-shrink-0"
className="text-[0.65rem] sm:text-[0.7rem] px-2 py-0.5 h-5 flex items-center gap-1 flex-shrink-0 whitespace-nowrap"
>
<svg
className="w-2.5 h-2.5 flex-shrink-0"
@@ -178,15 +218,17 @@ export default function PluginMarketCardComponent({
<path d="M20.59 13.41l-7.17 7.17a2 2 0 0 1-2.83 0L2 12V2h10l8.59 8.59a2 2 0 0 1 0 2.82z" />
<line x1="7" y1="7" x2="7.01" y2="7" />
</svg>
<span className="truncate">{tagNames[tag] || tag}</span>
<span className="truncate max-w-[5rem]">
{tagNames[tag] || tag}
</span>
</Badge>
))}
{cardVO.tags.length > 2 && (
{remainingTags > 0 && (
<Badge
variant="outline"
className="text-[0.65rem] sm:text-[0.7rem] px-2 py-0.5 h-5 flex items-center flex-shrink-0"
className="text-[0.65rem] sm:text-[0.7rem] px-1.5 py-0.5 h-5 flex items-center flex-shrink-0 whitespace-nowrap"
>
+{cardVO.tags.length - 2}
+{remainingTags}
</Badge>
)}
</div>

View File

@@ -35,6 +35,7 @@ export enum DynamicFormItemType {
SELECT = 'select',
LLM_MODEL_SELECTOR = 'llm-model-selector',
EMBEDDING_MODEL_SELECTOR = 'embedding-model-selector',
MODEL_FALLBACK_SELECTOR = 'model-fallback-selector',
PROMPT_EDITOR = 'prompt-editor',
UNKNOWN = 'unknown',
KNOWLEDGE_BASE_SELECTOR = 'knowledge-base-selector',

View File

@@ -356,6 +356,7 @@ export class BackendClient extends BaseHttpClient {
is_active: boolean;
platform: string | null;
user_id: string | null;
user_name: string | null;
}>;
total: number;
}> {
@@ -384,6 +385,7 @@ export class BackendClient extends BaseHttpClient {
level: string;
platform: string | null;
user_id: string | null;
user_name: string | null;
runner_name: string | null;
variables: string | null;
role: string | null;

View File

@@ -284,6 +284,27 @@ export default function Login() {
</form>
</Form>
)}
<p className="text-xs text-center text-muted-foreground">
{t('common.agreementNotice')}{' '}
<a
href="https://langbot.app/privacy"
target="_blank"
rel="noopener noreferrer"
className="underline hover:text-foreground transition-colors"
>
{t('common.privacyPolicy')}
</a>{' '}
{t('common.and')}{' '}
<a
href={t('common.dataCollectionPolicyUrl')}
target="_blank"
rel="noopener noreferrer"
className="underline hover:text-foreground transition-colors"
>
{t('common.dataCollectionPolicy')}
</a>
</p>
</CardContent>
</Card>
</div>

View File

@@ -253,6 +253,27 @@ export default function Register() {
</Button>
</form>
</Form>
<p className="text-xs text-center text-muted-foreground">
{t('common.agreementNotice')}{' '}
<a
href="https://langbot.app/privacy"
target="_blank"
rel="noopener noreferrer"
className="underline hover:text-foreground transition-colors"
>
{t('common.privacyPolicy')}
</a>{' '}
{t('common.and')}{' '}
<a
href={t('common.dataCollectionPolicyUrl')}
target="_blank"
rel="noopener noreferrer"
className="underline hover:text-foreground transition-colors"
>
{t('common.dataCollectionPolicy')}
</a>
</p>
</CardContent>
</Card>
</div>

View File

@@ -47,6 +47,12 @@ const enUS = {
copyFailed: 'Copy Failed',
test: 'Test',
forgotPassword: 'Forgot Password?',
agreementNotice: 'By continuing, you agree to our',
privacyPolicy: 'Privacy Policy',
and: 'and',
dataCollectionPolicy: 'Data Collection Policy',
dataCollectionPolicyUrl:
'https://docs.langbot.app/en/insight/data-collection-policy',
loading: 'Loading...',
fieldRequired: 'This field is required',
or: 'or',
@@ -230,6 +236,11 @@ const enUS = {
modelsCount: '{{count}} model(s)',
expandModels: 'Expand',
collapseModels: 'Collapse',
fallback: {
primary: 'Primary Model',
fallbackList: 'Fallback Models',
addFallback: 'Add Fallback Model',
},
},
bots: {
title: 'Bots',

View File

@@ -1,4 +1,4 @@
const jaJP = {
const jaJP = {
common: {
login: 'ログイン',
logout: 'ログアウト',
@@ -48,6 +48,12 @@ const jaJP = {
copyFailed: 'コピーに失敗しました',
test: 'テスト',
forgotPassword: 'パスワードを忘れた?',
agreementNotice: '続行することで、以下に同意したものとみなされます:',
privacyPolicy: 'プライバシーポリシー',
and: 'および',
dataCollectionPolicy: 'データ収集ポリシー',
dataCollectionPolicyUrl:
'https://docs.langbot.app/ja/insight/data-collection-policy',
loading: '読み込み中...',
fieldRequired: 'この項目は必須です',
or: 'または',
@@ -235,6 +241,11 @@ const jaJP = {
modelsCount: '{{count}} 個のモデル',
expandModels: '展開',
collapseModels: '折りたたむ',
fallback: {
primary: 'プライマリモデル',
fallbackList: 'フォールバックモデル',
addFallback: 'フォールバックモデルを追加',
},
},
bots: {
title: 'ボット',

View File

@@ -47,6 +47,12 @@ const zhHans = {
copyFailed: '复制失败',
test: '测试',
forgotPassword: '忘记密码?',
agreementNotice: '继续即表示您同意我们的',
privacyPolicy: '隐私政策',
and: '和',
dataCollectionPolicy: '数据收集政策',
dataCollectionPolicyUrl:
'https://docs.langbot.app/zh/insight/data-collection-policy',
loading: '加载中...',
fieldRequired: '此字段为必填项',
or: '或',
@@ -221,6 +227,11 @@ const zhHans = {
modelsCount: '{{count}} 个模型',
expandModels: '展开',
collapseModels: '收起',
fallback: {
primary: '主模型',
fallbackList: '备用模型',
addFallback: '添加备用模型',
},
},
bots: {
title: '机器人',

View File

@@ -47,6 +47,12 @@ const zhHant = {
copyFailed: '複製失敗',
test: '測試',
forgotPassword: '忘記密碼?',
agreementNotice: '繼續即表示您同意我們的',
privacyPolicy: '隱私政策',
and: '和',
dataCollectionPolicy: '數據收集政策',
dataCollectionPolicyUrl:
'https://docs.langbot.app/zh/insight/data-collection-policy',
loading: '載入中...',
fieldRequired: '此欄位為必填',
or: '或',
@@ -220,6 +226,11 @@ const zhHant = {
modelsCount: '{{count}} 個模型',
expandModels: '展開',
collapseModels: '收起',
fallback: {
primary: '主模型',
fallbackList: '備用模型',
addFallback: '新增備用模型',
},
},
bots: {
title: '機器人',