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36 Commits

Author SHA1 Message Date
fdc310
60579f7b3a refactor(gewechat): remove redundant set_webhook_url and login logic
Remove the unnecessary set_webhook_url method and its caller in botmgr,
instead inject webhook_prefix via adapter config for self-assembly.
Remove login logic from run_async since login is handled elsewhere.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-22 06:15:16 +08:00
fdc310
c4d4c90930 fix: add set_webhook_url call in botmgr for auto callback URL
Pass webhook_full_url to adapters that implement set_webhook_url(),
built from api.webhook_prefix config + bot_uuid.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-22 05:57:32 +08:00
fdc310
1a3ef217d9 fix: resolve pydantic init error and auto-generate webhook callback URL
- Fix AttributeError by removing self.config assignment before super().__init__()
- Remove callback_base_url from adapter config (no longer needed)
- Add set_webhook_url() method, called by botmgr with auto-built URL
- Add gewechat to webhook URL display list in bot.py
- botmgr now passes webhook_prefix + bot_uuid to adapters via set_webhook_url()

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-22 05:52:50 +08:00
fdc310
6e9fcccd7d feat: migrate gewechat adapter to unified webhook architecture
Move gewechat adapter from legacy (self-hosted Quart server) to the
unified webhook entry point at /api/bots/{bot_uuid}. This removes the
need for a dedicated port and aligns with the modern adapter pattern.

Key changes:
- Add set_bot_uuid() and handle_unified_webhook() methods
- Remove self-hosted Quart server from run_async()
- Auto-generate callback URL from callback_base_url + bot_uuid
- Update constructor signature to (config, logger)
- Rename legacy gewechat.yaml to prevent name conflict

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-22 04:59:29 +08:00
RockChinQ
865f6ee81b style: format telegram.py for ruff 2026-03-21 22:10:23 +08:00
fdc310
bd5ec59b7c fix:The fix is in place — content = '' is now reset at the start of each loop iteration , which prevents stale text from being duplicated across tool call and end-turn chunks. (#2060) 2026-03-21 22:08:35 +08:00
fdc310
9c0cc1003d Fixed the issue where the at bot did not remove the at symbol, result… (#2062)
* Fixed the issue where the at bot did not remove the at symbol, resulting in some commands not being activated in group chats. Also, adjusted the logic in the on_message section.

* fix:reply_message  del bot_name
2026-03-21 22:07:31 +08:00
Bijin
ea07d8ad00 fix(telegram): add document message support (docx/pdf/etc) (#2069)
The Telegram adapter only handles TEXT, COMMAND, PHOTO, and VOICE
messages. Document files (docx, pdf, etc.) sent by users are silently
dropped because:

1. MessageHandler filters lack filters.Document.ALL
2. target2yiri() has no message.document branch
3. yiri2target() has no platform_message.File branch
4. send_message() has no 'document' component handler

Changes:
- Add filters.Document.ALL to the MessageHandler filter set
- Add message.document parsing in target2yiri() → platform_message.File
- Add platform_message.File handling in yiri2target() → document component
- Add 'document' type handling in send_message() via bot.send_document()

This allows Telegram document messages to flow through the existing
PreProcessor and Dify file upload pipeline, consistent with how other
adapters (Lark, KOOK, Discord, WeCom) already handle files.

Closes #2065
2026-03-21 22:06:54 +08:00
youhuanghe
3ac3fad4bc chore: upgrade plugin sdk to 0.3.3 2026-03-19 12:48:29 +00:00
youhuanghe
254a13bba3 fix: 4355f0fa78 ruff lint 2026-03-16 06:39:29 +00:00
youhuanghe
4355f0fa78 feat(rag): expose vector listing API with backend filter support 2026-03-16 06:26:05 +00:00
Junyan Qin
031737f05d chore: remove all preset sensitive words 2026-03-16 13:42:19 +08:00
Nody the lobster
9e366fc536 fix: allow env overrides to create missing config keys (#2064)
Previously, environment variable overrides (e.g. SYSTEM__INSTANCE_ID)
were silently skipped if the target key didn't already exist in
data/config.yaml. This caused SaaS pods running older LangBot images
(whose config template lacked system.instance_id) to ignore the
SYSTEM__INSTANCE_ID env var, falling back to a random UUID that
didn't match the pod UUID — breaking idle timeout tracking.

Now env overrides create missing keys (as strings) and missing
intermediate dicts, so they work regardless of template version.

Co-authored-by: rocksclawbot <rocksclawbot@users.noreply.github.com>
2026-03-15 23:03:40 +08:00
youhuanghe
8bd6442965 chore: upgrade plugin sdk to 0.3.2 2026-03-14 12:56:54 +00:00
Junyan Qin
1a1eadb282 chore: bump version 4.9.3 2026-03-14 20:20:48 +08:00
Nody the lobster
eed72b1c12 fix: show error message on login page when backend is unreachable (#2063) 2026-03-14 19:20:01 +08:00
RockChinQ
351350ea03 fix: instance_id priority: config.yaml > file > generate new
- If system.instance_id set in config (via env var), use it
- If not set but file exists, read from file (don't generate new)
- If neither, generate new and save to file
2026-03-13 11:33:32 -04:00
RockChinQ
bc3d6ba92f feat: support instance_id in system config
Add instance_id field to system section in config.yaml.
Can be set via SYSTEM__INSTANCE_ID env var (auto-mapped).
Falls back to data/labels/instance_id.json if not set.
2026-03-13 11:31:51 -04:00
RockChinQ
345e4baf2a Revert "feat: support pre-setting instance_id via LANGBOT__INSTANCE_ID env var"
This reverts commit 6c64dc057f.
2026-03-13 11:30:36 -04:00
RockChinQ
6c64dc057f feat: support pre-setting instance_id via LANGBOT__INSTANCE_ID env var
In SaaS (cloud edition), the instance_id can now be injected via
environment variable to match the pod UUID. This enables zero-lookup
telemetry routing in Space - no need to reverse-lookup instance_id
to find the pod.
2026-03-13 11:26:16 -04:00
youhuanghe
eec0a9c9d9 feat(plugin): expose KB UUIDs in query variables and pass session context to retrieve API
Extract knowledge base UUID list into query.variables['_knowledge_base_uuids']
in PreProcessor so plugins can modify it during PromptPreProcessing. Runner now
reads from variables instead of pipeline_config. Also pass session_name,
bot_uuid, and sender_id to kb.retrieve() in the RETRIEVE_KNOWLEDGE_BASE handler
so knowledge engines receive proper session context.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-13 14:23:19 +00:00
Junyan Qin
6896a55485 fix: bot form error 2026-03-13 12:26:45 +08:00
Junyan Qin
4b0fad233e chore: bump version 4.9.2 2026-03-13 12:15:21 +08:00
Junyan Qin
52eb991a70 feat: add extra webhook prefix config 2026-03-13 12:06:22 +08:00
Junyan Qin
10c716be0c fix: bad model field ref 2026-03-13 11:47:31 +08:00
youhuanghe
6e77351eda refactor: up rag ingest timeout 2026-03-13 02:37:32 +00:00
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
59 changed files with 3738 additions and 1061 deletions

View File

@@ -1,6 +1,6 @@
[project]
name = "langbot"
version = "4.9.0"
version = "4.9.3"
description = "Production-grade platform for building agentic IM bots"
readme = "README.md"
license-files = ["LICENSE"]
@@ -64,7 +64,7 @@ dependencies = [
"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==0.3.3",
"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__ = '4.9.3'

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

@@ -4,7 +4,6 @@ import base64
import binascii
import httpx
import traceback
from urllib.parse import quote
from quart import Quart
import xml.etree.ElementTree as ET
from typing import Callable, Dict, Any
@@ -68,31 +67,6 @@ class WecomClient:
await self.logger.error(f'获取accesstoken失败:{response.json()}')
raise Exception(f'未获取access token: {data}')
async def get_user_info(self, userid: str) -> dict:
"""
Get user information by user ID using the application secret.
Args:
userid: The user ID to look up.
Returns:
dict: User information including 'name' field.
"""
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/user/get?access_token=' + self.access_token + '&userid=' + quote(userid)
async with httpx.AsyncClient() as client:
response = await client.get(url)
data = response.json()
if data.get('errcode') == 40014 or data.get('errcode') == 42001:
self.access_token = await self.get_access_token(self.secret)
return await self.get_user_info(userid)
if data.get('errcode', 0) != 0:
await self.logger.error(f'获取用户信息失败:{data}')
return {}
return data
async def get_users(self):
if not self.check_access_token_for_contacts():
self.access_token_for_contacts = await self.get_access_token(self.secret_for_contacts)

View File

@@ -68,14 +68,20 @@ class BotService:
'wecomcs',
'LINE',
'lark',
'gewechat',
]:
webhook_prefix = self.ap.instance_config.data['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
extra_webhook_prefix = self.ap.instance_config.data['api'].get('extra_webhook_prefix', '')
webhook_url = f'/bots/{bot_uuid}'
adapter_runtime_values['webhook_url'] = webhook_url
adapter_runtime_values['webhook_full_url'] = f'{webhook_prefix}{webhook_url}'
adapter_runtime_values['extra_webhook_full_url'] = (
f'{extra_webhook_prefix}{webhook_url}' if extra_webhook_prefix else ''
)
else:
adapter_runtime_values['webhook_url'] = None
adapter_runtime_values['webhook_full_url'] = None
adapter_runtime_values['extra_webhook_full_url'] = None
persistence_bot['adapter_runtime_values'] = adapter_runtime_values

View File

@@ -105,11 +105,16 @@ class LLMModelsService:
)
)
pipeline = result.first()
if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
pipeline_config = pipeline.config
pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
pipeline_data = {'config': pipeline_config}
await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
if pipeline is not None:
model_config = pipeline.config.get('ai', {}).get('local-agent', {}).get('model', {})
if not model_config.get('primary', ''):
pipeline_config = pipeline.config
pipeline_config['ai']['local-agent']['model'] = {
'primary': model_data['uuid'],
'fallbacks': [],
}
pipeline_data = {'config': pipeline_config}
await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
return model_data['uuid']

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

@@ -74,20 +74,26 @@ def _apply_env_overrides_to_config(cfg: dict) -> dict:
current = cfg
for i, key in enumerate(keys):
if not isinstance(current, dict) or key not in current:
if not isinstance(current, dict):
break
if i == len(keys) - 1:
# At the final key - check if it's a scalar value
if isinstance(current[key], (dict, list)):
# Skip dict and list types
pass
# At the final key
if key in current:
if isinstance(current[key], (dict, list)):
# Skip dict and list types
pass
else:
# Valid scalar value - convert and set it
converted_value = convert_value(env_value, current[key])
current[key] = converted_value
else:
# Valid scalar value - convert and set it
converted_value = convert_value(env_value, current[key])
current[key] = converted_value
# Key doesn't exist yet - create it as string
current[key] = env_value
else:
# Navigate deeper
# Navigate deeper - create intermediate dict if needed
if key not in current:
current[key] = {}
current = current[key]
return cfg
@@ -146,16 +152,50 @@ class LoadConfigStage(stage.BootingStage):
await ap.instance_config.dump_config()
# load or generate instance id
ap.instance_id = await config.load_json_config(
'data/labels/instance_id.json',
template_data={
'instance_id': f'instance_{str(uuid.uuid4())}',
'instance_create_ts': int(time.time()),
},
completion=False,
)
# Priority:
# 1. system.instance_id from config.yaml (can be set via SYSTEM__INSTANCE_ID env var)
# 2. data/labels/instance_id.json (if file exists)
# 3. Generate new and save to file
config_instance_id = ap.instance_config.data.get('system', {}).get('instance_id', '')
constants.instance_id = ap.instance_id.data['instance_id']
if config_instance_id:
# Use the instance_id from config.yaml
constants.instance_id = config_instance_id
# Still load/create the file for backward compat, but don't use its value
ap.instance_id = await config.load_json_config(
'data/labels/instance_id.json',
template_data={
'instance_id': f'instance_{str(uuid.uuid4())}',
'instance_create_ts': int(time.time()),
},
completion=False,
)
else:
# Try loading file-based instance id
instance_id_path = os.path.join('data', 'labels', 'instance_id.json')
if os.path.exists(instance_id_path):
# File exists, read it
ap.instance_id = await config.load_json_config(
'data/labels/instance_id.json',
template_data={
'instance_id': '',
'instance_create_ts': 0,
},
completion=False,
)
constants.instance_id = ap.instance_id.data['instance_id']
else:
# Neither config nor file, generate new and save to file
new_id = f'instance_{str(uuid.uuid4())}'
ap.instance_id = await config.load_json_config(
'data/labels/instance_id.json',
template_data={
'instance_id': new_id,
'instance_create_ts': int(time.time()),
},
completion=False,
)
constants.instance_id = new_id
constants.edition = ap.instance_config.data.get('system', {}).get('edition', 'community')
print(f'LangBot instance id: {constants.instance_id}')

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

@@ -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):
@@ -149,6 +176,16 @@ class PreProcessor(stage.PipelineStage):
query.variables['user_message_text'] = plain_text
query.user_message = provider_message.Message(role='user', content=content_list)
# Extract knowledge base UUIDs into query variables so plugins can modify them
# during PromptPreProcessing before the runner performs retrieval.
kb_uuids = query.pipeline_config['ai']['local-agent'].get('knowledge-bases', [])
if not kb_uuids:
old_kb_uuid = query.pipeline_config['ai']['local-agent'].get('knowledge-base', '')
if old_kb_uuid and old_kb_uuid != '__none__':
kb_uuids = [old_kb_uuid]
query.variables['_knowledge_base_uuids'] = list(kb_uuids)
# =========== 触发事件 PromptPreProcessing
event = events.PromptPreProcessing(

View File

@@ -272,6 +272,9 @@ class PlatformManager:
# 如果 adapter 支持 set_bot_uuid 方法,设置 bot_uuid用于统一 webhook
if hasattr(adapter_inst, 'set_bot_uuid'):
adapter_inst.set_bot_uuid(bot_entity.uuid)
adapter_inst.config['_webhook_prefix'] = self.ap.instance_config.data['api'].get(
'webhook_prefix', 'http://127.0.0.1:5300'
)
runtime_bot = RuntimeBot(ap=self.ap, bot_entity=bot_entity, adapter=adapter_inst, logger=logger)

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@@ -0,0 +1,609 @@
import gewechat_client
import typing
import asyncio
import traceback
import re
import copy
import threading
from langbot.pkg.utils import httpclient
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
import langbot_plugin.api.entities.builtin.platform.message as platform_message
import langbot_plugin.api.entities.builtin.platform.events as platform_events
import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
from ...utils import image
import xml.etree.ElementTree as ET
from typing import Optional, Tuple
from functools import partial
from ..logger import EventLogger
class GewechatMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
def __init__(self, config: dict):
self.config = config
@staticmethod
async def yiri2target(message_chain: platform_message.MessageChain) -> list[dict]:
content_list = []
for component in message_chain:
if isinstance(component, platform_message.At):
content_list.append({'type': 'at', 'target': component.target})
elif isinstance(component, platform_message.Plain):
content_list.append({'type': 'text', 'content': component.text})
elif isinstance(component, platform_message.Image):
if not component.url:
pass
content_list.append({'type': 'image', 'image': component.url})
elif isinstance(component, platform_message.Voice):
content_list.append({'type': 'voice', 'url': component.url, 'length': component.length})
elif isinstance(component, platform_message.Forward):
for node in component.node_list:
content_list.extend(await GewechatMessageConverter.yiri2target(node.message_chain))
content_list.append({'type': 'image', 'image': component.url})
elif isinstance(component, platform_message.WeChatMiniPrograms):
content_list.append(
{
'type': 'WeChatMiniPrograms',
'mini_app_id': component.mini_app_id,
'display_name': component.display_name,
'page_path': component.page_path,
'cover_img_url': component.image_url,
'title': component.title,
'user_name': component.user_name,
}
)
elif isinstance(component, platform_message.WeChatForwardMiniPrograms):
content_list.append(
{
'type': 'WeChatForwardMiniPrograms',
'xml_data': component.xml_data,
'image_url': component.image_url,
}
)
elif isinstance(component, platform_message.WeChatEmoji):
content_list.append(
{
'type': 'WeChatEmoji',
'emoji_md5': component.emoji_md5,
'emoji_size': component.emoji_size,
}
)
elif isinstance(component, platform_message.WeChatLink):
content_list.append(
{
'type': 'WeChatLink',
'link_title': component.link_title,
'link_desc': component.link_desc,
'link_thumb_url': component.link_thumb_url,
'link_url': component.link_url,
}
)
elif isinstance(component, platform_message.WeChatForwardLink):
content_list.append({'type': 'WeChatForwardLink', 'xml_data': component.xml_data})
elif isinstance(component, platform_message.WeChatForwardImage):
content_list.append({'type': 'WeChatForwardImage', 'xml_data': component.xml_data})
elif isinstance(component, platform_message.WeChatForwardFile):
content_list.append({'type': 'WeChatForwardFile', 'xml_data': component.xml_data})
elif isinstance(component, platform_message.WeChatAppMsg):
content_list.append({'type': 'WeChatAppMsg', 'app_msg': component.app_msg})
elif isinstance(component, platform_message.WeChatForwardQuote):
content_list.append({'type': 'WeChatAppMsg', 'app_msg': component.app_msg})
elif isinstance(component, platform_message.Forward):
for node in component.node_list:
if node.message_chain:
content_list.extend(await GewechatMessageConverter.yiri2target(node.message_chain))
return content_list
async def target2yiri(self, message: dict, bot_account_id: str) -> platform_message.MessageChain:
message_list = []
ats_bot = False
content = message['Data']['Content']['string']
content_no_preifx = content
is_group_message = self._is_group_message(message)
if is_group_message:
ats_bot = self._ats_bot(message, bot_account_id)
if '@所有人' in content:
message_list.append(platform_message.AtAll())
elif ats_bot:
message_list.append(platform_message.At(target=bot_account_id))
content_no_preifx, _ = self._extract_content_and_sender(content)
msg_type = message['Data']['MsgType']
handler_map = {
1: self._handler_text,
3: self._handler_image,
34: self._handler_voice,
49: self._handler_compound,
}
handler = handler_map.get(msg_type, self._handler_default)
handler_result = await handler(
message=message,
content_no_preifx=content_no_preifx,
)
if handler_result and len(handler_result) > 0:
message_list.extend(handler_result)
return platform_message.MessageChain(message_list)
async def _handler_text(self, message: Optional[dict], content_no_preifx: str) -> platform_message.MessageChain:
if message and self._is_group_message(message):
pattern = r'@\S{1,20}'
content_no_preifx = re.sub(pattern, '', content_no_preifx)
return platform_message.MessageChain([platform_message.Plain(content_no_preifx)])
async def _handler_image(self, message: Optional[dict], content_no_preifx: str) -> platform_message.MessageChain:
try:
image_xml = content_no_preifx
if not image_xml:
return platform_message.MessageChain([platform_message.Unknown('[图片内容为空]')])
base64_str, image_format = await image.get_gewechat_image_base64(
gewechat_url=self.config['gewechat_url'],
gewechat_file_url=self.config['gewechat_file_url'],
app_id=self.config['app_id'],
xml_content=image_xml,
token=self.config['token'],
image_type=2,
)
elements = [
platform_message.Image(base64=f'data:image/{image_format};base64,{base64_str}'),
platform_message.WeChatForwardImage(xml_data=image_xml),
]
return platform_message.MessageChain(elements)
except Exception as e:
print(f'处理图片失败: {str(e)}')
return platform_message.MessageChain([platform_message.Unknown('[图片处理失败]')])
async def _handler_voice(self, message: Optional[dict], content_no_preifx: str) -> platform_message.MessageChain:
message_List = []
try:
audio_base64 = message['Data']['ImgBuf']['buffer']
if not audio_base64:
message_List.append(platform_message.Unknown(text='[语音内容为空]'))
return platform_message.MessageChain(message_List)
voice_element = platform_message.Voice(base64=f'data:audio/silk;base64,{audio_base64}')
message_List.append(voice_element)
except KeyError as e:
print(f'语音数据字段缺失: {str(e)}')
message_List.append(platform_message.Unknown(text='[语音数据解析失败]'))
except Exception as e:
print(f'处理语音消息异常: {str(e)}')
message_List.append(platform_message.Unknown(text='[语音处理失败]'))
return platform_message.MessageChain(message_List)
async def _handler_compound(self, message: Optional[dict], content_no_preifx: str) -> platform_message.MessageChain:
try:
xml_data = ET.fromstring(content_no_preifx)
appmsg_data = xml_data.find('.//appmsg')
if appmsg_data:
data_type = appmsg_data.findtext('.//type', '')
sub_handler_map = {
'57': self._handler_compound_quote,
'5': self._handler_compound_link,
'6': self._handler_compound_file,
'33': self._handler_compound_mini_program,
'36': self._handler_compound_mini_program,
'2000': partial(self._handler_compound_unsupported, text='[转账消息]'),
'2001': partial(self._handler_compound_unsupported, text='[红包消息]'),
'51': partial(self._handler_compound_unsupported, text='[视频号消息]'),
}
handler = sub_handler_map.get(data_type, self._handler_compound_unsupported)
return await handler(
message=message,
xml_data=xml_data,
)
else:
return platform_message.MessageChain([platform_message.Unknown(text=content_no_preifx)])
except Exception as e:
print(f'解析复合消息失败: {str(e)}')
return platform_message.MessageChain([platform_message.Unknown(text=content_no_preifx)])
async def _handler_compound_quote(
self, message: Optional[dict], xml_data: ET.Element
) -> platform_message.MessageChain:
message_list = []
appmsg_data = xml_data.find('.//appmsg')
quote_data = ''
user_data = ''
sender_id = xml_data.findtext('.//fromusername')
if appmsg_data:
user_data = appmsg_data.findtext('.//title') or ''
quote_data = appmsg_data.find('.//refermsg').findtext('.//content')
message_list.append(
platform_message.WeChatForwardQuote(app_msg=ET.tostring(appmsg_data, encoding='unicode'))
)
if quote_data:
quote_data_message_list = platform_message.MessageChain()
try:
if '<msg>' not in quote_data:
quote_data_message_list.append(platform_message.Plain(quote_data))
else:
quote_data_xml = ET.fromstring(quote_data)
if quote_data_xml.find('img'):
quote_data_message_list.extend(await self._handler_image(None, quote_data))
elif quote_data_xml.find('voicemsg'):
quote_data_message_list.extend(await self._handler_voice(None, quote_data))
elif quote_data_xml.find('videomsg'):
quote_data_message_list.extend(await self._handler_default(None, quote_data))
else:
quote_data_message_list.extend(await self._handler_compound(None, quote_data))
except Exception as e:
print(f'处理引用消息异常 expcetion:{e}')
quote_data_message_list.append(platform_message.Plain(quote_data))
message_list.append(
platform_message.Quote(
sender_id=sender_id,
origin=quote_data_message_list,
)
)
if len(user_data) > 0:
pattern = r'@\S{1,20}'
user_data = re.sub(pattern, '', user_data)
message_list.append(platform_message.Plain(user_data))
return platform_message.MessageChain(message_list)
async def _handler_compound_file(self, message: dict, xml_data: ET.Element) -> platform_message.MessageChain:
xml_data_str = ET.tostring(xml_data, encoding='unicode')
return platform_message.MessageChain([platform_message.WeChatForwardFile(xml_data=xml_data_str)])
async def _handler_compound_link(self, message: dict, xml_data: ET.Element) -> platform_message.MessageChain:
message_list = []
try:
appmsg = xml_data.find('.//appmsg')
if appmsg is None:
return platform_message.MessageChain()
message_list.append(
platform_message.WeChatLink(
link_title=appmsg.findtext('title', ''),
link_desc=appmsg.findtext('des', ''),
link_url=appmsg.findtext('url', ''),
link_thumb_url=appmsg.findtext('thumburl', ''),
)
)
xml_data_str = ET.tostring(xml_data, encoding='unicode')
message_list.append(platform_message.WeChatForwardLink(xml_data=xml_data_str))
except Exception as e:
print(f'解析链接消息失败: {str(e)}')
return platform_message.MessageChain(message_list)
async def _handler_compound_mini_program(
self, message: dict, xml_data: ET.Element
) -> platform_message.MessageChain:
xml_data_str = ET.tostring(xml_data, encoding='unicode')
return platform_message.MessageChain([platform_message.WeChatForwardMiniPrograms(xml_data=xml_data_str)])
async def _handler_default(self, message: Optional[dict], content_no_preifx: str) -> platform_message.MessageChain:
if message:
msg_type = message['Data']['MsgType']
else:
msg_type = ''
return platform_message.MessageChain([platform_message.Unknown(text=f'[未知消息类型 msg_type:{msg_type}]')])
def _handler_compound_unsupported(
self, message: dict, xml_data: str, text: Optional[str] = None
) -> platform_message.MessageChain:
if not text:
text = f'[xml_data={xml_data}]'
content_list = []
content_list.append(platform_message.Unknown(text=f'[处理未支持复合消息类型[msg_type=49]|{text}'))
return platform_message.MessageChain(content_list)
def _ats_bot(self, message: dict, bot_account_id: str) -> bool:
ats_bot = False
try:
to_user_name = message['Wxid']
raw_content = message['Data']['Content']['string']
content_no_prefix, _ = self._extract_content_and_sender(raw_content)
push_content = message.get('Data', {}).get('PushContent', '')
ats_bot = ats_bot or ('在群聊中@了你' in push_content)
msg_source = message.get('Data', {}).get('MsgSource', '') or ''
if len(msg_source) > 0:
msg_source_data = ET.fromstring(msg_source)
at_user_list = msg_source_data.findtext('atuserlist') or ''
ats_bot = ats_bot or (to_user_name in at_user_list)
if message.get('Data', {}).get('MsgType', 0) == 49:
xml_data = ET.fromstring(content_no_prefix)
appmsg_data = xml_data.find('.//appmsg')
tousername = message['Wxid']
if appmsg_data:
quote_id = appmsg_data.find('.//refermsg').findtext('.//chatusr')
ats_bot = ats_bot or (quote_id == tousername)
except Exception as e:
print(f'Error in gewechat _ats_bot: {e}')
finally:
return ats_bot
def _extract_content_and_sender(self, raw_content: str) -> Tuple[str, Optional[str]]:
try:
regex = re.compile(r'^[a-zA-Z0-9_\-]{5,20}:')
line_split = raw_content.split('\n')
if len(line_split) > 0 and regex.match(line_split[0]):
raw_content = '\n'.join(line_split[1:])
sender_id = line_split[0].strip(':')
return raw_content, sender_id
except Exception as e:
print(f'_extract_content_and_sender got except: {e}')
finally:
return raw_content, None
def _is_group_message(self, message: dict) -> bool:
from_user_name = message['Data']['FromUserName']['string']
return from_user_name.endswith('@chatroom')
class GewechatEventConverter(abstract_platform_adapter.AbstractEventConverter):
def __init__(self, config: dict):
self.config = config
self.message_converter = GewechatMessageConverter(config)
@staticmethod
async def yiri2target(event: platform_events.MessageEvent) -> dict:
pass
async def target2yiri(self, event: dict, bot_account_id: str) -> platform_events.MessageEvent:
if event['Wxid'] == event['Data']['FromUserName']['string']:
return None
if event['Data']['FromUserName']['string'].startswith('gh_') or event['Data']['FromUserName'][
'string'
].startswith('weixin'):
return None
message_chain = await self.message_converter.target2yiri(copy.deepcopy(event), bot_account_id)
if not message_chain:
return None
if '@chatroom' in event['Data']['FromUserName']['string']:
sender_wxid = event['Data']['Content']['string'].split(':')[0]
return platform_events.GroupMessage(
sender=platform_entities.GroupMember(
id=sender_wxid,
member_name=event['Data']['FromUserName']['string'],
permission=platform_entities.Permission.Member,
group=platform_entities.Group(
id=event['Data']['FromUserName']['string'],
name=event['Data']['FromUserName']['string'],
permission=platform_entities.Permission.Member,
),
special_title='',
),
message_chain=message_chain,
time=event['Data']['CreateTime'],
source_platform_object=event,
)
else:
return platform_events.FriendMessage(
sender=platform_entities.Friend(
id=event['Data']['FromUserName']['string'],
nickname=event['Data']['FromUserName']['string'],
remark='',
),
message_chain=message_chain,
time=event['Data']['CreateTime'],
source_platform_object=event,
)
class GeWeChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
bot: gewechat_client.GewechatClient = None
bot_uuid: str = None
message_converter: GewechatMessageConverter = None
event_converter: GewechatEventConverter = None
listeners: typing.Dict[
typing.Type[platform_events.Event],
typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
] = {}
def __init__(self, config: dict, logger: EventLogger):
super().__init__(
config=config,
logger=logger,
)
self.message_converter = GewechatMessageConverter(config)
self.event_converter = GewechatEventConverter(config)
def set_bot_uuid(self, bot_uuid: str):
self.bot_uuid = bot_uuid
async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
data = await request.json
await self.logger.debug(f'Gewechat callback event: {data}')
if 'data' in data:
data['Data'] = data['data']
if 'type_name' in data:
data['TypeName'] = data['type_name']
if 'testMsg' in data:
return 'ok'
elif 'TypeName' in data and data['TypeName'] == 'AddMsg':
try:
event = await self.event_converter.target2yiri(data.copy(), self.bot_account_id)
except Exception:
await self.logger.error(f'Error in gewechat callback: {traceback.format_exc()}')
return 'ok'
if event and event.__class__ in self.listeners:
await self.listeners[event.__class__](event, self)
return 'ok'
return 'ok'
async def _handle_message(self, message: platform_message.MessageChain, target_id: str):
content_list = await self.message_converter.yiri2target(message)
at_targets = [item['target'] for item in content_list if item['type'] == 'at']
at_targets = at_targets or []
member_info = []
if at_targets:
member_info = self.bot.get_chatroom_member_detail(self.config['app_id'], target_id, at_targets[::-1])[
'data'
]
for msg in content_list:
if msg['type'] == 'text' and at_targets:
for member in member_info:
msg['content'] = f'@{member["nickName"]} {msg["content"]}'
handler_map = {
'text': lambda msg: self.bot.post_text(
app_id=self.config['app_id'],
to_wxid=target_id,
content=msg['content'],
ats=','.join(at_targets),
),
'image': lambda msg: self.bot.post_image(
app_id=self.config['app_id'],
to_wxid=target_id,
img_url=msg['image'],
),
'WeChatForwardMiniPrograms': lambda msg: self.bot.forward_mini_app(
app_id=self.config['app_id'],
to_wxid=target_id,
xml=msg['xml_data'],
cover_img_url=msg.get('image_url'),
),
'WeChatEmoji': lambda msg: self.bot.post_emoji(
app_id=self.config['app_id'],
to_wxid=target_id,
emoji_md5=msg['emoji_md5'],
emoji_size=msg['emoji_size'],
),
'WeChatLink': lambda msg: self.bot.post_link(
app_id=self.config['app_id'],
to_wxid=target_id,
title=msg['link_title'],
desc=msg['link_desc'],
link_url=msg['link_url'],
thumb_url=msg['link_thumb_url'],
),
'WeChatMiniPrograms': lambda msg: self.bot.post_mini_app(
app_id=self.config['app_id'],
to_wxid=target_id,
mini_app_id=msg['mini_app_id'],
display_name=msg['display_name'],
page_path=msg['page_path'],
cover_img_url=msg['cover_img_url'],
title=msg['title'],
user_name=msg['user_name'],
),
'WeChatForwardLink': lambda msg: self.bot.forward_url(
app_id=self.config['app_id'], to_wxid=target_id, xml=msg['xml_data']
),
'WeChatForwardImage': lambda msg: self.bot.forward_image(
app_id=self.config['app_id'], to_wxid=target_id, xml=msg['xml_data']
),
'WeChatForwardFile': lambda msg: self.bot.forward_file(
app_id=self.config['app_id'], to_wxid=target_id, xml=msg['xml_data']
),
'voice': lambda msg: self.bot.post_voice(
app_id=self.config['app_id'],
to_wxid=target_id,
voice_url=msg['url'],
voice_duration=msg['length'],
),
'WeChatAppMsg': lambda msg: self.bot.post_app_msg(
app_id=self.config['app_id'],
to_wxid=target_id,
appmsg=msg['app_msg'],
),
'at': lambda msg: None,
}
if handler := handler_map.get(msg['type']):
handler(msg)
else:
await self.logger.warning(f'未处理的消息类型: {msg["type"]}')
continue
async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
return await self._handle_message(message, target_id)
async def reply_message(
self,
message_source: platform_events.MessageEvent,
message: platform_message.MessageChain,
quote_origin: bool = False,
):
if message_source.source_platform_object:
target_id = message_source.source_platform_object['Data']['FromUserName']['string']
return await self._handle_message(message, target_id)
async def is_muted(self, group_id: int) -> bool:
pass
def register_listener(
self,
event_type: typing.Type[platform_events.Event],
callback: typing.Callable[
[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None
],
):
self.listeners[event_type] = callback
def unregister_listener(
self,
event_type: typing.Type[platform_events.Event],
callback: typing.Callable[
[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None
],
):
pass
def _build_callback_url(self) -> str:
webhook_prefix = self.config.get('_webhook_prefix', 'http://127.0.0.1:5300').rstrip('/')
return f'{webhook_prefix}/bots/{self.bot_uuid}'
async def run_async(self):
if not self.config['token']:
session = httpclient.get_session()
async with session.post(
f'{self.config["gewechat_url"]}/v2/api/tools/getTokenId',
json={'app_id': self.config['app_id']},
) as response:
if response.status != 200:
raise Exception(f'获取gewechat token失败: {await response.text()}')
self.config['token'] = (await response.json())['data']
self.bot = gewechat_client.GewechatClient(f'{self.config["gewechat_url"]}/v2/api', self.config['token'])
def gewechat_init_process():
profile = self.bot.get_profile(self.config['app_id'])
self.bot_account_id = profile['data']['nickName']
try:
callback_url = self._build_callback_url()
self.bot.set_callback(self.config['token'], callback_url)
print(f'Gewechat 回调地址已设置: {callback_url}')
except Exception as e:
raise Exception(f'设置 Gewechat 回调失败token失效{e}')
threading.Thread(target=gewechat_init_process).start()
# 统一 webhook 模式下,不启动独立的 HTTP 服务
# 保持适配器运行
while True:
await asyncio.sleep(1)
async def kill(self) -> bool:
return False

View File

@@ -0,0 +1,51 @@
apiVersion: v1
kind: MessagePlatformAdapter
metadata:
name: gewechat
label:
en_US: GeWeChat
zh_Hans: GeWeChat个人微信
description:
en_US: GeWeChat Adapter (Unified Webhook)
zh_Hans: GeWeChat 适配器(统一 Webhook请查看文档了解使用方式
icon: gewechat.png
spec:
config:
- name: gewechat_url
label:
en_US: GeWeChat URL
zh_Hans: GeWeChat URL
description:
en_US: GeWeChat API server address, e.g. http://127.0.0.1:2531
zh_Hans: GeWeChat API 服务器地址,如 http://127.0.0.1:2531
type: string
required: true
default: ""
- name: gewechat_file_url
label:
en_US: GeWeChat file download URL
zh_Hans: GeWeChat 文件下载URL
description:
en_US: GeWeChat file download service address
zh_Hans: GeWeChat 文件下载服务地址
type: string
required: true
default: ""
- name: app_id
label:
en_US: App ID
zh_Hans: 应用ID
type: string
required: true
default: ""
- name: token
label:
en_US: Token
zh_Hans: 令牌
type: string
required: true
default: ""
execution:
python:
path: ./gewechat.py
attr: GeWeChatAdapter

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

@@ -42,6 +42,25 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
photo_bytes = f.read()
components.append({'type': 'photo', 'photo': photo_bytes})
elif isinstance(component, platform_message.File):
file_bytes = None
if component.base64:
# Strip data URI prefix if present (e.g. "data:application/pdf;base64,...")
b64_data = component.base64
if ';base64,' in b64_data:
b64_data = b64_data.split(';base64,', 1)[1]
file_bytes = base64.b64decode(b64_data)
elif component.url:
session = httpclient.get_session()
async with session.get(component.url) as response:
file_bytes = await response.read()
elif component.path:
with open(component.path, 'rb') as f:
file_bytes = f.read()
file_name = getattr(component, 'name', None) or 'file'
components.append({'type': 'document', 'document': file_bytes, 'filename': file_name})
elif isinstance(component, platform_message.Forward):
for node in component.node_list:
components.extend(await TelegramMessageConverter.yiri2target(node.message_chain, bot))
@@ -104,6 +123,27 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
)
)
if message.document:
if message.caption:
message_components.extend(parse_message_text(message.caption))
file = await message.document.get_file()
file_name = message.document.file_name or 'document'
file_size = message.document.file_size or 0
file_format = message.document.mime_type or 'application/octet-stream'
file_bytes = None
async with httpclient.get_session(trust_env=True).get(file.file_path) as response:
file_bytes = await response.read()
message_components.append(
platform_message.File(
name=file_name,
size=file_size,
base64=f'data:{file_format};base64,{base64.b64encode(file_bytes).decode("utf-8")}',
)
)
return platform_message.MessageChain(message_components)
@@ -179,7 +219,10 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
application = ApplicationBuilder().token(config['token']).build()
bot = application.bot
application.add_handler(
MessageHandler(filters.TEXT | (filters.COMMAND) | filters.PHOTO | filters.VOICE, telegram_callback)
MessageHandler(
filters.TEXT | (filters.COMMAND) | filters.PHOTO | filters.VOICE | filters.Document.ALL,
telegram_callback,
)
)
super().__init__(
config=config,
@@ -218,6 +261,13 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
continue
args['photo'] = telegram.InputFile(photo)
await self.bot.send_photo(**args)
elif component_type == 'document':
doc = component.get('document')
if doc is None:
continue
filename = component.get('filename', 'file')
args['document'] = telegram.InputFile(doc, filename=filename)
await self.bot.send_document(**args)
async def reply_message(
self,

View File

@@ -148,54 +148,51 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
pass
if type(event) is platform_events.FriendMessage:
return event.source_platform_object
payload = {
'MsgType': 'text',
'Content': '',
'FromUserName': event.sender.id,
'ToUserName': bot_account_id,
'CreateTime': int(datetime.datetime.now().timestamp()),
'AgentID': event.sender.nickname,
}
wecom_event = WecomEvent.from_payload(payload=payload)
if not wecom_event:
raise ValueError('无法从 message_data 构造 WecomEvent 对象')
return wecom_event
@staticmethod
async def target2yiri(event: WecomEvent, bot: WecomClient = None):
async def target2yiri(event: WecomEvent):
"""
将 WecomEvent 转换为平台的 FriendMessage 对象。
Args:
event (WecomEvent): 企业微信事件。
bot (WecomClient): 企业微信客户端,用于获取用户信息。
Returns:
platform_events.FriendMessage: 转换后的 FriendMessage 对象。
"""
# Try to get the user's real name from the WeCom API
nickname = str(event.user_id)
if bot and event.user_id:
try:
user_info = await bot.get_user_info(event.user_id)
if user_info and user_info.get('name'):
nickname = user_info.get('name')
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=nickname,
nickname=str(event.agent_id),
remark='',
)
return platform_events.FriendMessage(
sender=friend, message_chain=yiri_chain, time=event.timestamp, source_platform_object=event
)
return platform_events.FriendMessage(sender=friend, message_chain=yiri_chain, time=event.timestamp)
elif event.type == 'image':
friend = platform_entities.Friend(
id=f'u{event.user_id}',
nickname=nickname,
nickname=str(event.agent_id),
remark='',
)
yiri_chain = await WecomMessageConverter.target2yiri_image(picurl=event.picurl, message_id=event.message_id)
return platform_events.FriendMessage(
sender=friend, message_chain=yiri_chain, time=event.timestamp, source_platform_object=event
)
return platform_events.FriendMessage(sender=friend, message_chain=yiri_chain, time=event.timestamp)
class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
@@ -213,6 +210,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
'secret',
'token',
'EncodingAESKey',
'contacts_secret',
]
missing_keys = [key for key in required_keys if key not in config]
@@ -225,7 +223,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
secret=config['secret'],
token=config['token'],
EncodingAESKey=config['EncodingAESKey'],
contacts_secret=config.get('contacts_secret', ''), # Optional, kept for backward compatibility
contacts_secret=config['contacts_secret'],
logger=logger,
unified_mode=True,
api_base_url=config.get('api_base_url', 'https://qyapi.weixin.qq.com/cgi-bin'),
@@ -250,17 +248,18 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
):
Wecom_event = await WecomEventConverter.yiri2target(message_source, self.bot_account_id, self.bot)
content_list = await WecomMessageConverter.yiri2target(message, self.bot)
# user_id is the original FromUserName from WecomEvent
user_id = Wecom_event.user_id
fixed_user_id = Wecom_event.user_id
# 删掉开头的u
fixed_user_id = fixed_user_id[1:]
for content in content_list:
if content['type'] == 'text':
await self.bot.send_private_msg(user_id, Wecom_event.agent_id, content['content'])
await self.bot.send_private_msg(fixed_user_id, Wecom_event.agent_id, content['content'])
elif content['type'] == 'image':
await self.bot.send_image(user_id, Wecom_event.agent_id, content['media_id'])
await self.bot.send_image(fixed_user_id, Wecom_event.agent_id, content['media_id'])
elif content['type'] == 'voice':
await self.bot.send_voice(user_id, Wecom_event.agent_id, content['media_id'])
await self.bot.send_voice(fixed_user_id, Wecom_event.agent_id, content['media_id'])
elif content['type'] == 'file':
await self.bot.send_file(user_id, Wecom_event.agent_id, content['media_id'])
await self.bot.send_file(fixed_user_id, Wecom_event.agent_id, content['media_id'])
async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
content_list = await WecomMessageConverter.yiri2target(message, self.bot)
@@ -288,7 +287,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
async def on_message(event: WecomEvent):
self.bot_account_id = event.receiver_id
try:
return await callback(await self.event_converter.target2yiri(event, self.bot), self)
return await callback(await self.event_converter.target2yiri(event), self)
except Exception:
await self.logger.error(f'Error in wecom callback: {traceback.format_exc()}')

View File

@@ -39,6 +39,13 @@ spec:
type: string
required: true
default: ""
- name: contacts_secret
label:
en_US: Contacts Secret
zh_Hans: 通讯录密钥
type: string
required: true
default: ""
- name: api_base_url
label:
en_US: API Base URL

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):
@@ -23,14 +24,18 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
return content
@staticmethod
async def target2yiri(event: WecomBotEvent):
async def target2yiri(event: WecomBotEvent, bot_name: str = ''):
yiri_msg_list = []
if event.type == 'group':
yiri_msg_list.append(platform_message.At(target=event.ai_bot_id))
yiri_msg_list.append(platform_message.Source(id=event.message_id, time=datetime.datetime.now()))
if event.content:
yiri_msg_list.append(platform_message.Plain(text=event.content))
content = event.content
if bot_name:
content = content.replace(f'@{bot_name}', '').strip()
yiri_msg_list.append(platform_message.Plain(text=content))
images = []
if event.images:
@@ -133,13 +138,15 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
def __init__(self, bot_name: str = ''):
self.bot_name = bot_name
@staticmethod
async def yiri2target(event: platform_events.MessageEvent):
return event.source_platform_object
@staticmethod
async def target2yiri(event: WecomBotEvent):
message_chain = await WecomBotMessageConverter.target2yiri(event)
async def target2yiri(self, event: WecomBotEvent):
message_chain = await WecomBotMessageConverter.target2yiri(event, bot_name=self.bot_name)
if event.type == 'single':
return platform_events.FriendMessage(
sender=platform_entities.Friend(
@@ -176,34 +183,53 @@ 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()
event_converter: WecomBotEventConverter
config: dict
bot_uuid: str = None
_ws_mode: bool = False
bot_name: str = ''
listeners: dict = {}
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_name = config.get('robot_name', '')
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', ''),
)
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,
)
bot_account_id = config.get('BotId', '')
event_converter = WecomBotEventConverter(bot_name=bot_name)
super().__init__(
config=config,
logger=logger,
bot=bot,
bot_account_id=bot_account_id,
bot_name=bot_name,
event_converter=event_converter,
)
self.listeners = {}
async def reply_message(
self,
@@ -212,7 +238,17 @@ 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)
_ws_mode = not self.config.get('enable-webhook', False)
if _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 +258,23 @@ 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
_ws_mode = not self.config.get('enable-webhook', False)
# 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 _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 +287,21 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
return True
async def send_message(self, target_type, target_id, message):
pass
_ws_mode = not self.config.get('enable-webhook', False)
if _ws_mode:
content = await self.message_converter.yiri2target(message)
await self.bot.send_message(target_id, content)
else:
pass
async def on_message(self, event: WecomBotEvent):
try:
lb_event = await self.event_converter.target2yiri(event)
if lb_event:
await self.listeners[type(lb_event)](lb_event, self)
except Exception:
await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
print(traceback.format_exc())
def register_listener(
self,
@@ -268,18 +310,13 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None
],
):
async def on_message(event: WecomBotEvent):
try:
return await callback(await self.event_converter.target2yiri(event), self)
except Exception:
await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
print(traceback.format_exc())
self.listeners[event_type] = callback
try:
if event_type == platform_events.FriendMessage:
self.bot.on_message('single')(on_message)
self.bot.on_message('single')(self.on_message)
elif event_type == platform_events.GroupMessage:
self.bot.on_message('group')(on_message)
self.bot.on_message('group')(self.on_message)
except Exception:
print(traceback.format_exc())
@@ -288,29 +325,28 @@ 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
"""
_ws_mode = not self.config.get('enable-webhook', False)
if _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
_ws_mode = not self.config.get('enable-webhook', False)
if _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:
_ws_mode = not self.config.get('enable-webhook', False)
if _ws_mode:
await self.bot.disconnect()
return True
return False
async def unregister_listener(

View File

@@ -11,35 +11,71 @@ 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: robot_name
label:
en_US: Robot Name
zh_Hans: 机器人名称
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

@@ -555,6 +555,18 @@ class RuntimeConnectionHandler(handler.Handler):
except Exception as e:
return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
@self.action(PluginToRuntimeAction.VECTOR_LIST)
async def vector_list(data: dict[str, Any]) -> handler.ActionResponse:
collection_id = data['collection_id']
filters = data.get('filters')
limit = data.get('limit', 20)
offset = data.get('offset', 0)
try:
items, total = await self.ap.rag_runtime_service.vector_list(collection_id, filters, limit, offset)
return handler.ActionResponse.success(data={'items': items, 'total': total})
except Exception as e:
return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
@self.action(PluginToRuntimeAction.GET_KNOWLEDEGE_FILE_STREAM)
async def get_knowledge_file_stream(data: dict[str, Any]) -> handler.ActionResponse:
storage_path = data['storage_path']
@@ -565,6 +577,16 @@ 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 +611,98 @@ 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:
session_name = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
entries = await kb.retrieve(
query_text,
settings={
'top_k': top_k,
'filters': filters,
'session_name': session_name,
'bot_uuid': query.bot_uuid or '',
'sender_id': str(query.sender_id),
},
)
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"""
@@ -895,7 +1009,7 @@ class RuntimeConnectionHandler(handler.Handler):
result = await self.call_action(
LangBotToRuntimeAction.RAG_INGEST_DOCUMENT,
{'plugin_author': plugin_author, 'plugin_name': plugin_name, 'context': context_data},
timeout=300, # Ingestion can be slow
timeout=1200, # Ingestion can be slow for large documents
)
return result

View File

@@ -288,10 +288,10 @@ class AnthropicMessages(requester.ProviderAPIRequester):
think_started = False
think_ended = False
finish_reason = False
content = ''
tool_name = ''
tool_id = ''
async for chunk in await self.client.messages.create(**args):
content = ''
tool_call = {'id': None, 'function': {'name': None, 'arguments': None}, 'type': 'function'}
if isinstance(
chunk, anthropic.types.raw_content_block_start_event.RawContentBlockStartEvent

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
@@ -26,29 +27,114 @@ 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)
kb_uuids = query.pipeline_config['ai']['local-agent'].get('knowledge-bases', [])
# Fallback to old field for backward compatibility
if not kb_uuids:
old_kb_uuid = query.pipeline_config['ai']['local-agent'].get('knowledge-base', '')
if old_kb_uuid and old_kb_uuid != '__none__':
kb_uuids = [old_kb_uuid]
# Get knowledge bases list from query variables (set by PreProcessor,
# may have been modified by plugins during PromptPreProcessing)
kb_uuids = query.variables.get('_knowledge_base_uuids', [])
user_message = copy.deepcopy(query.user_message)
@@ -77,6 +163,7 @@ class LocalAgentRunner(runner.RequestRunner):
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}',
},
@@ -119,51 +206,51 @@ 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:
@@ -175,21 +262,18 @@ 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,
@@ -204,7 +288,8 @@ 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:
@@ -245,7 +330,6 @@ 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
@@ -253,39 +337,38 @@ 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:
@@ -297,15 +380,13 @@ 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,
@@ -318,12 +399,12 @@ 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

@@ -75,6 +75,31 @@ class RAGRuntimeService:
count = await self.ap.vector_db_mgr.delete_by_filter(collection_name=collection_id, filter=filters)
return count
async def vector_list(
self,
collection_id: str,
filters: dict[str, Any] | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[dict[str, Any]], int]:
"""Handle VECTOR_LIST action.
Args:
collection_id: The collection to list from.
filters: Optional metadata filters.
limit: Maximum number of items to return.
offset: Number of items to skip.
Returns:
Tuple of (items, total).
"""
return await self.ap.vector_db_mgr.list_by_filter(
collection_name=collection_id,
filter=filters,
limit=limit,
offset=offset,
)
async def get_file_stream(self, storage_path: str) -> bytes:
"""Handle GET_KNOWLEDEGE_FILE_STREAM action.

View File

@@ -2,7 +2,7 @@ import langbot
semantic_version = f'v{langbot.__version__}'
required_database_version = 22
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

@@ -49,17 +49,25 @@ def normalize_filter(
def strip_unsupported_fields(
triples: list[tuple[str, str, Any]],
supported_fields: set[str],
field_aliases: dict[str, str] | None = None,
) -> list[tuple[str, str, Any]]:
"""Return only triples whose field is in *supported_fields*.
If *field_aliases* is provided, aliased field names are mapped to the
canonical backend name before the support check. For example,
``{'uuid': 'chunk_uuid'}`` allows callers to use ``uuid`` which is
transparently rewritten to ``chunk_uuid``.
Dropped fields are logged at WARNING level so the caller knows they were
silently ignored (useful for Milvus / pgvector which only store a fixed
schema).
"""
aliases = field_aliases or {}
kept: list[tuple[str, str, Any]] = []
for field, op, value in triples:
if field in supported_fields:
kept.append((field, op, value))
resolved = aliases.get(field, field)
if resolved in supported_fields:
kept.append((resolved, op, value))
else:
logger.warning(
'Filter field %r is not supported by this backend and will be ignored (supported: %s)',

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 {},
}
)
@@ -157,3 +157,17 @@ class VectorDBManager:
Number of deleted vectors (best-effort; some backends return 0).
"""
return await self.vector_db.delete_by_filter(collection_name, filter)
async def list_by_filter(
self,
collection_name: str,
filter: dict | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[dict], int]:
"""Proxy: List vectors by metadata filter with pagination.
Returns:
Tuple of (items, total).
"""
return await self.vector_db.list_by_filter(collection_name, filter, limit, offset)

View File

@@ -92,6 +92,28 @@ class VectorDatabase(abc.ABC):
"""
pass
async def list_by_filter(
self,
collection: str,
filter: dict[str, Any] | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[dict[str, Any]], int]:
"""List vectors matching the given metadata filter with pagination.
Args:
collection: Collection name.
filter: Optional metadata filter dict in canonical format.
limit: Maximum number of items to return.
offset: Number of items to skip.
Returns:
Tuple of (items, total) where items is a list of dicts with
keys 'id', 'document', 'metadata', and total is the best-effort
count of all matching vectors (-1 if unknown).
"""
return [], -1
@abc.abstractmethod
async def get_or_create_collection(self, collection: str):
"""Get or create collection."""

View File

@@ -221,6 +221,41 @@ class ChromaVectorDatabase(VectorDatabase):
self.ap.logger.info(f"Deleted embeddings from Chroma collection '{collection}' by filter")
return 0 # Chroma delete does not return a count
async def list_by_filter(
self,
collection: str,
filter: dict[str, Any] | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[dict[str, Any]], int]:
col = await self.get_or_create_collection(collection)
get_kwargs: dict[str, Any] = dict(
include=['metadatas', 'documents'],
limit=limit,
offset=offset,
)
if filter:
get_kwargs['where'] = filter
results = await asyncio.to_thread(col.get, **get_kwargs)
ids = results.get('ids', [])
metadatas = results.get('metadatas', []) or [None] * len(ids)
documents = results.get('documents', []) or [None] * len(ids)
items = []
for i, vid in enumerate(ids):
items.append(
{
'id': vid,
'document': documents[i] if i < len(documents) else None,
'metadata': metadatas[i] if i < len(metadatas) else {},
}
)
# Chroma col.count() gives total in collection; filtered count not available
total = await asyncio.to_thread(col.count) if not filter else -1
return items, total
async def delete_collection(self, collection: str):
if collection in self._collections:
del self._collections[collection]

View File

@@ -11,11 +11,14 @@ from langbot.pkg.core import app
# silently dropped with a warning.
_MILVUS_SUPPORTED_FIELDS = {'text', 'file_id', 'chunk_uuid'}
# Callers use canonical metadata key 'uuid' but Milvus stores it as 'chunk_uuid'.
_MILVUS_FIELD_ALIASES = {'uuid': 'chunk_uuid'}
def _build_milvus_expr(filter_dict: dict[str, Any]) -> str:
"""Translate canonical filter dict into a Milvus boolean expression string."""
triples = normalize_filter(filter_dict)
triples = strip_unsupported_fields(triples, _MILVUS_SUPPORTED_FIELDS)
triples = strip_unsupported_fields(triples, _MILVUS_SUPPORTED_FIELDS, _MILVUS_FIELD_ALIASES)
if not triples:
return ''
@@ -340,6 +343,62 @@ class MilvusVectorDatabase(VectorDatabase):
self.ap.logger.info(f"Deleted embeddings from Milvus collection '{collection}' by filter")
return 0 # Milvus delete does not return a count
async def list_by_filter(
self,
collection: str,
filter: dict[str, Any] | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[dict[str, Any]], int]:
collection = self._normalize_collection_name(collection)
await self.get_or_create_collection(collection)
query_kwargs: dict[str, Any] = dict(
collection_name=collection,
output_fields=['text', 'file_id', 'chunk_uuid'],
limit=limit,
offset=offset,
)
if filter:
expr = _build_milvus_expr(filter)
if expr:
query_kwargs['filter'] = expr
results = await asyncio.to_thread(self.client.query, **query_kwargs)
items = []
for row in results:
items.append(
{
'id': row.get('id', ''),
'document': row.get('text'),
'metadata': {
'text': row.get('text', ''),
'file_id': row.get('file_id', ''),
'uuid': row.get('chunk_uuid', ''),
},
}
)
# Milvus query with count(*)
total = -1
try:
count_kwargs: dict[str, Any] = dict(
collection_name=collection,
output_fields=['count(*)'],
)
if filter:
expr = _build_milvus_expr(filter)
if expr:
count_kwargs['filter'] = expr
count_result = await asyncio.to_thread(self.client.query, **count_kwargs)
if count_result:
total = count_result[0].get('count(*)', -1)
except Exception:
pass
return items, total
async def delete_collection(self, collection: str):
"""Delete a Milvus collection

View File

@@ -13,6 +13,9 @@ Base = declarative_base()
# pgvector schema only stores these metadata fields.
_PG_SUPPORTED_FIELDS = {'text', 'file_id', 'chunk_uuid'}
# Callers use canonical metadata key 'uuid' but pgvector stores it as 'chunk_uuid'.
_PG_FIELD_ALIASES = {'uuid': 'chunk_uuid'}
# Map schema field names to SQLAlchemy columns (resolved lazily from PgVectorEntry).
_PG_COLUMN_MAP = {
'text': 'text',
@@ -37,7 +40,7 @@ class PgVectorEntry(Base):
def _build_pg_conditions(filter_dict: dict[str, Any]) -> list:
"""Translate canonical filter dict into a list of SQLAlchemy conditions."""
triples = normalize_filter(filter_dict)
triples = strip_unsupported_fields(triples, _PG_SUPPORTED_FIELDS)
triples = strip_unsupported_fields(triples, _PG_SUPPORTED_FIELDS, _PG_FIELD_ALIASES)
conditions = []
for field, op, value in triples:
@@ -309,6 +312,65 @@ class PgVectorDatabase(VectorDatabase):
self.ap.logger.error(f'Error deleting from pgvector by filter: {e}')
raise
async def list_by_filter(
self,
collection: str,
filter: dict[str, Any] | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[dict[str, Any]], int]:
await self.get_or_create_collection(collection)
async with self.AsyncSessionLocal() as session:
try:
from sqlalchemy import select, func
stmt = (
select(
PgVectorEntry.id,
PgVectorEntry.text,
PgVectorEntry.file_id,
PgVectorEntry.chunk_uuid,
)
.filter(PgVectorEntry.collection == collection)
.offset(offset)
.limit(limit)
)
count_stmt = (
select(func.count()).select_from(PgVectorEntry).filter(PgVectorEntry.collection == collection)
)
if filter:
for cond in _build_pg_conditions(filter):
stmt = stmt.filter(cond)
count_stmt = count_stmt.filter(cond)
result = await session.execute(stmt)
rows = result.fetchall()
count_result = await session.execute(count_stmt)
total = count_result.scalar() or 0
items = []
for row in rows:
items.append(
{
'id': row.id,
'document': row.text or '',
'metadata': {
'text': row.text or '',
'file_id': row.file_id or '',
'uuid': row.chunk_uuid or '',
},
}
)
return items, total
except Exception as e:
self.ap.logger.error(f'Error listing from pgvector: {e}')
raise
async def delete_collection(self, collection: str):
"""Delete all vectors in a collection

View File

@@ -150,6 +150,97 @@ class QdrantVectorDatabase(VectorDatabase):
self.ap.logger.info(f"Deleted embeddings from Qdrant collection '{collection}' by filter")
return 0 # Qdrant delete does not return a count
async def list_by_filter(
self,
collection: str,
filter: dict[str, Any] | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[dict[str, Any]], int]:
exists = await self.client.collection_exists(collection)
if not exists:
return [], 0
qdrant_filter = _build_qdrant_filter(filter) if filter else None
# Qdrant scroll uses cursor-based pagination (offset = point ID),
# not numeric skip. To support numeric offset we scroll through
# `offset + limit` items and discard the first `offset`.
remaining_to_skip = offset
remaining_to_collect = limit
cursor: int | str | None = None
collected: list[dict[str, Any]] = []
while remaining_to_skip > 0 or remaining_to_collect > 0:
batch_size = remaining_to_skip + remaining_to_collect if remaining_to_skip > 0 else remaining_to_collect
scroll_kwargs: dict[str, Any] = dict(
collection_name=collection,
limit=min(batch_size, 256),
with_payload=True if remaining_to_skip == 0 else False,
with_vectors=False,
)
if qdrant_filter:
scroll_kwargs['scroll_filter'] = qdrant_filter
if cursor is not None:
scroll_kwargs['offset'] = cursor
points, next_cursor = await self.client.scroll(**scroll_kwargs)
if not points:
break
for point in points:
if remaining_to_skip > 0:
remaining_to_skip -= 1
continue
if remaining_to_collect <= 0:
break
# Re-fetch payload if we skipped it during the skip phase
payload = point.payload or {}
collected.append(
{
'id': str(point.id),
'document': payload.get('text') or payload.get('document'),
'metadata': payload,
}
)
remaining_to_collect -= 1
if next_cursor is None:
break
cursor = next_cursor
# If we skipped without payload, re-fetch the collected items' payloads
# (only needed when offset > 0 and items were collected in a skip batch)
if offset > 0 and collected:
refetch_ids = [item['id'] for item in collected if not item.get('metadata')]
if refetch_ids:
fetched_points = await self.client.retrieve(
collection_name=collection,
ids=refetch_ids,
with_payload=True,
with_vectors=False,
)
payload_map = {str(p.id): p.payload or {} for p in fetched_points}
for item in collected:
if item['id'] in payload_map:
payload = payload_map[item['id']]
item['metadata'] = payload
item['document'] = payload.get('text') or payload.get('document')
# Use count() for accurate total (supports filter)
total = -1
try:
count_result = await self.client.count(
collection_name=collection,
count_filter=qdrant_filter,
exact=True,
)
total = count_result.count
except Exception:
pass
return collected, total
async def delete_collection(self, collection: str):
try:
await self.client.delete_collection(collection)

View File

@@ -340,6 +340,50 @@ class SeekDBVectorDatabase(VectorDatabase):
self.ap.logger.info(f"Deleted embeddings from SeekDB collection '{collection}' by filter")
return 0 # SeekDB delete does not return a count
async def list_by_filter(
self,
collection: str,
filter: Dict[str, Any] | None = None,
limit: int = 20,
offset: int = 0,
) -> tuple[list[Dict[str, Any]], int]:
exists = await asyncio.to_thread(self.client.has_collection, collection)
if not exists:
return [], 0
if collection not in self._collections:
coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
self._collections[collection] = coll
else:
coll = self._collections[collection]
get_kwargs: Dict[str, Any] = dict(
include=['metadatas', 'documents'],
limit=limit,
offset=offset,
)
if filter:
get_kwargs['where'] = filter
results = await asyncio.to_thread(coll.get, **get_kwargs)
ids = results.get('ids', [])
metadatas = results.get('metadatas', []) or [None] * len(ids)
documents = results.get('documents', []) or [None] * len(ids)
items = []
for i, vid in enumerate(ids):
items.append(
{
'id': vid,
'document': documents[i] if i < len(documents) else None,
'metadata': metadatas[i] if i < len(metadatas) else {},
}
)
total = await asyncio.to_thread(coll.count) if not filter else -1
return items, total
async def delete_collection(self, collection: str):
"""Delete the entire collection.

View File

@@ -2,6 +2,7 @@ admins: []
api:
port: 5300
webhook_prefix: 'http://127.0.0.1:5300'
extra_webhook_prefix: ''
command:
enable: true
prefix:
@@ -15,6 +16,7 @@ proxy:
http: ''
https: ''
system:
instance_id: ''
edition: community
recovery_key: ''
allow_modify_login_info: true

View File

@@ -41,7 +41,10 @@
"runner": "local-agent"
},
"local-agent": {
"model": "",
"model": {
"primary": "",
"fallbacks": []
},
"max-round": 10,
"prompt": [
{

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

@@ -2,77 +2,5 @@
"说明": "mask将替换敏感词中的每一个字若mask_word值不为空则将敏感词整个替换为mask_word的值",
"mask": "*",
"mask_word": "",
"words": [
"习近平",
"胡锦涛",
"江泽民",
"温家宝",
"李克强",
"李长春",
"毛泽东",
"邓小平",
"周恩来",
"马克思",
"社会主义",
"共产党",
"共产主义",
"大陆官方",
"北京政权",
"中华帝国",
"中国政府",
"共狗",
"六四事件",
"天安门",
"六四",
"政治局常委",
"两会",
"共青团",
"学潮",
"八九",
"二十大",
"民进党",
"台独",
"台湾独立",
"台湾国",
"国民党",
"台湾民国",
"中华民国",
"pornhub",
"Pornhub",
"[Yy]ou[Pp]orn",
"porn",
"Porn",
"[Xx][Vv]ideos",
"[Rr]ed[Tt]ube",
"[Xx][Hh]amster",
"[Ss]pank[Ww]ire",
"[Ss]pank[Bb]ang",
"[Tt]ube8",
"[Yy]ou[Jj]izz",
"[Bb]razzers",
"[Nn]aughty[ ]?[Aa]merica",
"作爱",
"做爱",
"性交",
"性爱",
"自慰",
"阴茎",
"淫妇",
"肛交",
"交配",
"性关系",
"性活动",
"色情",
"色图",
"涩图",
"裸体",
"小穴",
"淫荡",
"性爱",
"翻墙",
"VPN",
"科学上网",
"挂梯子",
"GFW"
]
"words": []
}

View File

@@ -91,14 +91,15 @@ class TestWebhookDisplayPrefix:
def test_default_webhook_prefix(self):
"""Test that the default webhook display prefix is correctly set"""
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
# Should have the default value
assert cfg['api']['webhook_prefix'] == 'http://127.0.0.1:5300'
assert cfg['api']['extra_webhook_prefix'] == ''
def test_webhook_prefix_env_override(self):
"""Test overriding webhook_prefix via environment variable"""
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
# Set environment variable
os.environ['API__WEBHOOK_PREFIX'] = 'https://example.com:8080'
@@ -112,7 +113,7 @@ class TestWebhookDisplayPrefix:
def test_webhook_prefix_with_custom_domain(self):
"""Test webhook_prefix with custom domain"""
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
# Set to a custom domain
os.environ['API__WEBHOOK_PREFIX'] = 'https://bot.mycompany.com'
@@ -126,7 +127,7 @@ class TestWebhookDisplayPrefix:
def test_webhook_prefix_with_subdirectory(self):
"""Test webhook_prefix with subdirectory path"""
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
# Set to a URL with subdirectory
os.environ['API__WEBHOOK_PREFIX'] = 'https://example.com/langbot'
@@ -138,6 +139,37 @@ class TestWebhookDisplayPrefix:
# Cleanup
del os.environ['API__WEBHOOK_PREFIX']
def test_extra_webhook_prefix_default_empty(self):
"""Test that extra_webhook_prefix defaults to empty string"""
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
bot_uuid = 'test-bot-uuid'
webhook_prefix = cfg['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
extra_webhook_prefix = cfg['api'].get('extra_webhook_prefix', '')
webhook_url = f'/bots/{bot_uuid}'
assert f'{webhook_prefix}{webhook_url}' == 'http://127.0.0.1:5300/bots/test-bot-uuid'
# extra should be empty when not configured
assert extra_webhook_prefix == ''
def test_extra_webhook_prefix_env_override(self):
"""Test overriding extra_webhook_prefix via environment variable"""
cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
os.environ['API__EXTRA_WEBHOOK_PREFIX'] = 'https://extra.example.com'
result = _apply_env_overrides_to_config(cfg)
assert result['api']['extra_webhook_prefix'] == 'https://extra.example.com'
bot_uuid = 'test-bot-uuid'
extra_prefix = result['api']['extra_webhook_prefix']
webhook_url = f'/bots/{bot_uuid}'
assert f'{extra_prefix}{webhook_url}' == 'https://extra.example.com/bots/test-bot-uuid'
# Cleanup
del os.environ['API__EXTRA_WEBHOOK_PREFIX']
if __name__ == '__main__':
pytest.main([__file__, '-v'])

View File

@@ -194,7 +194,7 @@ def sample_query(sample_message_chain, sample_message_event, mock_adapter):
pipeline_config={
'ai': {
'runner': {'runner': 'local-agent'},
'local-agent': {'model': 'test-model-uuid', 'prompt': 'test-prompt'},
'local-agent': {'model': {'primary': 'test-model-uuid', 'fallbacks': []}, 'prompt': 'test-prompt'},
},
'output': {'misc': {'at-sender': False, 'quote-origin': False}},
'trigger': {'misc': {'combine-quote-message': False}},
@@ -219,7 +219,7 @@ def sample_pipeline_config():
return {
'ai': {
'runner': {'runner': 'local-agent'},
'local-agent': {'model': 'test-model-uuid', 'prompt': 'test-prompt'},
'local-agent': {'model': {'primary': 'test-model-uuid', 'fallbacks': []}, 'prompt': 'test-prompt'},
},
'output': {'misc': {'at-sender': False, 'quote-origin': False}},
'trigger': {'misc': {'combine-quote-message': False}},

570
uv.lock generated

File diff suppressed because it is too large Load Diff

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

@@ -1,4 +1,4 @@
import React, { useEffect, useState } from 'react';
import React, { useEffect, useMemo, useState } from 'react';
import {
IChooseAdapterEntity,
IPipelineEntity,
@@ -113,115 +113,73 @@ export default function BotForm({
const [dynamicFormConfigList, setDynamicFormConfigList] = useState<
IDynamicFormItemSchema[]
>([]);
const [filteredDynamicFormConfigList, setFilteredDynamicFormConfigList] =
useState<IDynamicFormItemSchema[]>([]);
const [, setIsLoading] = useState<boolean>(false);
const [webhookUrl, setWebhookUrl] = useState<string>('');
const webhookInputRef = React.useRef<HTMLInputElement>(null);
const [extraWebhookUrl, setExtraWebhookUrl] = useState<string>('');
const [copied, setCopied] = useState<boolean>(false);
const [extraCopied, setExtraCopied] = useState<boolean>(false);
// Watch adapter and adapter_config for filtering
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);
// Derive the filtered config list via useMemo instead of useEffect+setState
// to avoid creating new array references that would cause DynamicFormComponent
// to re-subscribe its form.watch, re-emit values, and trigger an infinite loop.
// Only depend on the specific field we care about (enable-webhook) rather than
// the entire currentAdapterConfig object, which changes on every emission.
const enableWebhook = currentAdapterConfig?.['enable-webhook'];
const filteredDynamicFormConfigList = useMemo(() => {
if (currentAdapter === 'lark' && enableWebhook === false) {
// Hide encrypt-key field when webhook is disabled
return dynamicFormConfigList.filter(
(config) => config.name !== 'encrypt-key',
);
}
// For non-Lark adapters or when webhook is enabled/undefined, show all fields
return dynamicFormConfigList;
}, [currentAdapter, enableWebhook, dynamicFormConfigList]);
useEffect(() => {
setBotFormValues();
}, []);
// Filter dynamic form config list based on enable-webhook status for Lark adapter
useEffect(() => {
if (currentAdapter === 'lark') {
const enableWebhook = currentAdapterConfig?.['enable-webhook'];
if (enableWebhook === false) {
// Hide encrypt-key field when webhook is disabled
setFilteredDynamicFormConfigList(
dynamicFormConfigList.filter(
(config) => config.name !== 'encrypt-key',
),
);
} else {
// Show all fields when webhook is enabled or undefined
setFilteredDynamicFormConfigList(dynamicFormConfigList);
}
// 复制到剪贴板的辅助函数
const copyToClipboard = (
text: string,
setStatus: React.Dispatch<React.SetStateAction<boolean>>,
) => {
if (navigator.clipboard && navigator.clipboard.writeText) {
navigator.clipboard
.writeText(text)
.then(() => {
setStatus(true);
setTimeout(() => setStatus(false), 2000);
})
.catch(() => {
// 降级创建临时textarea复制
fallbackCopy(text, setStatus);
});
} else {
// For non-Lark adapters, show all fields
setFilteredDynamicFormConfigList(dynamicFormConfigList);
fallbackCopy(text, setStatus);
}
}, [currentAdapter, adapterConfigJson, 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 = () => {
console.log('[Copy] Attempting to copy from input element');
const inputElement = webhookInputRef.current;
if (!inputElement) {
console.error('[Copy] Input element not found');
return;
}
try {
// 确保input元素可见且未被禁用
inputElement.disabled = false;
inputElement.readOnly = false;
// 聚焦并选中所有文本
inputElement.focus();
inputElement.select();
// 尝试使用现代API
if (navigator.clipboard && navigator.clipboard.writeText) {
console.log(
'[Copy] Using Clipboard API with input value:',
inputElement.value,
);
navigator.clipboard
.writeText(inputElement.value)
.then(() => {
console.log('[Copy] Clipboard API success');
inputElement.blur(); // 取消选中
inputElement.readOnly = true;
setCopied(true);
setTimeout(() => setCopied(false), 2000);
})
.catch((err) => {
console.error(
'[Copy] Clipboard API failed, trying execCommand:',
err,
);
// 降级到execCommand
const successful = document.execCommand('copy');
console.log('[Copy] execCommand result:', successful);
inputElement.blur();
inputElement.readOnly = true;
if (successful) {
setCopied(true);
setTimeout(() => setCopied(false), 2000);
}
});
} else {
// 直接使用execCommand
console.log(
'[Copy] Using execCommand with input value:',
inputElement.value,
);
const successful = document.execCommand('copy');
console.log('[Copy] execCommand result:', successful);
inputElement.blur();
inputElement.readOnly = true;
if (successful) {
setCopied(true);
setTimeout(() => setCopied(false), 2000);
}
}
} catch (err) {
console.error('[Copy] Copy failed:', err);
inputElement.readOnly = true;
const fallbackCopy = (
text: string,
setStatus: React.Dispatch<React.SetStateAction<boolean>>,
) => {
const textarea = document.createElement('textarea');
textarea.value = text;
textarea.style.position = 'fixed';
textarea.style.opacity = '0';
document.body.appendChild(textarea);
textarea.select();
const successful = document.execCommand('copy');
document.body.removeChild(textarea);
if (successful) {
setStatus(true);
setTimeout(() => setStatus(false), 2000);
}
};
@@ -246,6 +204,7 @@ export default function BotForm({
} else {
setWebhookUrl('');
}
setExtraWebhookUrl(val.extra_webhook_full_url || '');
})
.catch((err) => {
toast.error(
@@ -255,6 +214,7 @@ export default function BotForm({
} else {
form.reset();
setWebhookUrl('');
setExtraWebhookUrl('');
}
});
}
@@ -327,14 +287,20 @@ export default function BotForm({
setAdapterNameToDynamicConfigMap(adapterNameToDynamicConfigMap);
}
async function getBotConfig(
botId: string,
): Promise<z.infer<typeof formSchema> & { webhook_full_url?: string }> {
async function getBotConfig(botId: string): Promise<
z.infer<typeof formSchema> & {
webhook_full_url?: string;
extra_webhook_full_url?: string;
}
> {
return new Promise((resolve, reject) => {
httpClient
.getBot(botId)
.then((res) => {
const bot = res.bot;
const runtimeValues = bot.adapter_runtime_values as
| Record<string, unknown>
| undefined;
resolve({
adapter: bot.adapter,
description: bot.description,
@@ -342,10 +308,12 @@ export default function BotForm({
adapter_config: bot.adapter_config,
enable: bot.enable ?? true,
use_pipeline_uuid: bot.use_pipeline_uuid ?? '',
webhook_full_url: bot.adapter_runtime_values
? ((bot.adapter_runtime_values as Record<string, unknown>)
.webhook_full_url as string)
: undefined,
webhook_full_url: runtimeValues?.webhook_full_url as
| string
| undefined,
extra_webhook_full_url: runtimeValues?.extra_webhook_full_url as
| string
| undefined,
});
})
.catch((err) => {
@@ -536,13 +504,11 @@ export default function BotForm({
{/* Webhook 地址显示(统一 Webhook 模式) */}
{webhookUrl &&
(currentAdapter !== 'lark' ||
currentAdapterConfig?.['enable-webhook'] !== false) && (
(currentAdapter !== 'lark' || enableWebhook !== false) && (
<FormItem>
<FormLabel>{t('bots.webhookUrl')}</FormLabel>
<div className="flex items-center gap-2">
<Input
ref={webhookInputRef}
value={webhookUrl}
readOnly
className="flex-1 bg-gray-50 dark:bg-gray-900"
@@ -555,7 +521,7 @@ export default function BotForm({
type="button"
variant="outline"
size="sm"
onClick={copyToClipboard}
onClick={() => copyToClipboard(webhookUrl, setCopied)}
>
{copied ? (
<Check className="h-4 w-4 text-green-600 mr-2" />
@@ -565,8 +531,37 @@ export default function BotForm({
{t('common.copy')}
</Button>
</div>
{extraWebhookUrl && (
<div className="flex items-center gap-2 mt-2">
<Input
value={extraWebhookUrl}
readOnly
className="flex-1 bg-gray-50 dark:bg-gray-900"
onClick={(e) => {
(e.target as HTMLInputElement).select();
}}
/>
<Button
type="button"
variant="outline"
size="sm"
onClick={() =>
copyToClipboard(extraWebhookUrl, setExtraCopied)
}
>
{extraCopied ? (
<Check className="h-4 w-4 text-green-600 mr-2" />
) : (
<Copy className="h-4 w-4 mr-2" />
)}
{t('common.copy')}
</Button>
</div>
)}
<p className="text-sm text-gray-500 mt-1">
{t('bots.webhookUrlHint')}
{extraWebhookUrl
? t('bots.webhookUrlHintEither')
: t('bots.webhookUrlHint')}
</p>
</FormItem>
)}
@@ -673,7 +668,7 @@ export default function BotForm({
</div>
<DynamicFormComponent
itemConfigList={filteredDynamicFormConfigList}
initialValues={form.watch('adapter_config')}
initialValues={currentAdapterConfig}
onSubmit={(values) => {
form.setValue('adapter_config', values);
}}

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';
@@ -34,6 +34,35 @@ export default function DynamicFormComponent({
const previousInitialValues = useRef(initialValues);
const { t } = useTranslation();
// Normalize a form value according to its field type.
// This ensures legacy/malformed data (e.g. a plain string for
// model-fallback-selector) is coerced to the expected shape
// so that downstream components never crash.
const normalizeFieldValue = (
item: IDynamicFormItemSchema,
value: unknown,
): unknown => {
if (item.type === 'model-fallback-selector') {
if (value != null && typeof value === 'object' && !Array.isArray(value)) {
const obj = value as Record<string, unknown>;
return {
primary: typeof obj.primary === 'string' ? obj.primary : '',
fallbacks: Array.isArray(obj.fallbacks)
? (obj.fallbacks as unknown[]).filter(
(v): v is string => typeof v === 'string',
)
: [],
};
}
// Legacy string format or any other unexpected type
return {
primary: typeof value === 'string' ? value : '',
fallbacks: [],
};
}
return value;
};
// 根据 itemConfigList 动态生成 zod schema
const formSchema = z.object(
itemConfigList.reduce(
@@ -73,6 +102,12 @@ 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({
@@ -110,10 +145,10 @@ export default function DynamicFormComponent({
resolver: zodResolver(formSchema),
defaultValues: itemConfigList.reduce((acc, item) => {
// 优先使用 initialValues如果没有则使用默认值
const value = initialValues?.[item.name] ?? item.default;
const rawValue = initialValues?.[item.name] ?? item.default;
return {
...acc,
[item.name]: value,
[item.name]: normalizeFieldValue(item, rawValue),
};
}, {} as FormValues),
});
@@ -138,7 +173,8 @@ export default function DynamicFormComponent({
// 合并默认值和初始值
const mergedValues = itemConfigList.reduce(
(acc, item) => {
acc[item.name] = initialValues[item.name] ?? item.default;
const rawValue = initialValues[item.name] ?? item.default;
acc[item.name] = normalizeFieldValue(item, rawValue) as object;
return acc;
},
{} as Record<string, object>,
@@ -160,39 +196,44 @@ 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]);
onSubmitRef.current?.(initialFinalValues);
// 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();
// Update previousInitialValues to the emitted snapshot so that if the
// parent writes these values back as new initialValues, the deep
// comparison in the initialValues-sync useEffect won't detect a change
// and won't trigger an infinite update loop.
previousInitialValues.current = initialFinalValues as Record<
string,
object
>;
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);
previousInitialValues.current = finalValues as Record<string, object>;
});
return () => subscription.unsubscribe();
}, [form, itemConfigList, emitValues]);
}, [form, itemConfigList]);
return (
<Form {...form}>
@@ -231,6 +272,7 @@ 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 +335,193 @@ 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 rawModelValue = field.value;
const modelValue: { primary: string; fallbacks: string[] } =
rawModelValue != null &&
typeof rawModelValue === 'object' &&
!Array.isArray(rawModelValue)
? {
primary:
typeof (rawModelValue as Record<string, unknown>).primary ===
'string'
? ((rawModelValue as Record<string, unknown>)
.primary as string)
: '',
fallbacks: Array.isArray(
(rawModelValue as Record<string, unknown>).fallbacks,
)
? (
(rawModelValue as Record<string, unknown>)
.fallbacks as unknown[]
).filter((v): v is string => typeof v === 'string')
: [],
}
: {
primary: typeof rawModelValue === 'string' ? rawModelValue : '',
fallbacks: [],
};
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

@@ -23,7 +23,7 @@ import {
import { useEffect, useState } from 'react';
import { httpClient, initializeUserInfo } from '@/app/infra/http';
import { useRouter } from 'next/navigation';
import { Mail, Lock, Loader2 } from 'lucide-react';
import { Mail, Lock, Loader2, AlertCircle, RefreshCw } from 'lucide-react';
import langbotIcon from '@/app/assets/langbot-logo.webp';
import { toast } from 'sonner';
import { useTranslation } from 'react-i18next';
@@ -46,6 +46,8 @@ export default function Login() {
const [accountType, setAccountType] = useState<AccountType | null>(null);
const [hasPassword, setHasPassword] = useState(false);
const [loading, setLoading] = useState(true);
const [loadError, setLoadError] = useState<string | null>(null);
const [retrying, setRetrying] = useState(false);
const form = useForm<z.infer<ReturnType<typeof formSchema>>>({
resolver: zodResolver(formSchema(t)),
@@ -61,6 +63,7 @@ export default function Login() {
async function checkAccountInfo() {
try {
setLoadError(null);
const res = await httpClient.getAccountInfo();
if (!res.initialized) {
router.push('/register');
@@ -72,11 +75,22 @@ export default function Login() {
// Also check if already logged in
checkIfAlreadyLoggedIn();
} catch {
} catch (err) {
const errorMessage =
err instanceof Error ? err.message : t('common.loginLoadError');
setLoadError(errorMessage);
setLoading(false);
}
}
async function handleRetry() {
setRetrying(true);
setLoading(true);
setLoadError(null);
await checkAccountInfo();
setRetrying(false);
}
function checkIfAlreadyLoggedIn() {
httpClient
.checkUserToken()
@@ -129,6 +143,54 @@ export default function Login() {
);
}
// Show error state when account info failed to load
if (loadError) {
return (
<div className="min-h-screen flex items-center justify-center bg-gray-50 dark:bg-neutral-900">
<Card className="w-[375px] shadow-lg dark:shadow-white/10">
<CardHeader>
<div className="flex justify-between items-center mb-6">
<ThemeToggle />
<LanguageSelector />
</div>
<img
src={langbotIcon.src}
alt="LangBot"
className="w-16 h-16 mb-4 mx-auto"
/>
<CardTitle className="text-2xl text-center">
{t('common.welcome')}
</CardTitle>
</CardHeader>
<CardContent className="space-y-4">
<div className="flex flex-col items-center gap-3 py-4">
<AlertCircle className="h-10 w-10 text-destructive" />
<p className="text-sm text-center text-muted-foreground">
{t('common.loginLoadErrorDesc')}
</p>
<code className="text-xs bg-muted px-3 py-2 rounded max-w-full overflow-x-auto block text-center text-muted-foreground">
{loadError}
</code>
<Button
onClick={handleRetry}
disabled={retrying}
variant="outline"
className="mt-2 cursor-pointer"
>
{retrying ? (
<Loader2 className="mr-2 h-4 w-4 animate-spin" />
) : (
<RefreshCw className="mr-2 h-4 w-4" />
)}
{t('common.retry')}
</Button>
</div>
</CardContent>
</Card>
</div>
);
}
// Determine what to show based on account type
const showLocalLogin =
accountType === 'local' || (accountType === 'space' && hasPassword);

View File

@@ -11,6 +11,10 @@ const enUS = {
continueToLogin: 'Login to continue',
loginSuccess: 'Login successful',
loginFailed: 'Login failed, please check your email and password',
loginLoadError: 'Unable to connect to server',
loginLoadErrorDesc:
'Unable to connect to the LangBot backend. Please make sure the service is running and try again.',
retry: 'Retry',
enterEmail: 'Enter email address',
enterPassword: 'Enter password',
invalidEmail: 'Please enter a valid email address',
@@ -236,6 +240,11 @@ const enUS = {
modelsCount: '{{count}} model(s)',
expandModels: 'Expand',
collapseModels: 'Collapse',
fallback: {
primary: 'Primary Model',
fallbackList: 'Fallback Models',
addFallback: 'Add Fallback Model',
},
},
bots: {
title: 'Bots',
@@ -279,6 +288,8 @@ const enUS = {
webhookUrlCopied: 'Webhook URL copied',
webhookUrlHint:
'Click the input to select all, then press Ctrl+C (Mac: Cmd+C) to copy, or click the button',
webhookUrlHintEither:
'Use either of the two URLs above in your platform configuration',
logLevel: 'Log Level',
allLevels: 'All Levels',
selectLevel: 'Select Level',

View File

@@ -1,4 +1,4 @@
const jaJP = {
const jaJP = {
common: {
login: 'ログイン',
logout: 'ログアウト',
@@ -12,6 +12,10 @@ const jaJP = {
loginSuccess: 'ログインに成功しました',
loginFailed:
'ログインに失敗しました。メールアドレスまたはパスワードをご確認ください',
loginLoadError: 'サーバーに接続できません',
loginLoadErrorDesc:
'LangBot バックエンドに接続できません。サービスが起動していることを確認してから再試行してください。',
retry: '再試行',
enterEmail: 'メールアドレスを入力',
enterPassword: 'パスワードを入力',
invalidEmail: '有効なメールアドレスを入力してください',
@@ -241,6 +245,11 @@ 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',
@@ -284,6 +293,8 @@ const jaJP = {
webhookUrlCopied: 'Webhook URL をコピーしました',
webhookUrlHint:
'入力ボックスをクリックして全選択し、Ctrl+C (Mac: Cmd+C) でコピーするか、右側のボタンをクリックしてください',
webhookUrlHintEither:
'上記の2つのURLのいずれかをプラットフォーム設定に使用してください',
logLevel: 'ログレベル',
allLevels: 'すべてのレベル',
selectLevel: 'レベルを選択',

View File

@@ -11,6 +11,9 @@ const zhHans = {
continueToLogin: '登录以继续',
loginSuccess: '登录成功',
loginFailed: '登录失败,请检查邮箱和密码是否正确',
loginLoadError: '无法连接到服务器',
loginLoadErrorDesc: '无法连接到 LangBot 后端服务,请确认服务已启动后重试。',
retry: '重试',
enterEmail: '输入邮箱地址',
enterPassword: '输入密码',
invalidEmail: '请输入有效的邮箱地址',
@@ -227,6 +230,11 @@ 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',
@@ -268,6 +276,7 @@ const zhHans = {
webhookUrlCopied: 'Webhook 地址已复制',
webhookUrlHint:
'点击输入框自动全选,然后按 Ctrl+C (Mac: Cmd+C) 复制,或点击右侧按钮',
webhookUrlHintEither: '以上两个地址任选其一填入平台配置即可',
logLevel: '日志级别',
allLevels: '全部级别',
selectLevel: '选择级别',

View File

@@ -11,6 +11,9 @@ const zhHant = {
continueToLogin: '登入以繼續',
loginSuccess: '登入成功',
loginFailed: '登入失敗,請檢查電子郵件和密碼是否正確',
loginLoadError: '無法連線到伺服器',
loginLoadErrorDesc: '無法連線到 LangBot 後端服務,請確認服務已啟動後重試。',
retry: '重試',
enterEmail: '輸入電子郵件地址',
enterPassword: '輸入密碼',
invalidEmail: '請輸入有效的電子郵件地址',
@@ -226,6 +229,11 @@ 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',
@@ -267,6 +275,7 @@ const zhHant = {
webhookUrlCopied: 'Webhook 位址已複製',
webhookUrlHint:
'點擊輸入框自動全選,然後按 Ctrl+C (Mac: Cmd+C) 複製,或點擊右側按鈕',
webhookUrlHintEither: '以上兩個地址任選其一填入平台配置即可',
logLevel: '日誌級別',
allLevels: '全部級別',
selectLevel: '選擇級別',