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48 Commits

Author SHA1 Message Date
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
Guanchao Wang
89064a9d5b feat: add support for username (#2047)
* feat: add support for username

* fix: lint

* fix: migerations

* fix: change to version 21

* fix: remove duplicate dbm021 migration and rename dbm022

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

---------

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

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

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

* style: apply ruff formatting to difysvapi.py

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

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2026-03-11 14:45:55 +08:00
youhuanghe
bd15b630b0 fix: chroma ruff lint 2026-03-11 04:07:21 +00:00
youhuanghe
fe5ce68436 feat(vector): add full-text and hybrid search support for Chroma backend
- Implement full-text search via Chroma's $contains filter
  - Implement hybrid search with RRF (Reciprocal Rank Fusion) combining
    vector and full-text results, with min-max normalized distances
  - Fix add_embeddings to use col.upsert instead of col.add for idempotency
  - Bump chromadb dependency to >=1.0.0,<2.0.0
  - Re-lock uv.lock with official PyPI source
2026-03-11 03:59:14 +00:00
Typer_Body
0541b05966 refactor: optimized error handling (#2020)
* Update output.yaml

* Update default-pipeline-config.json

* Update chat.py

* Add files via upload

* Update chat.py

* Update default-pipeline-config.json

* Update output.yaml

* Update constants.py

* feat: update logic

* fix: update required database version to 21

---------

Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2026-03-10 22:01:23 +08:00
youhuanghe
13cb0aa9be bugfix: rollback filter, add to retrive settings 2026-03-10 12:49:24 +00:00
youhuanghe
a048369b38 feat: Pass session context (session_name) to knowledge engine retrieval filters.
Allow KnowledgeEngine plugins to filter retrieval results by session,enabling per-session memory isolation in plugin-based knowledge bases
2026-03-10 12:27:50 +00:00
Junyan Qin
9ae0c263dc fix: update documentation links and translations for knowledge engine 2026-03-09 20:31:50 +08:00
Junyan Qin
a4e66f6459 feat: update version to 4.9.0 in pyproject.toml, __init__.py, and uv.lock 2026-03-09 20:10:01 +08:00
huanghuoguoguo
2a74a8d6ae Feat/dbm20 rag (#2037)
* feat(rag): add knowledge base migration from v4.9.0 to plugin architecture

Rewrite dbm020 to backup old knowledge_bases data and preserve
external_knowledge_bases table. Add migration API endpoints and
frontend dialog so users can opt-in to auto-install LangRAG plugin
and restore their knowledge bases with original UUIDs preserved.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix(rag): query marketplace for actual plugin version instead of 'latest'

The marketplace API does not support 'latest' as a version string.
Fetch the plugin info first to get latest_version, then use that
concrete version for installation.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat(rag): add data-only migration option and fix dialog width

Add option to migrate knowledge base data without auto-installing
the LangRAG plugin (for offline/intranet environments). Also
narrow the migration dialog to match other confirmation dialogs.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: to red and no more

* fix lint

* fix ruff lint

* feat: add external migration

* fix: show

* feat: add external plugin auto download

* feat: update migration messages for knowledge base in multiple languages

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2026-03-09 20:05:38 +08:00
Guanchao Wang
d31f25c8df Merge pull request #2041 from langbot-app/fix/websocket-chat-bug
Fix/websocket chat bug
2026-03-09 16:11:17 +08:00
WangCham
11c05ea8db style(format): fix ruff formatting issues 2026-03-09 16:04:38 +08:00
WangCham
2b8bd1cc71 fix: invoke_llm failed when use plugin 2026-03-09 16:01:45 +08:00
doujianghub
9148e02679 fix: centralized pipeline config type coercion to prevent string-type crashes (#2031)
* fix: coerce pipeline config types at load time using metadata definitions

Pipeline configs stored in SQLAlchemy JSON columns can have values turned
into strings after UI edits (e.g. "120" instead of 120), causing runtime
arithmetic/logic errors. Add centralized type coercion in load_pipeline()
that leverages existing metadata YAML type definitions (integer, number,
float, boolean) to convert values before they reach downstream stages.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: address review - defensive getattr + add unit tests for config_coercion

- Use getattr with defaults for pipeline_config_meta_* attributes to
  avoid AttributeError when MockApplication lacks these fields
- Add 18 unit tests for config_coercion module covering all code paths

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add dynamic form stage tracking and snapshot management

* fix: standardize string formatting in config coercion and improve logging messages

---------

Co-authored-by: KPC <kpc@kpc.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2026-03-09 14:30:07 +08:00
fdc310
fd15284d91 fix(platform): websocket send_message not delivering to webchat frontend (#2039)
- Include websocket_proxy_bot in get_bot_by_uuid lookup so plugins can
  find it by uuid
- Rewrite send_message to broadcast directly via ws_connection_manager
  using the correct pipeline_uuid instead of misusing target_id
- Save messages to session history with unique IDs so they persist
  across page reloads and don't overwrite each other

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 13:22:03 +08:00
Junyan Qin
8c7a0ec027 fix: update langbot-plugin version to 0.3.0 2026-03-08 21:08:08 +08:00
youhuanghe
a1cef5c9bf bugfix: update uv.lock 2026-03-08 11:10:03 +00:00
youhuanghe
90438cec36 lint: update web knowledge pnpm lint 2026-03-08 11:05:00 +00:00
youhuanghe
95dd19f4d7 bugfix: now knowledge toast right msg 2026-03-08 11:01:13 +00:00
youhuanghe
c64eb58cf8 feat: update pyseekdb version to 1.1.0.post3 2026-03-08 10:42:20 +00:00
Junyan Qin
fbd3d7ae3a feat: enhance RecommendationLists component with responsive pagination and auto-advance functionality
- Added dynamic column measurement to adjust the number of visible plugins based on the grid layout.
- Implemented auto-advance feature for pagination every 5 seconds when there are more plugins than the visible count.
- Updated pagination controls to reflect the current page accurately.
- Refactored code to improve readability and maintainability.
2026-03-08 17:35:30 +08:00
77 changed files with 4630 additions and 1163 deletions

View File

@@ -1,6 +1,6 @@
[project]
name = "langbot"
version = "4.8.7"
version = "4.9.3"
description = "Production-grade platform for building agentic IM bots"
readme = "README.md"
license-files = ["LICENSE"]
@@ -61,10 +61,10 @@ dependencies = [
"html2text>=2024.2.26",
"langchain>=0.2.0",
"langchain-text-splitters>=0.0.1",
"chromadb>=0.4.24",
"chromadb>=1.0.0,<2.0.0",
"qdrant-client (>=1.15.1,<2.0.0)",
"pyseekdb==1.0.0b7",
"langbot-plugin==0.3.0rc1",
"pyseekdb==1.1.0.post3",
"langbot-plugin==0.3.2",
"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__ = '4.8.7'
__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

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

View File

@@ -0,0 +1,372 @@
import asyncio
import json
import httpx
import quart
import sqlalchemy
from ... import group
from ......core import taskmgr
from ......entity.persistence import metadata as persistence_metadata
from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
LANGRAG_PLUGIN_AUTHOR = 'langbot-team'
LANGRAG_PLUGIN_NAME = 'LangRAG'
LANGRAG_PLUGIN_ID = f'{LANGRAG_PLUGIN_AUTHOR}/{LANGRAG_PLUGIN_NAME}'
DEFAULT_SPACE_URL = 'https://space.langbot.app'
# Old Retriever plugin_name -> New Connector plugin_name
EXTERNAL_PLUGIN_NAME_MAPPING = {
'DifyDatasetsRetriever': 'DifyDatasetsConnector',
'RAGFlowRetriever': 'RAGFlowConnector',
'FastGPTRetriever': 'FastGPTConnector',
}
# Per-plugin: which old retriever_config fields belong to creation_settings.
# Remaining fields go to retrieval_settings.
# None means ALL fields go to creation_settings (no retrieval_schema).
EXTERNAL_PLUGIN_CREATION_FIELDS: dict[str, set[str] | None] = {
'langbot-team/DifyDatasetsConnector': {'api_base_url', 'dify_apikey', 'dataset_id'},
'langbot-team/RAGFlowConnector': {'api_base_url', 'api_key', 'dataset_ids'},
'langbot-team/FastGPTConnector': None, # all fields -> creation_settings
}
@group.group_class('knowledge/migration', '/api/v1/knowledge/migration')
class KnowledgeMigrationRouterGroup(group.RouterGroup):
async def _get_migration_flag(self) -> bool:
"""Check if rag_plugin_migration_needed flag is set."""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_metadata.Metadata).where(
persistence_metadata.Metadata.key == 'rag_plugin_migration_needed'
)
)
row = result.first()
return row is not None and row.value == 'true'
async def _set_migration_flag(self, value: str):
"""Set rag_plugin_migration_needed flag."""
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_metadata.Metadata)
.where(persistence_metadata.Metadata.key == 'rag_plugin_migration_needed')
.values(value=value)
)
async def _table_exists(self, table_name: str) -> bool:
"""Check if a table exists."""
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
).bindparams(table_name=table_name)
)
return result.scalar()
else:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
table_name=table_name
)
)
return result.first() is not None
async def _install_plugin_from_marketplace(
self, plugin_id: str, task_context: taskmgr.TaskContext, space_url: str
) -> None:
"""Install a single plugin from the marketplace."""
p_author, p_name = plugin_id.split('/', 1)
self.ap.logger.info(f'RAG migration: installing plugin {plugin_id} from marketplace...')
task_context.trace(f'Installing plugin {plugin_id} from marketplace...')
async with httpx.AsyncClient(trust_env=True, timeout=15) as client:
resp = await client.get(f'{space_url}/api/v1/marketplace/plugins/{p_author}/{p_name}')
resp.raise_for_status()
p_data = resp.json().get('data', {}).get('plugin', {})
p_version = p_data.get('latest_version')
if not p_version:
raise Exception(f'Could not determine latest version for {plugin_id}')
await self.ap.plugin_connector.install_plugin(
PluginInstallSource.MARKETPLACE,
{
'plugin_author': p_author,
'plugin_name': p_name,
'plugin_version': p_version,
},
task_context=task_context,
)
self.ap.logger.info(f'RAG migration: plugin {plugin_id} install request sent.')
async def _execute_rag_migration(self, task_context: taskmgr.TaskContext, install_plugin: bool = True):
"""Execute RAG migration: install required plugins and restore backup data."""
warnings = []
# Collect all plugins we need: LangRAG (always) + connector plugins (from external KBs)
needed_plugins: dict[str, str] = {
LANGRAG_PLUGIN_ID: LANGRAG_PLUGIN_NAME,
}
has_external = await self._table_exists('external_knowledge_bases')
if has_external:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT DISTINCT plugin_author, plugin_name FROM external_knowledge_bases;')
)
for row in result.fetchall():
plugin_author = row[0] or ''
plugin_name = row[1] or ''
mapped_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
plugin_id = f'{plugin_author}/{mapped_name}'
if plugin_id not in needed_plugins:
needed_plugins[plugin_id] = mapped_name
self.ap.logger.info(f'RAG migration: plugins needed: {list(needed_plugins.keys())}')
if install_plugin:
# Step 1: Install all required plugins from marketplace
task_context.trace('Installing required plugins...', action='install-plugin')
space_url = self.ap.instance_config.data.get('space', {}).get('url', DEFAULT_SPACE_URL).rstrip('/')
for plugin_id in needed_plugins:
try:
await self._install_plugin_from_marketplace(plugin_id, task_context, space_url)
except Exception as e:
self.ap.logger.warning(f'RAG migration: plugin {plugin_id} install returned: {e}')
task_context.trace(f'Plugin install note ({plugin_id}): {e}')
# Step 2: Wait for all plugins to become available as knowledge engines
task_context.trace(
f'Waiting for plugins to become available: {list(needed_plugins.keys())}...',
action='wait-plugin',
)
max_retries = 30
engine_id_set: set[str] = set()
for i in range(max_retries):
try:
engines = await self.ap.plugin_connector.list_knowledge_engines()
engine_id_set = {e.get('plugin_id') for e in engines}
except Exception:
pass
if all(pid in engine_id_set for pid in needed_plugins):
self.ap.logger.info(f'RAG migration: all plugins ready: {engine_id_set}')
task_context.trace('All required plugins are ready.')
break
if i == max_retries - 1:
still_missing = [pid for pid in needed_plugins if pid not in engine_id_set]
warning = f'Plugin(s) {still_missing} did not become available after {max_retries} retries'
self.ap.logger.warning(f'RAG migration: {warning}')
warnings.append(warning)
task_context.trace(warning)
await asyncio.sleep(2)
else:
try:
engines = await self.ap.plugin_connector.list_knowledge_engines()
engine_id_set = {e.get('plugin_id') for e in engines}
except Exception:
engine_id_set = set()
# Step 3: Restore internal knowledge bases from backup
task_context.trace('Restoring internal knowledge bases...', action='restore-internal')
if await self._table_exists('knowledge_bases_backup'):
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT * FROM knowledge_bases_backup;')
)
rows = result.fetchall()
columns = result.keys()
for row in rows:
row_dict = dict(zip(columns, row))
kb_uuid = row_dict.get('uuid')
name = row_dict.get('name', 'Untitled')
description = row_dict.get('description', '')
emoji = row_dict.get('emoji', '\U0001f4da')
embedding_model_uuid = row_dict.get('embedding_model_uuid', '')
top_k = row_dict.get('top_k', 5)
created_at = row_dict.get('created_at')
updated_at = row_dict.get('updated_at')
creation_settings = json.dumps({'embedding_model_uuid': embedding_model_uuid})
retrieval_settings = json.dumps({'top_k': top_k})
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'INSERT INTO knowledge_bases '
'(uuid, name, description, emoji, created_at, updated_at, '
'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
).bindparams(
uuid=kb_uuid,
name=name,
description=description,
emoji=emoji,
created_at=created_at,
updated_at=updated_at,
plugin_id=LANGRAG_PLUGIN_ID,
collection_id=kb_uuid,
creation_settings=creation_settings,
retrieval_settings=retrieval_settings,
)
)
try:
config = {'embedding_model_uuid': embedding_model_uuid}
await self.ap.plugin_connector.rag_on_kb_create(LANGRAG_PLUGIN_ID, kb_uuid, config)
task_context.trace(f'Restored internal KB: {name} ({kb_uuid})')
except Exception as e:
warning = f'Failed to notify plugin for KB {name} ({kb_uuid}): {e}'
warnings.append(warning)
task_context.trace(warning)
await self.ap.rag_mgr.load_knowledge_bases_from_db()
# Step 4: Restore external knowledge bases
task_context.trace('Restoring external knowledge bases...', action='restore-external')
if has_external:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT * FROM external_knowledge_bases;')
)
rows = result.fetchall()
columns = result.keys()
self.ap.logger.info(
f'RAG migration: {len(rows)} external KB(s) to restore. Available engines: {engine_id_set}'
)
task_context.trace(f'Found {len(rows)} external KB(s). Available engines: {engine_id_set}')
for row in rows:
row_dict = dict(zip(columns, row))
kb_uuid = row_dict.get('uuid')
name = row_dict.get('name', 'Untitled')
description = row_dict.get('description', '')
emoji = row_dict.get('emoji', '\U0001f517')
plugin_author = row_dict.get('plugin_author', '')
plugin_name = row_dict.get('plugin_name', '')
retriever_config = row_dict.get('retriever_config', {})
created_at = row_dict.get('created_at')
mapped_plugin_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
external_plugin_id = f'{plugin_author}/{mapped_plugin_name}'
self.ap.logger.info(
f'RAG migration: processing external KB "{name}" ({kb_uuid}), '
f'plugin: {plugin_author}/{plugin_name} -> {external_plugin_id}'
)
if isinstance(retriever_config, str):
try:
retriever_config = json.loads(retriever_config)
except (json.JSONDecodeError, TypeError):
retriever_config = {}
creation_fields = EXTERNAL_PLUGIN_CREATION_FIELDS.get(external_plugin_id)
if creation_fields is None:
creation_settings_dict = retriever_config
retrieval_settings_dict = {}
else:
creation_settings_dict = {k: v for k, v in retriever_config.items() if k in creation_fields}
retrieval_settings_dict = {k: v for k, v in retriever_config.items() if k not in creation_fields}
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'INSERT INTO knowledge_bases '
'(uuid, name, description, emoji, created_at, updated_at, '
'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
).bindparams(
uuid=kb_uuid,
name=name,
description=description,
emoji=emoji,
created_at=created_at,
updated_at=created_at,
plugin_id=external_plugin_id,
collection_id=kb_uuid,
creation_settings=json.dumps(creation_settings_dict),
retrieval_settings=json.dumps(retrieval_settings_dict),
)
)
if external_plugin_id not in engine_id_set:
warning = (
f'External KB "{name}" ({kb_uuid}) record saved, but plugin {external_plugin_id} '
f'is not installed yet. Install the connector plugin to use it.'
)
warnings.append(warning)
task_context.trace(warning)
else:
try:
await self.ap.plugin_connector.rag_on_kb_create(
external_plugin_id, kb_uuid, creation_settings_dict
)
task_context.trace(f'Restored external KB: {name} ({kb_uuid})')
except Exception as e:
warning = f'Failed to notify plugin for external KB {name} ({kb_uuid}): {e}'
warnings.append(warning)
task_context.trace(warning)
await self.ap.rag_mgr.load_knowledge_bases_from_db()
# Step 5: Clear migration flag
await self._set_migration_flag('false')
task_context.trace('RAG migration completed.', action='done')
if warnings:
task_context.trace(f'Completed with {len(warnings)} warning(s).')
async def initialize(self) -> None:
@self.route('/status', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
needed = await self._get_migration_flag()
internal_kb_count = 0
external_kb_count = 0
if needed:
if await self._table_exists('knowledge_bases_backup'):
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT COUNT(*) FROM knowledge_bases_backup;')
)
internal_kb_count = result.scalar() or 0
if await self._table_exists('external_knowledge_bases'):
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT COUNT(*) FROM external_knowledge_bases;')
)
external_kb_count = result.scalar() or 0
return self.success(
data={
'needed': needed,
'internal_kb_count': internal_kb_count,
'external_kb_count': external_kb_count,
}
)
@self.route('/execute', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
needed = await self._get_migration_flag()
if not needed:
return self.http_status(400, -1, 'RAG migration is not needed')
data = await quart.request.get_json(silent=True) or {}
install_plugin = data.get('install_plugin', True)
ctx = taskmgr.TaskContext.new()
wrapper = self.ap.task_mgr.create_user_task(
self._execute_rag_migration(task_context=ctx, install_plugin=install_plugin),
kind='rag-migration',
name='rag-migration-execute',
label='Migrating knowledge bases to plugin architecture',
context=ctx,
)
return self.success(data={'task_id': wrapper.id})
@self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
needed = await self._get_migration_flag()
if not needed:
return self.http_status(400, -1, 'RAG migration is not needed')
await self._set_migration_flag('false')
return self.success()

View File

@@ -70,12 +70,17 @@ class BotService:
'lark',
]:
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

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

View File

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

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@@ -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}')

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

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@@ -1,5 +1,3 @@
import json
import sqlalchemy
from .. import migration
@@ -9,20 +7,22 @@ class DBMigrateKnowledgeEnginePluginArchitecture(migration.DBMigration):
"""Migrate to unified Knowledge Engine plugin architecture.
Changes:
- Add knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings columns to knowledge_bases
- Migrate existing top_k values into retrieval_settings JSON
- Migrate existing embedding_model_uuid into creation_settings JSON
- Drop embedding_model_uuid and top_k columns (PostgreSQL only; SQLite leaves them unmapped)
- Drop external_knowledge_bases table (no longer needed; external KB data is not migrated)
- Backup existing knowledge_bases data to knowledge_bases_backup
- Clear knowledge_bases table and add new plugin architecture columns
- Drop old columns (PostgreSQL only; SQLite leaves them unmapped)
- Preserve external_knowledge_bases table as-is for future migration
- Set rag_plugin_migration_needed flag in metadata if old data exists
"""
async def upgrade(self):
"""Upgrade"""
has_internal_data = await self._backup_knowledge_bases()
has_external_data = await self._check_external_knowledge_bases()
await self._clear_knowledge_bases()
await self._add_columns_to_knowledge_bases()
await self._migrate_top_k_to_retrieval_settings()
await self._migrate_embedding_model_uuid_to_creation_settings()
await self._drop_old_columns()
await self._drop_external_knowledge_bases_table()
if has_internal_data or has_external_data:
await self._set_migration_flag()
async def _get_table_columns(self, table_name: str) -> list[str]:
"""Get column names from a table (works for both SQLite and PostgreSQL)."""
@@ -57,6 +57,50 @@ class DBMigrateKnowledgeEnginePluginArchitecture(migration.DBMigration):
)
return result.first() is not None
async def _backup_knowledge_bases(self) -> bool:
"""Backup knowledge_bases data. Returns True if data was backed up."""
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text('SELECT COUNT(*) FROM knowledge_bases;'))
count = result.scalar()
if count == 0:
return False
# Drop backup table if it already exists (from a previous failed migration)
if await self._table_exists('knowledge_bases_backup'):
await self.ap.persistence_mgr.execute_async(sqlalchemy.text('DROP TABLE knowledge_bases_backup;'))
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('CREATE TABLE knowledge_bases_backup AS SELECT * FROM knowledge_bases;')
)
self.ap.logger.info(
'Backed up %d knowledge base(s) to knowledge_bases_backup table.',
count,
)
return True
async def _check_external_knowledge_bases(self) -> bool:
"""Check if external_knowledge_bases table exists and has data.
The table is preserved as-is (not dropped) for future migration.
"""
if not await self._table_exists('external_knowledge_bases'):
return False
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT COUNT(*) FROM external_knowledge_bases;')
)
count = result.scalar()
if count > 0:
self.ap.logger.info(
'Found %d external knowledge base(s) in external_knowledge_bases table. '
'Table preserved for future migration.',
count,
)
return count > 0
async def _clear_knowledge_bases(self):
"""Clear all rows from knowledge_bases table (preserve table structure)."""
await self.ap.persistence_mgr.execute_async(sqlalchemy.text('DELETE FROM knowledge_bases;'))
async def _add_columns_to_knowledge_bases(self):
"""Add new RAG plugin architecture columns to knowledge_bases table."""
columns = await self._get_table_columns('knowledge_bases')
@@ -74,73 +118,6 @@ class DBMigrateKnowledgeEnginePluginArchitecture(migration.DBMigration):
sqlalchemy.text(f'ALTER TABLE knowledge_bases ADD COLUMN {col_name} {col_type};')
)
# For existing knowledge bases without knowledge_engine_plugin_id,
# set collection_id = uuid (same default as new KBs)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('UPDATE knowledge_bases SET collection_id = uuid WHERE collection_id IS NULL;')
)
async def _migrate_top_k_to_retrieval_settings(self):
"""Migrate existing top_k values into retrieval_settings JSON."""
columns = await self._get_table_columns('knowledge_bases')
if 'top_k' not in columns:
return
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'SELECT uuid, top_k FROM knowledge_bases WHERE top_k IS NOT NULL AND retrieval_settings IS NULL;'
)
)
rows = result.fetchall()
for row in rows:
kb_uuid = row[0]
top_k = row[1]
retrieval_settings = json.dumps({'top_k': top_k})
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('UPDATE knowledge_bases SET retrieval_settings = :rs WHERE uuid = :uuid;').bindparams(
rs=retrieval_settings, uuid=kb_uuid
)
)
async def _migrate_embedding_model_uuid_to_creation_settings(self):
"""Migrate existing embedding_model_uuid into creation_settings JSON."""
columns = await self._get_table_columns('knowledge_bases')
if 'embedding_model_uuid' not in columns:
return
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'SELECT uuid, embedding_model_uuid, creation_settings FROM knowledge_bases '
"WHERE embedding_model_uuid IS NOT NULL AND embedding_model_uuid != '';"
)
)
rows = result.fetchall()
for row in rows:
kb_uuid = row[0]
emb_uuid = row[1]
existing_settings = row[2]
if existing_settings and isinstance(existing_settings, str):
try:
settings = json.loads(existing_settings)
except (json.JSONDecodeError, TypeError):
settings = {}
elif isinstance(existing_settings, dict):
settings = existing_settings
else:
settings = {}
if 'embedding_model_uuid' not in settings:
settings['embedding_model_uuid'] = emb_uuid
new_settings = json.dumps(settings)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE knowledge_bases SET creation_settings = :cs WHERE uuid = :uuid;'
).bindparams(cs=new_settings, uuid=kb_uuid)
)
async def _drop_old_columns(self):
"""Drop embedding_model_uuid and top_k columns (PostgreSQL only).
@@ -162,22 +139,22 @@ class DBMigrateKnowledgeEnginePluginArchitecture(migration.DBMigration):
sqlalchemy.text('ALTER TABLE knowledge_bases DROP COLUMN top_k;')
)
async def _drop_external_knowledge_bases_table(self):
"""Drop the external_knowledge_bases table if it exists."""
if await self._table_exists('external_knowledge_bases'):
# Log existing external KBs before dropping, so users are aware of data loss
rows = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT * FROM external_knowledge_bases;')
async def _set_migration_flag(self):
"""Set rag_plugin_migration_needed flag in metadata table."""
# Check if the key already exists
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("SELECT value FROM metadata WHERE key = 'rag_plugin_migration_needed';")
)
row = result.first()
if row is not None:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("UPDATE metadata SET value = 'true' WHERE key = 'rag_plugin_migration_needed';")
)
existing = rows.fetchall()
if existing:
self.ap.logger.warning(
'Dropping external_knowledge_bases table with %d existing record(s). '
'These external KB configurations will be removed: %s',
len(existing),
[dict(row._mapping) for row in existing],
)
await self.ap.persistence_mgr.execute_async(sqlalchemy.text('DROP TABLE external_knowledge_bases;'))
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("INSERT INTO metadata (key, value) VALUES ('rag_plugin_migration_needed', 'true');")
)
self.ap.logger.info('Set rag_plugin_migration_needed=true in metadata.')
async def downgrade(self):
"""Downgrade"""

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

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

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@@ -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},
)

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@@ -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

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@@ -0,0 +1,105 @@
from __future__ import annotations
import logging
logger = logging.getLogger(__name__)
# metadata type -> coercion function
_COERCE_MAP = {
'integer': lambda v: int(v),
'number': lambda v: float(v),
'float': lambda v: float(v),
}
def _coerce_bool(v):
if isinstance(v, bool):
return v
if isinstance(v, str):
if v.lower() == 'true':
return True
if v.lower() == 'false':
return False
raise ValueError(f'Cannot convert string {v!r} to bool')
return bool(v)
def _coerce_value(value, expected_type: str):
"""Convert a single value to the expected type.
Returns the converted value, or the original value if no conversion needed.
"""
if value is None:
return value
if expected_type == 'boolean':
if isinstance(value, bool):
return value
return _coerce_bool(value)
coerce_fn = _COERCE_MAP.get(expected_type)
if coerce_fn is None:
return value
# Already the correct type
if expected_type == 'integer' and isinstance(value, int) and not isinstance(value, bool):
return value
if expected_type in ('number', 'float') and isinstance(value, (int, float)) and not isinstance(value, bool):
return float(value)
return coerce_fn(value)
def coerce_pipeline_config(
config: dict,
*metadata_list: dict,
) -> None:
"""Coerce pipeline config values according to metadata type definitions.
Walks each metadata dict (trigger, safety, ai, output) and converts
config values in-place so that strings coming from the JSON column are
cast to their declared types (integer, number/float, boolean).
Args:
config: The pipeline config dict to modify in-place.
*metadata_list: Metadata dicts loaded from the YAML templates.
"""
for meta in metadata_list:
section_name = meta.get('name')
if not section_name or section_name not in config:
continue
section = config[section_name]
if not isinstance(section, dict):
continue
for stage_def in meta.get('stages', []):
stage_name = stage_def.get('name')
if not stage_name or stage_name not in section:
continue
stage_config = section[stage_name]
if not isinstance(stage_config, dict):
continue
for field_def in stage_def.get('config', []):
field_name = field_def.get('name')
field_type = field_def.get('type')
if not field_name or not field_type or field_name not in stage_config:
continue
old_value = stage_config[field_name]
try:
new_value = _coerce_value(old_value, field_type)
if new_value is not old_value:
stage_config[field_name] = new_value
except (ValueError, TypeError) as e:
logger.warning(
'Failed to coerce config %s.%s.%s (%r) to %s: %s',
section_name,
stage_name,
field_name,
old_value,
field_type,
e,
)

View File

@@ -22,13 +22,10 @@ class LongTextProcessStage(stage.PipelineStage):
"""
strategy_impl: strategy.LongTextStrategy | None
is_split: bool
async def initialize(self, pipeline_config: dict):
config = pipeline_config['output']['long-text-processing']
self.is_split = config['strategy'] == 'split'
if config['strategy'] == 'none':
self.strategy_impl = None
return
@@ -93,23 +90,8 @@ class LongTextProcessStage(stage.PipelineStage):
len(str(query.resp_message_chain[-1]))
> query.pipeline_config['output']['long-text-processing']['threshold']
):
if self.is_split:
original_text = str(query.resp_message_chain[-1])
threshold = query.pipeline_config['output']['long-text-processing']['threshold']
segments = self.strategy_impl.split_text(original_text, threshold)
# Replace the last chain with the first segment, store extra segments separately
# to avoid interfering with existing multi-chain scenarios (e.g. agent tool calls)
query.resp_message_chain[-1] = platform_message.MessageChain(
[platform_message.Plain(text=segments[0])]
)
if len(segments) > 1:
query.set_variable(
'_longtext_split_extra_chains',
[platform_message.MessageChain([platform_message.Plain(text=seg)]) for seg in segments[1:]],
)
else:
query.resp_message_chain[-1] = platform_message.MessageChain(
await self.strategy_impl.process(str(query.resp_message_chain[-1]), query)
)
query.resp_message_chain[-1] = platform_message.MessageChain(
await self.strategy_impl.process(str(query.resp_message_chain[-1]), query)
)
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)

View File

@@ -1,224 +0,0 @@
from __future__ import annotations
import re
from .. import strategy as strategy_model
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
import langbot_plugin.api.entities.builtin.platform.message as platform_message
@strategy_model.strategy_class('split')
class SplitStrategy(strategy_model.LongTextStrategy):
"""Split long text into multiple message segments with Markdown awareness."""
async def process(self, message: str, query: pipeline_query.Query) -> list[platform_message.MessageComponent]:
segments = self.split_text(
message,
query.pipeline_config['output']['long-text-processing']['threshold'],
)
return [platform_message.Plain(text=segments[0])] if segments else []
def split_text(self, text: str, max_length: int) -> list[str]:
"""Split text into segments respecting Markdown structure.
Priority:
1. Markdown structural boundaries (headings, code blocks, horizontal rules)
2. Paragraph breaks (blank lines)
3. List item boundaries
4. Line breaks
5. Hard cut (fallback)
"""
if len(text) <= max_length:
return [text]
blocks = self._parse_markdown_blocks(text)
return self._merge_blocks(blocks, max_length)
def _parse_markdown_blocks(self, text: str) -> list[str]:
"""Parse text into Markdown-aware blocks.
Keeps code blocks intact and splits the rest by structural elements.
"""
blocks: list[str] = []
lines = text.split('\n')
current_block: list[str] = []
in_code_block = False
for line in lines:
stripped = line.strip()
# Toggle fenced code block state
if stripped.startswith('```'):
if in_code_block:
# End of code block - close it as one block
current_block.append(line)
blocks.append('\n'.join(current_block))
current_block = []
in_code_block = False
continue
else:
# Start of code block - flush current block first
if current_block:
blocks.append('\n'.join(current_block))
current_block = []
current_block.append(line)
in_code_block = True
continue
if in_code_block:
current_block.append(line)
continue
# Heading (# ...) - start a new block
if re.match(r'^#{1,6}\s', stripped):
if current_block:
blocks.append('\n'.join(current_block))
current_block = []
current_block.append(line)
continue
# Horizontal rule (---, ***, ___) - start a new block
if re.match(r'^(-{3,}|\*{3,}|_{3,})\s*$', stripped):
if current_block:
blocks.append('\n'.join(current_block))
current_block = []
blocks.append(line)
continue
# Blank line - paragraph boundary
if stripped == '':
if current_block:
current_block.append(line)
blocks.append('\n'.join(current_block))
current_block = []
continue
current_block.append(line)
# Flush remaining (including unclosed code blocks)
if current_block:
blocks.append('\n'.join(current_block))
return [b for b in blocks if b.strip()]
def _merge_blocks(self, blocks: list[str], max_length: int) -> list[str]:
"""Merge small blocks greedily until approaching max_length.
If a single block exceeds max_length, split it by lines as fallback.
"""
segments: list[str] = []
current = ''
for block in blocks:
candidate = (current + '\n\n' + block) if current else block
if len(candidate) <= max_length:
current = candidate
else:
# Flush current segment
if current:
segments.append(current)
# Check if this single block fits
if len(block) <= max_length:
current = block
else:
# Block too large - split it by lines
for part in self._split_large_block(block, max_length):
segments.append(part)
current = ''
if current:
segments.append(current)
return [s for s in segments if s.strip()]
def _split_large_block(self, block: str, max_length: int) -> list[str]:
"""Split an oversized block by lines, preserving code block fences.
For single-line plain text (no newlines), falls back to splitting at
natural language boundaries (spaces, punctuation).
"""
lines = block.split('\n')
# Single long line with no newlines - use plain text splitting
if len(lines) == 1:
return self._split_plain_text(block, max_length)
is_code_block = lines[0].strip().startswith('```')
segments: list[str] = []
current_lines: list[str] = []
current_len = 0
# For code blocks, track the opening fence to re-apply on continuations
code_fence = lines[0] if is_code_block else ''
for i, line in enumerate(lines):
line_len = len(line) + 1 # +1 for newline
# Single line exceeds limit on its own - split it first
if line_len > max_length:
if current_lines:
seg = '\n'.join(current_lines)
if is_code_block and not seg.rstrip().endswith('```'):
seg += '\n```'
segments.append(seg)
current_lines = []
current_len = 0
for part in self._split_plain_text(line, max_length):
segments.append(part)
continue
if current_len + line_len > max_length and current_lines:
segment = '\n'.join(current_lines)
# Close code block fence if splitting mid-code-block
if is_code_block and not segment.rstrip().endswith('```'):
segment += '\n```'
segments.append(segment)
current_lines = []
current_len = 0
# Re-open code block fence for continuation
if is_code_block and i < len(lines) - 1 and not line.strip().startswith('```'):
current_lines.append(code_fence)
current_len = len(code_fence) + 1
current_lines.append(line)
current_len += line_len
if current_lines:
segments.append('\n'.join(current_lines))
return segments
def _split_plain_text(self, text: str, max_length: int) -> list[str]:
"""Split a long plain text string (no newlines) at word/space boundaries."""
if len(text) <= max_length:
return [text]
segments: list[str] = []
remaining = text
while remaining:
if len(remaining) <= max_length:
segments.append(remaining)
break
chunk = remaining[:max_length]
min_pos = int(max_length * 0.3)
# Try to find a space to split at
pos = chunk.rfind(' ')
if pos >= min_pos:
split_pos = pos
else:
# Hard cut as last resort
split_pos = max_length
segments.append(remaining[:split_pos].rstrip())
remaining = remaining[split_pos:].lstrip()
return [s for s in segments if s]

View File

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

View File

@@ -13,6 +13,7 @@ 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.events as events
from ..utils import importutil
from .config_coercion import coerce_pipeline_config
import langbot_plugin.api.entities.builtin.provider.session as provider_session
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
@@ -420,6 +421,14 @@ class PipelineManager:
elif isinstance(pipeline_entity, dict):
pipeline_entity = persistence_pipeline.LegacyPipeline(**pipeline_entity)
coerce_pipeline_config(
pipeline_entity.config,
getattr(self.ap, 'pipeline_config_meta_trigger', {'name': 'trigger', 'stages': []}),
getattr(self.ap, 'pipeline_config_meta_safety', {'name': 'safety', 'stages': []}),
getattr(self.ap, 'pipeline_config_meta_ai', {'name': 'ai', 'stages': []}),
getattr(self.ap, 'pipeline_config_meta_output', {'name': 'output', 'stages': []}),
)
# initialize stage containers according to pipeline_entity.stages
stage_containers: list[StageInstContainer] = []
for stage_name in pipeline_entity.stages:

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

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

View File

@@ -55,15 +55,4 @@ class SendResponseBackStage(stage.PipelineStage):
quote_origin=quote_origin,
)
# Send extra chains produced by long text split strategy
extra_chains = query.get_variable('_longtext_split_extra_chains')
if extra_chains:
for chain in extra_chains:
await query.adapter.reply_message(
message_source=query.message_event,
message=chain,
quote_origin=False,
)
query.set_variable('_longtext_split_extra_chains', None)
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)

View File

@@ -282,6 +282,8 @@ class PlatformManager:
return runtime_bot
async def get_bot_by_uuid(self, bot_uuid: str) -> RuntimeBot | None:
if self.websocket_proxy_bot and self.websocket_proxy_bot.bot_entity.uuid == bot_uuid:
return self.websocket_proxy_bot
for bot in self.bots:
if bot.bot_entity.uuid == bot_uuid:
return bot

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

@@ -37,16 +37,24 @@ class WebSocketSession:
id: str
message_lists: dict[str, list[WebSocketMessage]] = {}
"""消息列表 {pipeline_uuid: [messages]}"""
stream_message_indexes: dict[str, dict[str, int]] = {}
"""流式消息索引 {pipeline_uuid: {resp_message_id: message_index}}"""
def __init__(self, id: str):
self.id = id
self.message_lists = {}
self.stream_message_indexes = {}
def get_message_list(self, pipeline_uuid: str) -> list[WebSocketMessage]:
if pipeline_uuid not in self.message_lists:
self.message_lists[pipeline_uuid] = []
return self.message_lists[pipeline_uuid]
def get_stream_message_indexes(self, pipeline_uuid: str) -> dict[str, int]:
if pipeline_uuid not in self.stream_message_indexes:
self.stream_message_indexes[pipeline_uuid] = {}
return self.stream_message_indexes[pipeline_uuid]
class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
"""WebSocket适配器 - 支持双向实时通信"""
@@ -89,20 +97,46 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
target_id: str,
message: platform_message.MessageChain,
) -> dict:
"""发送消息 - 这里用于主动推送消息到前端"""
message_data = {
'type': 'bot_message',
'target_type': target_type,
'target_id': target_id,
'content': str(message),
'message_chain': [component.__dict__ for component in message],
'timestamp': datetime.now().isoformat(),
}
"""发送消息 - 这里用于主动推送消息到前端
# 推送到所有相关连接
await self.outbound_message_queue.put(message_data)
对于 WebSocket 适配器,我们需要将消息广播到正确的 pipeline 连接。
target_id 可能是 launcher_id如 websocket_xxx或 pipeline_uuid。
我们需要尝试两种方式来确保消息能够送达。
"""
# 获取当前的 pipeline_uuid
pipeline_uuid = self.ap.platform_mgr.websocket_proxy_bot.bot_entity.use_pipeline_uuid
session_type = 'group' if target_type == 'group' else 'person'
return message_data
# 选择会话
session = self.websocket_group_session if session_type == 'group' else self.websocket_person_session
# 生成唯一消息ID
msg_id = len(session.get_message_list(pipeline_uuid)) + 1
message_data = WebSocketMessage(
id=msg_id,
role='assistant',
content=str(message),
message_chain=[component.__dict__ for component in message],
timestamp=datetime.now().isoformat(),
is_final=True,
)
# 保存到历史记录
session.get_message_list(pipeline_uuid).append(message_data)
# 直接广播到当前pipeline的连接
await ws_connection_manager.broadcast_to_pipeline(
pipeline_uuid,
{
'type': 'response',
'session_type': session_type,
'data': message_data.model_dump(),
},
session_type=session_type,
)
return message_data.model_dump()
async def reply_message(
self,
@@ -169,10 +203,16 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
pipeline_uuid = self.ap.platform_mgr.websocket_proxy_bot.bot_entity.use_pipeline_uuid
session_type = 'group' if isinstance(message_source, platform_events.GroupMessage) else 'person'
message_list = session.get_message_list(pipeline_uuid)
stream_message_indexes = session.get_stream_message_indexes(pipeline_uuid)
# 检查是否是新的流式消息通过bot_message对象判断
# 如果列表为空或者最后一条消息已经is_final=True则创建新消息
if not message_list or message_list[-1].is_final:
# Streaming messages in LangBot have a stable resp_message_id during the same assistant reply.
# Use it as the primary key to avoid overwriting an old card from a previous reply.
resp_message_id = str(getattr(bot_message, 'resp_message_id', '') or '')
existing_index = stream_message_indexes.get(resp_message_id) if resp_message_id else None
message_is_final = is_final and bot_message.tool_calls is None
if existing_index is None or existing_index >= len(message_list):
# 创建新消息
msg_id = len(message_list) + 1
message_data = WebSocketMessage(
@@ -181,27 +221,31 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
content=str(message),
message_chain=[component.__dict__ for component in message],
timestamp=datetime.now().isoformat(),
is_final=is_final and bot_message.tool_calls is None,
is_final=message_is_final,
)
# 只有在is_final时才保存到历史记录
if is_final and bot_message.tool_calls is None:
message_list.append(message_data)
# 立即添加到历史记录即使is_final=False以便后续块可以更新它
message_list.append(message_data)
if resp_message_id:
stream_message_indexes[resp_message_id] = len(message_list) - 1
else:
# 更新最后一条消息
msg_id = message_list[-1].id
# 更新同一条流式消息
old_message = message_list[existing_index]
msg_id = old_message.id
message_data = WebSocketMessage(
id=msg_id,
role='assistant',
content=str(message),
message_chain=[component.__dict__ for component in message],
timestamp=message_list[-1].timestamp, # 保持原始时间戳
is_final=is_final and bot_message.tool_calls is None,
timestamp=old_message.timestamp, # 保持原始时间戳
is_final=message_is_final,
)
# 如果是final更新历史记录中的最后一条
if is_final and bot_message.tool_calls is None:
message_list[-1] = message_data
# 更新历史记录中的对应消息
message_list[existing_index] = message_data
if message_is_final and resp_message_id:
stream_message_indexes.pop(resp_message_id, None)
# 直接广播到所有该pipeline的连接包含session_type信息
await ws_connection_manager.broadcast_to_pipeline(
@@ -410,6 +454,10 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
if session_type == 'person':
if pipeline_uuid in self.websocket_person_session.message_lists:
self.websocket_person_session.message_lists[pipeline_uuid] = []
if pipeline_uuid in self.websocket_person_session.stream_message_indexes:
self.websocket_person_session.stream_message_indexes[pipeline_uuid] = {}
else:
if pipeline_uuid in self.websocket_group_session.message_lists:
self.websocket_group_session.message_lists[pipeline_uuid] = []
if pipeline_uuid in self.websocket_group_session.stream_message_indexes:
self.websocket_group_session.stream_message_indexes[pipeline_uuid] = {}

View File

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

View File

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

View File

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

View File

@@ -337,7 +337,14 @@ class RuntimeConnectionHandler(handler.Handler):
)
messages_obj = [provider_message.Message.model_validate(message) for message in messages]
funcs_obj = [resource_tool.LLMTool.model_validate(func) for func in funcs]
# The func field is excluded during model_dump() in plugin side (marked as exclude=True),
# but it's a required field for LLMTool validation. We need to provide a placeholder
# function when reconstructing the LLMTool objects from serialized data.
async def _placeholder_func(**kwargs):
pass
funcs_obj = [resource_tool.LLMTool.model_validate({**func, 'func': _placeholder_func}) for func in funcs]
result = await llm_model.provider.invoke_llm(
query=None,
@@ -558,6 +565,16 @@ class RuntimeConnectionHandler(handler.Handler):
except Exception as e:
return _make_rag_error_response(e, 'FileServiceError', storage_path=storage_path)
@self.action(PluginToRuntimeAction.LIST_PARSERS)
async def list_parsers(data: dict[str, Any]) -> handler.ActionResponse:
"""Plugin requests host to list available parser plugins."""
mime_type = data.get('mime_type')
try:
parsers = await self.ap.knowledge_service.list_parsers(mime_type)
return handler.ActionResponse.success(data={'parsers': parsers})
except Exception as e:
return _make_rag_error_response(e, 'ParserDiscoveryError', mime_type=mime_type)
@self.action(PluginToRuntimeAction.INVOKE_PARSER)
async def invoke_parser(data: dict[str, Any]) -> handler.ActionResponse:
"""Plugin requests host to invoke a parser plugin."""
@@ -582,6 +599,98 @@ 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"""
@@ -888,7 +997,7 @@ 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

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

View File

@@ -4,6 +4,7 @@ import json
import copy
import typing
from .. import runner
from ..modelmgr import requester as modelmgr_requester
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
import langbot_plugin.api.entities.builtin.provider.message as provider_message
import langbot_plugin.api.entities.builtin.rag.context as rag_context
@@ -26,29 +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)
@@ -74,7 +160,14 @@ class LocalAgentRunner(runner.RequestRunner):
self.ap.logger.warning(f'Knowledge base {kb_uuid} not found, skipping')
continue
result = await kb.retrieve(user_message_text)
result = await kb.retrieve(
user_message_text,
settings={
'bot_uuid': query.bot_uuid or '',
'sender_id': str(query.sender_id),
'session_name': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
},
)
if result:
all_results.extend(result)
@@ -113,51 +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:
@@ -169,21 +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,
@@ -198,7 +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:
@@ -239,7 +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
@@ -247,39 +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:
@@ -291,15 +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,
@@ -312,12 +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

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

View File

@@ -2,7 +2,7 @@ import langbot
semantic_version = f'v{langbot.__version__}'
required_database_version = 19
required_database_version = 24
"""Tag the version of the database schema, used to check if the database needs to be migrated"""
debug_mode = False

View File

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

View File

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

View File

@@ -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": [
{
@@ -95,11 +98,12 @@
"max": 0
},
"misc": {
"hide-exception": true,
"exception-handling": "show-hint",
"failure-hint": "Request failed.",
"at-sender": true,
"quote-origin": true,
"track-function-calls": false,
"remove-think": false
}
}
}
}

View File

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

View File

@@ -37,10 +37,6 @@ stages:
label:
en_US: Convert to Image
zh_Hans: 转换为图片
- name: split
label:
en_US: Split into Multiple Messages
zh_Hans: 分割为多条消息发送
- name: none
label:
en_US: None
@@ -82,13 +78,39 @@ stages:
en_US: Misc
zh_Hans: 杂项
config:
- name: hide-exception
- name: exception-handling
label:
en_US: Hide Exception
zh_Hans: 不输出异常信息给用户
type: boolean
en_US: Exception Handling Strategy
zh_Hans: 异常处理策略
description:
en_US: Controls how error messages are displayed to the user when an AI request fails
zh_Hans: 控制 AI 请求失败时向用户展示错误信息的方式
type: select
required: true
default: true
default: show-hint
options:
- name: show-error
label:
en_US: Show Full Error
zh_Hans: 显示完整报错信息
- name: show-hint
label:
en_US: Show Failure Hint
zh_Hans: 仅文字提示
- name: hide
label:
en_US: Hide All
zh_Hans: 不显示任何异常信息
- name: failure-hint
label:
en_US: Failure Hint Text
zh_Hans: 失败提示文本
description:
en_US: The text to display when a request fails. Only effective when Exception Handling Strategy is set to "Show Failure Hint"
zh_Hans: 请求失败时显示的提示文本,仅在异常处理策略设置为"仅文字提示"时生效
type: string
required: false
default: 'Request failed.'
- name: at-sender
label:
en_US: At Sender
@@ -123,3 +145,4 @@ stages:
type: boolean
required: true
default: false

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}},

View File

@@ -0,0 +1,113 @@
"""Unit tests for config_coercion module"""
from __future__ import annotations
import pytest
from langbot.pkg.pipeline.config_coercion import _coerce_value, coerce_pipeline_config
class TestCoerceValue:
"""Tests for _coerce_value function"""
def test_none_passthrough(self):
assert _coerce_value(None, 'integer') is None
assert _coerce_value(None, 'boolean') is None
def test_string_to_integer(self):
assert _coerce_value('120', 'integer') == 120
assert _coerce_value('0', 'integer') == 0
assert _coerce_value('-5', 'integer') == -5
def test_integer_passthrough(self):
assert _coerce_value(42, 'integer') == 42
def test_string_to_float(self):
assert _coerce_value('3.14', 'number') == 3.14
assert _coerce_value('3.14', 'float') == 3.14
def test_int_to_float(self):
assert _coerce_value(3, 'number') == 3.0
assert isinstance(_coerce_value(3, 'number'), float)
def test_float_passthrough(self):
assert _coerce_value(3.14, 'float') == 3.14
def test_string_to_bool(self):
assert _coerce_value('true', 'boolean') is True
assert _coerce_value('True', 'boolean') is True
assert _coerce_value('false', 'boolean') is False
assert _coerce_value('False', 'boolean') is False
def test_bool_passthrough(self):
assert _coerce_value(True, 'boolean') is True
assert _coerce_value(False, 'boolean') is False
def test_invalid_bool_string_raises(self):
with pytest.raises(ValueError):
_coerce_value('notabool', 'boolean')
def test_unknown_type_passthrough(self):
assert _coerce_value('hello', 'string') == 'hello'
assert _coerce_value('hello', 'unknown') == 'hello'
def test_invalid_integer_raises(self):
with pytest.raises(ValueError):
_coerce_value('abc', 'integer')
class TestCoercePipelineConfig:
"""Tests for coerce_pipeline_config function"""
def _make_meta(self, section_name: str, stage_name: str, fields: list[dict]) -> dict:
return {
'name': section_name,
'stages': [{'name': stage_name, 'config': fields}],
}
def test_coerce_integer_in_config(self):
config = {'trigger': {'misc': {'timeout': '120'}}}
meta = self._make_meta('trigger', 'misc', [{'name': 'timeout', 'type': 'integer'}])
coerce_pipeline_config(config, meta)
assert config['trigger']['misc']['timeout'] == 120
def test_coerce_boolean_in_config(self):
config = {'output': {'misc': {'at-sender': 'true'}}}
meta = self._make_meta('output', 'misc', [{'name': 'at-sender', 'type': 'boolean'}])
coerce_pipeline_config(config, meta)
assert config['output']['misc']['at-sender'] is True
def test_missing_section_skipped(self):
config = {'ai': {}}
meta = self._make_meta('trigger', 'misc', [{'name': 'x', 'type': 'integer'}])
coerce_pipeline_config(config, meta) # should not raise
def test_missing_field_skipped(self):
config = {'trigger': {'misc': {}}}
meta = self._make_meta('trigger', 'misc', [{'name': 'nonexistent', 'type': 'integer'}])
coerce_pipeline_config(config, meta) # should not raise
def test_invalid_value_logs_warning(self, caplog):
config = {'trigger': {'misc': {'timeout': 'abc'}}}
meta = self._make_meta('trigger', 'misc', [{'name': 'timeout', 'type': 'integer'}])
import logging
with caplog.at_level(logging.WARNING):
coerce_pipeline_config(config, meta)
assert config['trigger']['misc']['timeout'] == 'abc' # unchanged
assert 'Failed to coerce' in caplog.text
def test_empty_metadata(self):
config = {'trigger': {'misc': {'timeout': '120'}}}
coerce_pipeline_config(config) # no metadata args, should not raise
def test_multiple_metadata(self):
config = {
'trigger': {'misc': {'timeout': '120'}},
'output': {'misc': {'at-sender': 'false'}},
}
meta_trigger = self._make_meta('trigger', 'misc', [{'name': 'timeout', 'type': 'integer'}])
meta_output = self._make_meta('output', 'misc', [{'name': 'at-sender', 'type': 'boolean'}])
coerce_pipeline_config(config, meta_trigger, meta_output)
assert config['trigger']['misc']['timeout'] == 120
assert config['output']['misc']['at-sender'] is False

517
uv.lock generated
View File

@@ -1,5 +1,5 @@
version = 1
revision = 2
revision = 3
requires-python = ">=3.11, <4.0"
resolution-markers = [
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[[package]]
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version = "12.9.4"
source = { registry = "https://pypi.org/simple" }
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{ name = "cuda-pathfinder", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
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[[package]]
name = "cuda-pathfinder"
version = "1.4.1"
source = { registry = "https://pypi.org/simple" }
wheels = [
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[[package]]
name = "dashscope"
version = "1.25.10"
@@ -1088,7 +1112,7 @@ wheels = [
[[package]]
name = "flask"
version = "3.1.2"
version = "3.1.3"
source = { registry = "https://pypi.org/simple" }
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{ name = "werkzeug" },
]
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version = "1.5.3"
source = { registry = "https://pypi.org/simple" }
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[[package]]
name = "jsonpatch"
version = "1.33"
@@ -1799,7 +1832,7 @@ wheels = [
[[package]]
name = "langbot"
version = "4.8.7"
version = "4.9.3"
source = { editable = "." }
dependencies = [
{ name = "aiocqhttp" },
@@ -1895,7 +1928,7 @@ requires-dist = [
{ name = "botocore", specifier = ">=1.42.39" },
{ name = "certifi", specifier = ">=2025.4.26" },
{ name = "chardet", specifier = ">=5.2.0" },
{ name = "chromadb", specifier = ">=0.4.24" },
{ name = "chromadb", specifier = ">=1.0.0,<2.0.0" },
{ name = "colorlog", specifier = "~=6.6.0" },
{ name = "cryptography", specifier = ">=44.0.3" },
{ name = "dashscope", specifier = ">=1.25.10" },
@@ -1904,7 +1937,7 @@ requires-dist = [
{ name = "ebooklib", specifier = ">=0.18" },
{ name = "gewechat-client", specifier = ">=0.1.5" },
{ name = "html2text", specifier = ">=2024.2.26" },
{ name = "langbot-plugin", specifier = "==0.2.7" },
{ name = "langbot-plugin", specifier = "==0.3.2" },
{ name = "langchain", specifier = ">=0.2.0" },
{ name = "langchain-text-splitters", specifier = ">=0.0.1" },
{ name = "lark-oapi", specifier = ">=1.4.15" },
@@ -1927,7 +1960,7 @@ requires-dist = [
{ name = "pymilvus", specifier = ">=2.6.4" },
{ name = "pynacl", specifier = ">=1.5.0" },
{ name = "pypdf2", specifier = ">=3.0.1" },
{ name = "pyseekdb", specifier = "==1.0.0b7" },
{ name = "pyseekdb", specifier = "==1.1.0.post3" },
{ name = "python-docx", specifier = ">=1.1.0" },
{ name = "python-socks", specifier = ">=2.7.1" },
{ name = "python-telegram-bot", specifier = ">=22.0" },
@@ -1960,7 +1993,7 @@ dev = [
[[package]]
name = "langbot-plugin"
version = "0.2.7"
version = "0.3.2"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiofiles" },
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{ name = "websockets" },
]
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"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

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

View File

@@ -11,7 +11,7 @@ import {
FormMessage,
} from '@/components/ui/form';
import DynamicFormItemComponent from '@/app/home/components/dynamic-form/DynamicFormItemComponent';
import { useCallback, useEffect, useRef } from 'react';
import { useEffect, useRef } from 'react';
import { extractI18nObject } from '@/i18n/I18nProvider';
import { useTranslation } from 'react-i18next';
@@ -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

@@ -422,12 +422,12 @@ export default function HomeSidebar({
const language = localStorage.getItem('langbot_language');
if (language === 'zh-Hans' || language === 'zh-Hant') {
window.open(
'https://docs.langbot.app/zh/insight/guide.html',
'https://docs.langbot.app/zh/insight/guide',
'_blank',
);
} else {
window.open(
'https://docs.langbot.app/en/insight/guide.html',
'https://docs.langbot.app/en/insight/guide',
'_blank',
);
}

View File

@@ -23,9 +23,9 @@ export const sidebarConfigList = [
route: '/home/bots',
description: t('bots.description'),
helpLink: {
en_US: 'https://docs.langbot.app/en/usage/platforms/readme.html',
zh_Hans: 'https://docs.langbot.app/zh/usage/platforms/readme.html',
ja_JP: 'https://docs.langbot.app/ja/usage/platforms/readme.html',
en_US: 'https://docs.langbot.app/en/usage/platforms/readme',
zh_Hans: 'https://docs.langbot.app/zh/usage/platforms/readme',
ja_JP: 'https://docs.langbot.app/ja/usage/platforms/readme',
},
}),
new SidebarChildVO({
@@ -44,9 +44,9 @@ export const sidebarConfigList = [
route: '/home/pipelines',
description: t('pipelines.description'),
helpLink: {
en_US: 'https://docs.langbot.app/en/usage/pipelines/readme.html',
zh_Hans: 'https://docs.langbot.app/zh/usage/pipelines/readme.html',
ja_JP: 'https://docs.langbot.app/ja/usage/pipelines/readme.html',
en_US: 'https://docs.langbot.app/en/usage/pipelines/readme',
zh_Hans: 'https://docs.langbot.app/zh/usage/pipelines/readme',
ja_JP: 'https://docs.langbot.app/ja/usage/pipelines/readme',
},
}),
new SidebarChildVO({
@@ -65,8 +65,8 @@ export const sidebarConfigList = [
route: '/home/monitoring',
description: t('monitoring.description'),
helpLink: {
en_US: 'https://docs.langbot.app/en/features/monitoring.html',
zh_Hans: 'https://docs.langbot.app/zh/features/monitoring.html',
en_US: '',
zh_Hans: '',
},
}),
new SidebarChildVO({
@@ -84,9 +84,9 @@ export const sidebarConfigList = [
route: '/home/knowledge',
description: t('knowledge.description'),
helpLink: {
en_US: 'https://docs.langbot.app/en/usage/knowledge/readme.html',
zh_Hans: 'https://docs.langbot.app/zh/usage/knowledge/readme.html',
ja_JP: 'https://docs.langbot.app/ja/usage/knowledge/readme.html',
en_US: 'https://docs.langbot.app/en/usage/knowledge/readme',
zh_Hans: 'https://docs.langbot.app/zh/usage/knowledge/readme',
ja_JP: 'https://docs.langbot.app/ja/usage/knowledge/readme',
},
}),
new SidebarChildVO({
@@ -105,9 +105,9 @@ export const sidebarConfigList = [
route: '/home/plugins',
description: t('plugins.description'),
helpLink: {
en_US: 'https://docs.langbot.app/en/usage/plugin/plugin-intro.html',
zh_Hans: 'https://docs.langbot.app/zh/usage/plugin/plugin-intro.html',
ja_JP: 'https://docs.langbot.app/ja/usage/plugin/plugin-intro.html',
en_US: 'https://docs.langbot.app/en/usage/plugin/plugin-intro',
zh_Hans: 'https://docs.langbot.app/zh/usage/plugin/plugin-intro',
ja_JP: 'https://docs.langbot.app/ja/usage/plugin/plugin-intro',
},
}),
];

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

@@ -36,11 +36,11 @@ export default function NewVersionDialog({
const getUpdateDocsUrl = () => {
const language = i18n.language;
if (language === 'zh-Hans' || language === 'zh-Hant') {
return 'https://docs.langbot.app/zh/deploy/update.html';
return 'https://docs.langbot.app/zh/deploy/update';
} else if (language === 'ja-JP') {
return 'https://docs.langbot.app/ja/deploy/update.html';
return 'https://docs.langbot.app/ja/deploy/update';
} else {
return 'https://docs.langbot.app/en/deploy/update.html';
return 'https://docs.langbot.app/en/deploy/update';
}
};

View File

@@ -22,6 +22,7 @@ import { Button } from '@/components/ui/button';
import { useTranslation } from 'react-i18next';
import { httpClient } from '@/app/infra/http/HttpClient';
import { KnowledgeBase } from '@/app/infra/entities/api';
import { CustomApiError } from '@/app/infra/entities/common';
import { toast } from 'sonner';
import KBForm from '@/app/home/knowledge/components/kb-form/KBForm';
import KBDoc from '@/app/home/knowledge/components/kb-docs/KBDoc';
@@ -68,7 +69,9 @@ export default function KBDetailDialog({
setKbInfo(resp.base);
} catch (e) {
console.error('Failed to load KB info:', e);
toast.error(t('knowledge.loadKnowledgeBaseFailed'));
toast.error(
t('knowledge.loadKnowledgeBaseFailed') + (e as CustomApiError).msg,
);
}
}
@@ -136,7 +139,9 @@ export default function KBDetailDialog({
onKbDeleted();
} catch (e) {
console.error('Failed to delete KB:', e);
toast.error(t('knowledge.deleteKnowledgeBaseFailed'));
toast.error(
t('knowledge.deleteKnowledgeBaseFailed') + (e as CustomApiError).msg,
);
} finally {
setShowDeleteConfirm(false);
}

View File

@@ -12,7 +12,7 @@ import { httpClient } from '@/app/infra/http/HttpClient';
import { toast } from 'sonner';
import { useTranslation } from 'react-i18next';
import { ParserInfo } from '@/app/infra/entities/api';
import { I18nObject } from '@/app/infra/entities/common';
import { CustomApiError, I18nObject } from '@/app/infra/entities/common';
import { extractI18nObject } from '@/i18n/I18nProvider';
interface FileUploadZoneProps {
@@ -97,7 +97,9 @@ export default function FileUploadZone({
onUploadSuccess();
} catch (error) {
console.error('File upload failed:', error);
const errorMessage = t('knowledge.documentsTab.uploadError');
const errorMessage =
t('knowledge.documentsTab.uploadError') +
(error as CustomApiError).msg;
toast.error(errorMessage, { id: toastId });
onUploadError(errorMessage);
} finally {

View File

@@ -1,7 +1,7 @@
import { useCallback, useEffect, useRef, useState } from 'react';
import { httpClient } from '@/app/infra/http/HttpClient';
import { KnowledgeBaseFile } from '@/app/infra/entities/api';
import { I18nObject } from '@/app/infra/entities/common';
import { I18nObject, CustomApiError } from '@/app/infra/entities/common';
import { columns, DocumentFile } from './documents/columns';
import { DataTable } from './documents/data-table';
import FileUploadZone from './FileUploadZone';
@@ -87,7 +87,10 @@ export default function KBDoc({
})
.catch((error) => {
console.error('Delete failed:', error);
toast.error(t('knowledge.documentsTab.fileDeleteFailed'));
toast.error(
t('knowledge.documentsTab.fileDeleteFailed') +
(error as CustomApiError).msg,
);
});
};

View File

@@ -1,4 +1,5 @@
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';
import { z } from 'zod';
@@ -23,6 +24,7 @@ import {
SelectValue,
} from '@/components/ui/select';
import { KnowledgeBase, KnowledgeEngine } from '@/app/infra/entities/api';
import { CustomApiError } from '@/app/infra/entities/common';
import { toast } from 'sonner';
import { extractI18nObject } from '@/i18n/I18nProvider';
import DynamicFormComponent from '@/app/home/components/dynamic-form/DynamicFormComponent';
@@ -217,7 +219,10 @@ export default function KBForm({
})
.catch((err) => {
console.error('update knowledge base failed', err);
toast.error(t('knowledge.updateKnowledgeBaseFailed'));
toast.error(
t('knowledge.updateKnowledgeBaseFailed') +
(err as CustomApiError).msg,
);
});
} else {
// Create knowledge base
@@ -228,17 +233,26 @@ export default function KBForm({
})
.catch((err) => {
console.error('create knowledge base failed', err);
toast.error(t('knowledge.createKnowledgeBaseFailed'));
toast.error(
t('knowledge.createKnowledgeBaseFailed') +
(err as CustomApiError).msg,
);
});
}
};
// 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
@@ -257,9 +271,12 @@ export default function KBForm({
<p className="text-muted-foreground">
{t('knowledge.noEnginesAvailable')}
</p>
<p className="text-sm text-muted-foreground">
<Link
href="/home/plugins"
className="text-sm text-primary hover:underline"
>
{t('knowledge.installEngineHint')}
</p>
</Link>
</div>
);
}

View File

@@ -0,0 +1,157 @@
'use client';
import { useState } from 'react';
import {
Dialog,
DialogContent,
DialogHeader,
DialogTitle,
DialogDescription,
DialogFooter,
} from '@/components/ui/dialog';
import { Button } from '@/components/ui/button';
import { useTranslation } from 'react-i18next';
import { httpClient } from '@/app/infra/http/HttpClient';
import { useAsyncTask, AsyncTaskStatus } from '@/hooks/useAsyncTask';
import { toast } from 'sonner';
import { Loader2 } from 'lucide-react';
interface KBMigrationDialogProps {
open: boolean;
onOpenChange: (open: boolean) => void;
internalKbCount: number;
externalKbCount: number;
onMigrationComplete: () => void;
}
export default function KBMigrationDialog({
open,
onOpenChange,
internalKbCount,
externalKbCount,
onMigrationComplete,
}: KBMigrationDialogProps) {
const { t } = useTranslation();
const [dismissing, setDismissing] = useState(false);
const asyncTask = useAsyncTask({
onSuccess: () => {
toast.success(t('knowledge.migration.success'));
onOpenChange(false);
onMigrationComplete();
},
onError: (error) => {
toast.error(`${t('knowledge.migration.error')}${error}`);
},
});
const handleMigration = async (installPlugin: boolean) => {
try {
const resp = await httpClient.executeRagMigration(installPlugin);
asyncTask.startTask(resp.task_id);
} catch {
toast.error(t('knowledge.migration.error'));
}
};
const handleDismiss = async () => {
setDismissing(true);
try {
await httpClient.dismissRagMigration();
onOpenChange(false);
} catch {
toast.error(t('knowledge.migration.dismissError'));
} finally {
setDismissing(false);
}
};
const isRunning = asyncTask.status === AsyncTaskStatus.RUNNING;
const isError = asyncTask.status === AsyncTaskStatus.ERROR;
const totalCount = internalKbCount + externalKbCount;
return (
<Dialog
open={open}
onOpenChange={(v) => {
if (!isRunning) onOpenChange(v);
}}
>
<DialogContent className="sm:max-w-md">
<DialogHeader>
<DialogTitle>{t('knowledge.migration.title')}</DialogTitle>
<DialogDescription>
{t('knowledge.migration.description')}
</DialogDescription>
</DialogHeader>
<div className="py-4 space-y-3">
{!isRunning && !isError && (
<p className="text-sm text-muted-foreground">
{t('knowledge.migration.detected', {
total: totalCount,
internal: internalKbCount,
external: externalKbCount,
})}
</p>
)}
{isRunning && (
<div className="flex items-center gap-3">
<Loader2 className="h-5 w-5 animate-spin text-primary" />
<p className="text-sm">{t('knowledge.migration.running')}</p>
</div>
)}
{isError && (
<div className="space-y-2">
<p className="text-sm text-destructive">
{t('knowledge.migration.error')}
</p>
{asyncTask.error && (
<p className="text-xs text-muted-foreground bg-muted p-2 rounded">
{asyncTask.error}
</p>
)}
</div>
)}
</div>
<DialogFooter className="flex flex-col gap-2 sm:flex-col">
{!isRunning && !isError && (
<>
<Button onClick={() => handleMigration(true)} className="w-full">
{t('knowledge.migration.startWithInstall')}
</Button>
<Button
variant="outline"
onClick={() => handleMigration(false)}
className="w-full"
>
{t('knowledge.migration.startDataOnly')}
</Button>
<p className="text-xs text-muted-foreground text-center">
{t('knowledge.migration.dataOnlyHint')}
</p>
</>
)}
{isError && (
<Button onClick={() => handleMigration(true)} className="w-full">
{t('knowledge.migration.retry')}
</Button>
)}
{!isRunning && (
<Button
variant="ghost"
onClick={handleDismiss}
disabled={dismissing}
className="w-full text-destructive hover:text-destructive"
>
{t('knowledge.migration.dismiss')}
</Button>
)}
</DialogFooter>
</DialogContent>
</Dialog>
);
}

View File

@@ -6,6 +6,7 @@ import { Button } from '@/components/ui/button';
import { Input } from '@/components/ui/input';
import { useTranslation } from 'react-i18next';
import { RetrieveResult } from '@/app/infra/entities/api';
import { CustomApiError } from '@/app/infra/entities/common';
import { toast } from 'sonner';
interface KBRetrieveGenericProps {
@@ -41,7 +42,7 @@ export default function KBRetrieveGeneric({
setResults(response.results);
} catch (error) {
console.error('Retrieve failed:', error);
toast.error(t('knowledge.retrieveError'));
toast.error(t('knowledge.retrieveError') + (error as CustomApiError).msg);
} finally {
setLoading(false);
}

View File

@@ -5,7 +5,6 @@
.knowledgeListContainer {
width: 100%;
margin-top: 2rem;
padding-left: 0.8rem;
padding-right: 0.8rem;
display: grid;

View File

@@ -7,6 +7,7 @@ import { useEffect, useState } from 'react';
import { KnowledgeBaseVO } from '@/app/home/knowledge/components/kb-card/KBCardVO';
import KBCard from '@/app/home/knowledge/components/kb-card/KBCard';
import KBDetailDialog from '@/app/home/knowledge/KBDetailDialog';
import KBMigrationDialog from '@/app/home/knowledge/components/kb-migration-dialog/KBMigrationDialog';
import { httpClient } from '@/app/infra/http/HttpClient';
import { KnowledgeBase } from '@/app/infra/entities/api';
@@ -18,10 +19,29 @@ export default function KnowledgePage() {
const [selectedKbId, setSelectedKbId] = useState<string>('');
const [detailDialogOpen, setDetailDialogOpen] = useState(false);
// Migration dialog state
const [migrationDialogOpen, setMigrationDialogOpen] = useState(false);
const [migrationInternalCount, setMigrationInternalCount] = useState(0);
const [migrationExternalCount, setMigrationExternalCount] = useState(0);
useEffect(() => {
getKnowledgeBaseList();
checkMigrationStatus();
}, []);
async function checkMigrationStatus() {
try {
const resp = await httpClient.getRagMigrationStatus();
if (resp.needed) {
setMigrationInternalCount(resp.internal_kb_count);
setMigrationExternalCount(resp.external_kb_count);
setMigrationDialogOpen(true);
}
} catch {
// Silently ignore - migration check is non-critical
}
}
async function getKnowledgeBaseList() {
const resp = await httpClient.getKnowledgeBases();
@@ -85,8 +105,20 @@ export default function KnowledgePage() {
getKnowledgeBaseList();
};
const handleMigrationComplete = () => {
getKnowledgeBaseList();
};
return (
<div>
<KBMigrationDialog
open={migrationDialogOpen}
onOpenChange={setMigrationDialogOpen}
internalKbCount={migrationInternalCount}
externalKbCount={migrationExternalCount}
onMigrationComplete={handleMigrationComplete}
/>
<KBDetailDialog
open={detailDialogOpen}
onOpenChange={setDetailDialogOpen}

View File

@@ -120,6 +120,8 @@ export default function PipelineFormComponent({
// Track unsaved changes by comparing current form values against a saved snapshot
const savedSnapshotRef = useRef<string>('');
// Track which dynamic form stages have completed their initial mount emission.
const initializedStagesRef = useRef<Set<string>>(new Set());
const watchedValues = form.watch();
const hasUnsavedChanges = useMemo(() => {
if (!isEditMode || !savedSnapshotRef.current) return false;
@@ -160,6 +162,7 @@ export default function PipelineFormComponent({
};
form.reset(loadedValues);
savedSnapshotRef.current = JSON.stringify(loadedValues);
initializedStagesRef.current.clear();
});
}
}, []);
@@ -235,6 +238,33 @@ export default function PipelineFormComponent({
});
}
// Called from DynamicFormComponent/N8nAuthFormComponent onSubmit callbacks.
// On the first emission for a stage (mount-time default filling), the
// snapshot is synchronously re-captured so that hasUnsavedChanges stays false.
function handleDynamicFormEmit(
formName: keyof FormValues,
stageName: string,
values: object,
) {
const stageKey = `${String(formName)}.${stageName}`;
const isFirstEmission = !initializedStagesRef.current.has(stageKey);
const currentValues =
// eslint-disable-next-line @typescript-eslint/no-explicit-any
(form.getValues(formName) as Record<string, any>) || {};
form.setValue(formName, {
...currentValues,
[stageName]: values,
});
if (isFirstEmission) {
initializedStagesRef.current.add(stageKey);
// Synchronously re-capture snapshot so that the useMemo comparison
// in the same render cycle still returns false.
savedSnapshotRef.current = JSON.stringify(form.getValues());
}
}
function renderDynamicForms(
stage: PipelineConfigStage,
formName: keyof FormValues,
@@ -264,13 +294,7 @@ export default function PipelineFormComponent({
{}
}
onSubmit={(values) => {
const currentValues =
// eslint-disable-next-line @typescript-eslint/no-explicit-any
(form.getValues(formName) as Record<string, any>) || {};
form.setValue(formName, {
...currentValues,
[stage.name]: values,
});
handleDynamicFormEmit(formName, stage.name, values);
}}
/>
</div>
@@ -302,13 +326,7 @@ export default function PipelineFormComponent({
{}
}
onSubmit={(values) => {
const currentValues =
// eslint-disable-next-line @typescript-eslint/no-explicit-any
(form.getValues(formName) as Record<string, any>) || {};
form.setValue(formName, {
...currentValues,
[stage.name]: values,
});
handleDynamicFormEmit(formName, stage.name, values);
}}
/>
</div>
@@ -333,13 +351,7 @@ export default function PipelineFormComponent({
(form.watch(formName) as Record<string, any>)?.[stage.name] || {}
}
onSubmit={(values) => {
const currentValues =
// eslint-disable-next-line @typescript-eslint/no-explicit-any
(form.getValues(formName) as Record<string, any>) || {};
form.setValue(formName, {
...currentValues,
[stage.name]: values,
});
handleDynamicFormEmit(formName, stage.name, values);
}}
/>
</div>

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(() => {
@@ -562,8 +524,7 @@ function MarketPageContent({
{/* Recommendation Lists */}
{!searchQuery &&
componentFilter === 'all' &&
selectedTags.length === 0 &&
currentPage === 1 && (
selectedTags.length === 0 && (
<div className="pt-4">
<RecommendationLists
lists={recommendationLists}

View File

@@ -1,6 +1,6 @@
'use client';
import { useState } from 'react';
import { useState, useRef, useEffect, useCallback } from 'react';
import { ChevronLeft, ChevronRight, Star } from 'lucide-react';
import { Button } from '@/components/ui/button';
import PluginMarketCardComponent from './plugin-market-card/PluginMarketCardComponent';
@@ -18,7 +18,7 @@ export interface RecommendationList {
plugins: PluginV4[];
}
const PAGE_SIZE = 4; // plugins per page in a recommendation row
// Match the main plugin grid: grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4
function pluginToVO(
plugin: PluginV4,
@@ -47,18 +47,53 @@ 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);
const [perPage, setPerPage] = useState(4);
const gridRef = useRef<HTMLDivElement>(null);
const plugins = list.plugins || [];
const totalPages = Math.ceil(plugins.length / PAGE_SIZE);
const start = page * PAGE_SIZE;
const visiblePlugins = plugins.slice(start, start + PAGE_SIZE);
// Measure how many columns the CSS grid actually renders
const measureCols = useCallback(() => {
if (!gridRef.current) return;
const style = window.getComputedStyle(gridRef.current);
const cols = style.gridTemplateColumns.split(' ').length;
setPerPage(cols);
}, []);
useEffect(() => {
measureCols();
const observer = new ResizeObserver(measureCols);
if (gridRef.current) observer.observe(gridRef.current);
return () => observer.disconnect();
}, [measureCols]);
// Auto-advance every 5 seconds
useEffect(() => {
if (plugins.length <= perPage) return;
const timer = setInterval(() => {
setPage((p) => {
const tp = Math.max(1, Math.ceil(plugins.length / perPage));
return p >= tp - 1 ? 0 : p + 1;
});
}, 5000);
return () => clearInterval(timer);
}, [plugins.length, perPage]);
const totalPages = Math.max(1, Math.ceil(plugins.length / perPage));
const safePage = Math.min(page, totalPages - 1);
if (safePage !== page) setPage(safePage);
const start = safePage * perPage;
const visiblePlugins = plugins.slice(start, start + perPage);
if (plugins.length === 0) return null;
@@ -77,19 +112,19 @@ function RecommendationListRow({
variant="ghost"
size="sm"
onClick={() => setPage((p) => Math.max(0, p - 1))}
disabled={page === 0}
disabled={safePage === 0}
className="h-7 w-7 p-0"
>
<ChevronLeft className="w-4 h-4" />
</Button>
<span className="text-xs text-muted-foreground px-1">
{page + 1} / {totalPages}
{safePage + 1} / {totalPages}
</span>
<Button
variant="ghost"
size="sm"
onClick={() => setPage((p) => Math.min(totalPages - 1, p + 1))}
disabled={page >= totalPages - 1}
disabled={safePage >= totalPages - 1}
className="h-7 w-7 p-0"
>
<ChevronRight className="w-4 h-4" />
@@ -97,7 +132,10 @@ function RecommendationListRow({
</div>
)}
</div>
<div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4 gap-6">
<div
ref={gridRef}
className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4 gap-6"
>
{visiblePlugins.map((plugin) => (
<PluginMarketCardComponent
key={plugin.author + ' / ' + plugin.name}
@@ -107,7 +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>
);
}
@@ -125,12 +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

@@ -1,6 +1,12 @@
import { PluginMarketCardVO } from './PluginMarketCardVO';
import { useTranslation } from 'react-i18next';
import { Badge } from '@/components/ui/badge';
import {
Tooltip,
TooltipContent,
TooltipProvider,
TooltipTrigger,
} from '@/components/ui/tooltip';
import {
Wrench,
AudioWaveform,
@@ -9,8 +15,9 @@ import {
ExternalLink,
Book,
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({
@@ -24,6 +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();
@@ -46,6 +90,13 @@ export default function PluginMarketCardComponent({
Parser: <FileText className="w-4 h-4" />,
};
// Plugins that only contain KnowledgeRetriever components are deprecated
const isDeprecated = (() => {
if (!cardVO.components) return false;
const keys = Object.keys(cardVO.components);
return keys.length > 0 && keys.every((k) => k === 'KnowledgeRetriever');
})();
return (
<div
className="w-[100%] h-auto min-h-[8rem] sm:min-h-[9rem] bg-white rounded-[10px] shadow-[0px_0px_4px_0_rgba(0,0,0,0.2)] p-3 sm:p-[1rem] hover:shadow-[0px_3px_6px_0_rgba(0,0,0,0.12)] transition-all duration-200 hover:scale-[1.005] dark:bg-[#1f1f22] relative"
@@ -66,8 +117,34 @@ export default function PluginMarketCardComponent({
<div className="text-[0.65rem] sm:text-[0.7rem] text-[#666] dark:text-[#999] truncate w-full">
{cardVO.pluginId}
</div>
<div className="text-base sm:text-[1.2rem] text-black dark:text-[#f0f0f0] truncate w-full">
{cardVO.label}
<div className="flex items-center gap-1.5 w-full min-w-0">
<div className="text-base sm:text-[1.2rem] text-black dark:text-[#f0f0f0] truncate">
{cardVO.label}
</div>
{isDeprecated && (
<TooltipProvider delayDuration={200}>
<Tooltip>
<TooltipTrigger
asChild
onClick={(e) => e.preventDefault()}
>
<Badge
variant="outline"
className="text-[0.6rem] px-1.5 py-0 h-4 flex-shrink-0 border-red-400 text-red-500 dark:border-red-500 dark:text-red-400 gap-0.5 cursor-help"
>
{t('market.deprecated')}
<Info className="w-2.5 h-2.5" />
</Badge>
</TooltipTrigger>
<TooltipContent
side="top"
className="max-w-[240px] text-xs"
>
{t('market.deprecatedTooltip')}
</TooltipContent>
</Tooltip>
</TooltipProvider>
)}
</div>
</div>
@@ -95,10 +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"
@@ -116,14 +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"
@@ -138,15 +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

@@ -262,6 +262,12 @@ export interface ApiRespSystemInfo {
limitation: SystemLimitation;
}
export interface RagMigrationStatusResp {
needed: boolean;
internal_kb_count: number;
external_kb_count: number;
}
export interface ApiRespPluginSystemStatus {
is_enable: boolean;
is_connected: boolean;

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

@@ -40,6 +40,7 @@ import {
ModelProvider,
ApiRespKnowledgeEngines,
ApiRespParsers,
RagMigrationStatusResp,
} from '@/app/infra/entities/api';
import { Plugin } from '@/app/infra/entities/plugin';
import { GetBotLogsRequest } from '@/app/infra/http/requestParam/bots/GetBotLogsRequest';
@@ -355,6 +356,7 @@ export class BackendClient extends BaseHttpClient {
is_active: boolean;
platform: string | null;
user_id: string | null;
user_name: string | null;
}>;
total: number;
}> {
@@ -383,6 +385,7 @@ export class BackendClient extends BaseHttpClient {
level: string;
platform: string | null;
user_id: string | null;
user_name: string | null;
runner_name: string | null;
variables: string | null;
role: string | null;
@@ -710,6 +713,23 @@ export class BackendClient extends BaseHttpClient {
return this.get('/api/v1/system/status/plugin-system');
}
// ============ RAG Migration API ============
public getRagMigrationStatus(): Promise<RagMigrationStatusResp> {
return this.get('/api/v1/knowledge/migration/status');
}
public executeRagMigration(
installPlugin: boolean = true,
): Promise<AsyncTaskCreatedResp> {
return this.post('/api/v1/knowledge/migration/execute', {
install_plugin: installPlugin,
});
}
public dismissRagMigration(): Promise<object> {
return this.post('/api/v1/knowledge/migration/dismiss');
}
public getPluginDebugInfo(): Promise<{
debug_url: string;
plugin_debug_key: string;

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);
@@ -284,6 +346,27 @@ export default function Login() {
</form>
</Form>
)}
<p className="text-xs text-center text-muted-foreground">
{t('common.agreementNotice')}{' '}
<a
href="https://langbot.app/privacy"
target="_blank"
rel="noopener noreferrer"
className="underline hover:text-foreground transition-colors"
>
{t('common.privacyPolicy')}
</a>{' '}
{t('common.and')}{' '}
<a
href={t('common.dataCollectionPolicyUrl')}
target="_blank"
rel="noopener noreferrer"
className="underline hover:text-foreground transition-colors"
>
{t('common.dataCollectionPolicy')}
</a>
</p>
</CardContent>
</Card>
</div>

View File

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

View File

@@ -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',
@@ -47,6 +51,12 @@ const enUS = {
copyFailed: 'Copy Failed',
test: 'Test',
forgotPassword: 'Forgot Password?',
agreementNotice: 'By continuing, you agree to our',
privacyPolicy: 'Privacy Policy',
and: 'and',
dataCollectionPolicy: 'Data Collection Policy',
dataCollectionPolicyUrl:
'https://docs.langbot.app/en/insight/data-collection-policy',
loading: 'Loading...',
fieldRequired: 'This field is required',
or: 'or',
@@ -230,6 +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',
@@ -273,6 +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',
@@ -483,6 +500,9 @@ const enUS = {
allComponents: 'All Components',
requestPlugin: 'Request Plugin',
viewDetails: 'View Details',
deprecated: 'Deprecated',
deprecatedTooltip:
'Please install the corresponding Knowledge Engine plugin.',
tags: {
filterByTags: 'Filter by Tags',
selected: 'selected',
@@ -707,7 +727,7 @@ const enUS = {
cannotChangeEmbeddingModel:
'Knowledge base created cannot be modified embedding model',
updateKnowledgeBaseSuccess: 'Knowledge base updated successfully',
updateKnowledgeBaseFailed: 'Knowledge base update failed',
updateKnowledgeBaseFailed: 'Knowledge base update failed: ',
documentsTab: {
name: 'Name',
status: 'Status',
@@ -717,14 +737,14 @@ const enUS = {
supportedFormats:
'Supports PDF, Word, TXT, Markdown, HTML, ZIP and other document formats',
uploadSuccess: 'File uploaded successfully!',
uploadError: 'File upload failed, please try again',
uploadError: 'File upload failed: ',
uploadingFile: 'Uploading file...',
fileSizeExceeded:
'File size exceeds 10MB limit. Please split into smaller files.',
actions: 'Actions',
delete: 'Delete File',
fileDeleteSuccess: 'File deleted successfully',
fileDeleteFailed: 'File deletion failed',
fileDeleteFailed: 'File deletion failed: ',
processing: 'Processing',
completed: 'Completed',
failed: 'Failed',
@@ -745,7 +765,7 @@ const enUS = {
content: 'Content',
fileName: 'File Name',
noResults: 'No results',
retrieveError: 'Retrieve failed',
retrieveError: 'Retrieve failed: ',
unknownEngine: 'Unknown Engine',
knowledgeEngine: 'Knowledge Engine',
knowledgeEngineRequired: 'Knowledge engine is required',
@@ -757,10 +777,10 @@ const enUS = {
engineSettingsReadonly: 'read-only in edit mode',
retrievalSettings: 'Retrieval Settings',
noEnginesAvailable: 'No knowledge base engines available',
installEngineHint: 'Please install a knowledge base plugin first',
createKnowledgeBaseFailed: 'Failed to create knowledge base',
loadKnowledgeBaseFailed: 'Failed to load knowledge base',
deleteKnowledgeBaseFailed: 'Failed to delete knowledge base',
installEngineHint: 'Please install a "Knowledge Engine" plugin first',
createKnowledgeBaseFailed: 'Failed to create knowledge base: ',
loadKnowledgeBaseFailed: 'Failed to load knowledge base: ',
deleteKnowledgeBaseFailed: 'Failed to delete knowledge base: ',
getKnowledgeBaseListError: 'Failed to get knowledge base list: ',
embeddingModel: 'Embedding Model',
embeddingModelRequired: 'Embedding model is required for this engine',
@@ -773,6 +793,23 @@ const enUS = {
retrieverConfiguration: 'Retriever Configuration',
retrieverInstallInfo: 'You can install Knowledge Retriever plugins from',
retrieverMarketLink: 'here',
migration: {
title: 'Knowledge Base Migration',
description:
'The new version has refactored the knowledge base into a plugin-based architecture, unifying built-in and external knowledge bases as "Knowledge Engine" plugins. Migration of legacy knowledge base data is required. Your old data has been automatically backed up in the database.',
detected:
'Found {{total}} knowledge base(s) to migrate ({{internal}} internal, {{external}} external).',
startWithInstall: 'Auto-install Plugin & Migrate',
startDataOnly: 'Migrate Data Only',
dataOnlyHint:
'"Migrate Data Only" is for offline/intranet environments. Please install the corresponding plugin manually after migration.',
dismiss: 'Discard Original Data',
running: 'Migrating knowledge bases, please wait...',
success: 'Knowledge base migration completed',
error: 'Knowledge base migration failed: ',
dismissError: 'Operation failed',
retry: 'Retry',
},
},
register: {
title: 'Initialize LangBot 👋',

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',
@@ -48,6 +52,12 @@ const jaJP = {
copyFailed: 'コピーに失敗しました',
test: 'テスト',
forgotPassword: 'パスワードを忘れた?',
agreementNotice: '続行することで、以下に同意したものとみなされます:',
privacyPolicy: 'プライバシーポリシー',
and: 'および',
dataCollectionPolicy: 'データ収集ポリシー',
dataCollectionPolicyUrl:
'https://docs.langbot.app/ja/insight/data-collection-policy',
loading: '読み込み中...',
fieldRequired: 'この項目は必須です',
or: 'または',
@@ -235,6 +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',
@@ -278,6 +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',
@@ -491,6 +508,9 @@ const jaJP = {
noTags: 'タグがありません',
},
viewDetails: '詳細を表示',
deprecated: '非推奨',
deprecatedTooltip:
'対応する「ナレッジエンジン」プラグインをインストールしてください。',
},
mcp: {
title: 'MCP',
@@ -709,7 +729,7 @@ const jaJP = {
cannotChangeEmbeddingModel:
'知識ベース作成後は埋め込みモデルを変更できません',
updateKnowledgeBaseSuccess: '知識ベースの更新に成功しました',
updateKnowledgeBaseFailed: '知識ベースの更新に失敗しました',
updateKnowledgeBaseFailed: '知識ベースの更新に失敗しました',
documentsTab: {
name: '名前',
status: 'ステータス',
@@ -720,14 +740,14 @@ const jaJP = {
supportedFormats:
'PDF、Word、TXT、Markdownなどのドキュメントファイルをサポートしています',
uploadSuccess: 'ファイルのアップロードに成功しました!',
uploadError: 'ファイルのアップロードに失敗しました。再度お試しください',
uploadError: 'ファイルのアップロードに失敗しました',
uploadingFile: 'ファイルをアップロード中...',
fileSizeExceeded:
'ファイルサイズが10MBの制限を超えています。より小さいファイルに分割してください。',
actions: 'アクション',
delete: 'ドキュメントを削除',
fileDeleteSuccess: 'ドキュメントの削除に成功しました',
fileDeleteFailed: 'ドキュメントの削除に失敗しました',
fileDeleteFailed: 'ドキュメントの削除に失敗しました',
processing: '処理中',
completed: '完了',
failed: '失敗',
@@ -748,10 +768,13 @@ const jaJP = {
content: '内容',
fileName: 'ファイル名',
noResults: '検索結果がありません',
retrieveError: '検索に失敗しました',
retrieveError: '検索に失敗しました',
noEnginesAvailable: '利用可能なナレッジエンジンがありません',
installEngineHint:
'先に「ナレッジエンジン」プラグインをインストールしてください',
unknownEngine: '不明なエンジン',
loadKnowledgeBaseFailed: 'ナレッジベースの読み込みに失敗しました',
deleteKnowledgeBaseFailed: 'ナレッジベースの削除に失敗しました',
loadKnowledgeBaseFailed: 'ナレッジベースの読み込みに失敗しました',
deleteKnowledgeBaseFailed: 'ナレッジベースの削除に失敗しました',
getKnowledgeBaseListError: 'ナレッジベース一覧の取得に失敗しました:',
addExternal: '外部ナレッジベースを追加',
createExternalSuccess: '外部ナレッジベースが正常に作成されました',
@@ -762,6 +785,23 @@ const jaJP = {
retrieverConfiguration: '検索器設定',
retrieverInstallInfo: 'ナレッジ検索器プラグインは',
retrieverMarketLink: 'こちらからインストールできます',
migration: {
title: 'ナレッジベースの移行',
description:
'新バージョンではナレッジベースをプラグインベースのアーキテクチャに再構築し、内蔵ナレッジベースと外部ナレッジベースを「ナレッジエンジン」プラグインとして統合しました。旧ナレッジベースデータの移行が必要です。旧データはデータベースに自動的にバックアップされています。',
detected:
'移行が必要なナレッジベースが{{total}}件見つかりました(内部{{internal}}件、外部{{external}}件)。',
startWithInstall: 'プラグインを自動インストールして移行',
startDataOnly: 'データのみ移行',
dataOnlyHint:
'「データのみ移行」はオフライン環境向けです。移行完了後に対応するプラグインを手動でインストールしてください。',
dismiss: '元データを破棄',
running: 'ナレッジベースを移行中です。しばらくお待ちください...',
success: 'ナレッジベースの移行が完了しました',
error: 'ナレッジベースの移行に失敗しました:',
dismissError: '操作に失敗しました',
retry: 'リトライ',
},
},
register: {
title: 'LangBot を初期化 👋',

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',
@@ -47,6 +50,12 @@ const zhHans = {
copyFailed: '复制失败',
test: '测试',
forgotPassword: '忘记密码?',
agreementNotice: '继续即表示您同意我们的',
privacyPolicy: '隐私政策',
and: '和',
dataCollectionPolicy: '数据收集政策',
dataCollectionPolicyUrl:
'https://docs.langbot.app/zh/insight/data-collection-policy',
loading: '加载中...',
fieldRequired: '此字段为必填项',
or: '或',
@@ -221,6 +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',
@@ -262,6 +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',
@@ -468,6 +483,8 @@ const zhHans = {
noTags: '暂无标签',
},
viewDetails: '查看详情',
deprecated: '已弃用',
deprecatedTooltip: '请安装对应「知识引擎」插件',
},
mcp: {
title: 'MCP',
@@ -679,7 +696,7 @@ const zhHans = {
updateTime: '更新于',
cannotChangeEmbeddingModel: '知识库创建后不可修改嵌入模型',
updateKnowledgeBaseSuccess: '知识库更新成功',
updateKnowledgeBaseFailed: '知识库更新失败',
updateKnowledgeBaseFailed: '知识库更新失败',
documentsTab: {
name: '名称',
status: '状态',
@@ -688,13 +705,13 @@ const zhHans = {
uploading: '上传中...',
supportedFormats: '支持 PDF、Word、TXT、Markdown、HTML、ZIP 等文档格式',
uploadSuccess: '文件上传成功!',
uploadError: '文件上传失败,请重试',
uploadError: '文件上传失败',
uploadingFile: '上传文件中...',
fileSizeExceeded: '文件大小超过 10MB 限制,请分割成较小的文件后上传',
actions: '操作',
delete: '删除文件',
fileDeleteSuccess: '文件删除成功',
fileDeleteFailed: '文件删除失败',
fileDeleteFailed: '文件删除失败',
processing: '处理中',
completed: '完成',
failed: '失败',
@@ -715,7 +732,7 @@ const zhHans = {
content: '内容',
fileName: '文件名',
noResults: '暂无结果',
retrieveError: '检索失败',
retrieveError: '检索失败',
unknownEngine: '未知引擎',
knowledgeEngine: '知识引擎',
knowledgeEngineRequired: '知识引擎不能为空',
@@ -726,10 +743,10 @@ const zhHans = {
engineSettingsReadonly: '编辑模式下不可修改',
retrievalSettings: '检索设置',
noEnginesAvailable: '没有可用的知识库引擎',
installEngineHint: '请先安装知识插件',
createKnowledgeBaseFailed: '知识库创建失败',
loadKnowledgeBaseFailed: '知识库加载失败',
deleteKnowledgeBaseFailed: '知识库删除失败',
installEngineHint: '请先安装知识引擎」插件',
createKnowledgeBaseFailed: '知识库创建失败',
loadKnowledgeBaseFailed: '知识库加载失败',
deleteKnowledgeBaseFailed: '知识库删除失败',
getKnowledgeBaseListError: '获取知识库列表失败:',
embeddingModel: '嵌入模型',
embeddingModelRequired: '此引擎需要选择嵌入模型',
@@ -742,6 +759,23 @@ const zhHans = {
retrieverConfiguration: '检索器配置',
retrieverInstallInfo: '您可以从',
retrieverMarketLink: '此处安装知识检索器插件',
migration: {
title: '知识库迁移',
description:
'新版本已将知识库重构为插件化架构,并统一内置知识库和外部知识库为「知识引擎」插件,需要对旧知识库数据进行迁移。您的旧数据已自动备份在数据库中。',
detected:
'共检测到 {{total}} 个知识库需要迁移({{internal}} 个内置知识库,{{external}} 个外部知识库)。',
startWithInstall: '自动安装插件并迁移',
startDataOnly: '仅迁移数据',
dataOnlyHint:
'「仅迁移数据」适合内网环境使用,请在迁移完成后自行安装对应插件',
dismiss: '丢弃原数据',
running: '正在迁移知识库,请稍候...',
success: '知识库迁移完成',
error: '知识库迁移失败:',
dismissError: '操作失败',
retry: '重试',
},
},
register: {
title: '初始化 LangBot 👋',

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',
@@ -47,6 +50,12 @@ const zhHant = {
copyFailed: '複製失敗',
test: '測試',
forgotPassword: '忘記密碼?',
agreementNotice: '繼續即表示您同意我們的',
privacyPolicy: '隱私政策',
and: '和',
dataCollectionPolicy: '數據收集政策',
dataCollectionPolicyUrl:
'https://docs.langbot.app/zh/insight/data-collection-policy',
loading: '載入中...',
fieldRequired: '此欄位為必填',
or: '或',
@@ -220,6 +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',
@@ -261,6 +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',
@@ -461,6 +476,8 @@ const zhHant = {
noTags: '暫無標籤',
},
viewDetails: '查看詳情',
deprecated: '已棄用',
deprecatedTooltip: '請安裝對應「知識引擎」插件',
},
mcp: {
title: 'MCP',
@@ -672,7 +689,7 @@ const zhHant = {
updateTime: '更新於',
cannotChangeEmbeddingModel: '知識庫建立後不可修改嵌入模型',
updateKnowledgeBaseSuccess: '知識庫更新成功',
updateKnowledgeBaseFailed: '知識庫更新失敗',
updateKnowledgeBaseFailed: '知識庫更新失敗',
documentsTab: {
name: '名稱',
status: '狀態',
@@ -681,13 +698,13 @@ const zhHant = {
uploading: '上傳中...',
supportedFormats: '支援 PDF、Word、TXT、Markdown 等文檔格式',
uploadSuccess: '文檔上傳成功!',
uploadError: '文檔上傳失敗,請重試',
uploadError: '文檔上傳失敗',
uploadingFile: '上傳文檔中...',
fileSizeExceeded: '檔案大小超過 10MB 限制,請分割成較小的檔案後上傳',
actions: '操作',
delete: '刪除文檔',
fileDeleteSuccess: '文檔刪除成功',
fileDeleteFailed: '文檔刪除失敗',
fileDeleteFailed: '文檔刪除失敗',
processing: '處理中',
completed: '完成',
failed: '失敗',
@@ -708,10 +725,12 @@ const zhHant = {
content: '內容',
fileName: '文檔名稱',
noResults: '暫無結果',
retrieveError: '檢索失敗',
retrieveError: '檢索失敗',
noEnginesAvailable: '沒有可用的知識庫引擎',
installEngineHint: '請先安裝「知識引擎」插件',
unknownEngine: '未知引擎',
loadKnowledgeBaseFailed: '知識庫載入失敗',
deleteKnowledgeBaseFailed: '知識庫刪除失敗',
loadKnowledgeBaseFailed: '知識庫載入失敗',
deleteKnowledgeBaseFailed: '知識庫刪除失敗',
getKnowledgeBaseListError: '取得知識庫列表失敗:',
addExternal: '添加外部知識庫',
createExternalSuccess: '外部知識庫創建成功',
@@ -722,6 +741,23 @@ const zhHant = {
retrieverConfiguration: '檢索器配置',
retrieverInstallInfo: '您可以從',
retrieverMarketLink: '此處安裝知識檢索器插件',
migration: {
title: '知識庫遷移',
description:
'新版本已將知識庫重構為插件化架構,並統一內建知識庫和外部知識庫為「知識引擎」插件,需要對舊知識庫資料進行遷移。您的舊資料已自動備份在資料庫中。',
detected:
'共檢測到 {{total}} 個知識庫需要遷移({{internal}} 個內建知識庫,{{external}} 個外部知識庫)。',
startWithInstall: '自動安裝插件並遷移',
startDataOnly: '僅遷移資料',
dataOnlyHint:
'「僅遷移資料」適合內網環境使用,請在遷移完成後自行安裝對應插件',
dismiss: '丟棄原數據',
running: '正在遷移知識庫,請稍候...',
success: '知識庫遷移完成',
error: '知識庫遷移失敗:',
dismissError: '操作失敗',
retry: '重試',
},
},
register: {
title: '初始化 LangBot 👋',