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feat: external knowledge bases (#1783)

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* Initial plan

* Add backend support for external knowledge bases

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

* Add frontend support for external knowledge bases with tabs UI

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

* Add i18n translations for all languages (Traditional Chinese and Japanese)

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

* Update knowledge base tab list styling to match plugins page

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

* perf: margin-top for kb page

* refactor: switch RetrievalResultEntry to langbot_plugin pkg ones

* feat: knowledge retriever listing and creating

* stash

* refactor: unify sync mechanism for polymorphic components

* feat: use unified retireval result struct in retrieval test page

* chore: remove unused methods

* feat: retriever icon displaying

* feat: localagent retrieval with external kbs

* chore: bump version of langbot-plugin to 0.2.0b1

* fix: i18n

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>
This commit is contained in:
Copilot
2025-11-27 23:19:43 +08:00
committed by GitHub
parent 3c04eeaff9
commit a8481e43f0
33 changed files with 1924 additions and 161 deletions
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29
src/langbot/pkg/entity/persistence/rag.py
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@@ -1,20 +1,6 @@
import sqlalchemy
from .base import Base
# Base = declarative_base()
# DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///./rag_knowledge.db')
# print("Using database URL:", DATABASE_URL)
# engine = create_engine(DATABASE_URL, connect_args={'check_same_thread': False})
# SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
# def create_db_and_tables():
# """Creates all database tables defined in the Base."""
# Base.metadata.create_all(bind=engine)
# print('Database tables created or already exist.')
class KnowledgeBase(Base):
__tablename__ = 'knowledge_bases'
@@ -43,8 +29,13 @@ class Chunk(Base):
text = sqlalchemy.Column(sqlalchemy.Text)
# class Vector(Base):
# __tablename__ = 'knowledge_base_vectors'
# uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
# chunk_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
# embedding = sqlalchemy.Column(sqlalchemy.LargeBinary)
class ExternalKnowledgeBase(Base):
__tablename__ = 'external_knowledge_bases'
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String, index=True)
description = sqlalchemy.Column(sqlalchemy.Text)
plugin_author = sqlalchemy.Column(sqlalchemy.String, nullable=False)
plugin_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
retriever_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
retriever_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())

0
src/langbot/pkg/entity/rag/__init__.py
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13
src/langbot/pkg/entity/rag/retriever.py
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@@ -1,13 +0,0 @@
from __future__ import annotations
import pydantic
from typing import Any
class RetrieveResultEntry(pydantic.BaseModel):
id: str
metadata: dict[str, Any]
distance: float