mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-04 04:54:36 +00:00
Merge branch 'rc/new-plugin' into refactor/new-plugin-system
This commit is contained in:
@@ -4,7 +4,7 @@ from .base import Base
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class Bot(Base):
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"""机器人"""
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"""Bot"""
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__tablename__ = 'bots'
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@@ -12,7 +12,7 @@ initial_metadata = [
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class Metadata(Base):
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"""数据库元数据"""
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"""Database metadata"""
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__tablename__ = 'metadata'
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@@ -4,7 +4,7 @@ from .base import Base
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class LLMModel(Base):
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"""LLM 模型"""
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"""LLM model"""
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__tablename__ = 'llm_models'
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@@ -23,3 +23,24 @@ class LLMModel(Base):
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server_default=sqlalchemy.func.now(),
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onupdate=sqlalchemy.func.now(),
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)
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class EmbeddingModel(Base):
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"""Embedding 模型"""
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__tablename__ = 'embedding_models'
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uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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requester_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
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api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
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extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
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created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
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updated_at = sqlalchemy.Column(
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sqlalchemy.DateTime,
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nullable=False,
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server_default=sqlalchemy.func.now(),
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onupdate=sqlalchemy.func.now(),
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)
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@@ -4,7 +4,7 @@ from .base import Base
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class LegacyPipeline(Base):
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"""旧版流水线"""
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"""Legacy pipeline"""
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__tablename__ = 'legacy_pipelines'
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@@ -20,13 +20,12 @@ class LegacyPipeline(Base):
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)
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for_version = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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is_default = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=False)
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stages = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
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config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
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class PipelineRunRecord(Base):
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"""流水线运行记录"""
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"""Pipeline run record"""
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__tablename__ = 'pipeline_run_records'
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@@ -43,3 +42,4 @@ class PipelineRunRecord(Base):
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started_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False)
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finished_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False)
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result = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
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knowledge_base_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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@@ -4,7 +4,7 @@ from .base import Base
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class PluginSetting(Base):
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"""插件配置"""
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"""Plugin setting"""
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__tablename__ = 'plugin_settings'
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50
pkg/entity/persistence/rag.py
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50
pkg/entity/persistence/rag.py
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@@ -0,0 +1,50 @@
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import sqlalchemy
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from .base import Base
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# Base = declarative_base()
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# DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///./rag_knowledge.db')
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# print("Using database URL:", DATABASE_URL)
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# engine = create_engine(DATABASE_URL, connect_args={'check_same_thread': False})
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# SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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# def create_db_and_tables():
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# """Creates all database tables defined in the Base."""
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# Base.metadata.create_all(bind=engine)
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# print('Database tables created or already exist.')
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class KnowledgeBase(Base):
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__tablename__ = 'knowledge_bases'
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uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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name = sqlalchemy.Column(sqlalchemy.String, index=True)
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description = sqlalchemy.Column(sqlalchemy.Text)
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created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
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embedding_model_uuid = sqlalchemy.Column(sqlalchemy.String, default='')
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top_k = sqlalchemy.Column(sqlalchemy.Integer, default=5)
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class File(Base):
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__tablename__ = 'knowledge_base_files'
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uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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kb_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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file_name = sqlalchemy.Column(sqlalchemy.String)
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extension = sqlalchemy.Column(sqlalchemy.String)
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created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
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status = sqlalchemy.Column(sqlalchemy.String, default='pending') # pending, processing, completed, failed
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class Chunk(Base):
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__tablename__ = 'knowledge_base_chunks'
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uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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file_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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text = sqlalchemy.Column(sqlalchemy.Text)
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# class Vector(Base):
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# __tablename__ = 'knowledge_base_vectors'
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# uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
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# chunk_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
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# embedding = sqlalchemy.Column(sqlalchemy.LargeBinary)
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13
pkg/entity/persistence/vector.py
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13
pkg/entity/persistence/vector.py
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@@ -0,0 +1,13 @@
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from sqlalchemy import Column, Integer, ForeignKey, LargeBinary
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from sqlalchemy.orm import declarative_base, relationship
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Base = declarative_base()
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class Vector(Base):
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__tablename__ = 'vectors'
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id = Column(Integer, primary_key=True, index=True)
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chunk_id = Column(Integer, ForeignKey('chunks.id'), unique=True)
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embedding = Column(LargeBinary) # Store embeddings as binary
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chunk = relationship('Chunk', back_populates='vector')
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0
pkg/entity/rag/__init__.py
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0
pkg/entity/rag/__init__.py
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13
pkg/entity/rag/retriever.py
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13
pkg/entity/rag/retriever.py
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@@ -0,0 +1,13 @@
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from __future__ import annotations
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import pydantic
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from typing import Any
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class RetrieveResultEntry(pydantic.BaseModel):
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id: str
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metadata: dict[str, Any]
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distance: float
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