feat(tenant): add public subscription plan list endpoint and enhance plan information

Add a public subscription plan list endpoint that can be accessed without authentication. Enhance the returned subscription plan information fields, including multi-language support and default free plan fallback logic. Additionally, implement automatic model binding for the knowledge base service.

api/app/services/knowledge_service.py

@@ -2,11 +2,14 @@ import uuid
 from sqlalchemy.orm import Session
 from app.models.user_model import User
 from app.models.knowledge_model import Knowledge
+from app.models.workspace_model import Workspace
+from app.models.models_model import ModelConfig
 from app.schemas.knowledge_schema import KnowledgeCreate, KnowledgeUpdate
 from app.repositories import knowledge_repository
 from app.core.logging_config import get_business_logger
+from app.repositories.model_repository import ModelConfigRepository
+from app.models.models_model import ModelType
 
-# Obtain a dedicated logger for business logic
 business_logger = get_business_logger()
 
 
@@ -60,13 +63,57 @@ def create_knowledge(
         db: Session, knowledge: KnowledgeCreate, current_user: User
 ) -> Knowledge:
     business_logger.info(f"Create a knowledge base: {knowledge.name}, creator: {current_user.username}")
-    
+
     try:
         knowledge.created_by = current_user.id
         if knowledge.workspace_id is None:
             knowledge.workspace_id = current_user.current_workspace_id
         if knowledge.parent_id is None:
             knowledge.parent_id = knowledge.workspace_id
+
+        workspace = db.query(Workspace).filter(Workspace.id == knowledge.workspace_id).first()
+        if not workspace:
+            raise Exception(f"Workspace {knowledge.workspace_id} not found")
+
+        tenant_id = workspace.tenant_id
+
+        if not knowledge.embedding_id:
+            embedding_models = ModelConfigRepository.get_by_type(
+                db=db, model_types=[ModelType.EMBEDDING], tenant_id=tenant_id, is_active=True
+            )
+            if embedding_models:
+                knowledge.embedding_id = embedding_models[0].id
+                business_logger.debug(f"Auto-bind embedding model: {embedding_models[0].id}")
+
+        if not knowledge.reranker_id:
+            rerank_models = ModelConfigRepository.get_by_type(
+                db=db, model_types=[ModelType.RERANK], tenant_id=tenant_id, is_active=True
+            )
+            if rerank_models:
+                knowledge.reranker_id = rerank_models[0].id
+                business_logger.debug(f"Auto-bind rerank model: {rerank_models[0].id}")
+
+        if not knowledge.llm_id:
+            llm_models = ModelConfigRepository.get_by_type(
+                db=db, model_types=[ModelType.LLM, ModelType.CHAT], tenant_id=tenant_id, is_active=True
+            )
+            if llm_models:
+                knowledge.llm_id = llm_models[0].id
+                business_logger.debug(f"Auto-bind llm model: {llm_models[0].id}")
+
+        if not knowledge.image2text_id:
+            image2text_models = db.query(ModelConfig).filter(
+                ModelConfig.tenant_id == tenant_id,
+                ModelConfig.type.in_([ModelType.CHAT.value, ModelType.IMAGE.value]),
+                ModelConfig.capability.contains(["vision"]),
+                ModelConfig.is_active == True,
+                ModelConfig.is_composite == False
+            ).order_by(ModelConfig.created_at.desc()).all()
+            if not image2text_models:
+                raise Exception("租户下没有可用的视觉模型，创建知识库失败")
+            knowledge.image2text_id = image2text_models[0].id
+            business_logger.debug(f"Auto-bind image2text model: {image2text_models[0].id}")
+
         business_logger.debug(f"Start creating the knowledge base: {knowledge.name}")
         db_knowledge = knowledge_repository.create_knowledge(
             db=db, knowledge=knowledge