fix:rag serve error

.env.template

@@ -241,4 +241,5 @@ DBGPT_LOG_LEVEL=INFO
 #*******************************************************************#
 #**                         API_KEYS                              **#
 #*******************************************************************#
+# API_KEYS - The list of API keys that are allowed to access the API. Each of the below are an option, separated by commas.
 # API_KEYS=dbgpt

dbgpt/app/openapi/api_v2.py

@@ -26,7 +26,7 @@ from dbgpt.app.openapi.api_v1.api_v1 import (
     stream_generator,
 )
 from dbgpt.app.scene import BaseChat, ChatScene
-from dbgpt.client.schemas import ChatCompletionRequestBody
+from dbgpt.client.schemas import ChatCompletionRequestBody, ChatMode
 from dbgpt.component import logger
 from dbgpt.core.awel import CommonLLMHttpRequestBody, CommonLLMHTTPRequestContext
 from dbgpt.model.cluster.apiserver.api import APISettings
@@ -94,7 +94,7 @@ async def chat_completions(
     check_chat_request(request)
     if request.conv_uid is None:
         request.conv_uid = str(uuid.uuid4())
-    if request.chat_mode == "chat_app":
+    if request.chat_mode == ChatMode.CHAT_APP.value:
         if request.stream is False:
             raise HTTPException(
                 status_code=400,
@@ -114,27 +114,14 @@ async def chat_completions(
             headers=headers,
             media_type="text/event-stream",
         )
-    elif request.chat_mode == ChatScene.ChatFlow.value():
+    elif request.chat_mode == ChatMode.CHAT_AWEL_FLOW.value:
-        # flow_ctx = CommonLLMHTTPRequestContext(
-        #     conv_uid=request.conv_uid,
-        #     chat_mode=request.chat_mode,
-        #     user_name=request.user_name,
-        #     sys_code=request.sys_code,
-        # )
-        # flow_req = CommonLLMHttpRequestBody(
-        #     model=request.model,
-        #     messages=request.chat_param,
-        #     stream=True,
-        #     context=flow_ctx,
-        # )
         return StreamingResponse(
             chat_flow_stream_wrapper(request),
             headers=headers,
             media_type="text/event-stream",
         )
     elif (
-        request.chat_mode is None
+        request.chat_mode is None or request.chat_mode == ChatMode.CHAT_KNOWLEDGE.value
-        or request.chat_mode == ChatScene.ChatKnowledge.value()
     ):
         with root_tracer.start_span(
             "get_chat_instance", span_type=SpanType.CHAT, metadata=request.dict()

dbgpt/client/schemas.py

@@ -1,4 +1,5 @@
 from datetime import datetime
+from enum import Enum
 from typing import Dict, List, Optional, Union
 
 from fastapi import File, UploadFile
@@ -60,6 +61,15 @@ class ChatCompletionRequestBody(BaseModel):
     )
 
 
+class ChatMode(Enum):
+    """Chat mode"""
+
+    CHAT_NORMAL = "chat_normal"
+    CHAT_APP = "chat_app"
+    CHAT_AWEL_FLOW = "chat_flow"
+    CHAT_KNOWLEDGE = "chat_knowledge"
+
+
 class SpaceModel(BaseModel):
     """name: knowledge space name"""
 

dbgpt/serve/rag/models/models.py

@@ -0,0 +1,147 @@
+from datetime import datetime
+from typing import Any, Dict, List, Union
+
+from sqlalchemy import Column, DateTime, Integer, String, Text
+
+from dbgpt.serve.rag.api.schemas import SpaceServeRequest, SpaceServeResponse
+from dbgpt.storage.metadata import BaseDao, Model
+
+
+class KnowledgeSpaceEntity(Model):
+    __tablename__ = "knowledge_space"
+    id = Column(Integer, primary_key=True)
+    name = Column(String(100))
+    vector_type = Column(String(100))
+    desc = Column(String(100))
+    owner = Column(String(100))
+    context = Column(Text)
+    gmt_created = Column(DateTime)
+    gmt_modified = Column(DateTime)
+
+    def __repr__(self):
+        return f"KnowledgeSpaceEntity(id={self.id}, name='{self.name}', vector_type='{self.vector_type}', desc='{self.desc}', owner='{self.owner}' context='{self.context}', gmt_created='{self.gmt_created}', gmt_modified='{self.gmt_modified}')"
+
+
+class KnowledgeSpaceDao(BaseDao):
+    def create_knowledge_space(self, space: SpaceServeRequest):
+        """Create knowledge space"""
+        session = self.get_raw_session()
+        knowledge_space = KnowledgeSpaceEntity(
+            name=space.name,
+            vector_type=space.vector_type,
+            desc=space.desc,
+            owner=space.owner,
+            gmt_created=datetime.now(),
+            gmt_modified=datetime.now(),
+        )
+        session.add(knowledge_space)
+        session.commit()
+        space_id = knowledge_space.id
+        session.close()
+        return space_id
+
+    def get_knowledge_space(self, query: KnowledgeSpaceEntity):
+        """Get knowledge space by query"""
+        session = self.get_raw_session()
+        knowledge_spaces = session.query(KnowledgeSpaceEntity)
+        if query.id is not None:
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.id == query.id
+            )
+        if query.name is not None:
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.name == query.name
+            )
+        if query.vector_type is not None:
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.vector_type == query.vector_type
+            )
+        if query.desc is not None:
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.desc == query.desc
+            )
+        if query.owner is not None:
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.owner == query.owner
+            )
+        if query.gmt_created is not None:
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.gmt_created == query.gmt_created
+            )
+        if query.gmt_modified is not None:
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.gmt_modified == query.gmt_modified
+            )
+        knowledge_spaces = knowledge_spaces.order_by(
+            KnowledgeSpaceEntity.gmt_created.desc()
+        )
+        result = knowledge_spaces.all()
+        session.close()
+        return result
+
+    def update_knowledge_space(self, space: KnowledgeSpaceEntity):
+        """Update knowledge space"""
+        session = self.get_raw_session()
+        session.merge(space)
+        session.commit()
+        session.close()
+        return True
+
+    def delete_knowledge_space(self, space: KnowledgeSpaceEntity):
+        """Delete knowledge space"""
+        session = self.get_raw_session()
+        if space:
+            session.delete(space)
+            session.commit()
+        session.close()
+
+    def from_request(
+        self, request: Union[SpaceServeRequest, Dict[str, Any]]
+    ) -> KnowledgeSpaceEntity:
+        """Convert the request to an entity
+
+        Args:
+            request (Union[ServeRequest, Dict[str, Any]]): The request
+
+        Returns:
+            T: The entity
+        """
+        request_dict = (
+            request.dict() if isinstance(request, SpaceServeRequest) else request
+        )
+        entity = KnowledgeSpaceEntity(**request_dict)
+        return entity
+
+    def to_request(self, entity: KnowledgeSpaceEntity) -> SpaceServeRequest:
+        """Convert the entity to a request
+
+        Args:
+            entity (T): The entity
+
+        Returns:
+            REQ: The request
+        """
+        return SpaceServeRequest(
+            id=entity.id,
+            name=entity.name,
+            vector_type=entity.vector_type,
+            desc=entity.desc,
+            owner=entity.owner,
+        )
+
+    def to_response(self, entity: KnowledgeSpaceEntity) -> SpaceServeResponse:
+        """Convert the entity to a response
+
+        Args:
+            entity (T): The entity
+
+        Returns:
+            REQ: The request
+        """
+        return SpaceServeResponse(
+            id=entity.id,
+            name=entity.name,
+            vector_type=entity.vector_type,
+            desc=entity.desc,
+            owner=entity.owner,
+        )

dbgpt/serve/rag/service/service.py

@@ -21,8 +21,8 @@ from dbgpt.configs.model_config import (
     EMBEDDING_MODEL_CONFIG,
     KNOWLEDGE_UPLOAD_ROOT_PATH,
 )
+from dbgpt.core import Chunk
 from dbgpt.core.awel.dag.dag_manager import DAGManager
-from dbgpt.rag.chunk import Chunk
 from dbgpt.rag.chunk_manager import ChunkParameters
 from dbgpt.rag.embedding import EmbeddingFactory
 from dbgpt.rag.knowledge import ChunkStrategy, KnowledgeFactory, KnowledgeType

examples/client/app_crud_example.py

@@ -23,8 +23,8 @@ Client: Simple App CRUD example
 
 
 async def main():
-    # initialize client
 
+    # initialize client
     DBGPT_API_KEY = "dbgpt"
     client = Client(api_key=DBGPT_API_KEY)
     res = await list_app(client)

examples/client/client_chat_example.py

@@ -55,6 +55,7 @@ Client: Simple Chat example
 
 
 async def main():
+
     # initialize client
     DBGPT_API_KEY = "dbgpt"
     client = Client(api_key=DBGPT_API_KEY)

examples/client/flow_crud_example.py

@@ -36,8 +36,8 @@ Client: Simple Flow CRUD example
 
 
 async def main():
-    # initialize client
 
+    # initialize client
     DBGPT_API_KEY = "dbgpt"
     client = Client(api_key=DBGPT_API_KEY)
     res = await list_flow(client)

examples/client/knowledge_crud_example.py

@@ -69,12 +69,13 @@ from dbgpt.client.knowledge import list_space
 
 async def main():
 
+    # initialize client
     DBGPT_API_KEY = "dbgpt"
     client = Client(api_key=DBGPT_API_KEY)
 
     # list all spaces
     res = await list_space(client)
-    print(res)
+    print(res.json())
 
     # get space
     # res = await get_space(client, space_id='5')