add a new api to search content by keyword for es
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1654d5a120
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@ -144,7 +144,7 @@ def mount_knowledge_routes(app: FastAPI):
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from server.knowledge_base.kb_doc_api import (list_files, upload_docs, delete_docs,
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from server.knowledge_base.kb_doc_api import (list_files, upload_docs, delete_docs,
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update_docs, download_doc, recreate_vector_store,
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update_docs, download_doc, recreate_vector_store,
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search_docs, DocumentWithVSId, update_info,
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search_docs, DocumentWithVSId, update_info,
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update_docs_by_id,)
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update_docs_by_id,search_content,Document)
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app.post("/chat/knowledge_base_chat",
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app.post("/chat/knowledge_base_chat",
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tags=["Chat"],
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tags=["Chat"],
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@ -189,6 +189,12 @@ def mount_knowledge_routes(app: FastAPI):
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summary="搜索知识库"
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summary="搜索知识库"
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)(search_docs)
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)(search_docs)
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app.post("/knowledge_base/search_content",
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tags=["Knowledge Base Management"],
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response_model=List[Document],
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summary="搜索文档库"
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)(search_content)
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app.post("/knowledge_base/update_docs_by_id",
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app.post("/knowledge_base/update_docs_by_id",
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tags=["Knowledge Base Management"],
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tags=["Knowledge Base Management"],
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response_model=BaseResponse,
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response_model=BaseResponse,
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@ -80,6 +80,20 @@ def search_docs(
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data = kb.list_docs(file_name=file_name, metadata=metadata)
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data = kb.list_docs(file_name=file_name, metadata=metadata)
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return data
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return data
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def search_content(
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query: str = Body("", description="用户输入", examples=["国网安徽信通准入手续"]),
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knowledge_base_name: str = Body(..., description="知识库名称", examples=["samples"]),
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top_k: int = Body(2, description="匹配文档数"),
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)-> List[Document]:
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print("kb_doc_api search_content")
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kb = KBServiceFactory.get_service_by_name(knowledge_base_name)
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if kb is not None:
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if query:
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docs = kb.search_content(query, top_k)
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print(f"search_content, docs:{docs}")
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return docs
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else:
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return None
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def update_docs_by_id(
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def update_docs_by_id(
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knowledge_base_name: str = Body(..., description="知识库名称", examples=["samples"]),
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knowledge_base_name: str = Body(..., description="知识库名称", examples=["samples"]),
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@ -181,6 +181,14 @@ class KBService(ABC):
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docs = self.do_search(query, top_k, score_threshold)
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docs = self.do_search(query, top_k, score_threshold)
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return docs
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return docs
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def search_content(self,
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query: str,
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top_k: int,
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)->List[Document]:
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print("KBService search_content")
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docs = self.searchbyContent(query,top_k)
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return docs
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def get_doc_by_ids(self, ids: List[str]) -> List[Document]:
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def get_doc_by_ids(self, ids: List[str]) -> List[Document]:
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return []
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return []
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@ -266,6 +274,16 @@ class KBService(ABC):
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"""
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"""
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pass
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pass
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@abstractmethod
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def searchbyContent(self,
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query: str,
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top_k: int,
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)->List[Document]:
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"""
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搜索知识库子类实自己逻辑
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"""
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pass
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@abstractmethod
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@abstractmethod
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def do_add_doc(self,
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def do_add_doc(self,
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docs: List[Document],
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docs: List[Document],
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@ -36,3 +36,6 @@ class DefaultKBService(KBService):
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def do_delete_doc(self):
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def do_delete_doc(self):
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pass
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pass
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def searchbyContent(self):
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pass
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@ -156,6 +156,28 @@ class ESKBService(KBService):
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k=top_k)
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k=top_k)
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return docs
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return docs
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def searchbyContent(self, query:str, top_k: int = 2):
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if self.es_client_python.indices.exists(index=self.index_name):
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print(f"******ESKBService searchByContent {self.index_name}")
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tem_query = {
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"query": {"match": {
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"context": "*" + query + "*"
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}}
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}
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search_results = self.es_client_python.search(index=self.index_name, body=tem_query, size=top_k)
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hits = [hit for hit in search_results["hits"]["hits"]]
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docs_and_scores = [
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(
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Document(
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page_content=hit["_source"]["context"],
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metadata=hit["_source"]["metadata"],
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)
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)
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for hit in hits
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]
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return docs_and_scores
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def del_doc_by_ids(self, ids: List[str]) -> bool:
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def del_doc_by_ids(self, ids: List[str]) -> bool:
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for doc_id in ids:
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for doc_id in ids:
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try:
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try:
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