dale_yxc/ragflow_python
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Fix some issues in API and test (#3001)

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### What problem does this PR solve?

Fix some issues in API and test

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

Co-authored-by: liuhua <10215101452@stu.ecun.edu.cn>
This commit is contained in:
liuhua
2024-10-24 20:05:21 +08:00
committed by GitHub
parent e997b42504
commit 161c7a231b
6 changed files with 64 additions and 76 deletions
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2
sdk/python/ragflow/modules/chat.py
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@@ -9,7 +9,7 @@ class Chat(Base):
self.id = ""
self.name = "assistant"
self.avatar = "path/to/avatar"
self.datasets = ["kb1"]
self.dataset_ids = ["kb1"]
self.llm = Chat.LLM(rag, {})
self.prompt = Chat.Prompt(rag, {})
super().__init__(rag, res_dict)

21
sdk/python/ragflow/ragflow.py
View File

@@ -64,8 +64,8 @@ class RAGFlow:
return DataSet(self, res["data"])
raise Exception(res["message"])
def delete_datasets(self, ids: List[str] = None, names: List[str] = None):
res = self.delete("/dataset",{"ids": ids, "names": names})
def delete_datasets(self, ids: List[str]):
res = self.delete("/dataset",{"ids": ids})
res=res.json()
if res.get("code") != 0:
raise Exception(res["message"])
@@ -89,11 +89,11 @@ class RAGFlow:
return result_list
raise Exception(res["message"])
def create_chat(self, name: str, avatar: str = "", datasets: List[DataSet] = [],
def create_chat(self, name: str, avatar: str = "", dataset_ids: List[str] = [],
llm: Chat.LLM = None, prompt: Chat.Prompt = None) -> Chat:
dataset_list = []
for dataset in datasets:
dataset_list.append(dataset.id)
for id in dataset_ids:
dataset_list.append(id)
if llm is None:
llm = Chat.LLM(self, {"model_name": None,
@@ -126,7 +126,7 @@ class RAGFlow:
temp_dict = {"name": name,
"avatar": avatar,
"datasets": dataset_list,
"dataset_ids": dataset_list,
"llm": llm.to_json(),
"prompt": prompt.to_json()}
res = self.post("/chat", temp_dict)
@@ -154,7 +154,9 @@ class RAGFlow:
raise Exception(res["message"])
def retrieve(self, datasets,documents,question="", offset=1, limit=1024, similarity_threshold=0.2,vector_similarity_weight=0.3,top_k=1024,rerank_id:str=None,keyword:bool=False,):
def retrieve(self, dataset_ids, document_ids=None, question="", offset=1, limit=1024, similarity_threshold=0.2, vector_similarity_weight=0.3, top_k=1024, rerank_id:str=None, keyword:bool=False, ):
if document_ids is None:
document_ids = []
data_json ={
"offset": offset,
"limit": limit,
@@ -164,10 +166,9 @@ class RAGFlow:
"rerank_id": rerank_id,
"keyword": keyword,
"question": question,
"datasets": datasets,
"documents": documents
"datasets": dataset_ids,
"documents": document_ids
}
# Send a POST request to the backend service (using requests library as an example, actual implementation may vary)
res = self.post(f'/retrieval',json=data_json)
res = res.json()