AI/ragflow
1
0
Fork 0
mirror of https://git.mirrors.martin98.com/https://github.com/infiniflow/ragflow.git synced 2025-08-14 02:45:54 +08:00
Code Issues Packages Projects Releases Wiki Activity

Fix some issues in API (#2982)

Browse Source 
### What problem does this PR solve?

Fix some issues in API

### 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 2024-10-23 12:02:18 +08:00 committed by GitHub
parent 43b959fe58
commit 8714754afc
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
14 changed files with 206 additions and 106 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

57
api/apps/sdk/chat.py
View File

@ -25,13 +25,14 @@ from api.utils.api_utils import get_error_data_result, token_required
from api.utils.api_utils import get_result
@manager.route('/chat', methods=['POST'])
@token_required
def create(tenant_id):
req=request.json
ids= req.get("knowledgebases")
ids= req.get("datasets")
if not ids:
return get_error_data_result(retmsg="`knowledgebases` is required")
return get_error_data_result(retmsg="`datasets` is required")
for kb_id in ids:
kbs = KnowledgebaseService.query(id=kb_id,tenant_id=tenant_id)
if not kbs:
@ -45,6 +46,8 @@ def create(tenant_id):
if llm:
if "model_name" in llm:
req["llm_id"] = llm.pop("model_name")
if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req["llm_id"],model_type="chat"):
return get_error_data_result(f"`model_name` {req.get('llm_id')} doesn't exist")
req["llm_setting"] = req.pop("llm")
e, tenant = TenantService.get_by_id(tenant_id)
if not e:
@ -73,10 +76,10 @@ def create(tenant_id):
req["top_n"] = req.get("top_n", 6)
req["top_k"] = req.get("top_k", 1024)
req["rerank_id"] = req.get("rerank_id", "")
if req.get("llm_id"):
if not TenantLLMService.query(llm_name=req["llm_id"]):
return get_error_data_result(retmsg="the model_name does not exist.")
else:
if req.get("rerank_id"):
if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req.get("rerank_id"),model_type="rerank"):
return get_error_data_result(f"`rerank_model` {req.get('rerank_id')} doesn't exist")
if not req.get("llm_id"):
req["llm_id"] = tenant.llm_id
if not req.get("name"):
return get_error_data_result(retmsg="`name` is required.")
@ -135,7 +138,7 @@ def create(tenant_id):
res["llm"] = res.pop("llm_setting")
res["llm"]["model_name"] = res.pop("llm_id")
del res["kb_ids"]
res["knowledgebases"] = req["knowledgebases"]
res["datasets"] = req["datasets"]
res["avatar"] = res.pop("icon")
return get_result(data=res)
@ -145,27 +148,32 @@ def update(tenant_id,chat_id):
if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value):
return get_error_data_result(retmsg='You do not own the chat')
req =request.json
if "knowledgebases" in req:
if not req.get("knowledgebases"):
return get_error_data_result(retmsg="`knowledgebases` can't be empty value")
kb_list = []
for kb in req.get("knowledgebases"):
if not kb["id"]:
return get_error_data_result(retmsg="knowledgebase needs id")
if not KnowledgebaseService.query(id=kb["id"], tenant_id=tenant_id):
return get_error_data_result(retmsg="you do not own the knowledgebase")
# if not DocumentService.query(kb_id=kb["id"]):
# return get_error_data_result(retmsg="There is a invalid knowledgebase")
kb_list.append(kb["id"])
req["kb_ids"] = kb_list
ids = req.get("datasets")
if "datasets" in req:
if not ids:
return get_error_data_result("`datasets` can't be empty")
if ids:
for kb_id in ids:
kbs = KnowledgebaseService.query(id=kb_id, tenant_id=tenant_id)
if not kbs:
return get_error_data_result(f"You don't own the dataset {kb_id}")
kb = kbs[0]
if kb.chunk_num == 0:
return get_error_data_result(f"The dataset {kb_id} doesn't own parsed file")
req["kb_ids"] = ids
llm = req.get("llm")
if llm:
if "model_name" in llm:
req["llm_id"] = llm.pop("model_name")
if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req["llm_id"],model_type="chat"):
return get_error_data_result(f"`model_name` {req.get('llm_id')} doesn't exist")
req["llm_setting"] = req.pop("llm")
e, tenant = TenantService.get_by_id(tenant_id)
if not e:
return get_error_data_result(retmsg="Tenant not found!")
if req.get("rerank_model"):
if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req.get("rerank_model"),model_type="rerank"):
return get_error_data_result(f"`rerank_model` {req.get('rerank_model')} doesn't exist")
# prompt
prompt = req.get("prompt")
key_mapping = {"parameters": "variables",
@ -185,9 +193,6 @@ def update(tenant_id,chat_id):
req["prompt_config"] = req.pop("prompt")
e, res = DialogService.get_by_id(chat_id)
res = res.to_json()
if "llm_id" in req:
if not TenantLLMService.query(llm_name=req["llm_id"]):
return get_error_data_result(retmsg="The `model_name` does not exist.")
if "name" in req:
if not req.get("name"):
return get_error_data_result(retmsg="`name` is not empty.")
@ -209,8 +214,8 @@ def update(tenant_id,chat_id):
# avatar
if "avatar" in req:
req["icon"] = req.pop("avatar")
if "knowledgebases" in req:
req.pop("knowledgebases")
if "datasets" in req:
req.pop("datasets")
if not DialogService.update_by_id(chat_id, req):
return get_error_data_result(retmsg="Chat not found!")
return get_result()
@ -279,7 +284,7 @@ def list_chat(tenant_id):
return get_error_data_result(retmsg=f"Don't exist the kb {kb_id}")
kb_list.append(kb[0].to_json())
del res["kb_ids"]
res["knowledgebases"] = kb_list
res["datasets"] = kb_list
res["avatar"] = res.pop("icon")
list_assts.append(res)
return get_result(data=list_assts)

40
api/apps/sdk/dataset.py
View File

@ -15,17 +15,17 @@
#
from flask import request
from api.db import StatusEnum, FileSource
from api.db.db_models import File
from api.db.services.document_service import DocumentService
from api.db.services.file2document_service import File2DocumentService
from api.db.services.file_service import FileService
from api.db.services.knowledgebase_service import KnowledgebaseService
from api.db.services.llm_service import TenantLLMService
from api.db.services.user_service import TenantService
from api.settings import RetCode
from api.utils import get_uuid
from api.utils.api_utils import get_result, token_required, get_error_data_result, valid
from api.utils.api_utils import get_result, token_required, get_error_data_result, valid,get_parser_config
@manager.route('/dataset', methods=['POST'])
@ -36,15 +36,17 @@ def create(tenant_id):
permission = req.get("permission")
language = req.get("language")
chunk_method = req.get("chunk_method")
valid_permission = ("me", "team")
valid_language =("Chinese", "English")
valid_chunk_method = ("naive","manual","qa","table","paper","book","laws","presentation","picture","one","knowledge_graph","email")
parser_config = req.get("parser_config")
valid_permission = {"me", "team"}
valid_language ={"Chinese", "English"}
valid_chunk_method = {"naive","manual","qa","table","paper","book","laws","presentation","picture","one","knowledge_graph","email"}
check_validation=valid(permission,valid_permission,language,valid_language,chunk_method,valid_chunk_method)
if check_validation:
return check_validation
if "tenant_id" in req or "embedding_model" in req:
req["parser_config"]=get_parser_config(chunk_method,parser_config)
if "tenant_id" in req:
return get_error_data_result(
retmsg="`tenant_id` or `embedding_model` must not be provided")
retmsg="`tenant_id` must not be provided")
chunk_count=req.get("chunk_count")
document_count=req.get("document_count")
if chunk_count or document_count:
@ -59,9 +61,13 @@ def create(tenant_id):
retmsg="`name` is not empty string!")
if KnowledgebaseService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value):
return get_error_data_result(
retmsg="Duplicated knowledgebase name in creating dataset.")
retmsg="Duplicated dataset name in creating dataset.")
req["tenant_id"] = req['created_by'] = tenant_id
if not req.get("embedding_model"):
req['embedding_model'] = t.embd_id
else:
if not TenantLLMService.query(tenant_id=tenant_id,model_type="embedding", llm_name=req.get("embedding_model")):
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
key_mapping = {
"chunk_num": "chunk_count",
"doc_num": "document_count",
@ -116,10 +122,12 @@ def update(tenant_id,dataset_id):
permission = req.get("permission")
language = req.get("language")
chunk_method = req.get("chunk_method")
valid_permission = ("me", "team")
valid_language =("Chinese", "English")
valid_chunk_method = ("naive","manual","qa","table","paper","book","laws","presentation","picture","one","knowledge_graph","email")
check_validation=valid(permission,valid_permission,language,valid_language,chunk_method,valid_chunk_method)
parser_config = req.get("parser_config")
valid_permission = {"me", "team"}
valid_language = {"Chinese", "English"}
valid_chunk_method = {"naive", "manual", "qa", "table", "paper", "book", "laws", "presentation", "picture", "one",
"knowledge_graph", "email"}
check_validation = valid(permission, valid_permission, language, valid_language, chunk_method, valid_chunk_method)
if check_validation:
return check_validation
if "tenant_id" in req:
@ -142,10 +150,16 @@ def update(tenant_id,dataset_id):
return get_error_data_result(
retmsg="If `chunk_count` is not 0, `chunk_method` is not changeable.")
req['parser_id'] = req.pop('chunk_method')
if req['parser_id'] != kb.parser_id:
req["parser_config"] = get_parser_config(chunk_method, parser_config)
if "embedding_model" in req:
if kb.chunk_num != 0 and req['embedding_model'] != kb.embd_id:
return get_error_data_result(
retmsg="If `chunk_count` is not 0, `embedding_method` is not changeable.")
if not req.get("embedding_model"):
return get_error_data_result("`embedding_model` can't be empty")
if not TenantLLMService.query(tenant_id=tenant_id,model_type="embedding", llm_name=req.get("embedding_model")):
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
req['embd_id'] = req.pop('embedding_model')
if "name" in req:
req["name"] = req["name"].strip()
@ -153,7 +167,7 @@ def update(tenant_id,dataset_id):
and len(KnowledgebaseService.query(name=req["name"], tenant_id=tenant_id,
status=StatusEnum.VALID.value)) > 0:
return get_error_data_result(
retmsg="Duplicated knowledgebase name in updating dataset.")
retmsg="Duplicated dataset name in updating dataset.")
if not KnowledgebaseService.update_by_id(kb.id, req):
return get_error_data_result(retmsg="Update dataset error.(Database error)")
return get_result(retcode=RetCode.SUCCESS)

79
api/apps/sdk/doc.py
View File

@ -39,7 +39,7 @@ from api.db.services.file2document_service import File2DocumentService
from api.db.services.file_service import FileService
from api.db.services.knowledgebase_service import KnowledgebaseService
from api.settings import RetCode, retrievaler
from api.utils.api_utils import construct_json_result
from api.utils.api_utils import construct_json_result,get_parser_config
from rag.nlp import search
from rag.utils import rmSpace
from rag.utils.es_conn import ELASTICSEARCH
@ -49,6 +49,10 @@ MAXIMUM_OF_UPLOADING_FILES = 256
MAXIMUM_OF_UPLOADING_FILES = 256
MAXIMUM_OF_UPLOADING_FILES = 256
MAXIMUM_OF_UPLOADING_FILES = 256
@manager.route('/dataset/<dataset_id>/document', methods=['POST'])
@token_required
@ -61,14 +65,41 @@ def upload(dataset_id, tenant_id):
if file_obj.filename == '':
return get_result(
retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR)
# total size
total_size = 0
for file_obj in file_objs:
file_obj.seek(0, os.SEEK_END)
total_size += file_obj.tell()
file_obj.seek(0)
MAX_TOTAL_FILE_SIZE=10*1024*1024
if total_size > MAX_TOTAL_FILE_SIZE:
return get_result(
retmsg=f'Total file size exceeds 10MB limit! ({total_size / (1024 * 1024):.2f} MB)',
retcode=RetCode.ARGUMENT_ERROR)
e, kb = KnowledgebaseService.get_by_id(dataset_id)
if not e:
raise LookupError(f"Can't find the knowledgebase with ID {dataset_id}!")
err, _ = FileService.upload_document(kb, file_objs, tenant_id)
raise LookupError(f"Can't find the dataset with ID {dataset_id}!")
err, files= FileService.upload_document(kb, file_objs, tenant_id)
if err:
return get_result(
retmsg="\n".join(err), retcode=RetCode.SERVER_ERROR)
return get_result()
# rename key's name
renamed_doc_list = []
for file in files:
doc = file[0]
key_mapping = {
"chunk_num": "chunk_count",
"kb_id": "dataset_id",
"token_num": "token_count",
"parser_id": "chunk_method"
}
renamed_doc = {}
for key, value in doc.items():
new_key = key_mapping.get(key, key)
renamed_doc[new_key] = value
renamed_doc["run"] = "UNSTART"
renamed_doc_list.append(renamed_doc)
return get_result(data=renamed_doc_list)
@manager.route('/dataset/<dataset_id>/info/<document_id>', methods=['PUT'])
@ -97,7 +128,7 @@ def update_doc(tenant_id, dataset_id, document_id):
for d in DocumentService.query(name=req["name"], kb_id=doc.kb_id):
if d.name == req["name"]:
return get_error_data_result(
retmsg="Duplicated document name in the same knowledgebase.")
retmsg="Duplicated document name in the same dataset.")
if not DocumentService.update_by_id(
document_id, {"name": req["name"]}):
return get_error_data_result(
@ -110,6 +141,9 @@ def update_doc(tenant_id, dataset_id, document_id):
if "parser_config" in req:
DocumentService.update_parser_config(doc.id, req["parser_config"])
if "chunk_method" in req:
valid_chunk_method = {"naive","manual","qa","table","paper","book","laws","presentation","picture","one","knowledge_graph","email"}
if req.get("chunk_method") not in valid_chunk_method:
return get_error_data_result(f"`chunk_method` {req['chunk_method']} doesn't exist")
if doc.parser_id.lower() == req["chunk_method"].lower():
return get_result()
@ -122,6 +156,7 @@ def update_doc(tenant_id, dataset_id, document_id):
"run": TaskStatus.UNSTART.value})
if not e:
return get_error_data_result(retmsg="Document not found!")
req["parser_config"] = get_parser_config(req["chunk_method"], req.get("parser_config"))
if doc.token_num > 0:
e = DocumentService.increment_chunk_num(doc.id, doc.kb_id, doc.token_num * -1, doc.chunk_num * -1,
doc.process_duation * -1)
@ -182,12 +217,21 @@ def list_docs(dataset_id, tenant_id):
for doc in docs:
key_mapping = {
"chunk_num": "chunk_count",
"kb_id": "knowledgebase_id",
"kb_id": "dataset_id",
"token_num": "token_count",
"parser_id": "chunk_method"
}
run_mapping = {
"0" :"UNSTART",
"1":"RUNNING",
"2":"CANCEL",
"3":"DONE",
"4":"FAIL"
}
renamed_doc = {}
for key, value in doc.items():
if key =="run":
renamed_doc["run"]=run_mapping.get(str(value))
new_key = key_mapping.get(key, key)
renamed_doc[new_key] = value
renamed_doc_list.append(renamed_doc)
@ -353,9 +397,10 @@ def list_chunks(tenant_id,dataset_id,document_id):
return get_result(data=res)
@manager.route('/dataset/<dataset_id>/document/<document_id>/chunk', methods=['POST'])
@token_required
def create(tenant_id,dataset_id,document_id):
def add_chunk(tenant_id,dataset_id,document_id):
if not KnowledgebaseService.query(id=dataset_id, tenant_id=tenant_id):
return get_error_data_result(retmsg=f"You don't own the dataset {dataset_id}.")
doc = DocumentService.query(id=document_id, kb_id=dataset_id)
@ -441,6 +486,7 @@ def rm_chunk(tenant_id,dataset_id,document_id):
return get_result()
@manager.route('/dataset/<dataset_id>/document/<document_id>/chunk/<chunk_id>', methods=['PUT'])
@token_required
def update_chunk(tenant_id,dataset_id,document_id,chunk_id):
@ -470,12 +516,12 @@ def update_chunk(tenant_id,dataset_id,document_id,chunk_id):
d["content_ltks"] = rag_tokenizer.tokenize(d["content_with_weight"])
d["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(d["content_ltks"])
if "important_keywords" in req:
if type(req["important_keywords"]) != list:
return get_error_data_result("`important_keywords` is required to be a list")
if not isinstance(req["important_keywords"],list):
return get_error_data_result("`important_keywords` should be a list")
d["important_kwd"] = req.get("important_keywords")
d["important_tks"] = rag_tokenizer.tokenize(" ".join(req["important_keywords"]))
if "available" in req:
d["available_int"] = req["available"]
d["available_int"] = int(req["available"])
embd_id = DocumentService.get_embd_id(document_id)
embd_mdl = TenantLLMService.model_instance(
tenant_id, LLMType.EMBEDDING.value, embd_id)
@ -498,6 +544,7 @@ def update_chunk(tenant_id,dataset_id,document_id,chunk_id):
return get_result()
@manager.route('/retrieval', methods=['POST'])
@token_required
def retrieval_test(tenant_id):
@ -505,6 +552,8 @@ def retrieval_test(tenant_id):
if not req.get("datasets"):
return get_error_data_result("`datasets` is required.")
kb_ids = req["datasets"]
if not isinstance(kb_ids,list):
return get_error_data_result("`datasets` should be a list")
kbs = KnowledgebaseService.get_by_ids(kb_ids)
embd_nms = list(set([kb.embd_id for kb in kbs]))
if len(embd_nms) != 1:
@ -518,9 +567,15 @@ def retrieval_test(tenant_id):
if "question" not in req:
return get_error_data_result("`question` is required.")
page = int(req.get("offset", 1))
size = int(req.get("limit", 30))
size = int(req.get("limit", 1024))
question = req["question"]
doc_ids = req.get("documents", [])
if not isinstance(req.get("documents"),list):
return get_error_data_result("`documents` should be a list")
doc_ids_list=KnowledgebaseService.list_documents_by_ids(kb_ids)
for doc_id in doc_ids:
if doc_id not in doc_ids_list:
return get_error_data_result(f"You don't own the document {doc_id}")
similarity_threshold = float(req.get("similarity_threshold", 0.2))
vector_similarity_weight = float(req.get("vector_similarity_weight", 0.3))
top = int(req.get("top_k", 1024))
@ -531,7 +586,7 @@ def retrieval_test(tenant_id):
try:
e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
if not e:
return get_error_data_result(retmsg="Knowledgebase not found!")
return get_error_data_result(retmsg="Dataset not found!")
embd_mdl = TenantLLMService.model_instance(
kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)

2
api/apps/sdk/session.py
View File

@ -199,7 +199,7 @@ def list(chat_id,tenant_id):
"content": chunk["content_with_weight"],
"document_id": chunk["doc_id"],
"document_name": chunk["docnm_kwd"],
"knowledgebase_id": chunk["kb_id"],
"dataset_id": chunk["kb_id"],
"image_id": chunk["img_id"],
"similarity": chunk["similarity"],
"vector_similarity": chunk["vector_similarity"],

12
api/db/services/knowledgebase_service.py
View File

@ -14,13 +14,23 @@
# limitations under the License.
#
from api.db import StatusEnum, TenantPermission
from api.db.db_models import Knowledgebase, DB, Tenant, User, UserTenant
from api.db.db_models import Knowledgebase, DB, Tenant, User, UserTenant,Document
from api.db.services.common_service import CommonService
class KnowledgebaseService(CommonService):
model = Knowledgebase
@classmethod
@DB.connection_context()
def list_documents_by_ids(cls,kb_ids):
doc_ids=cls.model.select(Document.id.alias("document_id")).join(Document,on=(cls.model.id == Document.kb_id)).where(
cls.model.id.in_(kb_ids)
)
doc_ids =list(doc_ids.dicts())
doc_ids = [doc["document_id"] for doc in doc_ids]
return doc_ids
@classmethod
@DB.connection_context()
def get_by_tenant_ids(cls, joined_tenant_ids, user_id,

19
api/utils/api_utils.py
View File

@ -338,3 +338,22 @@ def valid(permission,valid_permission,language,valid_language,chunk_method,valid
def valid_parameter(parameter,valid_values):
if parameter and parameter not in valid_values:
return get_error_data_result(f"{parameter} not in {valid_values}")
def get_parser_config(chunk_method,parser_config):
if parser_config:
return parser_config
if not chunk_method:
chunk_method = "naive"
key_mapping={"naive":{"chunk_token_num": 128, "delimiter": "\\n!?;。；！？", "html4excel": False,"layout_recognize": True, "raptor": {"user_raptor": False}},
"qa":{"raptor":{"use_raptor":False}},
"resume":None,
"manual":{"raptor":{"use_raptor":False}},
"table":None,
"paper":{"raptor":{"use_raptor":False}},
"book":{"raptor":{"use_raptor":False}},
"laws":{"raptor":{"use_raptor":False}},
"presentation":{"raptor":{"use_raptor":False}},
"one":None,
"knowledge_graph":{"chunk_token_num":8192,"delimiter":"\\n!?;。；！？","entity_types":["organization","person","location","event","time"]}}
parser_config=key_mapping[chunk_method]
return parser_config

2
sdk/python/ragflow/modules/chat.py
View File

@ -9,7 +9,7 @@ class Chat(Base):
self.id = ""
self.name = "assistant"
self.avatar = "path/to/avatar"
self.knowledgebases = ["kb1"]
self.datasets = ["kb1"]
self.llm = Chat.LLM(rag, {})
self.prompt = Chat.Prompt(rag, {})
super().__init__(rag, res_dict)

6
sdk/python/ragflow/modules/chunk.py
View File

@ -8,10 +8,10 @@ class Chunk(Base):
self.important_keywords = []
self.create_time = ""
self.create_timestamp = 0.0
self.knowledgebase_id = None
self.dataset_id = None
self.document_name = ""
self.document_id = ""
self.available = 1
self.available = True
for k in list(res_dict.keys()):
if k not in self.__dict__:
res_dict.pop(k)
@ -19,7 +19,7 @@ class Chunk(Base):
def update(self,update_message:dict):
res = self.put(f"/dataset/{self.knowledgebase_id}/document/{self.document_id}/chunk/{self.id}",update_message)
res = self.put(f"/dataset/{self.dataset_id}/document/{self.document_id}/chunk/{self.id}",update_message)
res = res.json()
if res.get("code") != 0 :
raise Exception(res["message"])

13
sdk/python/ragflow/modules/dataset.py
View File

@ -10,10 +10,6 @@ from .base import Base
class DataSet(Base):
class ParserConfig(Base):
def __init__(self, rag, res_dict):
self.chunk_token_count = 128
self.layout_recognize = True
self.delimiter = '\n!?。；！？'
self.task_page_size = 12
super().__init__(rag, res_dict)
def __init__(self, rag, res_dict):
@ -43,10 +39,15 @@ class DataSet(Base):
def upload_documents(self,document_list: List[dict]):
url = f"/dataset/{self.id}/document"
files = [("file",(ele["name"],ele["blob"])) for ele in document_list]
files = [("file",(ele["displayed_name"],ele["blob"])) for ele in document_list]
res = self.post(path=url,json=None,files=files)
res = res.json()
if res.get("code") != 0:
if res.get("code") == 0:
doc_list=[]
for doc in res["data"]:
document = Document(self.rag,doc)
doc_list.append(document)
return doc_list
raise Exception(res.get("message"))
def list_documents(self, id: str = None, keywords: str = None, offset: int =1, limit: int = 1024, orderby: str = "create_time", desc: bool = True):

20
sdk/python/ragflow/modules/document.py
View File

@ -5,12 +5,16 @@ from typing import List
class Document(Base):
class ParserConfig(Base):
def __init__(self, rag, res_dict):
super().__init__(rag, res_dict)
def __init__(self, rag, res_dict):
self.id = ""
self.name = ""
self.thumbnail = None
self.knowledgebase_id = None
self.chunk_method = ""
self.dataset_id = None
self.chunk_method = "naive"
self.parser_config = {"pages": [[1, 1000000]]}
self.source_type = "local"
self.type = ""
@ -31,14 +35,14 @@ class Document(Base):
def update(self, update_message: dict):
res = self.put(f'/dataset/{self.knowledgebase_id}/info/{self.id}',
res = self.put(f'/dataset/{self.dataset_id}/info/{self.id}',
update_message)
res = res.json()
if res.get("code") != 0:
raise Exception(res["message"])
def download(self):
res = self.get(f"/dataset/{self.knowledgebase_id}/document/{self.id}")
res = self.get(f"/dataset/{self.dataset_id}/document/{self.id}")
try:
res = res.json()
raise Exception(res.get("message"))
@ -48,7 +52,7 @@ class Document(Base):
def list_chunks(self,offset=0, limit=30, keywords="", id:str=None):
data={"document_id": self.id,"keywords": keywords,"offset":offset,"limit":limit,"id":id}
res = self.get(f'/dataset/{self.knowledgebase_id}/document/{self.id}/chunk', data)
res = self.get(f'/dataset/{self.dataset_id}/document/{self.id}/chunk', data)
res = res.json()
if res.get("code") == 0:
chunks=[]
@ -59,15 +63,15 @@ class Document(Base):
raise Exception(res.get("message"))
def add_chunk(self, content: str):
res = self.post(f'/dataset/{self.knowledgebase_id}/document/{self.id}/chunk', {"content":content})
def add_chunk(self, content: str,important_keywords:List[str]=[]):
res = self.post(f'/dataset/{self.dataset_id}/document/{self.id}/chunk', {"content":content,"important_keywords":important_keywords})
res = res.json()
if res.get("code") == 0:
return Chunk(self.rag,res["data"].get("chunk"))
raise Exception(res.get("message"))
def delete_chunks(self,ids:List[str]):
res = self.rm(f"dataset/{self.knowledgebase_id}/document/{self.id}/chunk",{"ids":ids})
res = self.rm(f"dataset/{self.dataset_id}/document/{self.id}/chunk",{"ids":ids})
res = res.json()
if res.get("code")!=0:
raise Exception(res.get("message"))

4
sdk/python/ragflow/modules/session.py
View File

@ -40,7 +40,7 @@ class Session(Base):
"content": chunk["content_with_weight"],
"document_id": chunk["doc_id"],
"document_name": chunk["docnm_kwd"],
"knowledgebase_id": chunk["kb_id"],
"dataset_id": chunk["kb_id"],
"image_id": chunk["img_id"],
"similarity": chunk["similarity"],
"vector_similarity": chunk["vector_similarity"],
@ -75,7 +75,7 @@ class Chunk(Base):
self.content = None
self.document_id = ""
self.document_name = ""
self.knowledgebase_id = ""
self.dataset_id = ""
self.image_id = ""
self.similarity = None
self.vector_similarity = None

33
sdk/python/ragflow/ragflow.py
View File

@ -49,17 +49,11 @@ class RAGFlow:
return res
def create_dataset(self, name: str, avatar: str = "", description: str = "", language: str = "English",
permission: str = "me",
document_count: int = 0, chunk_count: int = 0, chunk_method: str = "naive",
permission: str = "me",chunk_method: str = "naive",
parser_config: DataSet.ParserConfig = None) -> DataSet:
if parser_config is None:
parser_config = DataSet.ParserConfig(self, {"chunk_token_count": 128, "layout_recognize": True,
"delimiter": "\n!?。；！？", "task_page_size": 12})
parser_config = parser_config.to_json()
res = self.post("/dataset",
{"name": name, "avatar": avatar, "description": description, "language": language,
"permission": permission,
"document_count": document_count, "chunk_count": chunk_count, "chunk_method": chunk_method,
"permission": permission, "chunk_method": chunk_method,
"parser_config": parser_config
}
)
@ -93,11 +87,11 @@ class RAGFlow:
return result_list
raise Exception(res["message"])
def create_chat(self, name: str, avatar: str = "", knowledgebases: List[DataSet] = [],
def create_chat(self, name: str, avatar: str = "", datasets: List[DataSet] = [],
llm: Chat.LLM = None, prompt: Chat.Prompt = None) -> Chat:
datasets = []
for dataset in knowledgebases:
datasets.append(dataset.to_json())
dataset_list = []
for dataset in datasets:
dataset_list.append(dataset.to_json())
if llm is None:
llm = Chat.LLM(self, {"model_name": None,
@ -130,7 +124,7 @@ class RAGFlow:
temp_dict = {"name": name,
"avatar": avatar,
"knowledgebases": datasets,
"datasets": dataset_list,
"llm": llm.to_json(),
"prompt": prompt.to_json()}
res = self.post("/chat", temp_dict)
@ -158,25 +152,22 @@ class RAGFlow:
raise Exception(res["message"])
def retrieve(self, question="",datasets=None,documents=None, offset=1, limit=30, similarity_threshold=0.2,vector_similarity_weight=0.3,top_k=1024,rerank_id:str=None,keyword:bool=False,):
data_params = {
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,):
data_json ={
"offset": offset,
"limit": limit,
"similarity_threshold": similarity_threshold,
"vector_similarity_weight": vector_similarity_weight,
"top_k": top_k,
"knowledgebase_id": datasets,
"rerank_id":rerank_id,
"keyword":keyword
}
data_json ={
"rerank_id": rerank_id,
"keyword": keyword,
"question": question,
"datasets": datasets,
"documents": documents
}
# Send a POST request to the backend service (using requests library as an example, actual implementation may vary)
res = self.get(f'/retrieval', data_params,data_json)
res = self.post(f'/retrieval',json=data_json)
res = res.json()
if res.get("code") ==0:
chunks=[]

7
sdk/python/test/t_chat.py
View File

@ -1,4 +1,5 @@
from ragflow import RAGFlow, Chat
from xgboost.testing import datasets
from common import API_KEY, HOST_ADDRESS
from test_sdkbase import TestSdk
@ -11,7 +12,7 @@ class TestChat(TestSdk):
"""
rag = RAGFlow(API_KEY, HOST_ADDRESS)
kb = rag.create_dataset(name="test_create_chat")
chat = rag.create_chat("test_create", knowledgebases=[kb])
chat = rag.create_chat("test_create", datasets=[kb])
if isinstance(chat, Chat):
assert chat.name == "test_create", "Name does not match."
else:
@ -23,7 +24,7 @@ class TestChat(TestSdk):
"""
rag = RAGFlow(API_KEY, HOST_ADDRESS)
kb = rag.create_dataset(name="test_update_chat")
chat = rag.create_chat("test_update", knowledgebases=[kb])
chat = rag.create_chat("test_update", datasets=[kb])
if isinstance(chat, Chat):
assert chat.name == "test_update", "Name does not match."
res=chat.update({"name":"new_chat"})
@ -37,7 +38,7 @@ class TestChat(TestSdk):
"""
rag = RAGFlow(API_KEY, HOST_ADDRESS)
kb = rag.create_dataset(name="test_delete_chat")
chat = rag.create_chat("test_delete", knowledgebases=[kb])
chat = rag.create_chat("test_delete", datasets=[kb])
if isinstance(chat, Chat):
assert chat.name == "test_delete", "Name does not match."
res = rag.delete_chats(ids=[chat.id])

10
sdk/python/test/t_session.py
View File

@ -7,14 +7,14 @@ class TestSession:
def test_create_session(self):
rag = RAGFlow(API_KEY, HOST_ADDRESS)
kb = rag.create_dataset(name="test_create_session")
assistant = rag.create_chat(name="test_create_session", knowledgebases=[kb])
assistant = rag.create_chat(name="test_create_session", datasets=[kb])
session = assistant.create_session()
assert isinstance(session,Session), "Failed to create a session."
def test_create_chat_with_success(self):
rag = RAGFlow(API_KEY, HOST_ADDRESS)
kb = rag.create_dataset(name="test_create_chat")
assistant = rag.create_chat(name="test_create_chat", knowledgebases=[kb])
assistant = rag.create_chat(name="test_create_chat", datasets=[kb])
session = assistant.create_session()
question = "What is AI"
for ans in session.ask(question, stream=True):
@ -24,7 +24,7 @@ class TestSession:
def test_delete_sessions_with_success(self):
rag = RAGFlow(API_KEY, HOST_ADDRESS)
kb = rag.create_dataset(name="test_delete_session")
assistant = rag.create_chat(name="test_delete_session",knowledgebases=[kb])
assistant = rag.create_chat(name="test_delete_session",datasets=[kb])
session=assistant.create_session()
res=assistant.delete_sessions(ids=[session.id])
assert res is None, "Failed to delete the dataset."
@ -32,7 +32,7 @@ class TestSession:
def test_update_session_with_success(self):
rag=RAGFlow(API_KEY,HOST_ADDRESS)
kb=rag.create_dataset(name="test_update_session")
assistant = rag.create_chat(name="test_update_session",knowledgebases=[kb])
assistant = rag.create_chat(name="test_update_session",datasets=[kb])
session=assistant.create_session(name="old session")
res=session.update({"name":"new session"})
assert res is None,"Failed to update the session"
@ -41,7 +41,7 @@ class TestSession:
def test_list_sessions_with_success(self):
rag=RAGFlow(API_KEY,HOST_ADDRESS)
kb=rag.create_dataset(name="test_list_session")
assistant=rag.create_chat(name="test_list_session",knowledgebases=[kb])
assistant=rag.create_chat(name="test_list_session",datasets=[kb])
assistant.create_session("test_1")
assistant.create_session("test_2")
sessions=assistant.list_sessions()