pengjunjie/ragflow
1
0
Fork 1
mirror of https://github.com/infiniflow/ragflow.git synced 2025-12-08 20:42:30 +08:00
Code Issues Packages Projects Releases Wiki Activity

Feat: add or logic operations for meta data filters. (#11404)

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

#11376 #11387

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
This commit is contained in:
Kevin Hu
2025-11-20 14:31:12 +08:00
committed by GitHub
parent d2b1da0e26
commit 06cef71ba6
11 changed files with 129 additions and 48 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
api/db/services/canvas_service.py
View File

@ -177,7 +177,7 @@ class UserCanvasService(CommonService):
return True
def completion(tenant_id, agent_id, session_id=None, **kwargs):
async def completion(tenant_id, agent_id, session_id=None, **kwargs):
query = kwargs.get("query", "") or kwargs.get("question", "")
files = kwargs.get("files", [])
inputs = kwargs.get("inputs", {})
@ -219,7 +219,7 @@ def completion(tenant_id, agent_id, session_id=None, **kwargs):
"id": message_id
})
txt = ""
for ans in canvas.run(query=query, files=files, user_id=user_id, inputs=inputs):
async for ans in canvas.run(query=query, files=files, user_id=user_id, inputs=inputs):
ans["session_id"] = session_id
if ans["event"] == "message":
txt += ans["data"]["content"]
@ -237,7 +237,7 @@ def completion(tenant_id, agent_id, session_id=None, **kwargs):
API4ConversationService.append_message(conv["id"], conv)
def completion_openai(tenant_id, agent_id, question, session_id=None, stream=True, **kwargs):
async def completion_openai(tenant_id, agent_id, question, session_id=None, stream=True, **kwargs):
tiktoken_encoder = tiktoken.get_encoding("cl100k_base")
prompt_tokens = len(tiktoken_encoder.encode(str(question)))
user_id = kwargs.get("user_id", "")
@ -245,7 +245,7 @@ def completion_openai(tenant_id, agent_id, question, session_id=None, stream=Tru
if stream:
completion_tokens = 0
try:
for ans in completion(
async for ans in completion(
tenant_id=tenant_id,
agent_id=agent_id,
session_id=session_id,
@ -304,7 +304,7 @@ def completion_openai(tenant_id, agent_id, question, session_id=None, stream=Tru
try:
all_content = ""
reference = {}
for ans in completion(
async for ans in completion(
tenant_id=tenant_id,
agent_id=agent_id,
session_id=session_id,