Files
ragflow/api/db/services/canvas_service.py
天海蒼灆 9f715d6bc2 Feature (canvas): Add mind tagging support (#11359)
### What problem does this PR solve?
Resolve the issue of missing thinking labels when viewing pre-existing
conversations
### Type of change

- [x] New Feature (non-breaking change which adds functionality)
2025-11-20 10:11:28 +08:00

353 lines
13 KiB
Python

#
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import json
import logging
import time
from uuid import uuid4
from agent.canvas import Canvas
from api.db import CanvasCategory, TenantPermission
from api.db.db_models import DB, CanvasTemplate, User, UserCanvas, API4Conversation
from api.db.services.api_service import API4ConversationService
from api.db.services.common_service import CommonService
from common.misc_utils import get_uuid
from api.utils.api_utils import get_data_openai
import tiktoken
from peewee import fn
class CanvasTemplateService(CommonService):
model = CanvasTemplate
class DataFlowTemplateService(CommonService):
"""
Alias of CanvasTemplateService
"""
model = CanvasTemplate
class UserCanvasService(CommonService):
model = UserCanvas
@classmethod
@DB.connection_context()
def get_list(cls, tenant_id,
page_number, items_per_page, orderby, desc, id, title, canvas_category=CanvasCategory.Agent):
agents = cls.model.select()
if id:
agents = agents.where(cls.model.id == id)
if title:
agents = agents.where(cls.model.title == title)
agents = agents.where(cls.model.user_id == tenant_id)
agents = agents.where(cls.model.canvas_category == canvas_category)
if desc:
agents = agents.order_by(cls.model.getter_by(orderby).desc())
else:
agents = agents.order_by(cls.model.getter_by(orderby).asc())
agents = agents.paginate(page_number, items_per_page)
return list(agents.dicts())
@classmethod
@DB.connection_context()
def get_all_agents_by_tenant_ids(cls, tenant_ids, user_id):
# will get all permitted agents, be cautious
fields = [
cls.model.id,
cls.model.avatar,
cls.model.title,
cls.model.permission,
cls.model.canvas_type,
cls.model.canvas_category
]
# find team agents and owned agents
agents = cls.model.select(*fields).where(
(cls.model.user_id.in_(tenant_ids) & (cls.model.permission == TenantPermission.TEAM.value)) | (
cls.model.user_id == user_id
)
)
# sort by create_time, asc
agents.order_by(cls.model.create_time.asc())
# maybe cause slow query by deep paginate, optimize later
offset, limit = 0, 50
res = []
while True:
ag_batch = agents.offset(offset).limit(limit)
_temp = list(ag_batch.dicts())
if not _temp:
break
res.extend(_temp)
offset += limit
return res
@classmethod
@DB.connection_context()
def get_by_canvas_id(cls, pid):
try:
fields = [
cls.model.id,
cls.model.avatar,
cls.model.title,
cls.model.dsl,
cls.model.description,
cls.model.permission,
cls.model.update_time,
cls.model.user_id,
cls.model.create_time,
cls.model.create_date,
cls.model.update_date,
cls.model.canvas_category,
User.nickname,
User.avatar.alias('tenant_avatar'),
]
agents = cls.model.select(*fields) \
.join(User, on=(cls.model.user_id == User.id)) \
.where(cls.model.id == pid)
# obj = cls.model.query(id=pid)[0]
return True, agents.dicts()[0]
except Exception as e:
logging.exception(e)
return False, None
@classmethod
@DB.connection_context()
def get_by_tenant_ids(cls, joined_tenant_ids, user_id,
page_number, items_per_page,
orderby, desc, keywords, canvas_category=None
):
fields = [
cls.model.id,
cls.model.avatar,
cls.model.title,
cls.model.dsl,
cls.model.description,
cls.model.permission,
cls.model.user_id.alias("tenant_id"),
User.nickname,
User.avatar.alias('tenant_avatar'),
cls.model.update_time,
cls.model.canvas_category,
]
if keywords:
agents = cls.model.select(*fields).join(User, on=(cls.model.user_id == User.id)).where(
(((cls.model.user_id.in_(joined_tenant_ids)) & (cls.model.permission == TenantPermission.TEAM.value)) | (cls.model.user_id == user_id)),
(fn.LOWER(cls.model.title).contains(keywords.lower()))
)
else:
agents = cls.model.select(*fields).join(User, on=(cls.model.user_id == User.id)).where(
(((cls.model.user_id.in_(joined_tenant_ids)) & (cls.model.permission == TenantPermission.TEAM.value)) | (cls.model.user_id == user_id))
)
if canvas_category:
agents = agents.where(cls.model.canvas_category == canvas_category)
if desc:
agents = agents.order_by(cls.model.getter_by(orderby).desc())
else:
agents = agents.order_by(cls.model.getter_by(orderby).asc())
count = agents.count()
if page_number and items_per_page:
agents = agents.paginate(page_number, items_per_page)
return list(agents.dicts()), count
@classmethod
@DB.connection_context()
def accessible(cls, canvas_id, tenant_id):
from api.db.services.user_service import UserTenantService
e, c = UserCanvasService.get_by_canvas_id(canvas_id)
if not e:
return False
tids = [t.tenant_id for t in UserTenantService.query(user_id=tenant_id)]
if c["user_id"] != canvas_id and c["user_id"] not in tids:
return False
return True
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", {})
user_id = kwargs.get("user_id", "")
if session_id:
e, conv = API4ConversationService.get_by_id(session_id)
assert e, "Session not found!"
if not conv.message:
conv.message = []
if not isinstance(conv.dsl, str):
conv.dsl = json.dumps(conv.dsl, ensure_ascii=False)
canvas = Canvas(conv.dsl, tenant_id, agent_id)
else:
e, cvs = UserCanvasService.get_by_id(agent_id)
assert e, "Agent not found."
assert cvs.user_id == tenant_id, "You do not own the agent."
if not isinstance(cvs.dsl, str):
cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
session_id=get_uuid()
canvas = Canvas(cvs.dsl, tenant_id, agent_id)
canvas.reset()
conv = {
"id": session_id,
"dialog_id": cvs.id,
"user_id": user_id,
"message": [],
"source": "agent",
"dsl": cvs.dsl,
"reference": []
}
API4ConversationService.save(**conv)
conv = API4Conversation(**conv)
message_id = str(uuid4())
conv.message.append({
"role": "user",
"content": query,
"id": message_id
})
txt = ""
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"]
if ans["data"].get("start_to_think", False):
txt += "<think>"
elif ans["data"].get("end_to_think", False):
txt += "</think>"
yield "data:" + json.dumps(ans, ensure_ascii=False) + "\n\n"
conv.message.append({"role": "assistant", "content": txt, "created_at": time.time(), "id": message_id})
conv.reference = canvas.get_reference()
conv.errors = canvas.error
conv.dsl = str(canvas)
conv = conv.to_dict()
API4ConversationService.append_message(conv["id"], conv)
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", "")
if stream:
completion_tokens = 0
try:
for ans in completion(
tenant_id=tenant_id,
agent_id=agent_id,
session_id=session_id,
query=question,
user_id=user_id,
**kwargs
):
if isinstance(ans, str):
try:
ans = json.loads(ans[5:]) # remove "data:"
except Exception as e:
logging.exception(f"Agent OpenAI-Compatible completion_openai parse answer failed: {e}")
continue
if ans.get("event") not in ["message", "message_end"]:
continue
content_piece = ""
if ans["event"] == "message":
content_piece = ans["data"]["content"]
completion_tokens += len(tiktoken_encoder.encode(content_piece))
openai_data = get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
content=content_piece,
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
stream=True
)
if ans.get("data", {}).get("reference", None):
openai_data["choices"][0]["delta"]["reference"] = ans["data"]["reference"]
yield "data: " + json.dumps(openai_data, ensure_ascii=False) + "\n\n"
yield "data: [DONE]\n\n"
except Exception as e:
logging.exception(e)
yield "data: " + json.dumps(
get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
content=f"**ERROR**: {str(e)}",
finish_reason="stop",
prompt_tokens=prompt_tokens,
completion_tokens=len(tiktoken_encoder.encode(f"**ERROR**: {str(e)}")),
stream=True
),
ensure_ascii=False
) + "\n\n"
yield "data: [DONE]\n\n"
else:
try:
all_content = ""
reference = {}
for ans in completion(
tenant_id=tenant_id,
agent_id=agent_id,
session_id=session_id,
query=question,
user_id=user_id,
**kwargs
):
if isinstance(ans, str):
ans = json.loads(ans[5:])
if ans.get("event") not in ["message", "message_end"]:
continue
if ans["event"] == "message":
all_content += ans["data"]["content"]
if ans.get("data", {}).get("reference", None):
reference.update(ans["data"]["reference"])
completion_tokens = len(tiktoken_encoder.encode(all_content))
openai_data = get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
content=all_content,
finish_reason="stop",
param=None
)
if reference:
openai_data["choices"][0]["message"]["reference"] = reference
yield openai_data
except Exception as e:
logging.exception(e)
yield get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
prompt_tokens=prompt_tokens,
completion_tokens=len(tiktoken_encoder.encode(f"**ERROR**: {str(e)}")),
content=f"**ERROR**: {str(e)}",
finish_reason="stop",
param=None
)