ragflow/api/db/services/canvas_service.py
Yongteng Lei e6bad45c6d
Fix: update broken agent OpenAI-Compatible completion due to v0.20.0 changes (#9241)
### What problem does this PR solve?

Update broken agent OpenAI-Compatible completion due to v0.20.0. #9199 

Usage example:

**Referring the input is important, otherwise, will result in empty
output.**

<img width="1273" height="711" alt="Image"
src="https://github.com/user-attachments/assets/30740be8-f4d6-400d-9fda-d2616f89063f"
/>

<img width="622" height="247" alt="Image"
src="https://github.com/user-attachments/assets/0a2ca57a-9600-4cec-9362-0cafd0ab3aee"
/>

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
2025-08-05 17:47:25 +08:00

276 lines
9.7 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 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 api.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 UserCanvasService(CommonService):
model = UserCanvas
@classmethod
@DB.connection_context()
def get_list(cls, tenant_id,
page_number, items_per_page, orderby, desc, id, title):
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)
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_by_tenant_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,
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,
):
fields = [
cls.model.id,
cls.model.avatar,
cls.model.title,
cls.model.dsl,
cls.model.description,
cls.model.permission,
User.nickname,
User.avatar.alias('tenant_avatar'),
cls.model.update_time
]
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 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()
agents = agents.paginate(page_number, items_per_page)
return list(agents.dicts()), count
def completion(tenant_id, agent_id, session_id=None, **kwargs):
query = kwargs.get("query", "")
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
}
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"]
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 = conv.to_dict()
API4ConversationService.append_message(conv["id"], conv)
def completionOpenAI(tenant_id, agent_id, question, session_id=None, stream=True, **kwargs):
tiktokenenc = tiktoken.get_encoding("cl100k_base")
prompt_tokens = len(tiktokenenc.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 completionOpenAI parse answer failed: {e}")
continue
if ans.get("event") != "message":
continue
content_piece = ans["data"]["content"]
completion_tokens += len(tiktokenenc.encode(content_piece))
yield "data: " + json.dumps(
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
),
ensure_ascii=False
) + "\n\n"
yield "data: [DONE]\n\n"
except Exception as 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(tiktokenenc.encode(f"**ERROR**: {str(e)}")),
stream=True
),
ensure_ascii=False
) + "\n\n"
yield "data: [DONE]\n\n"
else:
try:
all_content = ""
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") != "message":
continue
all_content += ans["data"]["content"]
completion_tokens = len(tiktokenenc.encode(all_content))
yield 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
)
except Exception as e:
yield get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
prompt_tokens=prompt_tokens,
completion_tokens=len(tiktokenenc.encode(f"**ERROR**: {str(e)}")),
content=f"**ERROR**: {str(e)}",
finish_reason="stop",
param=None
)