ragflow/api/apps/conversation_app.py

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#
# 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 re
import traceback
from copy import deepcopy
import trio
from flask import Response, request
from flask_login import current_user, login_required
from api import settings
from api.db import LLMType
from api.db.db_models import APIToken
from api.db.services.conversation_service import ConversationService, structure_answer
from api.db.services.dialog_service import DialogService, ask, chat
from api.db.services.knowledgebase_service import KnowledgebaseService
from api.db.services.llm_service import LLMBundle
from api.db.services.tenant_llm_service import TenantLLMService
from api.db.services.user_service import TenantService, UserTenantService
from api.utils.api_utils import get_data_error_result, get_json_result, server_error_response, validate_request
from graphrag.general.mind_map_extractor import MindMapExtractor
from rag.app.tag import label_question
from rag.prompts.prompt_template import load_prompt
from rag.prompts.prompts import chunks_format
@manager.route("/set", methods=["POST"]) # noqa: F821
@login_required
def set_conversation():
req = request.json
conv_id = req.get("conversation_id")
is_new = req.get("is_new")
Fix: value too long error for chat name (#7697) ### What problem does this PR solve? Hello, when I input a very long line in the chat input box, it will fail with following error: ``` 2025-05-17 16:11:26,004 ERROR 182558 value too long for type character varying(255) Traceback (most recent call last): File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3291, in execute_sql cursor.execute(sql, params or ()) psycopg2.errors.StringDataRightTruncation: value too long for type character varying(255) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/var/home/sfc/Projects/ragflow/api/apps/conversation_app.py", line 68, in set_conversation ConversationService.save(**conv) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3128, in inner return fn(*args, **kwargs) File "/var/home/sfc/Projects/ragflow/api/db/services/common_service.py", line 145, in save return cls.save_n(**kwargs) File "/var/home/sfc/Projects/ragflow/api/db/services/common_service.py", line 139, in save_n sample_obj = cls.model(**kwargs).save(force_insert=True) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 6923, in save pk = self.insert(**field_dict).execute() File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2011, in inner return method(self, database, *args, **kwargs) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2082, in execute return self._execute(database) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2887, in _execute return super(Insert, self)._execute(database) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2598, in _execute cursor = self.execute_returning(database) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2605, in execute_returning cursor = database.execute(self) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3299, in execute return self.execute_sql(sql, params) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3289, in execute_sql with __exception_wrapper__: File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3059, in __exit__ reraise(new_type, new_type(exc_value, *exc_args), traceback) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 192, in reraise raise value.with_traceback(tb) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3291, in execute_sql cursor.execute(sql, params or ()) peewee.DataError: value too long for type character varying(255) ``` This PR fix it by truncate the `name` field in the `set_conversation` method in the `conversation_app.py`. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [ ] New Feature (non-breaking change which adds functionality) - [ ] Documentation Update - [ ] Refactoring - [ ] Performance Improvement - [ ] Other (please describe):
2025-05-19 10:25:41 +08:00
name = req.get("name", "New conversation")
req["user_id"] = current_user.id
Fix: value too long error for chat name (#7697) ### What problem does this PR solve? Hello, when I input a very long line in the chat input box, it will fail with following error: ``` 2025-05-17 16:11:26,004 ERROR 182558 value too long for type character varying(255) Traceback (most recent call last): File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3291, in execute_sql cursor.execute(sql, params or ()) psycopg2.errors.StringDataRightTruncation: value too long for type character varying(255) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/var/home/sfc/Projects/ragflow/api/apps/conversation_app.py", line 68, in set_conversation ConversationService.save(**conv) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3128, in inner return fn(*args, **kwargs) File "/var/home/sfc/Projects/ragflow/api/db/services/common_service.py", line 145, in save return cls.save_n(**kwargs) File "/var/home/sfc/Projects/ragflow/api/db/services/common_service.py", line 139, in save_n sample_obj = cls.model(**kwargs).save(force_insert=True) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 6923, in save pk = self.insert(**field_dict).execute() File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2011, in inner return method(self, database, *args, **kwargs) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2082, in execute return self._execute(database) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2887, in _execute return super(Insert, self)._execute(database) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2598, in _execute cursor = self.execute_returning(database) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 2605, in execute_returning cursor = database.execute(self) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3299, in execute return self.execute_sql(sql, params) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3289, in execute_sql with __exception_wrapper__: File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3059, in __exit__ reraise(new_type, new_type(exc_value, *exc_args), traceback) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 192, in reraise raise value.with_traceback(tb) File "/var/home/sfc/Projects/ragflow/.venv/lib/python3.10/site-packages/peewee.py", line 3291, in execute_sql cursor.execute(sql, params or ()) peewee.DataError: value too long for type character varying(255) ``` This PR fix it by truncate the `name` field in the `set_conversation` method in the `conversation_app.py`. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [ ] New Feature (non-breaking change which adds functionality) - [ ] Documentation Update - [ ] Refactoring - [ ] Performance Improvement - [ ] Other (please describe):
2025-05-19 10:25:41 +08:00
if len(name) > 255:
name = name[0:255]
del req["is_new"]
if not is_new:
del req["conversation_id"]
try:
if not ConversationService.update_by_id(conv_id, req):
return get_data_error_result(message="Conversation not found!")
e, conv = ConversationService.get_by_id(conv_id)
if not e:
return get_data_error_result(message="Fail to update a conversation!")
conv = conv.to_dict()
return get_json_result(data=conv)
except Exception as e:
return server_error_response(e)
try:
e, dia = DialogService.get_by_id(req["dialog_id"])
if not e:
return get_data_error_result(message="Dialog not found")
conv = {
"id": conv_id,
"dialog_id": req["dialog_id"],
"name": name,
"message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}],
"user_id": current_user.id,
"reference": [],
}
ConversationService.save(**conv)
return get_json_result(data=conv)
except Exception as e:
return server_error_response(e)
@manager.route("/get", methods=["GET"]) # noqa: F821
@login_required
def get():
conv_id = request.args["conversation_id"]
try:
e, conv = ConversationService.get_by_id(conv_id)
if not e:
return get_data_error_result(message="Conversation not found!")
tenants = UserTenantService.query(user_id=current_user.id)
avatar = None
for tenant in tenants:
dialog = DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id)
if dialog and len(dialog) > 0:
avatar = dialog[0].icon
break
else:
return get_json_result(data=False, message="Only owner of conversation authorized for this operation.", code=settings.RetCode.OPERATING_ERROR)
for ref in conv.reference:
if isinstance(ref, list):
continue
ref["chunks"] = chunks_format(ref)
conv = conv.to_dict()
conv["avatar"] = avatar
return get_json_result(data=conv)
except Exception as e:
return server_error_response(e)
@manager.route("/getsse/<dialog_id>", methods=["GET"]) # type: ignore # noqa: F821
def getsse(dialog_id):
token = request.headers.get("Authorization").split()
if len(token) != 2:
return get_data_error_result(message='Authorization is not valid!"')
token = token[1]
objs = APIToken.query(beta=token)
if not objs:
return get_data_error_result(message='Authentication error: API key is invalid!"')
try:
e, conv = DialogService.get_by_id(dialog_id)
if not e:
return get_data_error_result(message="Dialog not found!")
conv = conv.to_dict()
conv["avatar"] = conv["icon"]
del conv["icon"]
return get_json_result(data=conv)
except Exception as e:
return server_error_response(e)
@manager.route("/rm", methods=["POST"]) # noqa: F821
@login_required
def rm():
conv_ids = request.json["conversation_ids"]
try:
for cid in conv_ids:
exist, conv = ConversationService.get_by_id(cid)
if not exist:
return get_data_error_result(message="Conversation not found!")
tenants = UserTenantService.query(user_id=current_user.id)
for tenant in tenants:
if DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id):
break
else:
return get_json_result(data=False, message="Only owner of conversation authorized for this operation.", code=settings.RetCode.OPERATING_ERROR)
ConversationService.delete_by_id(cid)
return get_json_result(data=True)
except Exception as e:
return server_error_response(e)
@manager.route("/list", methods=["GET"]) # noqa: F821
@login_required
def list_conversation():
dialog_id = request.args["dialog_id"]
try:
if not DialogService.query(tenant_id=current_user.id, id=dialog_id):
return get_json_result(data=False, message="Only owner of dialog authorized for this operation.", code=settings.RetCode.OPERATING_ERROR)
convs = ConversationService.query(dialog_id=dialog_id, order_by=ConversationService.model.create_time, reverse=True)
convs = [d.to_dict() for d in convs]
return get_json_result(data=convs)
except Exception as e:
return server_error_response(e)
@manager.route("/completion", methods=["POST"]) # noqa: F821
@login_required
@validate_request("conversation_id", "messages")
def completion():
req = request.json
msg = []
for m in req["messages"]:
if m["role"] == "system":
continue
if m["role"] == "assistant" and not msg:
continue
msg.append(m)
message_id = msg[-1].get("id")
chat_model_id = req.get("llm_id", "")
req.pop("llm_id", None)
chat_model_config = {}
for model_config in [
"temperature",
"top_p",
"frequency_penalty",
"presence_penalty",
"max_tokens",
]:
config = req.get(model_config)
if config:
chat_model_config[model_config] = config
try:
e, conv = ConversationService.get_by_id(req["conversation_id"])
if not e:
return get_data_error_result(message="Conversation not found!")
conv.message = deepcopy(req["messages"])
e, dia = DialogService.get_by_id(conv.dialog_id)
if not e:
return get_data_error_result(message="Dialog not found!")
del req["conversation_id"]
del req["messages"]
if not conv.reference:
conv.reference = []
conv.reference = [r for r in conv.reference if r]
conv.reference.append({"chunks": [], "doc_aggs": []})
if chat_model_id:
if not TenantLLMService.get_api_key(tenant_id=dia.tenant_id, model_name=chat_model_id):
req.pop("chat_model_id", None)
req.pop("chat_model_config", None)
return get_data_error_result(message=f"Cannot use specified model {chat_model_id}.")
dia.llm_id = chat_model_id
dia.llm_setting = chat_model_config
is_embedded = bool(chat_model_id)
def stream():
nonlocal dia, msg, req, conv
try:
for ans in chat(dia, msg, True, **req):
ans = structure_answer(conv, ans, message_id, conv.id)
yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
if not is_embedded:
ConversationService.update_by_id(conv.id, conv.to_dict())
except Exception as e:
traceback.print_exc()
yield "data:" + json.dumps({"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}}, ensure_ascii=False) + "\n\n"
yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
if req.get("stream", True):
resp = Response(stream(), mimetype="text/event-stream")
resp.headers.add_header("Cache-control", "no-cache")
resp.headers.add_header("Connection", "keep-alive")
resp.headers.add_header("X-Accel-Buffering", "no")
resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
return resp
else:
answer = None
for ans in chat(dia, msg, **req):
answer = structure_answer(conv, ans, message_id, conv.id)
if not is_embedded:
ConversationService.update_by_id(conv.id, conv.to_dict())
break
return get_json_result(data=answer)
except Exception as e:
return server_error_response(e)
@manager.route("/tts", methods=["POST"]) # noqa: F821
@login_required
def tts():
req = request.json
text = req["text"]
tenants = TenantService.get_info_by(current_user.id)
if not tenants:
return get_data_error_result(message="Tenant not found!")
tts_id = tenants[0]["tts_id"]
if not tts_id:
return get_data_error_result(message="No default TTS model is set")
tts_mdl = LLMBundle(tenants[0]["tenant_id"], LLMType.TTS, tts_id)
def stream_audio():
try:
for txt in re.split(r"[,。/《》?;:!\n\r:;]+", text):
for chunk in tts_mdl.tts(txt):
yield chunk
except Exception as e:
yield ("data:" + json.dumps({"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e)}}, ensure_ascii=False)).encode("utf-8")
resp = Response(stream_audio(), mimetype="audio/mpeg")
resp.headers.add_header("Cache-Control", "no-cache")
resp.headers.add_header("Connection", "keep-alive")
resp.headers.add_header("X-Accel-Buffering", "no")
return resp
@manager.route("/delete_msg", methods=["POST"]) # noqa: F821
@login_required
@validate_request("conversation_id", "message_id")
def delete_msg():
req = request.json
e, conv = ConversationService.get_by_id(req["conversation_id"])
if not e:
return get_data_error_result(message="Conversation not found!")
conv = conv.to_dict()
for i, msg in enumerate(conv["message"]):
if req["message_id"] != msg.get("id", ""):
continue
assert conv["message"][i + 1]["id"] == req["message_id"]
conv["message"].pop(i)
conv["message"].pop(i)
conv["reference"].pop(max(0, i // 2 - 1))
break
ConversationService.update_by_id(conv["id"], conv)
return get_json_result(data=conv)
@manager.route("/thumbup", methods=["POST"]) # noqa: F821
@login_required
@validate_request("conversation_id", "message_id")
def thumbup():
req = request.json
e, conv = ConversationService.get_by_id(req["conversation_id"])
if not e:
return get_data_error_result(message="Conversation not found!")
up_down = req.get("thumbup")
feedback = req.get("feedback", "")
conv = conv.to_dict()
for i, msg in enumerate(conv["message"]):
if req["message_id"] == msg.get("id", "") and msg.get("role", "") == "assistant":
if up_down:
msg["thumbup"] = True
if "feedback" in msg:
del msg["feedback"]
else:
msg["thumbup"] = False
if feedback:
msg["feedback"] = feedback
break
ConversationService.update_by_id(conv["id"], conv)
return get_json_result(data=conv)
@manager.route("/ask", methods=["POST"]) # noqa: F821
@login_required
@validate_request("question", "kb_ids")
def ask_about():
req = request.json
uid = current_user.id
def stream():
nonlocal req, uid
try:
for ans in ask(req["question"], req["kb_ids"], uid):
yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
except Exception as e:
yield "data:" + json.dumps({"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}}, ensure_ascii=False) + "\n\n"
yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
resp = Response(stream(), mimetype="text/event-stream")
resp.headers.add_header("Cache-control", "no-cache")
resp.headers.add_header("Connection", "keep-alive")
resp.headers.add_header("X-Accel-Buffering", "no")
resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
return resp
@manager.route("/mindmap", methods=["POST"]) # noqa: F821
@login_required
@validate_request("question", "kb_ids")
def mindmap():
req = request.json
kb_ids = req["kb_ids"]
e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
if not e:
return get_data_error_result(message="Knowledgebase not found!")
embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id)
chat_mdl = LLMBundle(current_user.id, LLMType.CHAT)
question = req["question"]
ranks = settings.retrievaler.retrieval(question, embd_mdl, kb.tenant_id, kb_ids, 1, 12, 0.3, 0.3, aggs=False, rank_feature=label_question(question, [kb]))
mindmap = MindMapExtractor(chat_mdl)
mind_map = trio.run(mindmap, [c["content_with_weight"] for c in ranks["chunks"]])
mind_map = mind_map.output
if "error" in mind_map:
return server_error_response(Exception(mind_map["error"]))
return get_json_result(data=mind_map)
@manager.route("/related_questions", methods=["POST"]) # noqa: F821
@login_required
@validate_request("question")
def related_questions():
req = request.json
question = req["question"]
chat_mdl = LLMBundle(current_user.id, LLMType.CHAT)
prompt = load_prompt("related_question")
ans = chat_mdl.chat(
prompt,
[
{
"role": "user",
"content": f"""
Keywords: {question}
Related search terms:
""",
}
],
{"temperature": 0.9},
)
return get_json_result(data=[re.sub(r"^[0-9]\. ", "", a) for a in ans.split("\n") if re.match(r"^[0-9]\. ", a)])