mirror of
https://github.com/infiniflow/ragflow.git
synced 2025-12-08 12:32:30 +08:00
daea357940
### What problem does this PR solve? Fix invalid COMPONENT_EXEC_TIMEOUT. #10273 ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
115 lines
4.7 KiB
Python
115 lines
4.7 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 logging
|
|
import os
|
|
import time
|
|
from abc import ABC
|
|
import pandas as pd
|
|
import pywencai
|
|
|
|
from agent.tools.base import ToolParamBase, ToolMeta, ToolBase
|
|
from api.utils.api_utils import timeout
|
|
|
|
|
|
class WenCaiParam(ToolParamBase):
|
|
"""
|
|
Define the WenCai component parameters.
|
|
"""
|
|
|
|
def __init__(self):
|
|
self.meta:ToolMeta = {
|
|
"name": "iwencai",
|
|
"description": """
|
|
iwencai search: search platform is committed to providing hundreds of millions of investors with the most timely, accurate and comprehensive information, covering news, announcements, research reports, blogs, forums, Weibo, characters, etc.
|
|
robo-advisor intelligent stock selection platform: through AI technology, is committed to providing investors with intelligent stock selection, quantitative investment, main force tracking, value investment, technical analysis and other types of stock selection technologies.
|
|
fund selection platform: through AI technology, is committed to providing excellent fund, value investment, quantitative analysis and other fund selection technologies for foundation citizens.
|
|
""",
|
|
"parameters": {
|
|
"query": {
|
|
"type": "string",
|
|
"description": "The question/conditions to select stocks.",
|
|
"default": "{sys.query}",
|
|
"required": True
|
|
}
|
|
}
|
|
}
|
|
super().__init__()
|
|
self.top_n = 10
|
|
self.query_type = "stock"
|
|
|
|
def check(self):
|
|
self.check_positive_integer(self.top_n, "Top N")
|
|
self.check_valid_value(self.query_type, "Query type",
|
|
['stock', 'zhishu', 'fund', 'hkstock', 'usstock', 'threeboard', 'conbond', 'insurance',
|
|
'futures', 'lccp',
|
|
'foreign_exchange'])
|
|
|
|
def get_input_form(self) -> dict[str, dict]:
|
|
return {
|
|
"query": {
|
|
"name": "Query",
|
|
"type": "line"
|
|
}
|
|
}
|
|
|
|
class WenCai(ToolBase, ABC):
|
|
component_name = "WenCai"
|
|
|
|
@timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 12)))
|
|
def _invoke(self, **kwargs):
|
|
if not kwargs.get("query"):
|
|
self.set_output("report", "")
|
|
return ""
|
|
|
|
last_e = ""
|
|
for _ in range(self._param.max_retries+1):
|
|
try:
|
|
wencai_res = []
|
|
res = pywencai.get(query=kwargs["query"], query_type=self._param.query_type, perpage=self._param.top_n)
|
|
if isinstance(res, pd.DataFrame):
|
|
wencai_res.append(res.to_markdown())
|
|
elif isinstance(res, dict):
|
|
for item in res.items():
|
|
if isinstance(item[1], list):
|
|
wencai_res.append(item[0] + "\n" + pd.DataFrame(item[1]).to_markdown())
|
|
elif isinstance(item[1], str):
|
|
wencai_res.append(item[0] + "\n" + item[1])
|
|
elif isinstance(item[1], dict):
|
|
if "meta" in item[1].keys():
|
|
continue
|
|
wencai_res.append(pd.DataFrame.from_dict(item[1], orient='index').to_markdown())
|
|
elif isinstance(item[1], pd.DataFrame):
|
|
if "image_url" in item[1].columns:
|
|
continue
|
|
wencai_res.append(item[1].to_markdown())
|
|
else:
|
|
wencai_res.append(item[0] + "\n" + str(item[1]))
|
|
self.set_output("report", "\n\n".join(wencai_res))
|
|
return self.output("report")
|
|
except Exception as e:
|
|
last_e = e
|
|
logging.exception(f"WenCai error: {e}")
|
|
time.sleep(self._param.delay_after_error)
|
|
|
|
if last_e:
|
|
self.set_output("_ERROR", str(last_e))
|
|
return f"WenCai error: {last_e}"
|
|
|
|
assert False, self.output()
|
|
|
|
def thoughts(self) -> str:
|
|
return "Pulling live financial data for `{}`.".format(self.get_input().get("query", "-_-!"))
|