mirror of
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Format: dos2unix (#4467)
### What problem does this PR solve? Format the code ### Type of change - [x] Refactoring Signed-off-by: Jin Hai <haijin.chn@gmail.com>
This commit is contained in:
Jin Hai
@ -1,56 +1,56 @@
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#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from abc import ABC
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import pandas as pd
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import akshare as ak
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from agent.component.base import ComponentBase, ComponentParamBase
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class AkShareParam(ComponentParamBase):
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"""
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Define the AkShare component parameters.
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"""
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def __init__(self):
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super().__init__()
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self.top_n = 10
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def check(self):
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self.check_positive_integer(self.top_n, "Top N")
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class AkShare(ComponentBase, ABC):
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component_name = "AkShare"
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def _run(self, history, **kwargs):
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ans = self.get_input()
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ans = ",".join(ans["content"]) if "content" in ans else ""
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if not ans:
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return AkShare.be_output("")
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try:
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ak_res = []
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stock_news_em_df = ak.stock_news_em(symbol=ans)
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stock_news_em_df = stock_news_em_df.head(self._param.top_n)
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ak_res = [{"content": '<a href="' + i["新闻链接"] + '">' + i["新闻标题"] + '</a>\n 新闻内容: ' + i[
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"新闻内容"] + " \n发布时间:" + i["发布时间"] + " \n文章来源: " + i["文章来源"]} for index, i in stock_news_em_df.iterrows()]
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except Exception as e:
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return AkShare.be_output("**ERROR**: " + str(e))
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if not ak_res:
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return AkShare.be_output("")
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return pd.DataFrame(ak_res)
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#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from abc import ABC
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import pandas as pd
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import akshare as ak
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from agent.component.base import ComponentBase, ComponentParamBase
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class AkShareParam(ComponentParamBase):
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"""
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Define the AkShare component parameters.
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"""
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def __init__(self):
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super().__init__()
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self.top_n = 10
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def check(self):
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self.check_positive_integer(self.top_n, "Top N")
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class AkShare(ComponentBase, ABC):
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component_name = "AkShare"
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def _run(self, history, **kwargs):
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ans = self.get_input()
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ans = ",".join(ans["content"]) if "content" in ans else ""
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if not ans:
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return AkShare.be_output("")
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try:
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ak_res = []
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stock_news_em_df = ak.stock_news_em(symbol=ans)
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stock_news_em_df = stock_news_em_df.head(self._param.top_n)
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ak_res = [{"content": '<a href="' + i["新闻链接"] + '">' + i["新闻标题"] + '</a>\n 新闻内容: ' + i[
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"新闻内容"] + " \n发布时间:" + i["发布时间"] + " \n文章来源: " + i["文章来源"]} for index, i in stock_news_em_df.iterrows()]
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except Exception as e:
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return AkShare.be_output("**ERROR**: " + str(e))
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if not ak_res:
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return AkShare.be_output("")
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return pd.DataFrame(ak_res)
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@ -1,36 +1,36 @@
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#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from abc import ABC
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from agent.component.base import ComponentBase, ComponentParamBase
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class ConcentratorParam(ComponentParamBase):
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"""
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Define the Concentrator component parameters.
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"""
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def __init__(self):
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super().__init__()
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def check(self):
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return True
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class Concentrator(ComponentBase, ABC):
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component_name = "Concentrator"
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def _run(self, history, **kwargs):
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#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from abc import ABC
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from agent.component.base import ComponentBase, ComponentParamBase
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class ConcentratorParam(ComponentParamBase):
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"""
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Define the Concentrator component parameters.
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"""
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def __init__(self):
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super().__init__()
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def check(self):
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return True
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class Concentrator(ComponentBase, ABC):
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component_name = "Concentrator"
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def _run(self, history, **kwargs):
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return Concentrator.be_output("")
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@ -1,130 +1,130 @@
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#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import json
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from abc import ABC
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import pandas as pd
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import requests
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from agent.component.base import ComponentBase, ComponentParamBase
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class Jin10Param(ComponentParamBase):
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"""
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Define the Jin10 component parameters.
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"""
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def __init__(self):
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super().__init__()
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self.type = "flash"
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self.secret_key = "xxx"
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self.flash_type = '1'
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self.calendar_type = 'cj'
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self.calendar_datatype = 'data'
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self.symbols_type = 'GOODS'
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self.symbols_datatype = 'symbols'
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self.contain = ""
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self.filter = ""
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def check(self):
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self.check_valid_value(self.type, "Type", ['flash', 'calendar', 'symbols', 'news'])
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self.check_valid_value(self.flash_type, "Flash Type", ['1', '2', '3', '4', '5'])
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self.check_valid_value(self.calendar_type, "Calendar Type", ['cj', 'qh', 'hk', 'us'])
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self.check_valid_value(self.calendar_datatype, "Calendar DataType", ['data', 'event', 'holiday'])
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self.check_valid_value(self.symbols_type, "Symbols Type", ['GOODS', 'FOREX', 'FUTURE', 'CRYPTO'])
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self.check_valid_value(self.symbols_datatype, 'Symbols DataType', ['symbols', 'quotes'])
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class Jin10(ComponentBase, ABC):
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component_name = "Jin10"
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def _run(self, history, **kwargs):
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ans = self.get_input()
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ans = " - ".join(ans["content"]) if "content" in ans else ""
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if not ans:
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return Jin10.be_output("")
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jin10_res = []
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headers = {'secret-key': self._param.secret_key}
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try:
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if self._param.type == "flash":
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params = {
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'category': self._param.flash_type,
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'contain': self._param.contain,
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'filter': self._param.filter
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}
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response = requests.get(
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url='https://open-data-api.jin10.com/data-api/flash?category=' + self._param.flash_type,
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headers=headers, data=json.dumps(params))
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response = response.json()
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for i in response['data']:
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jin10_res.append({"content": i['data']['content']})
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if self._param.type == "calendar":
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params = {
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'category': self._param.calendar_type
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}
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response = requests.get(
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url='https://open-data-api.jin10.com/data-api/calendar/' + self._param.calendar_datatype + '?category=' + self._param.calendar_type,
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headers=headers, data=json.dumps(params))
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response = response.json()
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jin10_res.append({"content": pd.DataFrame(response['data']).to_markdown()})
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if self._param.type == "symbols":
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params = {
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'type': self._param.symbols_type
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}
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if self._param.symbols_datatype == "quotes":
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params['codes'] = 'BTCUSD'
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response = requests.get(
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url='https://open-data-api.jin10.com/data-api/' + self._param.symbols_datatype + '?type=' + self._param.symbols_type,
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headers=headers, data=json.dumps(params))
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response = response.json()
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if self._param.symbols_datatype == "symbols":
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for i in response['data']:
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i['Commodity Code'] = i['c']
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i['Stock Exchange'] = i['e']
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i['Commodity Name'] = i['n']
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i['Commodity Type'] = i['t']
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del i['c'], i['e'], i['n'], i['t']
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if self._param.symbols_datatype == "quotes":
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for i in response['data']:
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i['Selling Price'] = i['a']
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i['Buying Price'] = i['b']
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i['Commodity Code'] = i['c']
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i['Stock Exchange'] = i['e']
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i['Highest Price'] = i['h']
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i['Yesterday’s Closing Price'] = i['hc']
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i['Lowest Price'] = i['l']
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i['Opening Price'] = i['o']
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i['Latest Price'] = i['p']
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i['Market Quote Time'] = i['t']
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del i['a'], i['b'], i['c'], i['e'], i['h'], i['hc'], i['l'], i['o'], i['p'], i['t']
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jin10_res.append({"content": pd.DataFrame(response['data']).to_markdown()})
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if self._param.type == "news":
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params = {
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'contain': self._param.contain,
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'filter': self._param.filter
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}
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response = requests.get(
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url='https://open-data-api.jin10.com/data-api/news',
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headers=headers, data=json.dumps(params))
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response = response.json()
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jin10_res.append({"content": pd.DataFrame(response['data']).to_markdown()})
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except Exception as e:
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return Jin10.be_output("**ERROR**: " + str(e))
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if not jin10_res:
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return Jin10.be_output("")
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return pd.DataFrame(jin10_res)
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#
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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
|
||||
from abc import ABC
|
||||
import pandas as pd
|
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import requests
|
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from agent.component.base import ComponentBase, ComponentParamBase
|
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|
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class Jin10Param(ComponentParamBase):
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"""
|
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Define the Jin10 component parameters.
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"""
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def __init__(self):
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super().__init__()
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self.type = "flash"
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self.secret_key = "xxx"
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self.flash_type = '1'
|
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self.calendar_type = 'cj'
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self.calendar_datatype = 'data'
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self.symbols_type = 'GOODS'
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self.symbols_datatype = 'symbols'
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self.contain = ""
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self.filter = ""
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def check(self):
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self.check_valid_value(self.type, "Type", ['flash', 'calendar', 'symbols', 'news'])
|
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self.check_valid_value(self.flash_type, "Flash Type", ['1', '2', '3', '4', '5'])
|
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self.check_valid_value(self.calendar_type, "Calendar Type", ['cj', 'qh', 'hk', 'us'])
|
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self.check_valid_value(self.calendar_datatype, "Calendar DataType", ['data', 'event', 'holiday'])
|
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self.check_valid_value(self.symbols_type, "Symbols Type", ['GOODS', 'FOREX', 'FUTURE', 'CRYPTO'])
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self.check_valid_value(self.symbols_datatype, 'Symbols DataType', ['symbols', 'quotes'])
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|
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|
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class Jin10(ComponentBase, ABC):
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component_name = "Jin10"
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def _run(self, history, **kwargs):
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ans = self.get_input()
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ans = " - ".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
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return Jin10.be_output("")
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||||
|
||||
jin10_res = []
|
||||
headers = {'secret-key': self._param.secret_key}
|
||||
try:
|
||||
if self._param.type == "flash":
|
||||
params = {
|
||||
'category': self._param.flash_type,
|
||||
'contain': self._param.contain,
|
||||
'filter': self._param.filter
|
||||
}
|
||||
response = requests.get(
|
||||
url='https://open-data-api.jin10.com/data-api/flash?category=' + self._param.flash_type,
|
||||
headers=headers, data=json.dumps(params))
|
||||
response = response.json()
|
||||
for i in response['data']:
|
||||
jin10_res.append({"content": i['data']['content']})
|
||||
if self._param.type == "calendar":
|
||||
params = {
|
||||
'category': self._param.calendar_type
|
||||
}
|
||||
response = requests.get(
|
||||
url='https://open-data-api.jin10.com/data-api/calendar/' + self._param.calendar_datatype + '?category=' + self._param.calendar_type,
|
||||
headers=headers, data=json.dumps(params))
|
||||
|
||||
response = response.json()
|
||||
jin10_res.append({"content": pd.DataFrame(response['data']).to_markdown()})
|
||||
if self._param.type == "symbols":
|
||||
params = {
|
||||
'type': self._param.symbols_type
|
||||
}
|
||||
if self._param.symbols_datatype == "quotes":
|
||||
params['codes'] = 'BTCUSD'
|
||||
response = requests.get(
|
||||
url='https://open-data-api.jin10.com/data-api/' + self._param.symbols_datatype + '?type=' + self._param.symbols_type,
|
||||
headers=headers, data=json.dumps(params))
|
||||
response = response.json()
|
||||
if self._param.symbols_datatype == "symbols":
|
||||
for i in response['data']:
|
||||
i['Commodity Code'] = i['c']
|
||||
i['Stock Exchange'] = i['e']
|
||||
i['Commodity Name'] = i['n']
|
||||
i['Commodity Type'] = i['t']
|
||||
del i['c'], i['e'], i['n'], i['t']
|
||||
if self._param.symbols_datatype == "quotes":
|
||||
for i in response['data']:
|
||||
i['Selling Price'] = i['a']
|
||||
i['Buying Price'] = i['b']
|
||||
i['Commodity Code'] = i['c']
|
||||
i['Stock Exchange'] = i['e']
|
||||
i['Highest Price'] = i['h']
|
||||
i['Yesterday’s Closing Price'] = i['hc']
|
||||
i['Lowest Price'] = i['l']
|
||||
i['Opening Price'] = i['o']
|
||||
i['Latest Price'] = i['p']
|
||||
i['Market Quote Time'] = i['t']
|
||||
del i['a'], i['b'], i['c'], i['e'], i['h'], i['hc'], i['l'], i['o'], i['p'], i['t']
|
||||
jin10_res.append({"content": pd.DataFrame(response['data']).to_markdown()})
|
||||
if self._param.type == "news":
|
||||
params = {
|
||||
'contain': self._param.contain,
|
||||
'filter': self._param.filter
|
||||
}
|
||||
response = requests.get(
|
||||
url='https://open-data-api.jin10.com/data-api/news',
|
||||
headers=headers, data=json.dumps(params))
|
||||
response = response.json()
|
||||
jin10_res.append({"content": pd.DataFrame(response['data']).to_markdown()})
|
||||
except Exception as e:
|
||||
return Jin10.be_output("**ERROR**: " + str(e))
|
||||
|
||||
if not jin10_res:
|
||||
return Jin10.be_output("")
|
||||
|
||||
return pd.DataFrame(jin10_res)
|
||||
|
||||
@ -1,72 +1,72 @@
|
||||
#
|
||||
# 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
|
||||
from abc import ABC
|
||||
import pandas as pd
|
||||
import time
|
||||
import requests
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
|
||||
|
||||
class TuShareParam(ComponentParamBase):
|
||||
"""
|
||||
Define the TuShare component parameters.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.token = "xxx"
|
||||
self.src = "eastmoney"
|
||||
self.start_date = "2024-01-01 09:00:00"
|
||||
self.end_date = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
|
||||
self.keyword = ""
|
||||
|
||||
def check(self):
|
||||
self.check_valid_value(self.src, "Quick News Source",
|
||||
["sina", "wallstreetcn", "10jqka", "eastmoney", "yuncaijing", "fenghuang", "jinrongjie"])
|
||||
|
||||
|
||||
class TuShare(ComponentBase, ABC):
|
||||
component_name = "TuShare"
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
ans = self.get_input()
|
||||
ans = ",".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
||||
return TuShare.be_output("")
|
||||
|
||||
try:
|
||||
tus_res = []
|
||||
params = {
|
||||
"api_name": "news",
|
||||
"token": self._param.token,
|
||||
"params": {"src": self._param.src, "start_date": self._param.start_date,
|
||||
"end_date": self._param.end_date}
|
||||
}
|
||||
response = requests.post(url="http://api.tushare.pro", data=json.dumps(params).encode('utf-8'))
|
||||
response = response.json()
|
||||
if response['code'] != 0:
|
||||
return TuShare.be_output(response['msg'])
|
||||
df = pd.DataFrame(response['data']['items'])
|
||||
df.columns = response['data']['fields']
|
||||
tus_res.append({"content": (df[df['content'].str.contains(self._param.keyword, case=False)]).to_markdown()})
|
||||
except Exception as e:
|
||||
return TuShare.be_output("**ERROR**: " + str(e))
|
||||
|
||||
if not tus_res:
|
||||
return TuShare.be_output("")
|
||||
|
||||
return pd.DataFrame(tus_res)
|
||||
#
|
||||
# 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
|
||||
from abc import ABC
|
||||
import pandas as pd
|
||||
import time
|
||||
import requests
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
|
||||
|
||||
class TuShareParam(ComponentParamBase):
|
||||
"""
|
||||
Define the TuShare component parameters.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.token = "xxx"
|
||||
self.src = "eastmoney"
|
||||
self.start_date = "2024-01-01 09:00:00"
|
||||
self.end_date = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
|
||||
self.keyword = ""
|
||||
|
||||
def check(self):
|
||||
self.check_valid_value(self.src, "Quick News Source",
|
||||
["sina", "wallstreetcn", "10jqka", "eastmoney", "yuncaijing", "fenghuang", "jinrongjie"])
|
||||
|
||||
|
||||
class TuShare(ComponentBase, ABC):
|
||||
component_name = "TuShare"
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
ans = self.get_input()
|
||||
ans = ",".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
||||
return TuShare.be_output("")
|
||||
|
||||
try:
|
||||
tus_res = []
|
||||
params = {
|
||||
"api_name": "news",
|
||||
"token": self._param.token,
|
||||
"params": {"src": self._param.src, "start_date": self._param.start_date,
|
||||
"end_date": self._param.end_date}
|
||||
}
|
||||
response = requests.post(url="http://api.tushare.pro", data=json.dumps(params).encode('utf-8'))
|
||||
response = response.json()
|
||||
if response['code'] != 0:
|
||||
return TuShare.be_output(response['msg'])
|
||||
df = pd.DataFrame(response['data']['items'])
|
||||
df.columns = response['data']['fields']
|
||||
tus_res.append({"content": (df[df['content'].str.contains(self._param.keyword, case=False)]).to_markdown()})
|
||||
except Exception as e:
|
||||
return TuShare.be_output("**ERROR**: " + str(e))
|
||||
|
||||
if not tus_res:
|
||||
return TuShare.be_output("")
|
||||
|
||||
return pd.DataFrame(tus_res)
|
||||
|
||||
@ -1,80 +1,80 @@
|
||||
#
|
||||
# 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.
|
||||
#
|
||||
from abc import ABC
|
||||
import pandas as pd
|
||||
import pywencai
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
|
||||
|
||||
class WenCaiParam(ComponentParamBase):
|
||||
"""
|
||||
Define the WenCai component parameters.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
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'])
|
||||
|
||||
|
||||
class WenCai(ComponentBase, ABC):
|
||||
component_name = "WenCai"
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
ans = self.get_input()
|
||||
ans = ",".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
||||
return WenCai.be_output("")
|
||||
|
||||
try:
|
||||
wencai_res = []
|
||||
res = pywencai.get(query=ans, query_type=self._param.query_type, perpage=self._param.top_n)
|
||||
if isinstance(res, pd.DataFrame):
|
||||
wencai_res.append({"content": res.to_markdown()})
|
||||
if isinstance(res, dict):
|
||||
for item in res.items():
|
||||
if isinstance(item[1], list):
|
||||
wencai_res.append({"content": item[0] + "\n" + pd.DataFrame(item[1]).to_markdown()})
|
||||
continue
|
||||
if isinstance(item[1], str):
|
||||
wencai_res.append({"content": item[0] + "\n" + item[1]})
|
||||
continue
|
||||
if isinstance(item[1], dict):
|
||||
if "meta" in item[1].keys():
|
||||
continue
|
||||
wencai_res.append({"content": pd.DataFrame.from_dict(item[1], orient='index').to_markdown()})
|
||||
continue
|
||||
if isinstance(item[1], pd.DataFrame):
|
||||
if "image_url" in item[1].columns:
|
||||
continue
|
||||
wencai_res.append({"content": item[1].to_markdown()})
|
||||
continue
|
||||
|
||||
wencai_res.append({"content": item[0] + "\n" + str(item[1])})
|
||||
except Exception as e:
|
||||
return WenCai.be_output("**ERROR**: " + str(e))
|
||||
|
||||
if not wencai_res:
|
||||
return WenCai.be_output("")
|
||||
|
||||
return pd.DataFrame(wencai_res)
|
||||
#
|
||||
# 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.
|
||||
#
|
||||
from abc import ABC
|
||||
import pandas as pd
|
||||
import pywencai
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
|
||||
|
||||
class WenCaiParam(ComponentParamBase):
|
||||
"""
|
||||
Define the WenCai component parameters.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
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'])
|
||||
|
||||
|
||||
class WenCai(ComponentBase, ABC):
|
||||
component_name = "WenCai"
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
ans = self.get_input()
|
||||
ans = ",".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
||||
return WenCai.be_output("")
|
||||
|
||||
try:
|
||||
wencai_res = []
|
||||
res = pywencai.get(query=ans, query_type=self._param.query_type, perpage=self._param.top_n)
|
||||
if isinstance(res, pd.DataFrame):
|
||||
wencai_res.append({"content": res.to_markdown()})
|
||||
if isinstance(res, dict):
|
||||
for item in res.items():
|
||||
if isinstance(item[1], list):
|
||||
wencai_res.append({"content": item[0] + "\n" + pd.DataFrame(item[1]).to_markdown()})
|
||||
continue
|
||||
if isinstance(item[1], str):
|
||||
wencai_res.append({"content": item[0] + "\n" + item[1]})
|
||||
continue
|
||||
if isinstance(item[1], dict):
|
||||
if "meta" in item[1].keys():
|
||||
continue
|
||||
wencai_res.append({"content": pd.DataFrame.from_dict(item[1], orient='index').to_markdown()})
|
||||
continue
|
||||
if isinstance(item[1], pd.DataFrame):
|
||||
if "image_url" in item[1].columns:
|
||||
continue
|
||||
wencai_res.append({"content": item[1].to_markdown()})
|
||||
continue
|
||||
|
||||
wencai_res.append({"content": item[0] + "\n" + str(item[1])})
|
||||
except Exception as e:
|
||||
return WenCai.be_output("**ERROR**: " + str(e))
|
||||
|
||||
if not wencai_res:
|
||||
return WenCai.be_output("")
|
||||
|
||||
return pd.DataFrame(wencai_res)
|
||||
|
||||
@ -1,84 +1,84 @@
|
||||
#
|
||||
# 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
|
||||
from abc import ABC
|
||||
import pandas as pd
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
import yfinance as yf
|
||||
|
||||
|
||||
class YahooFinanceParam(ComponentParamBase):
|
||||
"""
|
||||
Define the YahooFinance component parameters.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.info = True
|
||||
self.history = False
|
||||
self.count = False
|
||||
self.financials = False
|
||||
self.income_stmt = False
|
||||
self.balance_sheet = False
|
||||
self.cash_flow_statement = False
|
||||
self.news = True
|
||||
|
||||
def check(self):
|
||||
self.check_boolean(self.info, "get all stock info")
|
||||
self.check_boolean(self.history, "get historical market data")
|
||||
self.check_boolean(self.count, "show share count")
|
||||
self.check_boolean(self.financials, "show financials")
|
||||
self.check_boolean(self.income_stmt, "income statement")
|
||||
self.check_boolean(self.balance_sheet, "balance sheet")
|
||||
self.check_boolean(self.cash_flow_statement, "cash flow statement")
|
||||
self.check_boolean(self.news, "show news")
|
||||
|
||||
|
||||
class YahooFinance(ComponentBase, ABC):
|
||||
component_name = "YahooFinance"
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
ans = self.get_input()
|
||||
ans = "".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
||||
return YahooFinance.be_output("")
|
||||
|
||||
yohoo_res = []
|
||||
try:
|
||||
msft = yf.Ticker(ans)
|
||||
if self._param.info:
|
||||
yohoo_res.append({"content": "info:\n" + pd.Series(msft.info).to_markdown() + "\n"})
|
||||
if self._param.history:
|
||||
yohoo_res.append({"content": "history:\n" + msft.history().to_markdown() + "\n"})
|
||||
if self._param.financials:
|
||||
yohoo_res.append({"content": "calendar:\n" + pd.DataFrame(msft.calendar).to_markdown() + "\n"})
|
||||
if self._param.balance_sheet:
|
||||
yohoo_res.append({"content": "balance sheet:\n" + msft.balance_sheet.to_markdown() + "\n"})
|
||||
yohoo_res.append(
|
||||
{"content": "quarterly balance sheet:\n" + msft.quarterly_balance_sheet.to_markdown() + "\n"})
|
||||
if self._param.cash_flow_statement:
|
||||
yohoo_res.append({"content": "cash flow statement:\n" + msft.cashflow.to_markdown() + "\n"})
|
||||
yohoo_res.append(
|
||||
{"content": "quarterly cash flow statement:\n" + msft.quarterly_cashflow.to_markdown() + "\n"})
|
||||
if self._param.news:
|
||||
yohoo_res.append({"content": "news:\n" + pd.DataFrame(msft.news).to_markdown() + "\n"})
|
||||
except Exception:
|
||||
logging.exception("YahooFinance got exception")
|
||||
|
||||
if not yohoo_res:
|
||||
return YahooFinance.be_output("")
|
||||
|
||||
return pd.DataFrame(yohoo_res)
|
||||
#
|
||||
# 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
|
||||
from abc import ABC
|
||||
import pandas as pd
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
import yfinance as yf
|
||||
|
||||
|
||||
class YahooFinanceParam(ComponentParamBase):
|
||||
"""
|
||||
Define the YahooFinance component parameters.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.info = True
|
||||
self.history = False
|
||||
self.count = False
|
||||
self.financials = False
|
||||
self.income_stmt = False
|
||||
self.balance_sheet = False
|
||||
self.cash_flow_statement = False
|
||||
self.news = True
|
||||
|
||||
def check(self):
|
||||
self.check_boolean(self.info, "get all stock info")
|
||||
self.check_boolean(self.history, "get historical market data")
|
||||
self.check_boolean(self.count, "show share count")
|
||||
self.check_boolean(self.financials, "show financials")
|
||||
self.check_boolean(self.income_stmt, "income statement")
|
||||
self.check_boolean(self.balance_sheet, "balance sheet")
|
||||
self.check_boolean(self.cash_flow_statement, "cash flow statement")
|
||||
self.check_boolean(self.news, "show news")
|
||||
|
||||
|
||||
class YahooFinance(ComponentBase, ABC):
|
||||
component_name = "YahooFinance"
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
ans = self.get_input()
|
||||
ans = "".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
||||
return YahooFinance.be_output("")
|
||||
|
||||
yohoo_res = []
|
||||
try:
|
||||
msft = yf.Ticker(ans)
|
||||
if self._param.info:
|
||||
yohoo_res.append({"content": "info:\n" + pd.Series(msft.info).to_markdown() + "\n"})
|
||||
if self._param.history:
|
||||
yohoo_res.append({"content": "history:\n" + msft.history().to_markdown() + "\n"})
|
||||
if self._param.financials:
|
||||
yohoo_res.append({"content": "calendar:\n" + pd.DataFrame(msft.calendar).to_markdown() + "\n"})
|
||||
if self._param.balance_sheet:
|
||||
yohoo_res.append({"content": "balance sheet:\n" + msft.balance_sheet.to_markdown() + "\n"})
|
||||
yohoo_res.append(
|
||||
{"content": "quarterly balance sheet:\n" + msft.quarterly_balance_sheet.to_markdown() + "\n"})
|
||||
if self._param.cash_flow_statement:
|
||||
yohoo_res.append({"content": "cash flow statement:\n" + msft.cashflow.to_markdown() + "\n"})
|
||||
yohoo_res.append(
|
||||
{"content": "quarterly cash flow statement:\n" + msft.quarterly_cashflow.to_markdown() + "\n"})
|
||||
if self._param.news:
|
||||
yohoo_res.append({"content": "news:\n" + pd.DataFrame(msft.news).to_markdown() + "\n"})
|
||||
except Exception:
|
||||
logging.exception("YahooFinance got exception")
|
||||
|
||||
if not yohoo_res:
|
||||
return YahooFinance.be_output("")
|
||||
|
||||
return pd.DataFrame(yohoo_res)
|
||||
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -1,113 +1,113 @@
|
||||
{
|
||||
"components": {
|
||||
"begin": {
|
||||
"obj":{
|
||||
"component_name": "Begin",
|
||||
"params": {
|
||||
"prologue": "Hi there!"
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": []
|
||||
},
|
||||
"answer:0": {
|
||||
"obj": {
|
||||
"component_name": "Answer",
|
||||
"params": {}
|
||||
},
|
||||
"downstream": ["categorize:0"],
|
||||
"upstream": ["begin"]
|
||||
},
|
||||
"categorize:0": {
|
||||
"obj": {
|
||||
"component_name": "Categorize",
|
||||
"params": {
|
||||
"llm_id": "deepseek-chat",
|
||||
"category_description": {
|
||||
"product_related": {
|
||||
"description": "The question is about the product usage, appearance and how it works.",
|
||||
"examples": "Why it always beaming?\nHow to install it onto the wall?\nIt leaks, what to do?",
|
||||
"to": "concentrator:0"
|
||||
},
|
||||
"others": {
|
||||
"description": "The question is not about the product usage, appearance and how it works.",
|
||||
"examples": "How are you doing?\nWhat is your name?\nAre you a robot?\nWhat's the weather?\nWill it rain?",
|
||||
"to": "concentrator:1"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"downstream": ["concentrator:0","concentrator:1"],
|
||||
"upstream": ["answer:0"]
|
||||
},
|
||||
"concentrator:0": {
|
||||
"obj": {
|
||||
"component_name": "Concentrator",
|
||||
"params": {}
|
||||
},
|
||||
"downstream": ["message:0"],
|
||||
"upstream": ["categorize:0"]
|
||||
},
|
||||
"concentrator:1": {
|
||||
"obj": {
|
||||
"component_name": "Concentrator",
|
||||
"params": {}
|
||||
},
|
||||
"downstream": ["message:1_0","message:1_1","message:1_2"],
|
||||
"upstream": ["categorize:0"]
|
||||
},
|
||||
"message:0": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 0_0!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:0"]
|
||||
},
|
||||
"message:1_0": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 1_0!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:1"]
|
||||
},
|
||||
"message:1_1": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 1_1!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:1"]
|
||||
},
|
||||
"message:1_2": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 1_2!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:1"]
|
||||
}
|
||||
},
|
||||
"history": [],
|
||||
"messages": [],
|
||||
"path": [],
|
||||
"reference": [],
|
||||
"answer": []
|
||||
{
|
||||
"components": {
|
||||
"begin": {
|
||||
"obj":{
|
||||
"component_name": "Begin",
|
||||
"params": {
|
||||
"prologue": "Hi there!"
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": []
|
||||
},
|
||||
"answer:0": {
|
||||
"obj": {
|
||||
"component_name": "Answer",
|
||||
"params": {}
|
||||
},
|
||||
"downstream": ["categorize:0"],
|
||||
"upstream": ["begin"]
|
||||
},
|
||||
"categorize:0": {
|
||||
"obj": {
|
||||
"component_name": "Categorize",
|
||||
"params": {
|
||||
"llm_id": "deepseek-chat",
|
||||
"category_description": {
|
||||
"product_related": {
|
||||
"description": "The question is about the product usage, appearance and how it works.",
|
||||
"examples": "Why it always beaming?\nHow to install it onto the wall?\nIt leaks, what to do?",
|
||||
"to": "concentrator:0"
|
||||
},
|
||||
"others": {
|
||||
"description": "The question is not about the product usage, appearance and how it works.",
|
||||
"examples": "How are you doing?\nWhat is your name?\nAre you a robot?\nWhat's the weather?\nWill it rain?",
|
||||
"to": "concentrator:1"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"downstream": ["concentrator:0","concentrator:1"],
|
||||
"upstream": ["answer:0"]
|
||||
},
|
||||
"concentrator:0": {
|
||||
"obj": {
|
||||
"component_name": "Concentrator",
|
||||
"params": {}
|
||||
},
|
||||
"downstream": ["message:0"],
|
||||
"upstream": ["categorize:0"]
|
||||
},
|
||||
"concentrator:1": {
|
||||
"obj": {
|
||||
"component_name": "Concentrator",
|
||||
"params": {}
|
||||
},
|
||||
"downstream": ["message:1_0","message:1_1","message:1_2"],
|
||||
"upstream": ["categorize:0"]
|
||||
},
|
||||
"message:0": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 0_0!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:0"]
|
||||
},
|
||||
"message:1_0": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 1_0!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:1"]
|
||||
},
|
||||
"message:1_1": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 1_1!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:1"]
|
||||
},
|
||||
"message:1_2": {
|
||||
"obj": {
|
||||
"component_name": "Message",
|
||||
"params": {
|
||||
"messages": [
|
||||
"Message 1_2!!!!!!!"
|
||||
]
|
||||
}
|
||||
},
|
||||
"downstream": ["answer:0"],
|
||||
"upstream": ["concentrator:1"]
|
||||
}
|
||||
},
|
||||
"history": [],
|
||||
"messages": [],
|
||||
"path": [],
|
||||
"reference": [],
|
||||
"answer": []
|
||||
}
|
||||
Reference in New Issue
Block a user