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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. | |
| # | |
| from abc import ABC | |
| import pandas as pd | |
| from agent.settings import DEBUG | |
| from agent.component.base import ComponentBase, ComponentParamBase | |
| from scholarly import scholarly | |
| class GoogleScholarParam(ComponentParamBase): | |
| """ | |
| Define the GoogleScholar component parameters. | |
| """ | |
| def __init__(self): | |
| super().__init__() | |
| self.top_n = 6 | |
| self.sort_by = 'relevance' | |
| self.year_low = None | |
| self.year_high = None | |
| self.patents = True | |
| def check(self): | |
| self.check_positive_integer(self.top_n, "Top N") | |
| self.check_valid_value(self.sort_by, "GoogleScholar Sort_by", ['date', 'relevance']) | |
| self.check_boolean(self.patents, "Whether or not to include patents, defaults to True") | |
| class GoogleScholar(ComponentBase, ABC): | |
| component_name = "GoogleScholar" | |
| def _run(self, history, **kwargs): | |
| ans = self.get_input() | |
| ans = " - ".join(ans["content"]) if "content" in ans else "" | |
| if not ans: | |
| return GoogleScholar.be_output("") | |
| scholar_client = scholarly.search_pubs(ans, patents=self._param.patents, year_low=self._param.year_low, | |
| year_high=self._param.year_high, sort_by=self._param.sort_by) | |
| scholar_res = [] | |
| for i in range(self._param.top_n): | |
| try: | |
| pub = next(scholar_client) | |
| scholar_res.append({"content": 'Title: ' + pub['bib']['title'] + '\n_Url: <a href="' + pub[ | |
| 'pub_url'] + '"></a> ' + "\n author: " + ",".join(pub['bib']['author']) + '\n Abstract: ' + pub[ | |
| 'bib'].get('abstract', 'no abstract')}) | |
| except StopIteration or Exception as e: | |
| print("**ERROR** " + str(e)) | |
| break | |
| if not scholar_res: | |
| return GoogleScholar.be_output("") | |
| df = pd.DataFrame(scholar_res) | |
| if DEBUG: print(df, ":::::::::::::::::::::::::::::::::") | |
| return df | |