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Update bibliography.py
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Saifeddine ALOUI
GitHub
parent
cb85e2643e
commit
163f90138d
@ -155,6 +155,254 @@ def arxiv_pdf_search_function(client: Optional[Any] = None):
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]
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}
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# Core function to search for PDFs on HAL and download them to a specified directory
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def hal_pdf_search(query: str, max_results: Optional[int] = 5, sort_by: Optional[str] = 'relevance', start_date: Optional[str] = None, end_date: Optional[str] = None, author: Optional[str] = None, client: Optional[Any] = None) -> (str, Dict[str, Any]):
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try:
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if client is None:
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download_to = Path("./pdf_search")
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else:
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download_to = client.discussion.discussion_folder / "pdf_search"
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# Construct the search URL with additional parameters
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url = f'https://api.archives-ouvertes.fr/search/?q={query}&rows={max_results}&sort={sort_by}'
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if start_date:
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url += f'&fq=submittedDate:[{start_date} TO {end_date if end_date else "*"}]'
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if author:
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url += f'&fq=authIdHal_s:{author}'
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ASCIIColors.multicolor(["URL:",url],[ASCIIColors.red, ASCIIColors.yellow])
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response = requests.get(url)
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response.raise_for_status()
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# Parse the response
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soup = BeautifulSoup(response.content, 'xml')
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entries = soup.find_all('doc')
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# Create the directory if it doesn't exist
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download_to.mkdir(parents=True, exist_ok=True)
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# Extract PDF URLs and additional information
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html_output = "<html><body>"
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report_content = ""
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pdf_info = {}
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for entry in entries:
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pdf_url = entry.find('str', {'name': 'fileMain_s'}).text
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pdf_name = pdf_url.split('/')[-1]
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pdf_path = download_to / pdf_name
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if client is None:
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local_url = f'/discussions/pdf_search/{pdf_name}'
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else:
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local_url = discussion_path_to_url(pdf_path)
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# Extract additional information
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title = entry.find('str', {'name': 'title_s'}).text
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authors = ', '.join(author.text for author in entry.find_all('str', {'name': 'authFullName_s'}))
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abstract = entry.find('str', {'name': 'abstract_s'}).text if entry.find('str', {'name': 'abstract_s'}) else 'N/A'
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published_date = entry.find('date', {'name': 'producedDate_tdate'}).text
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journal_ref = entry.find('str', {'name': 'journalTitle_s'}).text if entry.find('str', {'name': 'journalTitle_s'}) else 'N/A'
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# Write abstract and additional information to text file
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abstract_path = download_to / f"{pdf_name}_abstract.txt"
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with abstract_path.open('w', encoding='utf-8') as abstract_file:
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abstract_file.write(f"Title: {title}\n")
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abstract_file.write(f"Authors: {authors}\n")
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abstract_file.write(f"Abstract: {abstract}\n")
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abstract_file.write(f"Published Date: {published_date}\n")
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abstract_file.write(f"Journal/Conference: {journal_ref}\n")
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# Download PDF
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pdf_response = requests.get(pdf_url)
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with pdf_path.open('wb') as pdf_file:
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pdf_file.write(pdf_response.content)
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# Append to HTML output
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html_output += f"""
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<div>
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<h2>{title}</h2>
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<p><strong>Authors:</strong> {authors}</p>
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<p><strong>Abstract:</strong> {abstract}</p>
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<p><strong>Published Date:</strong> {published_date}</p>
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<p><strong>Journal/Conference:</strong> {journal_ref}</p>
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<p><a href="{pdf_url}" target="_blank">PDF Link</a></p>
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<p><a href="{local_url}" target="_blank">Local PDF</a></p>
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</div>
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"""
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# Append to report content
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report_content += f"""
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Title: {title}
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Authors: {authors}
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Abstract: {abstract}
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Published Date: {published_date}
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Journal/Conference: {journal_ref}
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PDF Link: {pdf_url}
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Local PDF: {local_url}
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------------------------
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"""
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# Append to pdf_info dict
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pdf_info[pdf_name] = {
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"title": title,
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"authors": authors,
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"abstract": abstract,
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"published_date": published_date,
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"journal_ref": journal_ref,
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"pdf_url": pdf_url,
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"local_url": local_url
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}
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# Save the report to a text file
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report_path = download_to / "pdf_search_report.txt"
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with report_path.open('w', encoding='utf-8') as report_file:
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report_file.write(report_content)
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html_output += "</body></html>"
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return html_output, pdf_info
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except Exception as e:
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return trace_exception(e), {}
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# Metadata function
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def hal_pdf_search_function(client: Optional[Any] = None):
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return {
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"function_name": "hal_pdf_search", # The function name in string
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"function": partial(hal_pdf_search, client=client), # The function to be called with partial to preset client
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"function_description": "Searches for PDFs on HAL based on a query, downloads them to a specified directory, and returns a HTML string containing article details and links, along with a dictionary containing detailed information about each PDF.", # Description of the function
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"function_parameters": [ # The set of parameters
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{"name": "query", "type": "str", "description": "The search query for HAL."},
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{"name": "max_results", "type": "int", "description": "The maximum number of results to return. (Optional)", "optional": True, "default": 5},
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{"name": "sort_by", "type": "str", "description": "The sorting criteria for the search results (e.g., relevance, lastUpdatedDate). (Optional)", "optional": True, "default": "relevance"},
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{"name": "start_date", "type": "str", "description": "The start date for the search results in the format YYYY-MM-DD. (Optional)", "optional": True},
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{"name": "end_date", "type": "str", "description": "The end date for the search results in the format YYYY-MM-DD. (Optional)", "optional": True},
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{"name": "author", "type": "str", "description": "The author name for the search results. (Optional)", "optional": True},
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]
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}
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# Core function to search for PDFs on ResearchGate and download them to a specified directory
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def researchgate_pdf_search(query: str, max_results: Optional[int] = 5, sort_by: Optional[str] = 'relevance', start_date: Optional[str] = None, end_date: Optional[str] = None, author: Optional[str] = None, client: Optional[Any] = None) -> (str, Dict[str, Any]):
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try:
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if client is None:
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download_to = Path("./pdf_search")
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else:
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download_to = client.discussion.discussion_folder / "pdf_search"
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# Construct the search URL with additional parameters
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url = f'https://www.researchgate.net/search/publication?q={query}&limit={max_results}&sort={sort_by}'
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if start_date:
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url += f'&startDate={start_date}'
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if end_date:
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url += f'&endDate={end_date}'
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if author:
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url += f'&author={author}'
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ASCIIColors.multicolor(["URL:",url],[ASCIIColors.red, ASCIIColors.yellow])
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response = requests.get(url)
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response.raise_for_status()
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# Parse the response
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soup = BeautifulSoup(response.content, 'html.parser')
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entries = soup.find_all('div', class_='nova-o-stack__item')
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# Create the directory if it doesn't exist
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download_to.mkdir(parents=True, exist_ok=True)
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# Extract PDF URLs and additional information
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html_output = "<html><body>"
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report_content = ""
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pdf_info = {}
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for entry in entries:
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pdf_link_tag = entry.find('a', class_='nova-e-link')
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if not pdf_link_tag:
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continue
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pdf_url = pdf_link_tag['href']
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pdf_name = pdf_url.split('/')[-1] + '.pdf'
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pdf_path = download_to / pdf_name
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if client is None:
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local_url = f'/discussions/pdf_search/{pdf_name}'
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else:
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local_url = discussion_path_to_url(pdf_path)
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# Extract additional information
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title = entry.find('h3', class_='nova-e-text').text.strip()
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authors = ', '.join(author.text.strip() for author in entry.find_all('span', class_='nova-e-text'))
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abstract = entry.find('div', class_='nova-e-text').text.strip() if entry.find('div', class_='nova-e-text') else 'N/A'
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published_date = entry.find('span', class_='nova-e-text--size-s').text.strip() if entry.find('span', class_='nova-e-text--size-s') else 'N/A'
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journal_ref = entry.find('span', class_='nova-e-text--size-s').text.strip() if entry.find('span', class_='nova-e-text--size-s') else 'N/A'
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# Write abstract and additional information to text file
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abstract_path = download_to / f"{pdf_name}_abstract.txt"
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with abstract_path.open('w', encoding='utf-8') as abstract_file:
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abstract_file.write(f"Title: {title}\n")
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abstract_file.write(f"Authors: {authors}\n")
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abstract_file.write(f"Abstract: {abstract}\n")
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abstract_file.write(f"Published Date: {published_date}\n")
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abstract_file.write(f"Journal/Conference: {journal_ref}\n")
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# Download PDF
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pdf_response = requests.get(pdf_url)
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with pdf_path.open('wb') as pdf_file:
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pdf_file.write(pdf_response.content)
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# Append to HTML output
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html_output += f"""
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<div>
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<h2>{title}</h2>
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<p><strong>Authors:</strong> {authors}</p>
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<p><strong>Abstract:</strong> {abstract}</p>
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<p><strong>Published Date:</strong> {published_date}</p>
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<p><strong>Journal/Conference:</strong> {journal_ref}</p>
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<p><a href="{pdf_url}" target="_blank">PDF Link</a></p>
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<p><a href="{local_url}" target="_blank">Local PDF</a></p>
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</div>
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"""
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# Append to report content
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report_content += f"""
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Title: {title}
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Authors: {authors}
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Abstract: {abstract}
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Published Date: {published_date}
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Journal/Conference: {journal_ref}
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PDF Link: {pdf_url}
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Local PDF: {local_url}
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------------------------
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"""
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# Append to pdf_info dict
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pdf_info[pdf_name] = {
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"title": title,
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"authors": authors,
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"abstract": abstract,
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"published_date": published_date,
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"journal_ref": journal_ref,
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"pdf_url": pdf_url,
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"local_url": local_url
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}
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# Save the report to a text file
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report_path = download_to / "pdf_search_report.txt"
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with report_path.open('w', encoding='utf-8') as report_file:
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report_file.write(report_content)
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html_output += "</body></html>"
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return html_output, pdf_info
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except Exception as e:
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return trace_exception(e), {}
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# Metadata function
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def researchgate_pdf_search_function(client: Optional[Any] = None):
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return {
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"function_name": "researchgate_pdf_search", # The function name in string
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"function": partial(researchgate_pdf_search, client=client), # The function to be called with partial to preset client
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"function_description": "Searches for PDFs on ResearchGate based on a query, downloads them to a specified directory, and returns a HTML string containing article details and links, along with a dictionary containing detailed information about each PDF.", # Description of the function
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"function_parameters": [ # The set of parameters
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{"name": "query", "type": "str", "description": "The search query for ResearchGate."},
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{"name": "max_results", "type": "int", "description": "The maximum number of results to return. (Optional)", "optional": True, "default": 5},
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{"name": "sort_by", "type": "str", "description": "The sorting criteria for the search results (e.g., relevance, lastUpdatedDate). (Optional)", "optional": True, "default": "relevance"},
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{"name": "start_date", "type": "str", "description": "The start date for the search results in the format YYYY-MM-DD. (Optional)", "optional": True},
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{"name": "end_date", "type": "str", "description": "The end date for the search results in the format YYYY-MM-DD. (Optional)", "optional": True},
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{"name": "author", "type": "str", "description": "The author name for the search results. (Optional)", "optional": True},
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]
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}
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# Define the core function
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def rate_relevance(search_prompt: str, text_example: str, llm) -> Tuple[str, Dict[str, float]]:
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