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dyxohjl666
commited on
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f7eb017
1
Parent(s):
3893bea
Support url input
Browse files- app.py +10 -29
- controlled_summarization.py +37 -9
app.py
CHANGED
@@ -6,27 +6,6 @@ from controlled_summarization import *
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from dataset_extraction import *
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import requests
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def download_pdf(url, dest_folder):
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"""
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Download a PDF from a given URL and save it to a specified destination folder.
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Parameters:
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url (str): URL of the PDF
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dest_folder (str): Destination folder to save the downloaded PDF
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"""
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if not os.path.exists(dest_folder):
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os.makedirs(dest_folder)
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response = requests.get(url, stream=True)
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filename = os.path.join(dest_folder, url.split("/")[-1])
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with open(filename, 'wb') as file:
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for chunk in response.iter_content(chunk_size=1024):
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if chunk:
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file.write(chunk)
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print(f"Downloaded {url} to {filename}")
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return filename
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# Example Usage
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#url = "https://arxiv.org/pdf/2305.14996.pdf"
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gr.Markdown(ctrlsum_file_md)
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with gr.Row():
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with gr.Column():
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ctrlsum_url = gr.
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ctrlsum_file = gr.File(label="Input File"
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ctrlsum_str = gr.TextArea(label="Input String", max_lines=5)
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with gr.Column():
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gr.Markdown("* Length 0 will exert no control over length.")
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ctrlsum_file_examples = gr.Examples(examples=[["examples/H01-1042_body.txt", 50, "automatic evaluation technique"],["examples/H01-1042.pdf", 0, "automatic evaluation technique"]],
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inputs=[ctrlsum_file, ctrlsum_file_length, ctrlsum_file_keywords])
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ctrlsum_file = download_pdf(ctrlsum_url.value, './cache/')
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ctrlsum_file_btn.click(
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fn=ctrlsum_for_file,
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inputs=[ctrlsum_file, ctrlsum_file_length, ctrlsum_file_keywords, ctrlsum_str],
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outputs=[ctrlsum_file_output, ctrlsum_str]
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)
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def clear():
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return None,0,None
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ctrlsum_file.change(clear, inputs=None,outputs=[ctrlsum_str,ctrlsum_file_length,ctrlsum_file_keywords])
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# Reference String Parsing
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with gr.TabItem("Reference String Parsing"):
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with gr.Box():
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from dataset_extraction import *
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import requests
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# Example Usage
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#url = "https://arxiv.org/pdf/2305.14996.pdf"
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gr.Markdown(ctrlsum_file_md)
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with gr.Row():
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with gr.Column():
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ctrlsum_url = gr.Textbox(label="PDF URL", max_lines=1)
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ctrlsum_file = gr.File(label="Input File")
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ctrlsum_str = gr.TextArea(label="Input String", max_lines=5)
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with gr.Column():
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gr.Markdown("* Length 0 will exert no control over length.")
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ctrlsum_file_examples = gr.Examples(examples=[["examples/H01-1042_body.txt", 50, "automatic evaluation technique"],["examples/H01-1042.pdf", 0, "automatic evaluation technique"]],
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inputs=[ctrlsum_file, ctrlsum_file_length, ctrlsum_file_keywords])
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ctrlsum_file_btn.click(
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fn=ctrlsum_for_file,
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inputs=[ctrlsum_file, ctrlsum_file_length, ctrlsum_file_keywords, ctrlsum_str, ctrlsum_url],
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outputs=[ctrlsum_file_output, ctrlsum_str, ctrlsum_file]
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)
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def clear():
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return None,0,None, None
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ctrlsum_file.upload(clear, inputs=None,outputs=[ctrlsum_str,ctrlsum_file_length,ctrlsum_file_keywords, ctrlsum_url])
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ctrlsum_url.input(clear, inputs=None, outputs=[ctrlsum_str, ctrlsum_file_length, ctrlsum_file_keywords, ctrlsum_file])
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ctrlsum_str.input(clear, inputs=None,
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outputs=[ctrlsum_url, ctrlsum_file_length, ctrlsum_file_keywords, ctrlsum_file])
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# Reference String Parsing
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with gr.TabItem("Reference String Parsing"):
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with gr.Box():
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controlled_summarization.py
CHANGED
@@ -1,12 +1,35 @@
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from typing import List, Tuple
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import torch
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from SciAssist import Summarization
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device = "gpu" if torch.cuda.is_available() else "cpu"
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ctrlsum_pipeline = Summarization(os_name="nt",checkpoint="google/flan-t5-base",device=device)
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def ctrlsum_for_str(input,length=None, keywords=None) -> List[Tuple[str, str]]:
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if keywords is not None:
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@@ -24,15 +47,20 @@ def ctrlsum_for_str(input,length=None, keywords=None) -> List[Tuple[str, str]]:
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return "".join(output)
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def ctrlsum_for_file(input, length=None, keywords=
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if input == None:
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if text=="":
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return None
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else:
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return ctrlsum_for_str(text,length,keywords),text
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else:
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filename
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if
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keywords = keywords.strip().split(",")
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if keywords[0] == "":
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keywords = None
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@@ -47,12 +75,12 @@ def ctrlsum_for_file(input, length=None, keywords=None, text="") -> List[Tuple[s
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results = ctrlsum_pipeline.predict(filename,
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save_results=False, length=length, keywords=keywords)
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else:
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return
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output = []
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for res in results["summary"]:
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output.append(f"{res}\n\n")
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return "".join(output), results["raw_text"]
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from typing import List, Tuple
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import torch
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from SciAssist import Summarization
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import os
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import requests
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device = "gpu" if torch.cuda.is_available() else "cpu"
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ctrlsum_pipeline = Summarization(os_name="nt",checkpoint="google/flan-t5-base",device=device)
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def download_pdf(url, dest_folder):
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"""
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Download a PDF from a given URL and save it to a specified destination folder.
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Parameters:
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url (str): URL of the PDF
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dest_folder (str): Destination folder to save the downloaded PDF
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"""
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if not os.path.exists(dest_folder):
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os.makedirs(dest_folder)
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response = requests.get(url, stream=True)
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filename = os.path.join(dest_folder, url.split("/")[-1])
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with open(filename, 'wb') as file:
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for chunk in response.iter_content(chunk_size=1024):
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if chunk:
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file.write(chunk)
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print(f"Downloaded {url} to {filename}")
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return filename
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def ctrlsum_for_str(input,length=None, keywords=None) -> List[Tuple[str, str]]:
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if keywords is not None:
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return "".join(output)
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def ctrlsum_for_file(input=None, length=None, keywords="", text="", url="") -> List[Tuple[str, str, str]]:
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if input == None and url == "":
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if text=="":
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return None,"Input cannot be left blank.",None
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else:
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return ctrlsum_for_str(text,length,keywords),text, None
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else:
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filename=""
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if url != "":
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if len(url) > 4:
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filename = download_pdf(url, './cache/')
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else:
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filename = input.name
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if keywords != "":
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keywords = keywords.strip().split(",")
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if keywords[0] == "":
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keywords = None
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results = ctrlsum_pipeline.predict(filename,
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save_results=False, length=length, keywords=keywords)
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else:
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return "File Format Error !", None, filename
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output = []
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for res in results["summary"]:
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output.append(f"{res}\n\n")
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return "".join(output), results["raw_text"], filename
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