Generate Article from PDF

Easily transform PDF documents into polished articles.

Description

The task transforms the content of PDF documents into professionally-crafted articles.

Applications

Content Extraction: Rapidly extract valuable information and text from PDF files.
Content Creation: Easily produce articles, summaries, and reports from PDF sources.
Streamlined Research: Simplify your research process by converting research papers and documents into easily digestible articles.
Content Recycling: Repurpose old PDFs into fresh, engaging articles for your audience.
Time Savings: Save hours of manual rewriting and editing by automating content generation.

How to use the task

Simply paste the link to your PDF document in the provided field.
The tool will generate a refined article for you.

Privacy

Please enter information about whether you may send sensitive user input information to a service as ChatGPT.

[1.0.0]:

First version

Version	AI Model	Created	Link
1.0.0		01.10.2023

API

The REST API allows you to call the tool with the same costs as when running the tool. Please generate an Personal access token before using the REST API.

Parameters

pdf_document_url (Pdf document url): Paste your pdf document url here.

Call the REST API by cURL
curl -v -H "Authorization: Bearer PERSONAL_ACCESS_TOKEN" https://api.anysolve.ai/rest/v1/u-anysolve-mr-generate-article-from-pdf/1.0.0?pdf_document_url=https%3A%2F%2Farxiv.org%2Fpdf%2F1805.01788.pdf

Install the package with pip
python3 -m pip install anysolve

Run in python3

import os
from anysolve import AnySolve

anysolve_token = os.environ.get('ANYSOLVE_PERSONAL_ACCESS_TOKEN') # Resolve your personal access token here
client = AnySolve(anysolve_token)
res = client.run('u-anysolve-mr-generate-article-from-pdf','1.0.0', {'pdf_document_url': 'https://arxiv.org/pdf/1805.01788.pdf'})

print(res)

Coming soon: Within AnySolve ChatComplete prompts you can use the following command to execute the task:
/run('u-anysolve-mr-generate-article-from-pdf','1.0.0', pdf_document_url='https://arxiv.org/pdf/1805.01788.pdf')

Task infos

Author: anysolve-mr

Status: Published

Version: 1.0.0

Runs: 13 times

Favorites: 3

Average costs: 95 Credits (0.096 EUR)

Created: 01.10.2023

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Input