semvec/pypi-packages huggingface dataset:
Kaede-API 0.1.0
A Python package to interact with Kaede API
Requires Python: >=3.6

Kaede API Client Is A Communication Standard Between The Kaede API And The User (EG: You) . This API Has Functions Such As OCR , Search Youtube & Etc (More Features Are Coming) . Using This API You Can Quickly Develop You Bot With Functions Like Music Searching & Playing Or Extracting  Text From A Image. Currently It Is Meant For Discord Bots But Once The Features Are Fully Completed I Will Make It For All Applications. If You Need Support Then I Will Be In The API Support Server In Discord At https://discord.gg/MmrB32XJY9
VectorAnalysis 0.0.3
how to culculate gradient, divergence and curl
Requires Python: >=3.8

# VectorAnalysis
This is a tutorial on how to use a PyPI application.
You can culculate gradient, divergence and curl by using this application.

# How to install VectorAnalysis
$ pip install VectorAnalysis

# How to run VectorAnalysis
You need also "sympy" to run this application.<br>
$ pip install sympy

example:<br>
In [1]: from sympy.vector import CoordSys3D<br>
In [2]: C = CoordSys3D('C')<br>
In [3]: g = C.x * C.y * C.z<br>
In [4]: gradient(g)<br>
Out[4]: C.y*C.z*C.i + C.x*C.z*C.j + C.x*C.y*C.k<br>
article-assistant 0.1.3
Draft and review articles through the use of Large Language Models (LLMs)

# Article-Assistant

#### Article Assistant is a comprehensive Python package designed to assist with authoring and reviewing scientific articles. Utilizing advanced AI models from OpenAI, the package offers tools for generating complete articles based on provided topics and descriptions and reviewing existing articles for clarity, accuracy, and overall quality.


### Features
* Authoring: Automatically generate well-structured review articles with sections including Title, Abstract, Introduction, Body, Conclusion, and Sources.
* Reviewing: Use a multi-agent AI system to review articles. The system includes:
  * SME Reviewer: Reviews the article for technical accuracy and provides detailed feedback. 
  * SME Search: Searches the internet for similar articles and provides recommendations based on findings. 
  * Lead Reviewer: Summarizes the findings from both SME agents into a single cohesive summary.


### Quick Start:

Install the Application:

    pip install article-assistant

Author a New Article:

    # Set API Key:
    api_key = os.getenv('OPENAI_API_KEY')
    author = Author(api_key)

    # Describe the article:
    topic = "quaternary ammonium compounds"
    description = "An article of quaternary ammonium compounds and their efficacy"

    # Generate the Article:
    outline = author.generate_outline(topic, description)
    paper_content = author.draft_paper(outline)
    author.save_to_word(paper_content, "Drafted_Paper.docx")

Review Existing Article:

    # Select files to review:
    review = Review()
    pdf_path = "path/to/file.pdf"

    # Run Review:
    results = review.review_article(pdf_path)

    # Print the results
    print("\nSummary by Lead Reviewer:")
    print(results["summary"])

    print("\nSME_Reviewer Outputs:")
    for output in results["sme_reviewer"]:
        print(output)

    print("\nSME_Search Outputs:")
    for output in results["sme_search"]:
        print(output)