spock-literature 0.0.7

A description of your package

spock

LLM Literature

• Free software: MIT License
• Documentation: Spock Documentation

Project Presentation:

An LLM-powered Slack bot for monitoring LLM literature and AC members' publications (e.g., Heisenberg).

Features:

• Notifies whenever an AC member publishes a paper.
• Provides the topics of AC members' papers.
• Retrieves information from scientific papers.
• Allows interaction from Slack chat.
• Monitors and analyzes various types of publications and outputs by Acceleration Consortium Members, including:
  • Peer-reviewed publications in relevant disciplines such as AI and materials science.
  • High-impact publications by citation count and journal impact factor.
  • Non-peer-reviewed scholarly publications, including arXiv submissions.
  • Other scholarly outputs like conference proceedings.
  • Estimations of new compositions of matter, AI algorithms, and datasets shared by members.

Implemented Features:

• Notification when an AC member publishes a paper.
• Identifies topics of given papers using a set of keywords.
• Retrieval-Augmented Generation (RAG) from given papers to extract data (currently in progress).
• Only working on last publications of the AC members

LLM Literature Scraping

• Define and focus on publications in relevant disciplines by Acceleration Consortium Members.
• Relevant Disciplines Include:
  • AI
  • Accelerated materials discovery
  • Self-Driving Labs (SDLs)
  • Autonomous labs
  • High-throughput experimentation
  • High-throughput Density Functional Theory (DFT), etc.
• Scrape the number of publications in peer-reviewed (non-arXiv) literature.
• Calculate the annual average over the last 5 years.

High Impact Publications

By Citation Count

• Identify publications in relevant disciplines that are in the top 10% by citation count across all journals.
• Calculate the annual average over the last 5 years.

By Journal Impact Factor

• Identify publications in relevant disciplines that are in the top 10% by journal impact factor.
• Calculate the annual average over the last 5 years.

Non-Peer-Reviewed Scholarly Publications

• Count non-peer-reviewed scholarly publications in relevant disciplines, including those on arXiv.
• Aim to filter out papers that are on both arXiv and published in journals.
• Calculate the annual average over the last 5 years.

Other Scholarly Creations or Outputs

• Include scholarly outputs that do not fit typical publication categories, such as conference proceedings.
• Identify any other outputs found by LLM that don't fit into the above categories.
• Calculate the annual average over the last 5 years.

New Compositions of Matter

• Estimate the number of new materials identified in patent applications or published literature by Acceleration Consortium Members.
• Provide a best estimate or a range for these numbers.
• Calculate either the annual average over the last 5 years or a total over the previous 5 years.

New AI or Screening Algorithms, Methods, Workflows, Models

• Estimate the number of new AI/screening algorithms, methods, workflows, or models identified in patent applications or published literature by Acceleration Consortium Members.
• Provide a best estimate or a range for these numbers.
• Calculate either the annual average over the last 5 years or a total over the previous 5 years.

AI and Material Related Datasets Shared

• Estimate the number of datasets related to AI and materials released to the public by Acceleration Consortium Members.
• Provide a best estimate or a range for these numbers.
• Calculate either the annual average over the last 5 years or a total over the previous 5 years.

Code Overview

Author object:

• Takes as input the name of an AC author
• Has the ability to fetch their last publication
  • Uses the scholarly API to get the data (filled)
• Updates a json file with the data it had about the publication

The Publication object:

• Takes as input a publication filled (output of a scholarly)
• Gets data such as the year of publication, abstract, link etc...
• Uses a LLM on the abstract to get the topics of the publication (Updating it)
• Uses webscrapping of the scholarly home page of the author to get the link to the PDF of the publication (if found - Working on it)

RAG use - still working on it:

• Embedding used: fast emnbedding (updating it to Ollama's)
• Getting pertinent information from the PDF

Bot object:

• Runs a Slack bot which is able to send messages and respond to slack slash(/) commands