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Automatically annotate papers using LLMs

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Type: GitHub Repository Original link: https://github.com/neuml/annotateai Publication date: 2025-09-04


Summary
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WHAT - AnnotateAI is a Python library that uses Large Language Models (LLMs) to automatically annotate scientific and medical articles, highlighting key sections and providing context to readers.

WHY - It is relevant for the AI business because it automates the annotation of complex documents, improving efficiency in reading and understanding scientific and medical articles, a rapidly growing sector.

WHO - The main players are NeuML, the company developing AnnotateAI, and the community of developers using LLMs and document annotation tools.

WHERE - It positions itself in the market of automatic document annotation tools, integrating with the AI ecosystem through the use of LLMs supported by txtai.

WHEN - It is a relatively new but already functional project, with significant growth potential in the scientific and medical sectors.

BUSINESS IMPACT:

  • Opportunities: Integration with our existing stack to offer automatic annotation services to clients in the medical and scientific sectors.
  • Risks: Competition with other automatic annotation tools and the need to keep the LLMs used up-to-date.
  • Integration: Possible integration with our AI stack to enhance document analysis service offerings.

TECHNICAL SUMMARY:

  • Core technology stack: Python, txtai, LLMs supported by txtai, PyPI.
  • Scalability and architectural limits: Supports PDF and works well with medical and scientific articles, but may require optimizations for very long or complex documents.
  • Key technical differentiators: Use of LLMs for contextual annotation, support for various LLMs through txtai, ease of installation and configuration.

Use Cases
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  • Private AI Stack: Integration into proprietary pipelines
  • Client Solutions: Implementation for client projects
  • Development Acceleration: Reduction of time-to-market for projects
  • Strategic Intelligence: Input for technological roadmap
  • Competitive Analysis: Monitoring AI ecosystem

Resources
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Original Links #


Article recommended and selected by the Human Technology eXcellence team, elaborated through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-04 19:27 Original source: https://github.com/neuml/annotateai

Related Articles #

Articoli Interessanti - This article is part of a series.
Part : Everything as Code: How We Manage Our Company In One Monorepo At Kasava, we've embraced the concept of "everything as code" to streamline our operations and ensure consistency across our projects. This approach allows us to manage our entire company within a single monorepo, providing a unified source of truth for all our configurations, infrastructure, and applications. **Why a Monorepo?** A monorepo offers several advantages: 1. **Unified Configuration**: All our settings, from development environments to production, are stored in one place. This makes it easier to maintain consistency and reduces the risk of configuration drift. 2. **Simplified Dependency Management**: With all our code in one repository, managing dependencies becomes more straightforward. We can easily track which versions of libraries and tools are being used across different projects. 3. **Enhanced Collaboration**: A single repository fosters better collaboration among team members. Everyone has access to the same codebase, making it easier to share knowledge and work together on projects. 4. **Consistent Build and Deployment Processes**: By standardizing our build and deployment processes, we ensure that all our applications follow the same best practices. This leads to more reliable and predictable deployments. **Our Monorepo Structure** Our monorepo is organized into several key directories: - **/config**: Contains all configuration files for various environments, including development, staging, and production. - **/infrastructure**: Houses the infrastructure as code (IaC) scripts for provisioning and managing our cloud resources. - **/apps**: Includes all our applications, both internal tools and customer-facing products. - **/lib**: Stores reusable libraries and modules that can be shared across different projects. - **/scripts**: Contains utility scripts for automating various tasks, such as data migrations and backups. **Tools and Technologies** To manage our monorepo effectively, we use a combination of tools and technologies: - **Version Control**: Git is our primary version control system, and we use GitHub for hosting our repositories. - **Continuous Integration/Continuous Deployment (CI/CD)**: We employ Jenkins for automating our build, test, and deployment processes. - **Infrastructure as Code (IaC)**: Terraform is our tool of choice for managing cloud infrastructure. - **Configuration Management**: Ansible is used for configuring and managing our servers and applications. - **Monitoring and Logging**: We use Prometheus and Grafana for monitoring,
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