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@dev-ananta dev-ananta released this 02 Oct 14:39
· 1 commit to main since this release
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Local Research AI – v3 Pre-Release

Local Research AI is a lightweight, locally-hosted artificial intelligence system designed to generate structured reports based on web research. It focuses on providing methodical, step-by-step approaches rather than direct recommendations — making it ideal for users who want a clear framework for deeper analysis.

⚠️ Early Development Notice:
This is the first pre-release (v3). The system is still in its foundational stage, and output is highly structured but not yet deeply informative. Expect methodical outlines and research processes rather than detailed conclusions.


🧠 Overview

Local Research AI automatically gathers and organizes web-based information into structured reports.
Instead of simply listing results, it focuses on how to think about a research question and how to approach solving it.

For example:

  • When asked "What are the best stocks to buy?"
    The system will not list stock names. Instead, it will provide a detailed methodology for researching and evaluating stocks — such as screening criteria, risk assessment steps, and evaluation frameworks.

⚙️ Features (Current Pre-Release)

  • 🧭 Structured Report Generation: Outputs are formatted into clear, methodical sections.
  • 🌐 Web-Guided Research: Utilizes online sources to form foundational research steps.
  • 🧱 Local Execution: Designed to run locally without relying on external APIs.
  • 🧪 Experimental Core: Built as a testbed for future, more sophisticated analysis capabilities.

🚧 Current Limitations

  • ❌ Reports are not yet deeply informative – they focus on structure over detail.
  • 📊 Results may lack actionable recommendations.
  • 🐣 System is still in its early-stage prototype phase and subject to significant change.

📈 Roadmap

  • Add support for deeper analytical insights in generated reports.
  • Improve contextual awareness and synthesis of web data.
  • Expand beyond methodologies into actionable recommendations.
  • Optimize local performance and modularize core components.

📦 Version

v3 – Pre-Release 1
This marks the first public iteration of Local Research AI and serves as a foundation for future development.


🧪 Disclaimer

This project is in active development and is not production-ready. Use it for experimentation, feedback, and local testing only.