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A Rust and Python Synthetic Integration for an agentic-LLM approach to build a research agent for local knowledge representation.

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molina

Welcome to the molina project, a synthetic research agent for local knowledge representation.

Notice here the absence of the terms Artificial and Intelligence, this is deliverate. This is not an artificially sweetened project, is not a claim to be the panacea, neither the $n-th$ attempt to solve general let alone narrow intelligence because this is definitely not a claim of something being intelligent.

What is this then ?, a tool, built with an agentic approach, for you to interact with by the act of formulating research-related questions, which will get you responses using only the academic papers you provide as the knowledge base.

The name is in honor to THE greatest Mexican researcher of all times, Mario Molina (1943-2020).

Problems

Challenges of the use of Large Language Models (LLMs), as an academic research assistant, are:

  • Hallucination.
  • Lack of domain-specific knowledge.
  • Outdated information.
  • Bias in Training Data.
  • Interpretability and Response Attribution.

Those seem very closely related to what a expert human research should also avoid.

Install

Clone the repo

git clone https://github.com/iteralabs/molina

Create a virtual environment and source into it.

python -m venv local_venv
source local_venv/bin/activate

Install packages dependencies with pip

pip install -r requirements.txt
python molina/main.py

Copyright disclaimer

The purpose of this tool is not to promote or condone the unauthorized downloading or use of copyrighted materials. All users of this should only use legally obtained documents, self-archive documents and materials in their projects.

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A Rust and Python Synthetic Integration for an agentic-LLM approach to build a research agent for local knowledge representation.

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