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Slurper ingests data and creates vectorized data for LLMs

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Slurper

Slurper is a set of components that work to orchestrate the collection and parsing of unstructured web data and other media to be ETL'd for use in embeddings/vectors for LLM processing.

Requirements

Right now we rely heavily on LangChain but that may change as the modularized nature of the architecture allows us to choose optimized elements that produce more accurate outcomes.

Components

Slurper-react

This is the React front-end for interfacing with the Rails API back-end. (React/Javascript/Typescript/Tailwind/MUI)

Slurper-rails

This is the Rails back-end for reporting agent progress. (Rails API)

Slurper-python

This is the Python back-end for agents processing. (Python3/FastAPI)

Structure

/agents/ - Agents connect different required components to achieve a specific goal. They are labeled with their specific action. /extractors/ - Extractors extract information from different mediums /transformers/ - Transformers take the information from extractors and normalize them in a way that can be combined later. Right now this means taking the extracted data and vectorizing the aggregate for uniform lookups.

Component Diagram

Slurper Diagram

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Slurper ingests data and creates vectorized data for LLMs

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