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Small, yet powerful conversational agent framework

Project description

Small and Mighty Conversational Agent Framework

This is an experimental project to develop next generation of conversational agents that can connect the world of unconstrained generation of Large Language Models (LLM) to the world of structured data sources. Our goal is to build a modular and configurable framework to seamlessly integrate language agents with data sources to build conversational experiences for next generation of digital systems.

THIS PROJECT IS IN ACTIVE DEVELOPMENT. PROCEED WITH CAUTION!


Test Python

The Big Idea about Small Things

To achieve our goals, we are pursuing two fundamental ideas:

  1. Sequence to structure: Convert sequence to sequence models to sequence to structure extraction ones. This is about extracting the structure of information required to properly fulfill a user request from her natural language utterances.
  2. Structure Informed Generation: Generate responses that combine both unstructured and structured information.

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