LLM-Interface

This project is a work in progress and is not expected to use in a production programs.

This project provides a framework for utilizing LLMs in a structured way in Kotlin through the use of DSLs. You can either bring your own LLM by extending the LLM class or use a pre-existing such as OpenAIModel.

Features

This list is non-exhaustive and subject to change.

• Basic prompting (send message, receive message)
• Message History in DSL
• LLM Features
  • API
    • Functions (Allows for LLM to use defined functions, e.g., RAG or Web Search, or custom)
    • Database API
  • Sequence Processing (CoT)
    • Generating a list of steps to solve a given problem
      • Executing said list with different API tools
  • Image Processing
  • Embedding Support (OpenAI Model, Generalizable Functions)
    • Generalizable Functions
    • OpenAI Model
  • Extracting key information from large documents
• Observer (Tools to monitor LLM performance in automated sequence tasks)
  • Metric Based Observation
  • LLM Based Observation
• Document
  • Parsing
    • PDFs
      • OCR
      • Text Metadata Extraction
    • Generic Text
      • Plain Text .txt
      • Microsoft Word .docx or .doc
      • Rich Text Format .rtf
• Batch Processing
  • PDFs
  • LLM Requests

Related Research Papers

ReAct, method for improving accuracy complex tasks

Self-Consistency Improves ... - Improved CoT Reasoning

Future Demos & Research

• Demos
  • Document Tagging Demo
• Research
  • Testing a combined ReAct + Observational Sub-stepping Approach with different datasets:
    • ALFWorld
    • WebShop