dynamic-learning-model 1.2.6

A Dynamic Learning Model for processing NLP queries using hybrid AI and reasoning.

Dynamic Learning Model

ABOUT:

The Dynamic Learning Model (DLM) is a hybrid AI system designed to learn, adapt, and intelligently respond to user queries. It combines natural language understanding with structured reasoning, continually improving as it is trained.

Key capabilities include:

• FAQ Handling: Learns and responds to frequently asked questions based on the knowledge it has been trained on.

• Chain-of-Thought (CoT) Reasoning: Performs clear, step-by-step logic to solve non-ambiguous arithmetic and unit conversion problems.

• Custom Knowledge Integration: DLM is fully extensible. You can initialize it with an empty SQL database and train it with your domain-specific knowledge.

Whether you're building a student support bot, a domain-specific assistant, or a computation system, DLM offers a flexible foundation to power your intelligent applications

REQUIRED PARAMETERS:

• The constructor requires passing in two parameters:
  • Bot Mode: 't' = training, 'c' = commercial, 'e' = experimental
  • Empty SQL Database for training the bot with queries
• The ask() method also requires passing in two parameters:
  • Query: "What is the definition of FAFSA" (as an example)
  • Display Thought: "True" to allow the bot's Chain of Thought to be displayed, or else "False"

GET STARTED:

• To install, run:

pip install dynamic-learning-model

• Python 3.12 or higher is required to use this bot in your program

(Experimental 'e' mode [computation queries])

from dlm import DLM

computation_bot = DLM("e", "college_knowledge.db")

computation_bot.ask("Compute the following: 5 * 5 * 5 + 5 / 5", True)

(Training 't' mode [training queries])

• You can find the training password in the __trainingPwd variable defined within the DLM.py file

from dlm import DLM

training_bot = DLM("t", "college_knowledge.db")

training_bot.ask("What is FAFSA in college?", True)

(Commercial 'c' mode [deployment/production use after training])

from dlm import DLM

commercial_bot = DLM("c", "college_knowledge.db")

commercial_bot.ask("What is the difference between FAFSA and CADAA in California?", False)

HIGH-LEVEL PIPELINE VISUALS: