Professor Codephreak

The asyncio library in Python provides a framework for writing single-threaded concurrent code using coroutines, which are a type of asynchronous function. It allows you to manage asynchronous operations easily and is suitable for I/O-bound and high-level structured network code. Key Concepts Basic Usage Here’s a simple example of using asyncio to run a couple of coroutines: Creating Tasks You can use asyncio.create_task() to schedule a coroutine to run concurrently: Anticipate Futures Futures represent a […]

understandin the ezAGI framework requires a fundamental comprehension of reasoning with SocraticReasoning.py disclaimer: ezAGI fundamental Augmented Generative Intelligence may or not be be fun. use at own risk. breaking changes version 1 To fully audit the behavior of how the premise field is populated in the SocraticReasoning class, we will: SocraticReasoning.py Audit Initialization and setup of SocraticReasoning class Adding Premises Programmatically Adding Premises Interactively Now, let’s look at the interactive part of the interact method: […]

https://github.com/langchain-ai/langgraph/blob/main/examples/rag/langgraph_rag_agent_llama3_local.ipynb Building reliable local agents using LangGraph and LLaMA3-8b within the RAGE framework involves several key components and methodologies: Model Integration and Local Deployment: LLaMA3-8b: Utilize this robust language model for generating responses based on user queries. It serves as the core generative engine in the RAGE system. LangGraph: Enhance the responses of LLaMA3 by integrating structured knowledge graphs through LangGraph, boosting the model’s capability to deliver contextually relevant and accurate information. Advanced RAGE Techniques: […]