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easyAGI: Augmenting the Intelligence of Large Language Models

easy augmented general intelligence In the rapidly evolving field of artificial intelligence, the concept of Autonomous General Intelligence (AGI) represents a significant milestone. However, the journey towards AGI is complex and requires innovative approaches to streamline and simplify the development process. Enter easyAGI, a transformative framework designed to augment the intelligence of existing Large Language Models (LLMs). This article explores the core aspects of easyAGI and its impact on the landscape of AGI and LLMs. […]

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Hackathon Challenge:

OpenAI Assistants API Llama-Index/MongoDB In this hackathon, you will build and iterate on an LLM-based application using AI observability to validate the performance of your app. You can choose between two sets of tools for building your app: Tool set 1: The OpenAI Assistants API Tool set 2: Llama-Index, MongoDB and GPT-4. With either choice, you will use TruLens to validate and improve the performance of your application. By bringing together TruEra, OpenAI, Llama-Index, and […]

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Reliable fully local RAG agents with LLaMA3

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: […]

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