MASTERMIND

MASTERMIND

Here are some key aspects of MASTERMIND:

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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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day0

Day 0, Moment 0: The Clock Starts Now

Deploying now: mindX releases Moment 0 of a Gödel machine — the proof kernel, formal utility, and G1–G8 predicates live over an up memory substrate (PostgreSQL + pgvectorscale, RAGE active). 6/8 predicates pass; honest verdict NOT_YET. Count from zero.

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RAGE

RAGE

RAGE Retrieval Augmented Generative Engine

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