SmartWrks: Difference between revisions
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We expand the Agent's cognitive capabilities by contextualing information in the form of text using Retrieval-Augmented Generation ( | |||
We expand the Agent's cognitive capabilities by contextualing information in the form of text using Retrieval-Augmented Generation "RAG". ([https://github.blog/ai-and-ml/generative-ai/what-is-retrieval-augmented-generation-and-what-does-it-do-for-generative-ai/ Reference]) | |||
and documents and expand the [https://python.langchain.com/docs/integrations/llms/ollama LangChain] and [https://github.com/crewAIInc/crewAI crewAI] libraries | and documents and expand the [https://python.langchain.com/docs/integrations/llms/ollama LangChain] and [https://github.com/crewAIInc/crewAI crewAI] libraries |
Latest revision as of 12:25, 15 September 2024
Our Cognitive workfow:
The only irreproducible outside technology is the actual language model, and while we explore many, we've foucused our development on the Llama 3.1 Models Instruct by Meta (Git).
We run the base weights in the Ollama Platform (Git, Website), Using inexpensive GPUs to run multiple "Agents". To interact and deploy multiple agents we use "LM Studio" (Website)
We expand the Agent's cognitive capabilities by contextualing information in the form of text using Retrieval-Augmented Generation "RAG". (Reference)