LLMs, RAG, & the missing storage layer for AI
LLM agents rely on their Long-Term Memory (LTM) to store and retrieve crucial memories. Conversations, thoughts, plans, actions, observations, skills, and behaviors are all stored within a vector database. The LTM enables pre-processing and post-processing of memories, ensuring optimal retrieval. By considering factors such as context, recency, imp... See more
Introducing our work on general-purpose LLM Agents | GoodAI
Building a Knowledge base for custom LLMs using Langchain, Chroma, and GPT4All
cismography.medium.com
📦 Service Deployment - Ray Serve (https://lnkd.in/eAV-Y6RN)
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Tra... See more
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Tra... See more