Implementing Local RAG with Groq and Llama 3: Phidata Framework Application and Performance Showcase

Implementing Local RAG with Groq and Llama 3: Phidata Framework Application and Performance Showcase

Phidata is a framework designed for building AI agents with memory, knowledge, and tools. https://www.phidata.com/ https://github.com/phidatahq/phidata https://docs.phidata.com/introduction Three Aspects of Phidata Enhancing LLM Functionality: Memory: Phidata stores chat history in a database, allowing large language models to support longer conversations, thereby better understanding and tracking the context of dialogues. Knowledge: By storing business-relevant information in … Read more

Llama 3.3: Meta AI Releases New Text-Based Language Model

Llama 3.3: Meta AI Releases New Text-Based Language Model

πŸš€ Quick Read Model Parameters: Llama 3.3 has 70B parameters, comparable to the 405B parameters of Llama 3.1. Multilingual Support: Supports input and output in 8 languages including English, German, French, etc. Application Scenarios: Suitable for chatbots, customer service automation, language translation, and various other scenarios. Main Content What is Llama 3.3 WeChat Official Account: … Read more