Building Memory-Aware AI Agents with AdalFlow | Persistent Memory, JSON Store & Multi-Session
Автор: BazAI
Загружено: 2025-11-06
Просмотров: 42
Описание:
Welcome back to Bazai — today we’re diving deep into how to build persistent-memory AI agents using AdalFlow.
In this hands-on walkthrough, we’ll explore how AdalFlow gives your agents true cognitive continuity — remembering user preferences, summarizing long conversations, and managing context across multiple sessions.
🚀 What you’ll learn:
What AdalFlow is and how it enables persistent, file-backed memory
The difference between short-term and long-term agent memory
How JSONMemoryStore safely preserves history and facts
History Compaction — automatic summarization that prevents prompt bloat
Global memory sharing for multi-agent collaboration
Tool-based design: remember, recall, jot, counter
Real Colab demo using OpenAI GPT models
Debugging and fixing common errors in AdalFlow agents
💡 Key Takeaway:
Persistent memory turns LLM agents from reactive responders into adaptive collaborators that learn, recall, and evolve with you.
📂 Colab Notebook & Code:
🔗 https://colab.research.google.com/dri...
https://chat.z.ai/space/x0a8q9k90d70-ppt
📣 Subscribe to Bazai for more deep-tech walkthroughs on Agentic AI, LangGraph, CrewAI, and AdalFlow-powered workflows.
#Bazai #AdalFlow #AIagents #PersistentMemory #LLM
https://colab.research.google.com/dri...
https://chat.z.ai/space/x0a8q9k90d70-ppt
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