This is very similar to how we think about context management in Deep Agents: compaction should redu...
Harrison Chase(@hwchase17) · 人工智能
This is very similar to how we think about context management in Deep Agents: compaction should reduce what is sent to the model, not erase the underlying work history. In Deep Agents, the logic is: - every agent gets a filesystem to work with (can be real or virtual) - when a tool result is too large, we write the full result to the filesystem (/large_tool_results) and replace the model-visible message with a preview - when the conversation gets long, we offload older messages to the filesystem (/conversation_history) history first, then generate a summary - the agent can also decide to compact proactively via a compact_conversation tool, which uses the same offload + summarize logic Summarization middleware with all this logic: github.com/langchain-ai/d… OpenAI @OpenAI This is GPT-6 Astra. Anything you can do on a computer, Astra can do for you. Fast. Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 11 🔄 0 ❤️ 44 👀 3859 📊 14 ⚡ Powered by xgo.ing