Langrepl CLI (Made by the LangChain Community) A sophisticated terminal tool for building LLM agents with deep agents, featuring persistent conversations and LangGraph Studio integration for visual debugging. Key Features:
– Deep Agent Architecture
– Visual debugging
AGENTS
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Langrepl CLI: Terminal Tool for LLM Agents with Visual Debugging
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Efficiency and Intelligence in AI Agent Development
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By the end of testing, it was beating every open-source agent in the field and holding its own against proprietary systems built with 10x the resources. Turns out intelligence isn’t about size. It’s about how well you manage what you already know.
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Optimizing AI Agent Context Management and Token Efficiency
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Most agents collapse when their context fills up.
This one doesn’t. Even after 100 turns, its entire memory grows from ~3.5K to just ~7K tokens. That’s like running a 500-page research project and still remembering only what matters. And instead of stacking logs endlessly like -

Autonomous AI Agent Logic for Note Curation and Information Compression
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Instead of drowning in its own notes, the agent actively curates them. Every turn it asks: what’s worth keeping, and what can I compress? It runs a loop that looks almost human think → fold → explain → act and builds its own hierarchy of ideas.
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Alibaba’s AgentFold introduces a human-style memory system for web agents
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Alibaba just dropped a monster paper in agent research. It’s called AgentFold, and it basically gives web agents a human-style memory system that manages itself. Here’s why it’s wild Current agents either: ∙ keep everything (context bloat, chaos)
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Recursive Language Models for Near-Infinite Context Agents
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One of our best talks yet. Thanks @a1zhang for the amazing presentation + Q&A on Recursive Language Models! If you're interested in how we can get agents to handle near-infinite contexts, this one is a must. Watch the recording here!
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Agents vs Workflows: Breaking Down AI Architecture Patterns
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You could technically make an agent into a workflow by having the workflow have LLM steps which dynamically route… but it starts to get all confusing that way, and the user experience is also more tricky. I've started to like the way @AnthropicAI breaks it down: * Skills
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@testingcatalog — 2025-10-31
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Opera launched Opera Deep Research Agent (ODRA) for in-depth research and analysis. Deep Research is now available on the Opera Neon browser. https://t.co/X6nJqcFebE pic.twitter.com/SzjEETo0Hx
— 🚨 AI News | TestingCatalog (@testingcatalog) 31 octobre 2025Opera launched Opera Deep Research Agent (ODRA) for in-depth research and analysis. Deep Research is now available on the Opera Neon browser.
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ChatGPT Atlas Agent Mode Now Available
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try agent mode in ChatGPT Atlas: https://t.co/wrqeiPztTV
— Greg Brockman (@gdb) 31 octobre 2025try agent mode in ChatGPT Atlas:
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Moonshot launches KIMI CLI with MCP support
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Moonshot released KIMI CLI, a command line coding agent with MCP support!