LangChain built LangSmith LLM Gateway for agent cost control
It provides real-time budgets per org, workspace, user, or API key, enabling spend visibility for engineering leaders.
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Platform for building, testing, deploying, and observing AI agents
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In short: LangChain launched LangSmith Engine and Sandboxes, enhancing agent debugging and secure execution, and expanded Deep Agents with new capabilities.
It provides real-time budgets per org, workspace, user, or API key, enabling spend visibility for engineering leaders.
It involves access to sensitive data, exposure to untrusted content, and external communication, requiring sandboxing.
It automates trace analysis and recommends fixes for agent quality.
Interpreters provide a middle ground between serial tool calls and sandboxes, enabling agents to write and execute code inside the agent loop, reducing token usage and improving control.
Three patched LangGraph flaws could let attackers chain SQL injection and unsafe deserialization for RCE in self-hosted deployments.
AI agent safety benchmark BeSafe-Bench tested 13 production-grade agents and found none could complete 40% of tasks while respecting all safety constraints. With EU AI...
Detailed information about CVE-2026-7846: Time-of-check Time-of-use in chatchat-space Langchain-Chatchat affecting chatchat-space Langchain-Chatchat. Get real-t...
Axtria Inc., a global leader in AI-first data analytics solutions for the life sciences industry, today announced a strategic ...
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