GPT-6 Astra 执行循环：LangGraph+E2B 搭建方案
用 LangGraph 管状态、E2B 跑沙箱、Langfuse 追踪、DeepEval 验证，把 Astra 的推理与执行验证分离，并附可直接粘贴的提示词。
GPT-6 Astra needs a f*cking execution loop Most AI agents can write code The real problem starts when something breaks and the model has to figure out what failed, recover and finish the job without losing context The trick: separate reasoning from execution and verification here's the setup: → GPT-6 Astra handles planning and complex decisions → LangGraph manages agent state and execution loops https://github.com/langchain-ai/langgraph → E2B runs generated code inside isolated sandboxes https://github.com/e2b-dev/E2B → Langfuse traces tool calls, errors and retries https://github.com/langfuse/langfuse → DeepEval evaluates outputs against defined tests https://github.com/confident-ai/deepeval The important part isn't running more agents It's knowing when to stop, retry or ask for human intervention One failed test should trigger a targeted repair, not another complete rewrite paste this into your coding agent ↓ "Build an AI execution loop with LangGraph, E2B, Langfuse and DeepEval Add isolated execution, test-based verification, structured error logs and targeted retries Limit repairs to 2 attempts per failure Preserve task state between attempts and require human approval if verification still fails Show the architecture before writing code" bookmark this before building your next AI agent
这条是引用着另一条写的：x.com/promixyz/status/2102424036416348494