nuglifeleoji/Sentry

选用指南

AI 根据 README 整理 · 2026/10/22 10:02:05

使用方式

通过 Python 库集成到代理循环中，使用 SentryRunner 提交步骤并获取修复提示。

查看 README 依据

git clone https://github.com/nuglifeleoji/Sentry.git cd Sentry python -m venv .venv source .venv/bin/activate python -m pip install -e . sentry-validate configs/paper.yaml ``` ### Integrate Sentry into Your Agent Loop Configure a model provider, then submit each completed agent-environment cycle to Sentry: ```python from Sentry import SentryRunner, agent_step_from_parts runner = SentryRunner.from_yaml("configs/providers/openai_compatible.yaml") runner.start_task( objective=task_objective, action_schema=environment_action_schema, ) try: step = agent_step_from_parts(

step_id=0, reasoning=reasoning, raw_action=raw_action, tool_name=tool_name, tool_args=tool_args, observation=observation, parsed_ok=True, schema_valid=True, accepted_by_environment=True, ) repair = runner.step(step, terminal=False) if repair is not None: agent_messages.append(repair.prompt_text) finally: runner.finalize() ``` Your application remains responsible for generating, validating, and executing actions. See the integration guide for the full lifecycle and validity rules.

部署要求

需要 Python 3.10 或更高版本，并配置模型提供者（如 OpenAI 兼容 API）。

查看 README 依据

- **37% average improvement** over the strongest runtime-intervention baseline across WebShop, AppWorld, SWE-bench Lite, and Mind2Web Replay. - **39% average improvement** over the strongest context-evolution baseline on held-out WebShop and Mind2Web Replay tasks. - **1.54× base-agent token usage**, versus up to 2.44× for other runtime methods, while saving 31.7s per task on SWE-bench Lite and 45.6s on AppWorld. - **81.7% recovery rate** across 939 detected failures. ## Quick Start ### Installation Sentry requires Python 3.10 or later. ```bash

git clone https://github.com/nuglifeleoji/Sentry.git cd Sentry python -m venv .venv source .venv/bin/activate python -m pip install -e . sentry-validate configs/paper.yaml ``` ### Integrate Sentry into Your Agent Loop Configure a model provider, then submit each completed agent-environment cycle to Sentry: ```python from Sentry import SentryRunner, agent_step_from_parts runner = SentryRunner.from_yaml("configs/providers/openai_compatible.yaml") runner.start_task( objective=task_objective, action_schema=environment_action_schema, ) try: step = agent_step_from_parts(

已知限制

当前仓库仅包含项目概述和论文，完整代码和文档计划在 2-3 周后发布。

查看 README 依据

This repository currently contains the project overview and paper. We are finalizing our code and documentation and plan to release the full version in 2-3 weeks.