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Pydantic AI v2.60.0 (2026-10-22)

Pydantic AI v2.60.0 adds DockerSandbox and BoxLiteSandbox workspace capabilities, updates ModelSelectionContext with usage and retry limits, strengthens security sanitization, and introduces several compatibility updates including deprecating RetryPromptPart.

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人类阅读

为什么值得关注

Pydantic AI release v2.60.0 introduces several new sandbox harness capabilities, including DockerSandbox (supporting local Docker or Podman containers), BoxLiteSandbox (a local BoxLite micro-VM workspace), and existing VM reuse in SmolSandboxBackend. Key compatibility updates and deprecations include: - Deprecation of RetryPromptPart in favor of ToolReturnPart(outcome='retried') and RetryFeedbackPart. - Embedding models now raise standard model error categories like ModelRateLimitError. - ModelSelectionContext now includes usage limits, deadlines, run ID, conversation ID, output retry counts, and retry budgets. - BedrockConverseModel defaults maxTokens to Claude's maximum output while streaming behind the scenes. - MCP capability default IDs are derived strictly from the server URL hostname, rejecting multiple servers on one host without explicit IDs. - OpenAIDecisionsProvider is deprecated in favor of passing OpenAIProvider to OpenAIDecisionsModel. - Security and sanitization hardening: stripping request-level instructions from untrusted history, dropping client-supplied TextContent.metadata from user prompts, case-insensitive FileSystem denial patterns, and protecting .git files.

Agent 解析

可执行摘要

Pydantic AI v2.60.0 introduces DockerSandbox and BoxLiteSandbox workspaces, adds run metadata (usage limits, deadline, run/conversation ID, retry count/budget) to ModelSelectionContext, updates BedrockConverseModel defaults, and replaces RetryPromptPart with ToolReturnPart(outcome='retried') and RetryFeedbackPart.

Agent 实用度
77/100
可信度
96%
机器格式
JSON + Markdown
下一步

开发者应核对什么

  • Migrate code using RetryPromptPart to ToolReturnPart(outcome='retried') and RetryFeedbackPart.
  • Replace usages of OpenAIDecisionsProvider with OpenAIProvider when configuring OpenAIDecisionsModel.
  • Explicitly set IDs when defining multiple MCP servers hosted on the same hostname to avoid initialization errors.
  • Verify error handling around embedding calls to support newly raised ModelRateLimitError exceptions.
分类

标签与路由

pydantic-aityped-agentspython
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