changelogOpenAI

OpenCode v1.14.25 Adds Roslyn LSP Support for Razor and Fixes GPT-5.5 Context Limits

TL;DR

OpenCode shipped v1.14.25 with Roslyn LSP support for Razor, .cshtml, and C# script files. The release fixes GPT-5.5 with OpenAI OAuth to use correct context limits and adds request details to LSP permission prompts.

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OpenCode released v1.14.25 with support for Roslyn Language Server Protocol (LSP) across Razor, .cshtml, and C# script files.

Core Changes

The release addresses a context compaction issue where GPT-5.5 with OpenAI OAuth was not using correct context limits. The fix ensures the model operates within its specified token boundaries.

LSP permission prompts now include granular request details: the specific operation being performed, target file path, and cursor position. This gives developers visibility into what code assistance tools are accessing before granting permission.

The permission configuration system now preserves rule order and exposes full IntelliSense support for tool permission keys, improving the developer experience when configuring access controls.

Shell commands maintain the correct working directory after login shell startup files execute, fixing a bug where the working directory would change unexpectedly during shell initialization.

Community Contributions

Two community members contributed to this release:

  • @altendky clarified git amend conditions to require verifying commits have landed (PR #19937)
  • @b0o added Prettier to devDependencies for the build system (PR #23255)

What This Means

The Roslyn LSP integration expands OpenCode's C# development capabilities beyond standard .cs files into web development with Razor templates and scripting scenarios. The GPT-5.5 context fix is critical for developers using OpenAI's OAuth flow, as incorrect context limits can cause the model to prematurely compress or drop relevant code context. Enhanced permission prompts with operation details give developers better control over what their AI coding assistants can access, addressing security and privacy concerns in enterprise environments.

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