feat: add model-routed protocols for OpenCode Go - #2285
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No actionable comments were generated in the recent review. 🎉 ℹ️ Recent review info⚙️ Run configurationConfiguration used: defaults Review profile: CHILL Plan: Pro Plus Run ID: 📒 Files selected for processing (5)
🚧 Files skipped from review as they are similar to previous changes (2)
Included review availability: Your plan provides up to 8 included reviews per hour; 6 remain after this review. 📝 WalkthroughWalkthroughOpenCode Go now declares Chat Completions and Responses support. Model-aware routing selects Chat, Anthropic, or Responses formats. The orchestrator resolves the format per request and tests cover routing and tool filtering. ChangesOpenCode multi-format routing
Estimated code review effort: 3 (Moderate) | ~25 minutes Merge Risk: 🟡 Moderate · up to The change adds model-routed protocol behavior, but the current head still fails the repository's configured Go struct-literal lint in channel endpoint code, so merge readiness requires fixing or explicitly accepting that check failure. Sequence Diagram(s)sequenceDiagram
participant OpenCodeRequest
participant OutboundTransformer
participant APIFormatResolver
participant ModelSpecificOutbound
OpenCodeRequest->>OutboundTransformer: Transform request
OutboundTransformer->>APIFormatResolver: Resolve format for model
APIFormatResolver->>ModelSpecificOutbound: Select protocol transformer
ModelSpecificOutbound-->>OpenCodeRequest: Return routed URL and payload
Suggested reviewers: 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 3
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Inline comments:
In `@internal/server/biz/channel_endpoint.go`:
- Around line 200-203: Make the new literals exhaustive for exhaustruct_v5: in
internal/server/biz/channel_endpoint.go lines 200-203, explicitly set Path,
BaseURL, and Transport on both ChannelEndpoint values; in
internal/server/orchestrator/outbound_test.go lines 1180-1194, update the
mockTransformer and llm.Request literals; and in
internal/server/biz/channel_llm_openai_compatible_test.go lines 26-75, update
the credentials, request, message, and message-content literals. Use the
repository-approved narrow suppression only where intentional zero-value fields
should remain.
In `@internal/server/orchestrator/outbound_test.go`:
- Around line 40-43: Add an empty separator line between the embedded
mockTransformer field and resolvedFormat in requestFormatMockTransformer to
satisfy the embeddedstructfieldcheck lint rule.
In `@llm/transformer/opencode/outbound.go`:
- Around line 133-141: Update the model routing checks in outbound.go to require
the family delimiter, matching deepseek-, grok-, gpt-, muse-, minimax-, and
qwen3- rather than bare prefixes. Add near-match cases such as museum-v1 and
gptfoo in outbound_test.go, asserting they use the Chat route.
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ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro Plus
Run ID: f57acc49-bcd1-45ce-8eff-4cc34a479b9e
📒 Files selected for processing (10)
frontend/src/features/channels/data/channel-config.test.mjsfrontend/src/features/channels/data/config_channels.tsfrontend/src/features/channels/data/config_providers.tsinternal/server/biz/channel_endpoint.gointernal/server/biz/channel_endpoint_mapping_test.gointernal/server/biz/channel_llm_openai_compatible_test.gointernal/server/orchestrator/outbound.gointernal/server/orchestrator/outbound_test.gollm/transformer/opencode/outbound.gollm/transformer/opencode/outbound_test.go
Included review availability: Your plan provides up to 8 included reviews per hour; 7 remain after this review.
AkaChou
marked this pull request as draft
August 20, 2026 15:51
AkaChou
marked this pull request as ready for review
August 20, 2026 15:54
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不建议根据模型名来匹配协议。实测 OpenCode Go 中的模型并非只支持文档中列举的协议，以 deepseek-v4-flash 为例，实测同时支持三种协议，其他模型也有类似情况。既然 OpenCode Go 已经支持这些协议，axonhub 中没必要再做一次转换了。@looplj 建议 revert 9f7160b ══════════════════════════════════════════════════
▶ 1) Chat Completions
──────────────────────────────────────────────────
curl -X POST "https://opencode.ai/zen/go/v1/chat/completions" \
-H "Authorization: Bearer $OCGO_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"deepseek-v4-flash","messages":[{"role":"user","content":"hi"}],"max_tokens":16}'
──────────────────────────────────────────────────
{"id":"router-166aee0868799f07a6646b29d779cea0","object":"chat.completion","created":1787546356,"model":"deepseek-v4-flash","choices":[{"index":0,"finish_reason":"stop","logprobs":null,"message":{"role":"assistant","content":"Hello! How can I help you today?","reasoning_content":"We need respond to user. They said hi. Need engage. Keep concise. Maybe \"Hello! How can I help you today?\" That's fine.","tool_calls":null}}],"usage":{"prompt_tokens":84,"completion_tokens":42,"total_tokens":126,"prompt_tokens_details":{}},"cost":"0"}
[HTTP 200]
══════════════════════════════════════════════════
▶ 2) Responses API
──────────────────────────────────────────────────
curl -X POST "https://opencode.ai/zen/go/v1/responses" \
-H "Authorization: Bearer $OCGO_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"deepseek-v4-flash","input":"hi","max_output_tokens":16}'
──────────────────────────────────────────────────
{"id":"cc492bfe-2ca9-4d75-ae57-3d8698901eec","object":"response","created_at":1787546357,"completed_at":1787546358,"status":"incomplete","parallel_tool_calls":true,"temperature":1,"top_p":1,"max_output_tokens":16,"previous_response_id":null,"background":false,"truncation":"disabled","top_logprobs":0,"max_tool_calls":null,"prompt_cache_retention":null,"model":"deepseek-v4-flash","error":null,"incomplete_details":{"reason":"max_output_tokens"},"output":[{"id":"1335ea60-0207-40aa-b5f2-1694de87a28b","type":"reasoning","status":"incomplete","encrypted_content":"cc492bfe-2ca9-4d75-ae57-3d8698901eec-0","content":[{"type":"reasoning_text","text":"We need answer user. Need be careful. User \"hi\". We can respond"}],"summary":[]}],"usage":{"input_tokens":84,"output_tokens":16,"total_tokens":100,"input_tokens_details":{"cached_tokens":0},"output_tokens_details":{"reasoning_tokens":16}},"instructions":null,"tool_choice":"auto","tools":[],"reasoning":{"effort":null,"summary":null},"text":{"verbosity":null,"format":{"type":"text"}},"moderation":null,"cost":"0"}
[HTTP 200]
══════════════════════════════════════════════════
▶ 3) Anthropic Messages
──────────────────────────────────────────────────
curl -X POST "https://opencode.ai/zen/go/v1/messages" \
-H "Authorization: Bearer $OCGO_KEY" \
-H "x-api-key: $OCGO_KEY" -H "anthropic-version: 2023-06-01" \
-H "Content-Type: application/json" \
-d '{"model":"deepseek-v4-flash","max_tokens":16,"messages":[{"role":"user","content":"hi"}]}'
──────────────────────────────────────────────────
{"id":"0f3fd547-81bf-40ce-a190-394f0eb8eb09","type":"message","role":"assistant","stop_reason":"max_tokens","stop_sequence":null,"model":"deepseek-v4-flash","content":[{"type":"thinking","thinking":"We need answer. Need think. User says hi. We should respond friendly.","signature":"0f3fd547-81bf-40ce-a190-394f0eb8eb09"}],"usage":{"input_tokens":84,"output_tokens":16,"cache_creation_input_tokens":0,"cache_read_input_tokens":0},"cost":"0"}
[HTTP 200]
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Contributor
Author
确实，但也要考虑部分模型确实只支持单一节点的情况，最好的办法其实还是可以灵活配置，比如可以支持配置模型勾选支持端点，单独配置这些模型支持的思考级别，这点在 cc-switch 最新版的中已经实现，如果能够对接起来或许更方便。还有一种就是像 cpa 一样支持模型后面添加后缀来支持思考级别。 |
能够对模型进行细化配置肯定是更好的，不过你说的 cpa 那种添加后缀来自动推理思考级别好像已经有了，不过我没试过 |
Owner
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统一的 opencode_go 自动路由，有需要指定格式的，自己选择使用 _anthropic, _response 渠道是否可行。 |
Contributor
Author
一、 关于入站协议自动路由与强制指定 二、 关于思考等级（Reasoning Effort）的映射与降级痛点 现状问题： 2.为什么不能简单全局映射 xhigh -> max？ 如果全局将 xhigh 提升为 max，遇到那些最高仅支持 xhigh 的模型时，上游接口就会直接抛错（400 Bad Request）。这就导致用户针对不同模型、不同思考强度，必须分别维护不同的请求体覆盖规则。 建议： 2.协议层保持 1:1 等级映射：主流协议目前大多已规范化支持 none / low / medium / high / xhigh / max。在协议转换（如 Anthropic ↔ OpenAI Chat / Responses）过程中，建议不做全局截断/硬降级，尽量保持同级别透传/转换（例如 max 对应转换为目标协议的 max），如此若上游报错，用户只需要在客户端更改思考等级即可，以减少用户针对不同模型分别写请求体覆盖的心智负担。 |
Owner
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渠道支持 model route 比较合理。 xhigh-max 那是历史问题，之前的 openai 没有 max ，可以单独 pr 处理。 |
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关联
Related to #2240，作为 OpenCode Go Responses 支持合并后的后续问题。
#2105 仅作为背景说明：它描述了 Responses → Chat 的特殊工具语义转换缺失。本 PR 不实现完整的 custom/tool_search/namespace 转换，只处理本次 OpenCode 动态路由引入的协议判断错位。
本次工作
OpenCode Go 渠道默认暴露 OpenAI Chat Completions 和 OpenAI Responses 两个 endpoint。
前端 API Format 下拉支持在同一个 OpenCode Go 渠道中选择 Chat、Responses 和 Anthropic Messages。
OpenCode transformer 按模型前缀选择实际上游协议：
gpt-*、grok-*、muse-*→ Responsesminimax-*、qwen3-*→ Anthropic Messagesdeepseek-*和其他模型 → Chat Completions保持模型 ID 原样进行前缀匹配，不自动转小写或去除空格。
审核意见修复
审查指出：当客户端发送 Responses 请求并使用
glm-*、deepseek-*或minimax-*时，候选 endpoint 会报告openai/responses，但 OpenCode 实际会路由到 Chat 或 Anthropic。这样中间件会错误保留 Responses 专用 custom tool 续接消息。现在编排层在中间件执行前读取 transformer 根据实际模型解析出的上游协议：
glm-*→ 按 Chat 协议过滤 Responses 专用 custom tool 消息；minimax-*、qwen3-*→ 按 Anthropic 协议处理；gpt-*、grok-*、muse-*→ 保留 Responses 专用消息。验证
cd llm && go test ./transformer/opencodego test ./internal/server/orchestrator -run 'TestResolveOutboundAPIFormat|TestPersistentOutboundTransformer_FiltersResponsesCustomToolsForModelRoutedOpenCode|TestFilterResponseCustomToolMessagesForNonResponsesOutbound' -count=1go test ./internal/server/biz -run 'TestOpenCodeChannel_ResponsesEndpointUsesModelRoutedOutbound|TestDefaultEndpointsForChannelType_UseLLMAPIFormatValues' -count=1cd frontend && pnpm test:unit -- src/features/channels/data/channel-config.test.mjs后续优化项
当前思考强度设置和转换仍然依赖渠道级配置，无法根据模型分别设置或转换。例如同一 OpenCode Go 渠道中的不同模型可能需要不同的 reasoning effort 映射。后续可以增加模型级或其他粒度思考强度配置和转换能力。
Summary by CodeRabbit
New Features
Bug Fixes