feat: 加入embeddings、rerank - #287
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1. Embedding 502 修复 (internal/relay/transformers.go) - 从 embedding 兼容列表中移除了 openai_response 类型。openai_response 的 outbound transformer 会构造错误的 URL 路径，导致上游必定失败。 ──- 你需要将 LM Studio embedding 渠道的类型改为 openai_embedding 或 openai_chat_completion，这样 outbound transformer 才能正确构造 /v1/embeddings 请求路径。 2. /v1/rerank 支持 (internal/relay/rerank.go + internal/server/server.go) - 新增了 Jina/Cohere 格式的 rerank 透传 handler，复用现有的 group/balancer/metrics 基础设施。 - 支持负载均衡、熔断、重试、自定义 header、代理等所有渠道特性。 - 使用方式：创建一个渠道指向 rerank 服务（如 Jina），创建分组映射模型名，然后通过 POST /v1/rerank 调用。 3. 分组/渠道重名错误优化 (internal/db/errors.go + handlers) - 新增 IsDuplicateError 工具函数，检测 SQLite/MySQL/PostgreSQL 的 UNIQUE 约束错误。 - 创建分组或渠道时如果名称重复，现在返回 HTTP 409 + "Resource already exists"，而不是原始的数据库错误信息。
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Commit 97d6a04 axonhub/llm 另外这个go mod tidy 好像获取不到 |
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chenjingxiong
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Jun 21, 2026
…truirui#208 已内置) 合入的 PR： - bestruirui#262 添加活动热力图自定义日期范围选择功能 (cherry-pick) - bestruirui#271 修复日志无法滚动问题 (手动适配：VirtualizedGrid reachEnd 重置 + 日志分页偏移) - bestruirui#287 加入 rerank 转发路由 + 重复资源检测 (手动适配) - bestruirui#208 空响应检测触发负载均衡重试 → 已被 axonhub/llm 内置 WithEmptyResponseDetection() 覆盖，无需手动移植 跳过的 PR： - bestruirui#282 TOTP + JSON 替换 (+1425/-115，改动过大) - bestruirui#270 key 选择模式 (改了已删除的 images.go，需大量适配) - bestruirui#199 熔断器开关 (改了已删除的 transformer，冲突复杂) - bestruirui#198 渠道标签系统 (13 文件，改动偏大) - bestruirui#194 日志筛选增强 (8 文件 +512/-86，改动偏大) - bestruirui#190 统计清除 (合并提交多，冲突复杂) - bestruirui#184 渠道排序 (排序已内置上游，复制功能非核心) 版本升级至 v0.9.28-2 Co-Authored-By: Claude <noreply@anthropic.com>
hadc188
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Aug 5, 2026
同步上游: - feat: API 转换迁移到 axonhub/llm(含渠道类型字符串迁移 003) - perf: 前端 Next.js 改为 Vite - fix: 日志清理/清空并发、日志内存延迟释放、ParamOverride、saveLog 回归 - feat: DeepSeek thinking + Nvidia chat template 支持 本地修复(基于议题/PR 调研): - feat: 支持 /v1/responses/compact(codex 压缩,bestruirui#294) - fix: 首字超时覆盖「等待上游响应头」阶段(bestruirui#289) - feat: 渠道 key 选择模式(成本/轮询/加权随机,bestruirui#270,修复 bestruirui#245) - feat: 支持 /v1/rerank(Jina/Cohere,bestruirui#287) - feat: 渠道/分组重名返回 409 - fix: http client 增加 ResponseHeaderTimeout 兜底
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才能正确构造 /v1/embeddings 请求路径。