4.1 KiB
4.1 KiB
open-sse
Provider-agnostic SSE engine: one OpenAI-style request → any provider (LLM chat, image, embedding, tts, stt, search), streamed back in the client's format.
Request lifecycle (chat)
handlers/chatCore.js → services/model.js parseModel (resolve provider/model) → pre-translate hooks (rtk/ tool_result compress, rtk/headroom.js proxy compress, rtk/caveman.js system inject — all fail-open) → executors/index.js getExecutor(provider) → translator/index.js translateRequest (client format → provider format) → executor.execute() (streams upstream) → translateResponse (provider chunks → client format) → SSE out.
Directory map
config/— ALL constants/config (no hardcode elsewhere).providers.js/registry/(provider defs),providerModels.js(alias→models matrix),runtimeConfig.js(timeouts, token limits),*Constants.js.translator/— format conversion.request/<from>-to-<to>.js,response/<from>-to-<to>.js,schema/(enums: ROLE, CLAUDE_BLOCK…),concerns/(shared logic),formats.js+formats/(per-format).index.jsis the registry/entry.executors/— per-provider upstream call.base.js(BaseExecutor), one file per special provider,index.jsmap.providers/— registry build +capabilities.js+pricing.js. Entry:index.js(PROVIDERS).handlers/— per-modality cores (chat/image/embedding/tts/stt/search) + sub-provider folders.chatCore/has the streaming/non-streaming/sse-to-json handlers.rtk/— request token-killer.index.jscompressestool_resultcontent in-place (OpenAI/Claude/Kiro shapes);filters/per-tool compressors +autodetect.js;headroom.jsexternal compress proxy;caveman.jssystem-prompt injector.transformer/—responsesTransformer.js(Chat Completions SSE → Codex Responses API SSE),streamToJsonConverter.js.shared/— cross-provider auth/identity:clineAuth.js,machineId.js,qoder/.services/—model.js,provider.js,accountFallback.js,combo.js,compact.js,tokenRefresh/+tokenRefresh.js,oauthCredentialManager.js,usage/,projectId.js,kiroModels.js/qoderModels.js.utils/— streamHandler, stream, sse, error, sessionManager, claudeCloaking, clientDetector, proxyFetch (patches global fetch), cursorProtobuf/cursorChecksum, ollamaTransform.
Conventions
- Config-driven, DRY, camelCase. NEVER hardcode values, models, or block/role strings — use
config/+schema/constants. - Translator pipeline pivots through OpenAI as the intermediate format. A translator registered on the exact
source:targetpair (e.g.claude:kiro) runs as a direct route, skipping the lossy double-hop. - Translators self-register via
register(from, to, reqFn, resFn)as an import side-effect — new files MUST be imported intranslator/index.js.
How to add
- Provider: copy
providers/REGISTRY_TEMPLATE.js→providers/registry/{id}.js; add models toconfig/providerModels.js. Generic providers need no executor (DefaultExecutor handles OpenAI-compatible APIs). - Executor (only for non-standard upstream): subclass
BaseExecutor(overridegetBaseUrls/buildHeaders/buildUrl/execute), register inexecutors/index.jsmap.getExecutorfalls back toDefaultExecutorwhen absent. - Translator: add
request|response/<from>-to-<to>.jscallingregister(...), then import it intranslator/index.js. Reuseschema/+concerns/— don't re-implement parsing.
Pitfalls
- OpenAI bridge is lossy (thinking, non-base64 images, tool ids, is_error) — prefer a direct route for fragile pairs.
registry/index.jsis an auto-generated static import list; regenerate it (don't hand-edit) after adding aregistry/{id}.js. REGISTRY_TEMPLATE is excluded by design.- Special binary/protobuf formats (kiro EventStream, cursor protobuf, commandcode NDJSON) don't round-trip through OpenAI — handle in their executor.
rtk/+headroom.jsmutate the request body in-place and are fail-open: any error returns null and leaves the body untouched — never throw out of them. RTK skipsis_error/status:"error"tool results to preserve traces.