mirror of
https://github.com/diegosouzapw/OmniRoute.git
synced 2026-08-02 13:22:11 +03:00
Cherry-pick from codex/omniroute-fixes-20260324: - Replace MCP singleton transport with per-session architecture for Streamable HTTP - Fix Claude passthrough via OpenAI round-trip normalization - Add detectFormatFromEndpoint() for endpoint-aware format detection - Support raw code#state in OAuth modal for Claude Code remote auth - Expose cloudConfigured/cloudUrl/machineId in settings API - Switch docker-compose.prod.yml target to runner-cli - Add 3 new tests for round-trip and detectFormat PR: #562
296 lines
9.3 KiB
TypeScript
296 lines
9.3 KiB
TypeScript
import { FORMATS } from "./formats.ts";
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import { ensureToolCallIds, fixMissingToolResponses } from "./helpers/toolCallHelper.ts";
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import { prepareClaudeRequest } from "./helpers/claudeHelper.ts";
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import { filterToOpenAIFormat } from "./helpers/openaiHelper.ts";
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import { getRequestTranslator, getResponseTranslator } from "./registry.ts";
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import { bootstrapTranslatorRegistry } from "./bootstrap.ts";
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import { normalizeThinkingConfig } from "../services/provider.ts";
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import { applyThinkingBudget } from "../services/thinkingBudget.ts";
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import { normalizeRoles } from "../services/roleNormalizer.ts";
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bootstrapTranslatorRegistry();
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export { register } from "./registry.ts";
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function normalizeResponsesInputItem(item) {
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if (typeof item === "string") {
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return {
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type: "message",
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role: "user",
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content: [{ type: "input_text", text: item }],
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};
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}
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if (!item || typeof item !== "object") return item;
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if (item.type || item.role) {
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return item.type ? item : { type: "message", ...item };
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}
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if (typeof item.text === "string") {
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return {
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type: "message",
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role: "user",
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content: [{ type: "input_text", text: item.text }],
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};
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}
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return item;
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}
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function normalizeOpenAIResponsesRequest(body) {
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if (!body || typeof body !== "object") return body;
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const normalized = { ...body };
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if (typeof normalized.input === "string") {
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normalized.input = [
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{
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type: "message",
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role: "user",
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content: [{ type: "input_text", text: normalized.input }],
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},
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];
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return normalized;
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}
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if (Array.isArray(normalized.input)) {
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normalized.input = normalized.input.map(normalizeResponsesInputItem);
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return normalized;
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}
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if (normalized.input && typeof normalized.input === "object") {
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normalized.input = [normalizeResponsesInputItem(normalized.input)];
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return normalized;
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}
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return normalized;
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}
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/** @param options.normalizeToolCallId - When true, use 9-char tool call ids (e.g. Mistral); when false, leave ids as-is */
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/** @param options.preserveDeveloperRole - undefined/true: keep developer for OpenAI format (default); false: map to system */
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// Translate request: source -> openai -> target
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export function translateRequest(
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sourceFormat,
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targetFormat,
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model,
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body,
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stream = true,
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credentials = null,
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provider = null,
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reqLogger = null,
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options?: { normalizeToolCallId?: boolean; preserveDeveloperRole?: boolean }
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) {
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let result = body;
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const use9CharId = options?.normalizeToolCallId === true;
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const preserveDeveloperRole = options?.preserveDeveloperRole;
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// Phase 2: Apply thinking budget control before normalization
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result = applyThinkingBudget(result);
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// Normalize thinking config: remove if lastMessage is not user
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normalizeThinkingConfig(result);
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// Ensure tool_calls have id; optionally normalize to 9-char for providers like Mistral
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ensureToolCallIds(result, { use9CharId });
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// Fix missing tool responses (insert empty tool_result if needed)
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fixMissingToolResponses(result);
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// Normalize roles: developer→system unless preserved, system→user for incompatible models.
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// This handles (1) sourceFormat openai with messages containing developer → non-openai target
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// or preserveDeveloperRole=false, and (2) all other paths where result.messages already exists.
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if (result.messages && Array.isArray(result.messages)) {
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result.messages = normalizeRoles(
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result.messages,
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provider || "",
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model || "",
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targetFormat,
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preserveDeveloperRole
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);
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}
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// If same format, skip translation steps
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if (sourceFormat !== targetFormat) {
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// Check for direct translation path first (e.g., Claude → Gemini)
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const directTranslator = getRequestTranslator(sourceFormat, targetFormat);
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if (directTranslator && sourceFormat !== FORMATS.OPENAI && targetFormat !== FORMATS.OPENAI) {
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result = directTranslator(model, result, stream, credentials);
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} else {
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// Fallback: hub-and-spoke via OpenAI
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// Step 1: source -> openai (if source is not openai)
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if (sourceFormat !== FORMATS.OPENAI) {
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const toOpenAI = getRequestTranslator(sourceFormat, FORMATS.OPENAI);
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if (toOpenAI) {
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result = toOpenAI(model, result, stream, credentials);
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// Log OpenAI intermediate format
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reqLogger?.logOpenAIRequest?.(result);
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}
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}
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// Step 2: openai -> target (if target is not openai)
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if (targetFormat !== FORMATS.OPENAI) {
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const fromOpenAI = getRequestTranslator(FORMATS.OPENAI, targetFormat);
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if (fromOpenAI) {
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result = fromOpenAI(model, result, stream, credentials);
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}
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}
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}
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}
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// Always normalize to clean OpenAI format when target is OpenAI
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// This handles hybrid requests (e.g., OpenAI messages + Claude tools)
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if (targetFormat === FORMATS.OPENAI) {
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result = filterToOpenAIFormat(result);
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}
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// Final step: prepare request for Claude format endpoints
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if (targetFormat === FORMATS.CLAUDE) {
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result = prepareClaudeRequest(result, provider);
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}
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// Normalize openai-responses input shape for providers that require list input.
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if (targetFormat === FORMATS.OPENAI_RESPONSES) {
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result = normalizeOpenAIResponsesRequest(result);
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}
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// Second role normalization: only for OPENAI_RESPONSES. Here messages are built from input
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// after the translation step, so the first normalizeRoles (above) did not see them. For
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// sourceFormat openai with messages already on the body, the first block handles developer
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// → system (non-openai target or preserveDeveloperRole=false); no second pass needed.
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if (
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sourceFormat === FORMATS.OPENAI_RESPONSES &&
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result.messages &&
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Array.isArray(result.messages)
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) {
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result.messages = normalizeRoles(
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result.messages,
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provider || "",
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model || "",
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targetFormat,
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preserveDeveloperRole
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);
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}
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// Ensure unique tool_call ids on final payload (translators may have introduced duplicates)
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ensureToolCallIds(result, { use9CharId });
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fixMissingToolResponses(result);
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return result;
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}
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// Translate response chunk: target -> openai -> source
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export function translateResponse(targetFormat, sourceFormat, chunk, state) {
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// If same format, return as-is
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if (sourceFormat === targetFormat) {
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return [chunk];
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}
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let results = [chunk];
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let openaiResults = null; // Store OpenAI intermediate results
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// Check for direct translation path first (e.g., Gemini → Claude)
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const directTranslator = getResponseTranslator(targetFormat, sourceFormat);
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if (directTranslator && targetFormat !== FORMATS.OPENAI && sourceFormat !== FORMATS.OPENAI) {
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const converted = directTranslator(chunk, state);
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if (converted) {
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results = Array.isArray(converted) ? converted : [converted];
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} else {
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results = [];
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}
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return results;
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}
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// Fallback: hub-and-spoke via OpenAI
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// Step 1: target -> openai (if target is not openai)
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if (targetFormat !== FORMATS.OPENAI) {
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const toOpenAI = getResponseTranslator(targetFormat, FORMATS.OPENAI);
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if (toOpenAI) {
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results = [];
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const converted = toOpenAI(chunk, state);
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if (converted) {
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results = Array.isArray(converted) ? converted : [converted];
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openaiResults = results; // Store OpenAI intermediate
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}
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}
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}
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// Step 2: openai -> source (if source is not openai)
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if (sourceFormat !== FORMATS.OPENAI) {
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const fromOpenAI = getResponseTranslator(FORMATS.OPENAI, sourceFormat);
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if (fromOpenAI) {
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const finalResults = [];
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for (const r of results) {
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const converted = fromOpenAI(r, state);
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if (converted) {
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finalResults.push(...(Array.isArray(converted) ? converted : [converted]));
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}
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}
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results = finalResults;
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}
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}
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// Attach OpenAI intermediate results for logging
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if (openaiResults && sourceFormat !== FORMATS.OPENAI && targetFormat !== FORMATS.OPENAI) {
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(results as { _openaiIntermediate?: unknown })._openaiIntermediate = openaiResults;
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}
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return results;
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}
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// Check if translation needed
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export function needsTranslation(sourceFormat, targetFormat) {
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return sourceFormat !== targetFormat;
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}
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// Initialize state for streaming response based on format
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export function initState(sourceFormat) {
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// Base state for all formats
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const base = {
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messageId: null,
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model: null,
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textBlockStarted: false,
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thinkingBlockStarted: false,
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inThinkingBlock: false,
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currentBlockIndex: null,
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toolCalls: new Map(),
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finishReason: null,
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finishReasonSent: false,
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usage: null,
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contentBlockIndex: -1,
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};
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// Add openai-responses specific fields
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if (sourceFormat === FORMATS.OPENAI_RESPONSES) {
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return {
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...base,
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seq: 0,
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responseId: `resp_${Date.now()}`,
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created: Math.floor(Date.now() / 1000),
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started: false,
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msgTextBuf: {},
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msgItemAdded: {},
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msgContentAdded: {},
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msgItemDone: {},
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reasoningId: "",
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reasoningIndex: -1,
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reasoningBuf: "",
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reasoningPartAdded: false,
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reasoningDone: false,
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inThinking: false,
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funcArgsBuf: {},
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funcNames: {},
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funcCallIds: {},
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funcArgsDone: {},
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funcItemDone: {},
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completedSent: false,
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};
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}
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return base;
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}
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// Initialize all translators (no-op, kept for backward compatibility)
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export function initTranslators() {
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bootstrapTranslatorRegistry();
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}
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