mirror of
https://github.com/diegosouzapw/OmniRoute.git
synced 2026-07-26 09:52:11 +03:00
Includes version bump — v2.6.9 — committed ATOMICALLY with all changes:
fixes:
- fix(ci/t11): Remove 'any' from comments in openai-responses.ts + chatCore.ts
(\bany\b regex counted comment text as explicit any violations)
- fix(chatCore/#409): Normalize unsupported content part types before forwarding
Cursor sends {type:'file'} for .md attachments; Copilot/OpenAI providers reject
with 'type has to be either image_url or text'. Now: file/document→text block,
unknown types dropped with debug log. Fixes claude-* models via github-copilot.
workflow:
- chore(generate-release): ATOMIC COMMIT RULE — npm version patch MUST run before
feature commits so the release tag always points to a commit with full changes
423 lines
13 KiB
TypeScript
423 lines
13 KiB
TypeScript
/**
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* Translator: OpenAI Responses API -> OpenAI Chat Completions
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*
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* Responses API uses: { input: [...], instructions: "..." }
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* Chat API uses: { messages: [...] }
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*/
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import { register } from "../registry.ts";
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import { FORMATS } from "../formats.ts";
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import { generateToolCallId } from "../helpers/toolCallHelper.ts";
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type JsonRecord = Record<string, unknown>;
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const UNSUPPORTED_TOOLS = ["file_search", "code_interpreter", "web_search_preview"];
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function toRecord(value: unknown): JsonRecord {
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return value && typeof value === "object" && !Array.isArray(value) ? (value as JsonRecord) : {};
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}
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function toArray(value: unknown): unknown[] {
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return Array.isArray(value) ? value : [];
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}
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function toString(value: unknown, fallback = ""): string {
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return typeof value === "string" ? value : fallback;
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}
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function unsupportedFeature(message: string): Error & { statusCode: number; errorType: string } {
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const error = new Error(message) as Error & { statusCode: number; errorType: string };
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error.statusCode = 400;
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error.errorType = "unsupported_feature";
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return error;
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}
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/**
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* Convert OpenAI Responses API request to OpenAI Chat Completions format
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*/
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export function openaiResponsesToOpenAIRequest(
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model: unknown,
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body: unknown,
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stream: unknown,
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credentials: unknown
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): unknown {
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void model;
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void stream;
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void credentials;
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const root = toRecord(body);
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if (root.input === undefined) return body;
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// Validate unsupported features - return clear errors instead of silent failure
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const tools = toArray(root.tools);
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if (tools.length > 0) {
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for (const toolValue of tools) {
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const tool = toRecord(toolValue);
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if (UNSUPPORTED_TOOLS.includes(toString(tool.type))) {
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throw unsupportedFeature(
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`Unsupported Responses API feature: ${toString(tool.type)} tool type is not supported by omniroute`
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);
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}
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}
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}
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if (root.background) {
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throw unsupportedFeature(
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"Unsupported Responses API feature: background mode is not supported by omniroute"
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);
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}
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const result: JsonRecord = { ...root };
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const messages: JsonRecord[] = [];
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result.messages = messages;
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// Convert instructions to system message
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if (typeof root.instructions === "string" && root.instructions.length > 0) {
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messages.push({ role: "system", content: root.instructions });
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}
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// Group items by conversation turn
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let currentAssistantMsg: JsonRecord | null = null;
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let pendingToolResults: JsonRecord[] = [];
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const inputItems = toArray(root.input);
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for (const itemValue of inputItems) {
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const item = toRecord(itemValue);
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// Determine item type - Droid CLI sends role-based items without 'type' field
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// Fallback: if no type but has role property, treat as message
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const itemType = toString(item.type) || (item.role ? "message" : "");
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if (itemType === "message") {
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// Flush pending assistant message with tool calls
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if (currentAssistantMsg) {
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messages.push(currentAssistantMsg);
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currentAssistantMsg = null;
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}
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// Flush pending tool results
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if (pendingToolResults.length > 0) {
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for (const toolResult of pendingToolResults) {
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messages.push(toolResult);
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}
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pendingToolResults = [];
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}
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// Convert content: input_text -> text, output_text -> text
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const content = Array.isArray(item.content)
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? item.content.map((contentValue) => {
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const contentItem = toRecord(contentValue);
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if (contentItem.type === "input_text") {
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return { type: "text", text: toString(contentItem.text) };
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}
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if (contentItem.type === "output_text") {
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return { type: "text", text: toString(contentItem.text) };
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}
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return contentValue;
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})
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: item.content;
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messages.push({ role: toString(item.role), content });
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continue;
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}
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if (itemType === "function_call") {
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// Skip tool calls with empty names to avoid infinite placeholder_tool loops
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const fnName = toString(item.name).trim();
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if (!fnName) {
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continue;
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}
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// Start or append assistant message with tool_calls
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if (!currentAssistantMsg) {
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currentAssistantMsg = {
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role: "assistant",
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content: null,
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tool_calls: [],
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};
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}
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const toolCalls = Array.isArray(currentAssistantMsg.tool_calls)
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? currentAssistantMsg.tool_calls
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: [];
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toolCalls.push({
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id: toString(item.call_id),
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type: "function",
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function: {
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name: fnName,
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arguments: item.arguments,
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},
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});
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currentAssistantMsg.tool_calls = toolCalls;
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continue;
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}
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if (itemType === "function_call_output") {
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// Flush assistant message first if present
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if (currentAssistantMsg) {
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messages.push(currentAssistantMsg);
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currentAssistantMsg = null;
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}
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// Flush pending tool results first
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if (pendingToolResults.length > 0) {
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for (const toolResult of pendingToolResults) {
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messages.push(toolResult);
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}
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pendingToolResults = [];
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}
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// Add tool result immediately
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messages.push({
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role: "tool",
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tool_call_id: toString(item.call_id),
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content: typeof item.output === "string" ? item.output : JSON.stringify(item.output),
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});
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continue;
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}
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if (itemType === "reasoning") {
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// Skip reasoning items - they are display-only metadata
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continue;
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}
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}
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// Flush remainder
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if (currentAssistantMsg) {
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messages.push(currentAssistantMsg);
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}
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if (pendingToolResults.length > 0) {
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for (const toolResult of pendingToolResults) {
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messages.push(toolResult);
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}
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}
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// Convert tools format
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if (Array.isArray(root.tools)) {
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result.tools = root.tools.map((toolValue) => {
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const tool = toRecord(toolValue);
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if (tool.function) return toolValue;
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return {
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type: "function",
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function: {
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name: toString(tool.name),
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description: toString(tool.description),
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parameters: tool.parameters,
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strict: tool.strict,
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},
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};
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});
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}
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// Filter orphaned tool results (no matching tool_call in assistant messages)
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const allToolCallIds = new Set<string>();
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for (const m of messages) {
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const rec = toRecord(m);
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if (Array.isArray(rec.tool_calls)) {
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for (const tc of rec.tool_calls as { id?: string }[]) {
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if (tc.id) allToolCallIds.add(String(tc.id));
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}
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}
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}
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result.messages = messages.filter((m) => {
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const rec = toRecord(m);
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if (rec.role === "tool" && rec.tool_call_id) {
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return allToolCallIds.has(String(rec.tool_call_id));
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}
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return true;
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});
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// Cleanup Responses API specific fields
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delete result.input;
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delete result.instructions;
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delete result.include;
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delete result.prompt_cache_key;
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delete result.store;
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delete result.reasoning;
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return result;
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}
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/**
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* Convert OpenAI Chat Completions to OpenAI Responses API format
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*/
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export function openaiToOpenAIResponsesRequest(
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model: unknown,
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body: unknown,
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stream: unknown,
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credentials: unknown
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): unknown {
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void stream;
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void credentials;
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const root = toRecord(body);
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const result: JsonRecord = {
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model,
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input: [],
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stream: true,
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store: false,
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};
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const input = result.input as JsonRecord[];
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// Extract first system message as instructions
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let hasSystemMessage = false;
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const messages = toArray(root.messages);
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for (const messageValue of messages) {
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const msg = toRecord(messageValue);
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const role = toString(msg.role);
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if (role === "system") {
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if (!hasSystemMessage) {
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result.instructions = typeof msg.content === "string" ? msg.content : "";
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hasSystemMessage = true;
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}
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continue;
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}
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// Convert user messages
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if (role === "user") {
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const content =
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typeof msg.content === "string"
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? [{ type: "input_text", text: msg.content }]
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: Array.isArray(msg.content)
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? msg.content.map((contentValue) => {
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const contentItem = toRecord(contentValue);
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if (contentItem.type === "text") {
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return { type: "input_text", text: toString(contentItem.text) };
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}
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if (contentItem.type === "image_url") {
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const imgUrl = contentItem.image_url as string | { url?: string };
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return {
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type: "input_image",
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image_url: typeof imgUrl === "string" ? imgUrl : imgUrl?.url || "",
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};
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}
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return contentValue;
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})
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: [{ type: "input_text", text: "" }];
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input.push({
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type: "message",
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role: "user",
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content,
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});
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}
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// Convert assistant messages
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if (role === "assistant") {
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// Skip reasoning_content — OpenAI Responses API requires server-generated
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// rs_* IDs for reasoning items. Synthesizing client-side IDs (e.g. reasoning_N)
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// causes 400 errors from Responses-compatible upstreams. (#224)
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// Skip thinking blocks in array content — same rs_* ID constraint applies
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// Build assistant output content
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const outputContent: unknown[] = [];
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if (typeof msg.content === "string" && msg.content) {
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outputContent.push({ type: "output_text", text: msg.content });
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} else if (Array.isArray(msg.content)) {
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for (const contentValue of msg.content) {
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const contentItem = toRecord(contentValue);
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if (contentItem.type === "text" && contentItem.text) {
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outputContent.push({ type: "output_text", text: toString(contentItem.text) });
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} else if (contentItem.type === "thinking" || contentItem.type === "redacted_thinking") {
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// Reasoning already moved above
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continue;
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} else {
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outputContent.push(contentValue);
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}
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}
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}
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// Only add assistant message if content exists
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if (outputContent.length > 0) {
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input.push({
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type: "message",
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role: "assistant",
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content: outputContent,
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});
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}
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// Convert tool_calls to function_call items
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if (Array.isArray(msg.tool_calls)) {
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for (const toolCallValue of msg.tool_calls) {
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const toolCall = toRecord(toolCallValue);
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const fn = toRecord(toolCall.function);
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// Skip tool calls with empty names to avoid infinite placeholder_tool loops
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const fnName = toString(fn.name).trim();
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if (!fnName) {
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continue;
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}
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input.push({
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type: "function_call",
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call_id: toString(toolCall.id).trim() || generateToolCallId(),
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name: fnName,
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arguments: toString(fn.arguments, "{}"),
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});
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}
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}
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}
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// Convert tool results
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if (role === "tool") {
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input.push({
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type: "function_call_output",
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call_id: toString(msg.tool_call_id),
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output: msg.content,
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});
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}
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}
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// Filter orphaned function_call_output items (no matching function_call)
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// This happens when Claude Code compaction removes messages but leaves tool results
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const knownCallIds = new Set(
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input
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.filter(
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(item: { type?: string; call_id?: string }) => item.type === "function_call" && item.call_id
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)
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.map((item: { type?: string; call_id?: string }) => item.call_id)
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);
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result.input = input.filter((item: { type?: string; call_id?: string }) => {
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if (item.type === "function_call_output" && item.call_id) {
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return knownCallIds.has(item.call_id);
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}
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return true;
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});
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// If no system message, keep empty instructions
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if (!hasSystemMessage) {
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result.instructions = "";
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}
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// Convert tools format
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if (Array.isArray(root.tools)) {
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result.tools = root.tools.map((toolValue) => {
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const tool = toRecord(toolValue);
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if (tool.type === "function") {
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const fn = toRecord(tool.function);
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return {
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type: "function",
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name: toString(fn.name),
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description: toString(fn.description),
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parameters: fn.parameters,
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strict: fn.strict,
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};
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}
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return toolValue;
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});
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}
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// Pass through relevant fields
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if (root.service_tier !== undefined) result.service_tier = root.service_tier;
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if (root.temperature !== undefined) result.temperature = root.temperature;
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if (root.max_tokens !== undefined) result.max_tokens = root.max_tokens;
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if (root.top_p !== undefined) result.top_p = root.top_p;
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return result;
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}
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// Register both directions
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register(FORMATS.OPENAI_RESPONSES, FORMATS.OPENAI, openaiResponsesToOpenAIRequest, null);
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register(FORMATS.OPENAI, FORMATS.OPENAI_RESPONSES, openaiToOpenAIResponsesRequest, null);
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