mirror of
https://github.com/tiennm99/ccs.git
synced 2026-07-16 08:17:11 +00:00
feat(proxy): enhance Anthropic-to-OpenAI message transformation and schema sanitization
This commit is contained in:
@@ -1,5 +1,7 @@
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import { normalizeSchemaForOpenAI } from '../../utils/schema-sanitizer';
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interface AnthropicThinking {
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type?: 'enabled' | 'disabled' | string;
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type?: 'enabled' | 'disabled' | 'adaptive' | string;
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budget_tokens?: number;
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}
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@@ -14,6 +16,7 @@ interface AnthropicImageBlock {
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type?: string;
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media_type?: string;
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data?: string;
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url?: string;
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};
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}
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@@ -28,6 +31,7 @@ interface AnthropicToolResultBlock {
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type: 'tool_result';
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tool_use_id?: string;
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content?: unknown;
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is_error?: boolean;
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}
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type AnthropicContentBlock =
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@@ -42,6 +46,10 @@ interface AnthropicMessage {
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content?: string | AnthropicContentBlock[];
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}
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interface AnthropicOutputConfig {
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effort?: 'low' | 'medium' | 'high' | 'max' | string;
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}
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interface AnthropicProxyRequestShape {
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model?: unknown;
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system?: unknown;
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@@ -54,6 +62,7 @@ interface AnthropicProxyRequestShape {
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tools?: unknown;
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stream?: unknown;
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thinking?: AnthropicThinking;
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output_config?: AnthropicOutputConfig;
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}
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interface OpenAITextPart {
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@@ -108,7 +117,6 @@ export interface ProxyOpenAIRequest {
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metadata?: Record<string, unknown>;
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}
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const TOOL_RESULT_SERIALIZATION_FALLBACK = '[unserializable content]';
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const TOOL_USE_ARGUMENTS_FALLBACK = '{}';
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function assertObject(value: unknown, label: string): Record<string, unknown> {
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@@ -168,17 +176,63 @@ function flattenTextContent(content: unknown, label: string): string {
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.join('\n');
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}
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function toToolResultContent(content: unknown, label: string): string {
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/**
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* Convert tool_result content to OpenAI-compatible format.
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* Handles strings, arrays with text/image blocks, and error prefixing.
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* Ported from openclaude's convertToolResultContent.
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*/
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function convertToolResultContent(
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content: unknown,
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isError: boolean
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): string | OpenAIContentPart[] {
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if (content === undefined) {
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return '';
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}
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if (typeof content === 'string') {
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return content;
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return isError ? `Error: ${content}` : content;
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}
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if (Array.isArray(content)) {
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return flattenTextContent(content, label);
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if (!Array.isArray(content)) {
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const text = safeJsonStringify(content, '[unserializable content]');
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return isError ? `Error: ${text}` : text;
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}
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return safeJsonStringify(content, TOOL_RESULT_SERIALIZATION_FALLBACK);
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const parts: OpenAIContentPart[] = [];
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for (const block of content) {
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if (block?.type === 'text' && typeof block.text === 'string') {
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parts.push({ type: 'text', text: block.text });
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continue;
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}
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if (block?.type === 'image') {
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const source = block.source;
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if (source?.type === 'url' && source.url) {
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parts.push({ type: 'image_url', image_url: { url: source.url } });
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} else if (source?.type === 'base64' && source.media_type && source.data) {
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parts.push({
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type: 'image_url',
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image_url: { url: `data:${source.media_type};base64,${source.data}` },
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});
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}
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continue;
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}
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if (typeof block?.text === 'string') {
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parts.push({ type: 'text', text: block.text });
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}
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}
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if (parts.length === 0) return '';
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if (parts.length === 1 && parts[0].type === 'text') {
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const text = (parts[0] as OpenAITextPart).text;
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return isError ? `Error: ${text}` : text;
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}
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if (isError && parts[0]?.type === 'text') {
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parts[0] = { ...parts[0], text: `Error: ${(parts[0] as OpenAITextPart).text}` };
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} else if (isError) {
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parts.unshift({ type: 'text', text: 'Error:' });
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}
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return parts;
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}
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function createFallbackToolId(messageIndex: number, blockIndex: number): string {
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@@ -187,16 +241,27 @@ function createFallbackToolId(messageIndex: number, blockIndex: number): string
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function toImagePart(block: AnthropicImageBlock, label: string): OpenAIImagePart {
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const source = block.source;
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if (!source || source.type !== 'base64' || !source.media_type || !source.data) {
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throw new Error(`${label}.source must be a base64 image payload`);
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if (!source) {
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throw new Error(`${label}.source is missing`);
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}
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return {
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type: 'image_url',
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image_url: {
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url: `data:${source.media_type};base64,${source.data}`,
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},
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};
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if (source.type === 'url' && source.url) {
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return {
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type: 'image_url',
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image_url: { url: source.url },
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};
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}
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if (source.type === 'base64' && source.media_type && source.data) {
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return {
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type: 'image_url',
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image_url: {
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url: `data:${source.media_type};base64,${source.data}`,
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},
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};
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}
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throw new Error(`${label}.source must be a base64 or url image payload`);
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}
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function isImageBlock(block: AnthropicContentBlock): block is AnthropicImageBlock {
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@@ -234,30 +299,46 @@ function transformTools(value: unknown): ProxyOpenAIRequest['tools'] {
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(entry): entry is { name?: unknown; description?: unknown; input_schema?: unknown } =>
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typeof entry === 'object' && entry !== null
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)
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.map((entry) => ({
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type: 'function' as const,
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function: {
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name: typeof entry.name === 'string' ? entry.name : 'tool',
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...(typeof entry.description === 'string' ? { description: entry.description } : {}),
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parameters:
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typeof entry.input_schema === 'object' && entry.input_schema !== null
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? (entry.input_schema as Record<string, unknown>)
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: { type: 'object', properties: {} },
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},
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}));
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.map((entry) => {
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const rawSchema =
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typeof entry.input_schema === 'object' && entry.input_schema !== null
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? (entry.input_schema as Record<string, unknown>)
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: { type: 'object', properties: {} };
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return {
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type: 'function' as const,
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function: {
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name: typeof entry.name === 'string' ? entry.name : 'tool',
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...(typeof entry.description === 'string' ? { description: entry.description } : {}),
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parameters: normalizeSchemaForOpenAI(rawSchema),
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},
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};
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});
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return tools.length > 0 ? tools : undefined;
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}
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function mapThinkingToReasoning(
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thinking: AnthropicThinking | undefined
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thinking: AnthropicThinking | undefined,
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outputConfig: AnthropicOutputConfig | undefined
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): Pick<ProxyOpenAIRequest, 'reasoning' | 'reasoning_effort'> {
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if (!thinking || thinking.type === 'disabled') {
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return {};
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}
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if (thinking.type === 'adaptive') {
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const effort = toOpenAIEffort(resolveOutputConfigEffort(outputConfig) ?? 'high');
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return {
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reasoning_effort: effort,
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reasoning: {
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enabled: true,
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effort,
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},
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};
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}
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if (thinking.type !== 'enabled') {
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throw new Error('thinking.type must be "enabled" or "disabled"');
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return {};
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}
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const effort =
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@@ -274,6 +355,29 @@ function mapThinkingToReasoning(
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};
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}
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const VALID_EFFORT_LEVELS = new Set(['low', 'medium', 'high', 'max']);
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function resolveOutputConfigEffort(
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outputConfig: AnthropicOutputConfig | undefined
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): string | undefined {
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if (!outputConfig || typeof outputConfig.effort !== 'string') {
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return undefined;
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}
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const normalized = outputConfig.effort.trim().toLowerCase();
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return VALID_EFFORT_LEVELS.has(normalized) ? normalized : undefined;
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}
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/**
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* Map Anthropic effort levels to OpenAI-compatible reasoning_effort.
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* Anthropic's `max` has no standard OpenAI equivalent — most providers
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* only accept low/medium/high and reject unknown values with a 400.
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* Ported from openclaude's standardEffortToOpenAI() which maps max -> xhigh
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* for Codex; for generic OpenAI-compat providers we clamp to high.
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*/
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function toOpenAIEffort(effort: string): string {
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return effort === 'max' ? 'high' : effort;
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}
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function transformMessages(messagesValue: unknown): OpenAIMessage[] {
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if (!Array.isArray(messagesValue)) {
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throw new Error('messages must be an array');
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@@ -298,10 +402,65 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
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throw new Error(`messages[${messageIndex}].content must be a string or array`);
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}
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const userParts: OpenAIContentPart[] = [];
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if (role === 'user') {
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const userParts: OpenAIContentPart[] = [];
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let sawToolResult = false;
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content.forEach((block, blockIndex) => {
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const parsed = assertObject(
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block,
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`messages[${messageIndex}].content[${blockIndex}]`
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) as AnthropicContentBlock;
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if (parsed.type === 'thinking' || parsed.type === 'redacted_thinking') {
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return;
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}
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if (parsed.type === 'text') {
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const text = typeof parsed.text === 'string' ? parsed.text : '';
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userParts.push({ type: 'text', text });
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return;
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}
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if (isImageBlock(parsed)) {
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userParts.push(toImagePart(parsed, `messages[${messageIndex}].content[${blockIndex}]`));
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return;
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}
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if (isToolResultBlock(parsed)) {
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if (typeof parsed.tool_use_id !== 'string' || parsed.tool_use_id.trim().length === 0) {
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throw new Error(
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`messages[${messageIndex}].content[${blockIndex}].tool_use_id must be a non-empty string`
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);
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}
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sawToolResult = true;
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flushUserContent(translatedMessages, userParts);
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translatedMessages.push({
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role: 'tool',
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tool_call_id: parsed.tool_use_id,
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content: convertToolResultContent(parsed.content, parsed.is_error === true),
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});
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return;
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}
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if (isToolUseBlock(parsed)) {
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return;
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}
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throw new Error(
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`messages[${messageIndex}].content[${blockIndex}].type "${String(parsed.type)}" is not supported`
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);
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});
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if (userParts.length > 0 || !sawToolResult) {
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flushUserContent(translatedMessages, userParts);
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}
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return;
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}
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// Assistant role
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const assistantTextParts: string[] = [];
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const toolCalls: NonNullable<OpenAIMessage['tool_calls']> = [];
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let sawToolResult = false;
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content.forEach((block, blockIndex) => {
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const parsed = assertObject(
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@@ -309,32 +468,17 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
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`messages[${messageIndex}].content[${blockIndex}]`
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) as AnthropicContentBlock;
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if (parsed.type === 'text') {
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const text = typeof parsed.text === 'string' ? parsed.text : '';
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if (role === 'user') {
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userParts.push({ type: 'text', text });
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} else {
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assistantTextParts.push(text);
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}
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if (parsed.type === 'thinking' || parsed.type === 'redacted_thinking') {
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return;
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}
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if (isImageBlock(parsed)) {
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if (role !== 'user') {
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throw new Error(
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`messages[${messageIndex}].content[${blockIndex}] image requires user role`
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);
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}
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userParts.push(toImagePart(parsed, `messages[${messageIndex}].content[${blockIndex}]`));
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if (parsed.type === 'text') {
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const text = typeof parsed.text === 'string' ? parsed.text : '';
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assistantTextParts.push(text);
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return;
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}
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if (isToolUseBlock(parsed)) {
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if (role !== 'assistant') {
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throw new Error(
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`messages[${messageIndex}].content[${blockIndex}] tool_use requires assistant role`
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);
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}
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toolCalls.push({
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id:
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typeof parsed.id === 'string' && parsed.id.length > 0
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@@ -349,52 +493,61 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
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return;
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}
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if (isToolResultBlock(parsed)) {
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if (role !== 'user') {
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throw new Error(
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`messages[${messageIndex}].content[${blockIndex}] tool_result requires user role`
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);
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}
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if (typeof parsed.tool_use_id !== 'string' || parsed.tool_use_id.trim().length === 0) {
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throw new Error(
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`messages[${messageIndex}].content[${blockIndex}].tool_use_id must be a non-empty string`
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);
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}
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sawToolResult = true;
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flushUserContent(translatedMessages, userParts);
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translatedMessages.push({
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role: 'tool',
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tool_call_id: parsed.tool_use_id,
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content: toToolResultContent(
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parsed.content,
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`messages[${messageIndex}].content[${blockIndex}].content`
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),
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});
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if (isImageBlock(parsed) || isToolResultBlock(parsed)) {
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return;
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}
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throw new Error(
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`messages[${messageIndex}].content[${blockIndex}].type "${String(parsed.type)}" is not supported`
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);
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});
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if (role === 'assistant') {
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translatedMessages.push({
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role: 'assistant',
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content: assistantTextParts.join('\n'),
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tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
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});
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return;
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}
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if (userParts.length > 0 || !sawToolResult) {
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flushUserContent(translatedMessages, userParts);
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}
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translatedMessages.push({
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role: 'assistant',
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content: assistantTextParts.join('\n'),
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tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
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});
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});
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return translatedMessages;
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}
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/**
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* Coalesce consecutive messages of the same role.
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* OpenAI/vLLM/Ollama/Mistral require strict user<->assistant alternation.
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* Multiple consecutive tool messages are allowed (assistant -> tool* -> user).
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* Ported from openclaude's coalescing pass.
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*/
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function coalesceMessages(messages: OpenAIMessage[]): OpenAIMessage[] {
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const coalesced: OpenAIMessage[] = [];
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for (const msg of messages) {
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const prev = coalesced[coalesced.length - 1];
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if (prev && prev.role === msg.role && msg.role !== 'tool' && msg.role !== 'system') {
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const prevContent = prev.content;
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const curContent = msg.content;
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if (typeof prevContent === 'string' && typeof curContent === 'string') {
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prev.content = prevContent + (prevContent && curContent ? '\n' : '') + curContent;
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} else {
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const toArray = (
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c: string | OpenAIContentPart[] | null | undefined
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): OpenAIContentPart[] => {
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if (!c) return [];
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if (typeof c === 'string') return c ? [{ type: 'text', text: c }] : [];
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return c;
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};
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prev.content = [...toArray(prevContent), ...toArray(curContent)];
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}
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if (msg.tool_calls?.length) {
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prev.tool_calls = [...(prev.tool_calls ?? []), ...msg.tool_calls];
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}
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} else {
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coalesced.push({ ...msg });
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}
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}
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return coalesced;
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}
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export class ProxyRequestTransformer {
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transform(raw: unknown): ProxyOpenAIRequest {
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const source = assertObject(raw || {}, 'request') as AnthropicProxyRequestShape;
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@@ -414,14 +567,14 @@ export class ProxyRequestTransformer {
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? source.model.trim()
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: undefined,
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||||
stream: source.stream === true,
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messages: allMessages,
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messages: coalesceMessages(allMessages),
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max_tokens: asNumber(source.max_tokens),
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temperature: asNumber(source.temperature),
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top_p: asNumber(source.top_p),
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stop: asStringArray(source.stop_sequences),
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metadata: asMetadata(source.metadata),
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tools: transformTools(source.tools),
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...mapThinkingToReasoning(source.thinking),
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...mapThinkingToReasoning(source.thinking, source.output_config),
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};
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||||
}
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||||
}
|
||||
|
||||
@@ -0,0 +1,284 @@
|
||||
/**
|
||||
* Schema Sanitizer
|
||||
*
|
||||
* Strips JSON Schema keywords that OpenAI-compatible providers reject,
|
||||
* cleans enum/const values, and normalizes type fields.
|
||||
*/
|
||||
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||||
const OPENAI_INCOMPATIBLE_SCHEMA_KEYWORDS = new Set([
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'$comment',
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||||
'$schema',
|
||||
'default',
|
||||
'else',
|
||||
'examples',
|
||||
'format',
|
||||
'if',
|
||||
'maxLength',
|
||||
'maximum',
|
||||
'minLength',
|
||||
'minimum',
|
||||
'multipleOf',
|
||||
'pattern',
|
||||
'patternProperties',
|
||||
'propertyNames',
|
||||
'then',
|
||||
'unevaluatedProperties',
|
||||
]);
|
||||
|
||||
function isSchemaRecord(value: unknown): value is Record<string, unknown> {
|
||||
return value !== null && typeof value === 'object' && !Array.isArray(value);
|
||||
}
|
||||
|
||||
function stripSchemaKeywords(schema: unknown, keywords: Set<string>): unknown {
|
||||
if (Array.isArray(schema)) {
|
||||
return schema.map((item) => stripSchemaKeywords(item, keywords));
|
||||
}
|
||||
|
||||
if (!isSchemaRecord(schema)) {
|
||||
return schema;
|
||||
}
|
||||
|
||||
const result: Record<string, unknown> = {};
|
||||
for (const [key, value] of Object.entries(schema)) {
|
||||
if (key === 'properties' && isSchemaRecord(value)) {
|
||||
const sanitizedProps: Record<string, unknown> = {};
|
||||
for (const [propName, propSchema] of Object.entries(value)) {
|
||||
sanitizedProps[propName] = stripSchemaKeywords(propSchema, keywords);
|
||||
}
|
||||
result[key] = sanitizedProps;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (keywords.has(key)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
result[key] = stripSchemaKeywords(value, keywords);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
function deepEqualJsonValue(a: unknown, b: unknown): boolean {
|
||||
if (Object.is(a, b)) return true;
|
||||
if (typeof a !== typeof b) return false;
|
||||
|
||||
if (Array.isArray(a) && Array.isArray(b)) {
|
||||
return a.length === b.length && a.every((value, index) => deepEqualJsonValue(value, b[index]));
|
||||
}
|
||||
|
||||
if (isSchemaRecord(a) && isSchemaRecord(b)) {
|
||||
const aKeys = Object.keys(a);
|
||||
const bKeys = Object.keys(b);
|
||||
return (
|
||||
aKeys.length === bKeys.length &&
|
||||
aKeys.every((key) => key in b && deepEqualJsonValue(a[key], b[key]))
|
||||
);
|
||||
}
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
function matchesJsonSchemaType(type: string, value: unknown): boolean {
|
||||
switch (type) {
|
||||
case 'string':
|
||||
return typeof value === 'string';
|
||||
case 'number':
|
||||
return typeof value === 'number' && Number.isFinite(value);
|
||||
case 'integer':
|
||||
return typeof value === 'number' && Number.isInteger(value);
|
||||
case 'boolean':
|
||||
return typeof value === 'boolean';
|
||||
case 'object':
|
||||
return value !== null && typeof value === 'object' && !Array.isArray(value);
|
||||
case 'array':
|
||||
return Array.isArray(value);
|
||||
case 'null':
|
||||
return value === null;
|
||||
default:
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
function getJsonSchemaTypes(record: Record<string, unknown>): string[] {
|
||||
const raw = record.type;
|
||||
if (typeof raw === 'string') {
|
||||
return [raw];
|
||||
}
|
||||
if (Array.isArray(raw)) {
|
||||
return raw.filter((value): value is string => typeof value === 'string');
|
||||
}
|
||||
return [];
|
||||
}
|
||||
|
||||
function schemaAllowsValue(schema: Record<string, unknown>, value: unknown): boolean {
|
||||
if (Array.isArray(schema.anyOf)) {
|
||||
return schema.anyOf.some((item) =>
|
||||
schemaAllowsValue(sanitizeSchemaForOpenAICompat(item), value)
|
||||
);
|
||||
}
|
||||
|
||||
if (Array.isArray(schema.oneOf)) {
|
||||
return (
|
||||
schema.oneOf.filter((item) => schemaAllowsValue(sanitizeSchemaForOpenAICompat(item), value))
|
||||
.length === 1
|
||||
);
|
||||
}
|
||||
|
||||
if (Array.isArray(schema.allOf)) {
|
||||
return schema.allOf.every((item) =>
|
||||
schemaAllowsValue(sanitizeSchemaForOpenAICompat(item), value)
|
||||
);
|
||||
}
|
||||
|
||||
if ('const' in schema && !deepEqualJsonValue(schema.const, value)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
if (Array.isArray(schema.enum)) {
|
||||
if (!schema.enum.some((item) => deepEqualJsonValue(item, value))) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
const types = getJsonSchemaTypes(schema);
|
||||
if (types.length > 0 && !types.some((type) => matchesJsonSchemaType(type, value))) {
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
function sanitizeTypeField(record: Record<string, unknown>): void {
|
||||
const allowed = new Set(['string', 'number', 'integer', 'boolean', 'object', 'array', 'null']);
|
||||
|
||||
const raw = record.type;
|
||||
if (typeof raw === 'string') {
|
||||
if (!allowed.has(raw)) delete record.type;
|
||||
return;
|
||||
}
|
||||
|
||||
if (!Array.isArray(raw)) return;
|
||||
|
||||
const filtered = raw.filter(
|
||||
(value, index): value is string =>
|
||||
typeof value === 'string' && allowed.has(value) && raw.indexOf(value) === index
|
||||
);
|
||||
|
||||
if (filtered.length === 0) {
|
||||
delete record.type;
|
||||
} else if (filtered.length === 1) {
|
||||
record.type = filtered[0];
|
||||
} else {
|
||||
record.type = filtered;
|
||||
}
|
||||
}
|
||||
|
||||
export function sanitizeSchemaForOpenAICompat(schema: unknown): Record<string, unknown> {
|
||||
const stripped = stripSchemaKeywords(schema, OPENAI_INCOMPATIBLE_SCHEMA_KEYWORDS);
|
||||
if (!isSchemaRecord(stripped)) {
|
||||
return {};
|
||||
}
|
||||
|
||||
const record = { ...stripped };
|
||||
|
||||
sanitizeTypeField(record);
|
||||
|
||||
if (isSchemaRecord(record.properties)) {
|
||||
const sanitizedProps: Record<string, unknown> = {};
|
||||
for (const [key, value] of Object.entries(record.properties)) {
|
||||
sanitizedProps[key] = sanitizeSchemaForOpenAICompat(value);
|
||||
}
|
||||
record.properties = sanitizedProps;
|
||||
}
|
||||
|
||||
if ('items' in record) {
|
||||
if (Array.isArray(record.items)) {
|
||||
record.items = record.items.map((item) => sanitizeSchemaForOpenAICompat(item));
|
||||
} else {
|
||||
record.items = sanitizeSchemaForOpenAICompat(record.items);
|
||||
}
|
||||
}
|
||||
|
||||
for (const key of ['anyOf', 'oneOf', 'allOf'] as const) {
|
||||
if (Array.isArray(record[key])) {
|
||||
record[key] = (record[key] as unknown[]).map((item) => sanitizeSchemaForOpenAICompat(item));
|
||||
}
|
||||
}
|
||||
|
||||
const properties = isSchemaRecord(record.properties) ? record.properties : undefined;
|
||||
|
||||
if (Array.isArray(record.required) && properties) {
|
||||
record.required = record.required.filter(
|
||||
(value): value is string => typeof value === 'string' && value in properties
|
||||
);
|
||||
}
|
||||
|
||||
const schemaWithoutEnum = { ...record };
|
||||
delete schemaWithoutEnum.enum;
|
||||
|
||||
if (Array.isArray(record.enum)) {
|
||||
const filteredEnum = record.enum.filter((value) => schemaAllowsValue(schemaWithoutEnum, value));
|
||||
if (filteredEnum.length > 0) {
|
||||
record.enum = filteredEnum;
|
||||
} else {
|
||||
delete record.enum;
|
||||
}
|
||||
}
|
||||
|
||||
const schemaWithoutConst = { ...record };
|
||||
delete schemaWithoutConst.const;
|
||||
if ('const' in record && !schemaAllowsValue(schemaWithoutConst, record.const)) {
|
||||
delete record.const;
|
||||
}
|
||||
|
||||
return record;
|
||||
}
|
||||
|
||||
/**
|
||||
* Normalize a tool parameter schema for OpenAI-compatible providers.
|
||||
* Strips incompatible keywords and optionally enforces strict mode
|
||||
* (additionalProperties: false, required = all property keys).
|
||||
*/
|
||||
export function normalizeSchemaForOpenAI(
|
||||
schema: Record<string, unknown>,
|
||||
strict = true
|
||||
): Record<string, unknown> {
|
||||
const record = sanitizeSchemaForOpenAICompat(schema);
|
||||
|
||||
if (record.type === 'object' && record.properties) {
|
||||
const properties = record.properties as Record<string, Record<string, unknown>>;
|
||||
const existingRequired = Array.isArray(record.required) ? (record.required as string[]) : [];
|
||||
|
||||
const normalizedProps: Record<string, unknown> = {};
|
||||
for (const [key, value] of Object.entries(properties)) {
|
||||
normalizedProps[key] = normalizeSchemaForOpenAI(value as Record<string, unknown>, strict);
|
||||
}
|
||||
record.properties = normalizedProps;
|
||||
|
||||
record.required = existingRequired.filter((k) => k in normalizedProps);
|
||||
if (strict) {
|
||||
record.additionalProperties = false;
|
||||
}
|
||||
}
|
||||
|
||||
if ('items' in record) {
|
||||
if (Array.isArray(record.items)) {
|
||||
record.items = (record.items as unknown[]).map((item) =>
|
||||
normalizeSchemaForOpenAI(item as Record<string, unknown>, strict)
|
||||
);
|
||||
} else {
|
||||
record.items = normalizeSchemaForOpenAI(record.items as Record<string, unknown>, strict);
|
||||
}
|
||||
}
|
||||
|
||||
for (const key of ['anyOf', 'oneOf', 'allOf'] as const) {
|
||||
if (key in record && Array.isArray(record[key])) {
|
||||
record[key] = (record[key] as unknown[]).map((item) =>
|
||||
normalizeSchemaForOpenAI(item as Record<string, unknown>, strict)
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
return record;
|
||||
}
|
||||
Reference in New Issue
Block a user