feat(proxy): enhance Anthropic-to-OpenAI message transformation and schema sanitization

This commit is contained in:
Grandis SYF
2026-04-18 13:49:20 +07:00
parent eaa37c749e
commit 2672e35362
2 changed files with 525 additions and 88 deletions
+241 -88
View File
@@ -1,5 +1,7 @@
import { normalizeSchemaForOpenAI } from '../../utils/schema-sanitizer';
interface AnthropicThinking {
type?: 'enabled' | 'disabled' | string;
type?: 'enabled' | 'disabled' | 'adaptive' | string;
budget_tokens?: number;
}
@@ -14,6 +16,7 @@ interface AnthropicImageBlock {
type?: string;
media_type?: string;
data?: string;
url?: string;
};
}
@@ -28,6 +31,7 @@ interface AnthropicToolResultBlock {
type: 'tool_result';
tool_use_id?: string;
content?: unknown;
is_error?: boolean;
}
type AnthropicContentBlock =
@@ -42,6 +46,10 @@ interface AnthropicMessage {
content?: string | AnthropicContentBlock[];
}
interface AnthropicOutputConfig {
effort?: 'low' | 'medium' | 'high' | 'max' | string;
}
interface AnthropicProxyRequestShape {
model?: unknown;
system?: unknown;
@@ -54,6 +62,7 @@ interface AnthropicProxyRequestShape {
tools?: unknown;
stream?: unknown;
thinking?: AnthropicThinking;
output_config?: AnthropicOutputConfig;
}
interface OpenAITextPart {
@@ -108,7 +117,6 @@ export interface ProxyOpenAIRequest {
metadata?: Record<string, unknown>;
}
const TOOL_RESULT_SERIALIZATION_FALLBACK = '[unserializable content]';
const TOOL_USE_ARGUMENTS_FALLBACK = '{}';
function assertObject(value: unknown, label: string): Record<string, unknown> {
@@ -168,17 +176,63 @@ function flattenTextContent(content: unknown, label: string): string {
.join('\n');
}
function toToolResultContent(content: unknown, label: string): string {
/**
* Convert tool_result content to OpenAI-compatible format.
* Handles strings, arrays with text/image blocks, and error prefixing.
* Ported from openclaude's convertToolResultContent.
*/
function convertToolResultContent(
content: unknown,
isError: boolean
): string | OpenAIContentPart[] {
if (content === undefined) {
return '';
}
if (typeof content === 'string') {
return content;
return isError ? `Error: ${content}` : content;
}
if (Array.isArray(content)) {
return flattenTextContent(content, label);
if (!Array.isArray(content)) {
const text = safeJsonStringify(content, '[unserializable content]');
return isError ? `Error: ${text}` : text;
}
return safeJsonStringify(content, TOOL_RESULT_SERIALIZATION_FALLBACK);
const parts: OpenAIContentPart[] = [];
for (const block of content) {
if (block?.type === 'text' && typeof block.text === 'string') {
parts.push({ type: 'text', text: block.text });
continue;
}
if (block?.type === 'image') {
const source = block.source;
if (source?.type === 'url' && source.url) {
parts.push({ type: 'image_url', image_url: { url: source.url } });
} else if (source?.type === 'base64' && source.media_type && source.data) {
parts.push({
type: 'image_url',
image_url: { url: `data:${source.media_type};base64,${source.data}` },
});
}
continue;
}
if (typeof block?.text === 'string') {
parts.push({ type: 'text', text: block.text });
}
}
if (parts.length === 0) return '';
if (parts.length === 1 && parts[0].type === 'text') {
const text = (parts[0] as OpenAITextPart).text;
return isError ? `Error: ${text}` : text;
}
if (isError && parts[0]?.type === 'text') {
parts[0] = { ...parts[0], text: `Error: ${(parts[0] as OpenAITextPart).text}` };
} else if (isError) {
parts.unshift({ type: 'text', text: 'Error:' });
}
return parts;
}
function createFallbackToolId(messageIndex: number, blockIndex: number): string {
@@ -187,16 +241,27 @@ function createFallbackToolId(messageIndex: number, blockIndex: number): string
function toImagePart(block: AnthropicImageBlock, label: string): OpenAIImagePart {
const source = block.source;
if (!source || source.type !== 'base64' || !source.media_type || !source.data) {
throw new Error(`${label}.source must be a base64 image payload`);
if (!source) {
throw new Error(`${label}.source is missing`);
}
return {
type: 'image_url',
image_url: {
url: `data:${source.media_type};base64,${source.data}`,
},
};
if (source.type === 'url' && source.url) {
return {
type: 'image_url',
image_url: { url: source.url },
};
}
if (source.type === 'base64' && source.media_type && source.data) {
return {
type: 'image_url',
image_url: {
url: `data:${source.media_type};base64,${source.data}`,
},
};
}
throw new Error(`${label}.source must be a base64 or url image payload`);
}
function isImageBlock(block: AnthropicContentBlock): block is AnthropicImageBlock {
@@ -234,30 +299,46 @@ function transformTools(value: unknown): ProxyOpenAIRequest['tools'] {
(entry): entry is { name?: unknown; description?: unknown; input_schema?: unknown } =>
typeof entry === 'object' && entry !== null
)
.map((entry) => ({
type: 'function' as const,
function: {
name: typeof entry.name === 'string' ? entry.name : 'tool',
...(typeof entry.description === 'string' ? { description: entry.description } : {}),
parameters:
typeof entry.input_schema === 'object' && entry.input_schema !== null
? (entry.input_schema as Record<string, unknown>)
: { type: 'object', properties: {} },
},
}));
.map((entry) => {
const rawSchema =
typeof entry.input_schema === 'object' && entry.input_schema !== null
? (entry.input_schema as Record<string, unknown>)
: { type: 'object', properties: {} };
return {
type: 'function' as const,
function: {
name: typeof entry.name === 'string' ? entry.name : 'tool',
...(typeof entry.description === 'string' ? { description: entry.description } : {}),
parameters: normalizeSchemaForOpenAI(rawSchema),
},
};
});
return tools.length > 0 ? tools : undefined;
}
function mapThinkingToReasoning(
thinking: AnthropicThinking | undefined
thinking: AnthropicThinking | undefined,
outputConfig: AnthropicOutputConfig | undefined
): Pick<ProxyOpenAIRequest, 'reasoning' | 'reasoning_effort'> {
if (!thinking || thinking.type === 'disabled') {
return {};
}
if (thinking.type === 'adaptive') {
const effort = toOpenAIEffort(resolveOutputConfigEffort(outputConfig) ?? 'high');
return {
reasoning_effort: effort,
reasoning: {
enabled: true,
effort,
},
};
}
if (thinking.type !== 'enabled') {
throw new Error('thinking.type must be "enabled" or "disabled"');
return {};
}
const effort =
@@ -274,6 +355,29 @@ function mapThinkingToReasoning(
};
}
const VALID_EFFORT_LEVELS = new Set(['low', 'medium', 'high', 'max']);
function resolveOutputConfigEffort(
outputConfig: AnthropicOutputConfig | undefined
): string | undefined {
if (!outputConfig || typeof outputConfig.effort !== 'string') {
return undefined;
}
const normalized = outputConfig.effort.trim().toLowerCase();
return VALID_EFFORT_LEVELS.has(normalized) ? normalized : undefined;
}
/**
* Map Anthropic effort levels to OpenAI-compatible reasoning_effort.
* Anthropic's `max` has no standard OpenAI equivalent — most providers
* only accept low/medium/high and reject unknown values with a 400.
* Ported from openclaude's standardEffortToOpenAI() which maps max -> xhigh
* for Codex; for generic OpenAI-compat providers we clamp to high.
*/
function toOpenAIEffort(effort: string): string {
return effort === 'max' ? 'high' : effort;
}
function transformMessages(messagesValue: unknown): OpenAIMessage[] {
if (!Array.isArray(messagesValue)) {
throw new Error('messages must be an array');
@@ -298,10 +402,65 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
throw new Error(`messages[${messageIndex}].content must be a string or array`);
}
const userParts: OpenAIContentPart[] = [];
if (role === 'user') {
const userParts: OpenAIContentPart[] = [];
let sawToolResult = false;
content.forEach((block, blockIndex) => {
const parsed = assertObject(
block,
`messages[${messageIndex}].content[${blockIndex}]`
) as AnthropicContentBlock;
if (parsed.type === 'thinking' || parsed.type === 'redacted_thinking') {
return;
}
if (parsed.type === 'text') {
const text = typeof parsed.text === 'string' ? parsed.text : '';
userParts.push({ type: 'text', text });
return;
}
if (isImageBlock(parsed)) {
userParts.push(toImagePart(parsed, `messages[${messageIndex}].content[${blockIndex}]`));
return;
}
if (isToolResultBlock(parsed)) {
if (typeof parsed.tool_use_id !== 'string' || parsed.tool_use_id.trim().length === 0) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].tool_use_id must be a non-empty string`
);
}
sawToolResult = true;
flushUserContent(translatedMessages, userParts);
translatedMessages.push({
role: 'tool',
tool_call_id: parsed.tool_use_id,
content: convertToolResultContent(parsed.content, parsed.is_error === true),
});
return;
}
if (isToolUseBlock(parsed)) {
return;
}
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].type "${String(parsed.type)}" is not supported`
);
});
if (userParts.length > 0 || !sawToolResult) {
flushUserContent(translatedMessages, userParts);
}
return;
}
// Assistant role
const assistantTextParts: string[] = [];
const toolCalls: NonNullable<OpenAIMessage['tool_calls']> = [];
let sawToolResult = false;
content.forEach((block, blockIndex) => {
const parsed = assertObject(
@@ -309,32 +468,17 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
`messages[${messageIndex}].content[${blockIndex}]`
) as AnthropicContentBlock;
if (parsed.type === 'text') {
const text = typeof parsed.text === 'string' ? parsed.text : '';
if (role === 'user') {
userParts.push({ type: 'text', text });
} else {
assistantTextParts.push(text);
}
if (parsed.type === 'thinking' || parsed.type === 'redacted_thinking') {
return;
}
if (isImageBlock(parsed)) {
if (role !== 'user') {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] image requires user role`
);
}
userParts.push(toImagePart(parsed, `messages[${messageIndex}].content[${blockIndex}]`));
if (parsed.type === 'text') {
const text = typeof parsed.text === 'string' ? parsed.text : '';
assistantTextParts.push(text);
return;
}
if (isToolUseBlock(parsed)) {
if (role !== 'assistant') {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] tool_use requires assistant role`
);
}
toolCalls.push({
id:
typeof parsed.id === 'string' && parsed.id.length > 0
@@ -349,52 +493,61 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
return;
}
if (isToolResultBlock(parsed)) {
if (role !== 'user') {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] tool_result requires user role`
);
}
if (typeof parsed.tool_use_id !== 'string' || parsed.tool_use_id.trim().length === 0) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].tool_use_id must be a non-empty string`
);
}
sawToolResult = true;
flushUserContent(translatedMessages, userParts);
translatedMessages.push({
role: 'tool',
tool_call_id: parsed.tool_use_id,
content: toToolResultContent(
parsed.content,
`messages[${messageIndex}].content[${blockIndex}].content`
),
});
if (isImageBlock(parsed) || isToolResultBlock(parsed)) {
return;
}
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].type "${String(parsed.type)}" is not supported`
);
});
if (role === 'assistant') {
translatedMessages.push({
role: 'assistant',
content: assistantTextParts.join('\n'),
tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
});
return;
}
if (userParts.length > 0 || !sawToolResult) {
flushUserContent(translatedMessages, userParts);
}
translatedMessages.push({
role: 'assistant',
content: assistantTextParts.join('\n'),
tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
});
});
return translatedMessages;
}
/**
* Coalesce consecutive messages of the same role.
* OpenAI/vLLM/Ollama/Mistral require strict user<->assistant alternation.
* Multiple consecutive tool messages are allowed (assistant -> tool* -> user).
* Ported from openclaude's coalescing pass.
*/
function coalesceMessages(messages: OpenAIMessage[]): OpenAIMessage[] {
const coalesced: OpenAIMessage[] = [];
for (const msg of messages) {
const prev = coalesced[coalesced.length - 1];
if (prev && prev.role === msg.role && msg.role !== 'tool' && msg.role !== 'system') {
const prevContent = prev.content;
const curContent = msg.content;
if (typeof prevContent === 'string' && typeof curContent === 'string') {
prev.content = prevContent + (prevContent && curContent ? '\n' : '') + curContent;
} else {
const toArray = (
c: string | OpenAIContentPart[] | null | undefined
): OpenAIContentPart[] => {
if (!c) return [];
if (typeof c === 'string') return c ? [{ type: 'text', text: c }] : [];
return c;
};
prev.content = [...toArray(prevContent), ...toArray(curContent)];
}
if (msg.tool_calls?.length) {
prev.tool_calls = [...(prev.tool_calls ?? []), ...msg.tool_calls];
}
} else {
coalesced.push({ ...msg });
}
}
return coalesced;
}
export class ProxyRequestTransformer {
transform(raw: unknown): ProxyOpenAIRequest {
const source = assertObject(raw || {}, 'request') as AnthropicProxyRequestShape;
@@ -414,14 +567,14 @@ export class ProxyRequestTransformer {
? source.model.trim()
: undefined,
stream: source.stream === true,
messages: allMessages,
messages: coalesceMessages(allMessages),
max_tokens: asNumber(source.max_tokens),
temperature: asNumber(source.temperature),
top_p: asNumber(source.top_p),
stop: asStringArray(source.stop_sequences),
metadata: asMetadata(source.metadata),
tools: transformTools(source.tools),
...mapThinkingToReasoning(source.thinking),
...mapThinkingToReasoning(source.thinking, source.output_config),
};
}
}
+284
View File
@@ -0,0 +1,284 @@
/**
* Schema Sanitizer
*
* Strips JSON Schema keywords that OpenAI-compatible providers reject,
* cleans enum/const values, and normalizes type fields.
*/
const OPENAI_INCOMPATIBLE_SCHEMA_KEYWORDS = new Set([
'$comment',
'$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;
}