Merge pull request #1037 from grndis/main

feat(proxy): enhance Anthropic-to-OpenAI message transformation
This commit is contained in:
Kai (Tam Nhu) Tran
2026-04-18 20:10:37 -04:00
committed by GitHub
4 changed files with 763 additions and 82 deletions
+369 -82
View File
@@ -1,5 +1,5 @@
interface AnthropicThinking {
type?: 'enabled' | 'disabled' | string;
type?: 'enabled' | 'disabled' | 'adaptive' | string;
budget_tokens?: number;
}
@@ -14,6 +14,7 @@ interface AnthropicImageBlock {
type?: string;
media_type?: string;
data?: string;
url?: string;
};
}
@@ -28,6 +29,7 @@ interface AnthropicToolResultBlock {
type: 'tool_result';
tool_use_id?: string;
content?: unknown;
is_error?: boolean;
}
type AnthropicContentBlock =
@@ -42,6 +44,16 @@ interface AnthropicMessage {
content?: string | AnthropicContentBlock[];
}
interface AnthropicOutputConfig {
effort?: 'low' | 'medium' | 'high' | 'max' | string;
}
interface AnthropicToolChoice {
type?: 'auto' | 'any' | 'tool' | 'none' | string;
name?: string;
disable_parallel_tool_use?: boolean;
}
interface AnthropicProxyRequestShape {
model?: unknown;
system?: unknown;
@@ -52,8 +64,10 @@ interface AnthropicProxyRequestShape {
stop_sequences?: unknown;
metadata?: unknown;
tools?: unknown;
tool_choice?: AnthropicToolChoice;
stream?: unknown;
thinking?: AnthropicThinking;
output_config?: AnthropicOutputConfig;
}
interface OpenAITextPart {
@@ -100,6 +114,17 @@ export interface ProxyOpenAIRequest {
parameters: Record<string, unknown>;
};
}>;
tool_choice?:
| 'auto'
| 'none'
| 'required'
| {
type: 'function';
function: {
name: string;
};
};
parallel_tool_calls?: boolean;
messages: OpenAIMessage[];
max_tokens?: number;
temperature?: number;
@@ -108,7 +133,6 @@ 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 +192,49 @@ 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, label: string): string {
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: ${text}` : text;
}
return safeJsonStringify(content, TOOL_RESULT_SERIALIZATION_FALLBACK);
const parts: string[] = [];
for (const [index, block] of content.entries()) {
const parsed = assertObject(block, `${label}[${index}]`);
if (parsed.type === 'text' && typeof parsed.text === 'string') {
parts.push(parsed.text);
continue;
}
if (parsed.type === 'image') {
throw new Error(`${label}[${index}].type "image" is not supported in tool_result content`);
}
if (typeof parsed.text === 'string') {
parts.push(parsed.text);
continue;
}
throw new Error(`${label}[${index}].type "${String(parsed.type)}" is not supported`);
}
const text = parts.join('\n');
if (!text) {
return isError ? 'Error:' : '';
}
return isError ? `Error: ${text}` : text;
}
function createFallbackToolId(messageIndex: number, blockIndex: number): string {
@@ -187,16 +243,27 @@ function createFallbackToolId(messageIndex: number, blockIndex: number): string
function toImagePart(block: AnthropicImageBlock, label: string): OpenAIImagePart {
const source = block.source;
if (!source || source.type !== 'base64' || !source.media_type || !source.data) {
throw new Error(`${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 +301,85 @@ 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: rawSchema,
},
};
});
return tools.length > 0 ? tools : undefined;
}
function transformToolChoice(
value: AnthropicToolChoice | undefined,
hasTools: boolean
): Pick<ProxyOpenAIRequest, 'tool_choice' | 'parallel_tool_calls'> {
if (!value) {
return hasTools ? { tool_choice: 'auto' } : {};
}
if (!hasTools) {
throw new Error('tool_choice requires tools');
}
const parallelToolCalls =
value.disable_parallel_tool_use === true ? { parallel_tool_calls: false } : {};
switch (value.type) {
case undefined:
case 'auto':
return { tool_choice: 'auto', ...parallelToolCalls };
case 'none':
return { tool_choice: 'none' };
case 'any':
return { tool_choice: 'required', ...parallelToolCalls };
case 'tool':
if (typeof value.name !== 'string' || value.name.trim().length === 0) {
throw new Error('tool_choice.name must be a non-empty string when type is "tool"');
}
return {
tool_choice: {
type: 'function',
function: { name: value.name.trim() },
},
...parallelToolCalls,
};
default:
throw new Error('tool_choice.type must be "auto", "any", "tool", or "none"');
}
}
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"');
throw new Error('thinking.type must be "enabled", "adaptive", or "disabled"');
}
const effort =
@@ -274,12 +396,37 @@ 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');
}
const translatedMessages: OpenAIMessage[] = [];
let pendingToolUseIds: Set<string> | null = null;
let hasPendingToolUseIds = false;
messagesValue.forEach((message, messageIndex) => {
const parsedMessage = assertObject(message, `messages[${messageIndex}]`) as AnthropicMessage;
@@ -288,8 +435,19 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
throw new Error(`messages[${messageIndex}].role must be "user" or "assistant"`);
}
if (pendingToolUseIds && pendingToolUseIds.size > 0 && role !== 'user') {
throw new Error(
`messages[${messageIndex}].role must be "user" with tool_result blocks after assistant tool_use`
);
}
const content = parsedMessage.content;
if (typeof content === 'string') {
if (pendingToolUseIds && pendingToolUseIds.size > 0) {
throw new Error(
`messages[${messageIndex}].content must start with tool_result blocks for pending tool_use ids`
);
}
translatedMessages.push({ role, content });
return;
}
@@ -298,10 +456,119 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
throw new Error(`messages[${messageIndex}].content must be a string or array`);
}
const userParts: OpenAIContentPart[] = [];
if (role === 'user') {
const userParts: OpenAIContentPart[] = [];
let sawToolResult = false;
const resolvedToolUseIds = new Set<string>();
content.forEach((block, blockIndex) => {
const parsed = assertObject(
block,
`messages[${messageIndex}].content[${blockIndex}]`
) as AnthropicContentBlock;
if (parsed.type === 'thinking' || parsed.type === 'redacted_thinking') {
return;
}
if (parsed.type === 'text') {
if (sawToolResult) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] text is not allowed after tool_result blocks`
);
}
const text = typeof parsed.text === 'string' ? parsed.text : '';
userParts.push({ type: 'text', text });
return;
}
if (isImageBlock(parsed)) {
if (sawToolResult) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] image is not allowed after tool_result blocks`
);
}
userParts.push(toImagePart(parsed, `messages[${messageIndex}].content[${blockIndex}]`));
return;
}
if (isToolResultBlock(parsed)) {
if (!pendingToolUseIds || pendingToolUseIds.size === 0) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] tool_result requires a preceding assistant tool_use`
);
}
if (userParts.length > 0) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] tool_result blocks must come before other user content`
);
}
if (typeof parsed.tool_use_id !== 'string' || parsed.tool_use_id.trim().length === 0) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].tool_use_id must be a non-empty string`
);
}
if (!pendingToolUseIds.has(parsed.tool_use_id)) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].tool_use_id "${parsed.tool_use_id}" does not match a pending tool_use`
);
}
if (resolvedToolUseIds.has(parsed.tool_use_id)) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].tool_use_id "${parsed.tool_use_id}" is duplicated`
);
}
sawToolResult = true;
resolvedToolUseIds.add(parsed.tool_use_id);
translatedMessages.push({
role: 'tool',
tool_call_id: parsed.tool_use_id,
content: convertToolResultContent(
parsed.content,
parsed.is_error === true,
`messages[${messageIndex}].content[${blockIndex}].content`
),
});
return;
}
if (isToolUseBlock(parsed)) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] tool_use requires assistant role`
);
}
throw new Error(
`messages[${messageIndex}].content[${blockIndex}].type "${String(parsed.type)}" is not supported`
);
});
if (sawToolResult) {
if (resolvedToolUseIds.size !== pendingToolUseIds?.size) {
throw new Error(
`messages[${messageIndex}].content must provide tool_result blocks for all pending tool_use ids`
);
}
pendingToolUseIds = null;
hasPendingToolUseIds = false;
return;
}
if (pendingToolUseIds && pendingToolUseIds.size > 0) {
throw new Error(
`messages[${messageIndex}].content must start with tool_result blocks for pending tool_use ids`
);
}
if (userParts.length > 0) {
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 +576,17 @@ 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
@@ -349,28 +601,16 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
return;
}
if (isImageBlock(parsed)) {
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] image requires user role`
);
}
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`
),
});
return;
throw new Error(
`messages[${messageIndex}].content[${blockIndex}] tool_result requires user role`
);
}
throw new Error(
@@ -378,26 +618,72 @@ function transformMessages(messagesValue: unknown): OpenAIMessage[] {
);
});
if (role === 'assistant') {
translatedMessages.push({
role: 'assistant',
content: assistantTextParts.join('\n'),
tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
});
if (assistantTextParts.length === 0 && toolCalls.length === 0) {
return;
}
if (userParts.length > 0 || !sawToolResult) {
flushUserContent(translatedMessages, userParts);
}
pendingToolUseIds =
toolCalls.length > 0 ? new Set(toolCalls.map((toolCall) => toolCall.id)) : null;
hasPendingToolUseIds = toolCalls.length > 0;
translatedMessages.push({
role: 'assistant',
content: assistantTextParts.join('\n'),
tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
});
});
if (hasPendingToolUseIds) {
throw new Error('messages must provide tool_result blocks for the latest assistant tool_use');
}
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;
const tools = transformTools(source.tools);
const messages = transformMessages(source.messages);
const system = source.system;
const allMessages =
@@ -414,14 +700,15 @@ 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),
tools,
...transformToolChoice(source.tool_choice, tools !== undefined),
...mapThinkingToReasoning(source.thinking, source.output_config),
};
}
}
@@ -116,13 +116,63 @@ describe('openai proxy messages endpoint', () => {
const parsedUpstream = upstreamBody as {
messages?: Array<{ role: string; content: string }>;
tool_choice?: unknown;
tools?: Array<{ type: string; function: { name: string } }>;
};
expect(parsedUpstream.messages?.[0]).toEqual({ role: 'user', content: 'Find docs' });
expect(parsedUpstream.tool_choice).toBe('auto');
expect(parsedUpstream.tools?.[0]?.type).toBe('function');
expect(parsedUpstream.tools?.[0]?.function.name).toBe('search');
});
it('preserves tool schemas and forwards explicit tool_choice semantics upstream', async () => {
const response = await requestProxy({
model: 'hf-model',
messages: [{ role: 'user', content: [{ type: 'text', text: 'Search docs' }] }],
tools: [
{
name: 'search',
description: 'Search docs',
input_schema: {
type: 'object',
properties: {
q: { type: 'string', pattern: '^[a-z]+$' },
},
required: ['q'],
additionalProperties: true,
},
},
],
tool_choice: {
type: 'tool',
name: 'search',
disable_parallel_tool_use: true,
},
});
expect(response.status).toBe(200);
const parsedUpstream = upstreamBody as {
tool_choice?: unknown;
parallel_tool_calls?: boolean;
tools?: Array<{ type: string; function: { parameters: Record<string, unknown> } }>;
};
expect(parsedUpstream.tool_choice).toEqual({
type: 'function',
function: { name: 'search' },
});
expect(parsedUpstream.parallel_tool_calls).toBe(false);
expect(parsedUpstream.tools?.[0]?.function.parameters).toEqual({
type: 'object',
properties: {
q: { type: 'string', pattern: '^[a-z]+$' },
},
required: ['q'],
additionalProperties: true,
});
});
it('falls back to Anthropic JSON for non-streaming requests', async () => {
const response = await requestProxy({
model: 'hf-model',
@@ -155,6 +205,24 @@ describe('openai proxy messages endpoint', () => {
expect(body.error?.message).toContain('Invalid JSON');
});
it('returns invalid_request_error for orphan tool_result blocks', async () => {
const response = await requestProxy({
model: 'hf-model',
messages: [
{
role: 'user',
content: [{ type: 'tool_result', tool_use_id: 'toolu_orphan', content: 'orphan' }],
},
],
});
const body = (await response.json()) as { error?: { type?: string; message?: string } };
expect(response.status).toBe(400);
expect(body.error?.type).toBe('invalid_request_error');
expect(body.error?.message).toContain('tool_result requires a preceding assistant tool_use');
});
it('rejects requests without the local proxy auth token', async () => {
const response = await fetch(`http://127.0.0.1:${proxyPort}/v1/messages`, {
method: 'POST',
@@ -214,4 +214,75 @@ describe('openai proxy request routing', () => {
expect(hits).toEqual(['thinker']);
expect(bodies[0]?.body).toMatchObject({ model: 'deepseek-reasoner' });
});
it('routes adaptive thinking requests through the configured think scenario', async () => {
const primaryPort = await getPort();
const thinkPort = await getPort();
const hits: string[] = [];
const bodies: Array<{ label: string; body: unknown }> = [];
await startMockUpstream(primaryPort, 'primary', hits, bodies);
await startMockUpstream(thinkPort, 'thinker', hits, bodies);
const primarySettings = writeSettings('hf', {
ANTHROPIC_BASE_URL: `http://127.0.0.1:${primaryPort}`,
ANTHROPIC_AUTH_TOKEN: 'hf_token',
ANTHROPIC_MODEL: 'hf-default',
CCS_DROID_PROVIDER: 'generic-chat-completion-api',
});
const thinkSettings = writeSettings('thinker', {
ANTHROPIC_BASE_URL: `http://127.0.0.1:${thinkPort}`,
ANTHROPIC_AUTH_TOKEN: 'think_token',
ANTHROPIC_MODEL: 'deepseek-reasoner',
CCS_DROID_PROVIDER: 'generic-chat-completion-api',
});
fs.writeFileSync(
path.join(tempDir, '.ccs', 'config.json'),
JSON.stringify(
{
profiles: { hf: primarySettings, thinker: thinkSettings },
proxy: {
routing: {
think: 'thinker:deepseek-reasoner',
},
},
},
null,
2
),
'utf8'
);
const profile: OpenAICompatProfileConfig = {
profileName: 'hf',
settingsPath: primarySettings,
baseUrl: `http://127.0.0.1:${primaryPort}`,
apiKey: 'hf_token',
provider: 'generic-chat-completion-api',
model: 'hf-default',
};
proxyServer = startOpenAICompatProxyServer({
profile,
port: proxyPort,
authToken: 'test-proxy-token',
});
const response = await requestProxy({
model: 'hf-default',
thinking: { type: 'adaptive' },
output_config: { effort: 'max' },
messages: [{ role: 'user', content: 'think adaptively' }],
});
expect(response.status).toBe(200);
expect(await response.json()).toMatchObject({
content: [{ type: 'text', text: 'Reply from thinker' }],
});
expect(hits).toEqual(['thinker']);
expect(bodies[0]?.body).toMatchObject({
model: 'deepseek-reasoner',
reasoning_effort: 'high',
reasoning: { enabled: true, effort: 'high' },
});
});
});
@@ -0,0 +1,255 @@
import { describe, expect, it } from 'bun:test';
import { ProxyRequestTransformer } from '../../../../src/proxy/transformers/request-transformer';
describe('ProxyRequestTransformer regressions', () => {
it('drops assistant messages that only contain stripped thinking blocks', () => {
const result = new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [
{ type: 'thinking', text: 'internal' },
{ type: 'redacted_thinking', text: 'hidden' },
],
},
],
});
expect(result.messages).toEqual([]);
});
it('maps adaptive thinking through output_config effort for OpenAI-compatible upstreams', () => {
const result = new ProxyRequestTransformer().transform({
messages: [{ role: 'user', content: 'hello' }],
thinking: { type: 'adaptive' },
output_config: { effort: 'max' },
});
expect(result.reasoning_effort).toBe('high');
expect(result.reasoning).toEqual({ enabled: true, effort: 'high' });
});
it('rejects unsupported thinking types instead of silently dropping them', () => {
expect(() =>
new ProxyRequestTransformer().transform({
messages: [{ role: 'user', content: 'hello' }],
thinking: { type: 'typo' },
})
).toThrow('thinking.type must be "enabled", "adaptive", or "disabled"');
});
it('keeps Anthropic role validation for tool_use, image, and tool_result blocks', () => {
expect(() =>
new ProxyRequestTransformer().transform({
messages: [{ role: 'user', content: [{ type: 'tool_use', name: 'search', input: {} }] }],
})
).toThrow('tool_use requires assistant role');
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [
{
type: 'image',
source: { type: 'url', url: 'https://example.com/image.png' },
},
],
},
],
})
).toThrow('image requires user role');
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [{ type: 'tool_result', tool_use_id: 'toolu_1', content: 'nope' }],
},
],
})
).toThrow('tool_result requires user role');
});
it('rejects orphaned, incomplete, or mixed-order tool_result blocks', () => {
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'user',
content: [{ type: 'tool_result', tool_use_id: 'toolu_1', content: 'orphan' }],
},
],
})
).toThrow('tool_result requires a preceding assistant tool_use');
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [
{ type: 'tool_use', id: 'toolu_1', name: 'search', input: { q: 'docs' } },
{ type: 'tool_use', id: 'toolu_2', name: 'open', input: { url: 'https://example.com' } },
],
},
{
role: 'user',
content: [{ type: 'tool_result', tool_use_id: 'toolu_1', content: 'partial' }],
},
],
})
).toThrow('must provide tool_result blocks for all pending tool_use ids');
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [{ type: 'tool_use', id: 'toolu_1', name: 'vision', input: { detail: 'high' } }],
},
{
role: 'user',
content: [
{ type: 'text', text: 'Here you go' },
{ type: 'tool_result', tool_use_id: 'toolu_1', content: 'result' },
],
},
],
})
).toThrow('tool_result blocks must come before other user content');
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [{ type: 'tool_use', id: 'toolu_1', name: 'vision', input: { detail: 'high' } }],
},
{
role: 'user',
content: 'plain follow-up',
},
],
})
).toThrow('must start with tool_result blocks for pending tool_use ids');
});
it('rejects tool_result content that cannot be represented as OpenAI tool text', () => {
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [{ type: 'tool_use', id: 'toolu_1', name: 'vision', input: { detail: 'high' } }],
},
{
role: 'user',
content: [
{
type: 'tool_result',
tool_use_id: 'toolu_1',
content: [{ type: 'image', source: { type: 'url', url: 'https://example.com/error.png' } }],
},
],
},
],
})
).toThrow('type "image" is not supported in tool_result content');
});
it('rejects unsupported assistant blocks instead of silently dropping them', () => {
expect(() =>
new ProxyRequestTransformer().transform({
messages: [
{
role: 'assistant',
content: [{ type: 'server_tool_use', id: 'srv_1' }],
},
],
})
).toThrow('type "server_tool_use" is not supported');
});
it('translates url images and tool_choice while coalescing repeated turns', () => {
const result = new ProxyRequestTransformer().transform({
tool_choice: {
type: 'tool',
name: 'vision',
disable_parallel_tool_use: true,
},
tools: [{ name: 'vision', description: 'Inspect image', input_schema: { type: 'object' } }],
messages: [
{
role: 'user',
content: [{ type: 'image', source: { type: 'url', url: 'https://example.com/cat.png' } }],
},
{ role: 'user', content: [{ type: 'text', text: 'Describe it' }] },
{
role: 'assistant',
content: [{ type: 'text', text: 'Checking' }],
},
{
role: 'assistant',
content: [{ type: 'tool_use', id: 'toolu_1', name: 'vision', input: { detail: 'high' } }],
},
{
role: 'user',
content: [
{
type: 'tool_result',
tool_use_id: 'toolu_1',
is_error: true,
content: [{ type: 'text', text: 'fetch failed' }],
},
],
},
],
});
expect(result.tool_choice).toEqual({
type: 'function',
function: { name: 'vision' },
});
expect(result.parallel_tool_calls).toBe(false);
expect(result.messages[0]).toEqual({
role: 'user',
content: [
{ type: 'image_url', image_url: { url: 'https://example.com/cat.png' } },
{ type: 'text', text: 'Describe it' },
],
});
expect(result.messages[1]).toEqual({
role: 'assistant',
content: 'Checking',
tool_calls: [
{
id: 'toolu_1',
type: 'function',
function: {
name: 'vision',
arguments: '{"detail":"high"}',
},
},
],
});
expect(result.messages[2]).toEqual({
role: 'tool',
tool_call_id: 'toolu_1',
content: 'Error: fetch failed',
});
});
it('defaults tools to auto tool_choice when none is specified', () => {
const result = new ProxyRequestTransformer().transform({
messages: [{ role: 'user', content: 'hello' }],
tools: [{ name: 'search', description: 'Search docs', input_schema: { type: 'object' } }],
});
expect(result.tool_choice).toBe('auto');
});
});