mirror of
https://github.com/tiennm99/ccs.git
synced 2026-07-16 10:16:49 +00:00
Merge pull request #1037 from grndis/main
feat(proxy): enhance Anthropic-to-OpenAI message transformation
This commit is contained in:
@@ -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');
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user