File size: 3,415 Bytes
1f21206 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | /**
* Response transformation: OpenAI Chat Completions → Anthropic Messages
* Derived from cc-switch (https://github.com/farion1231/cc-switch)
* Original work by Jason Young, MIT License
*/
import type {
OpenAIChatResponse,
AnthropicResponse,
AnthropicContentBlock,
} from './types.js'
import { parseOpenAIToolArguments } from './toolArguments.js'
/**
* Convert OpenAI Chat Completions response to Anthropic Messages response.
*/
export function openaiChatToAnthropic(response: OpenAIChatResponse, model: string): AnthropicResponse {
const choice = response.choices?.[0]
if (!choice) {
return createEmptyResponse(response, model)
}
const content: AnthropicContentBlock[] = []
// Convert reasoning/thinking content (all provider formats)
const msg = choice.message as Record<string, unknown>
// Format 1: reasoning_content (DeepSeek, OpenRouter, XAI, Perplexity)
if (typeof msg.reasoning_content === 'string' && msg.reasoning_content) {
content.push({ type: 'thinking', thinking: msg.reasoning_content })
}
// Format 2: reasoning (GLM-5, Cerebras, Groq)
else if (typeof msg.reasoning === 'string' && msg.reasoning) {
content.push({ type: 'thinking', thinking: msg.reasoning })
}
// Format 3: thinking_blocks (OpenAI o-series)
else if (Array.isArray(msg.thinking_blocks)) {
for (const tb of msg.thinking_blocks as Array<Record<string, unknown>>) {
if (tb.type === 'thinking' && typeof tb.thinking === 'string') {
content.push({ type: 'thinking', thinking: tb.thinking, signature: tb.signature as string | undefined })
}
}
}
// Convert text content
if (choice.message.content) {
content.push({ type: 'text', text: choice.message.content })
}
// Convert tool calls
if (choice.message.tool_calls) {
for (const tc of choice.message.tool_calls) {
content.push({
type: 'tool_use',
id: tc.id,
name: tc.function.name,
input: parseOpenAIToolArguments(tc.function.arguments),
})
}
}
// If no content at all, add empty text
if (content.length === 0) {
content.push({ type: 'text', text: '' })
}
return {
id: response.id || `msg_${Date.now()}`,
type: 'message',
role: 'assistant',
content,
model: response.model || model,
stop_reason: mapFinishReason(choice.finish_reason),
stop_sequence: null,
usage: mapUsage(response.usage),
}
}
function mapFinishReason(reason: string | null): string {
switch (reason) {
case 'stop': return 'end_turn'
case 'tool_calls': return 'tool_use'
case 'length': return 'max_tokens'
case 'content_filter': return 'end_turn'
default: return 'end_turn'
}
}
function mapUsage(usage?: OpenAIChatResponse['usage']): AnthropicResponse['usage'] {
if (!usage) {
return { input_tokens: 0, output_tokens: 0 }
}
return {
input_tokens: usage.prompt_tokens || 0,
output_tokens: usage.completion_tokens || 0,
cache_read_input_tokens: usage.prompt_tokens_details?.cached_tokens || 0,
}
}
function createEmptyResponse(response: OpenAIChatResponse, model: string): AnthropicResponse {
return {
id: response.id || `msg_${Date.now()}`,
type: 'message',
role: 'assistant',
content: [{ type: 'text', text: '' }],
model: response.model || model,
stop_reason: 'end_turn',
stop_sequence: null,
usage: mapUsage(response.usage),
}
}
|