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import { ZenData } from "@opencode-ai/console-core/model.js"
import {
fromAnthropicChunk,
fromAnthropicRequest,
fromAnthropicResponse,
toAnthropicChunk,
toAnthropicRequest,
toAnthropicResponse,
} from "./anthropic"
import {
fromOpenaiChunk,
fromOpenaiRequest,
fromOpenaiResponse,
toOpenaiChunk,
toOpenaiRequest,
toOpenaiResponse,
} from "./openai"
import {
fromOaCompatibleChunk,
fromOaCompatibleRequest,
fromOaCompatibleResponse,
toOaCompatibleChunk,
toOaCompatibleRequest,
toOaCompatibleResponse,
} from "./openai-compatible"
export type UsageInfo = {
inputTokens: number
outputTokens: number
reasoningTokens?: number
cacheReadTokens?: number
cacheWrite5mTokens?: number
cacheWrite1hTokens?: number
}
export type ProviderHelper = (input: {
reqModel: string
providerModel: string
adjustCacheUsage?: boolean
workspaceID?: string
}) => {
format: ZenData.Format
modifyUrl: (providerApi: string, isStream?: boolean) => string
modifyHeaders: (headers: Headers, body: Record<string, any>, apiKey: string) => void
modifyBody: (body: Record<string, any>) => Record<string, any>
createBinaryStreamDecoder: () => ((chunk: Uint8Array) => Uint8Array | undefined) | undefined
streamSeparator: string
createUsageParser: () => {
parse: (chunk: string) => void
retrieve: () => any
}
normalizeUsage: (usage: any) => UsageInfo
}
export interface CommonMessage {
role: "system" | "user" | "assistant" | "tool"
content?: string | Array<CommonContentPart>
tool_call_id?: string
tool_calls?: CommonToolCall[]
}
export interface CommonContentPart {
type: "text" | "image_url"
text?: string
image_url?: { url: string }
}
export interface CommonToolCall {
id: string
type: "function"
function: {
name: string
arguments: string
}
}
export interface CommonTool {
type: "function"
function: {
name: string
description?: string
parameters?: Record<string, any>
}
}
export interface CommonUsage {
input_tokens?: number
output_tokens?: number
total_tokens?: number
prompt_tokens?: number
completion_tokens?: number
cache_read_input_tokens?: number
cache_creation?: {
ephemeral_5m_input_tokens?: number
ephemeral_1h_input_tokens?: number
}
input_tokens_details?: {
cached_tokens?: number
}
output_tokens_details?: {
reasoning_tokens?: number
}
}
export interface CommonRequest {
model: string
max_tokens?: number
temperature?: number
top_p?: number
stop?: string | string[]
messages: CommonMessage[]
stream?: boolean
tools?: CommonTool[]
tool_choice?: "auto" | "required" | { type: "function"; function: { name: string } }
}
export interface CommonResponse {
id: string
object: "chat.completion"
created: number
model: string
choices: Array<{
index: number
message: {
role: "assistant"
content?: string
tool_calls?: CommonToolCall[]
}
finish_reason: "stop" | "tool_calls" | "length" | "content_filter" | null
}>
usage?: {
prompt_tokens?: number
completion_tokens?: number
total_tokens?: number
prompt_tokens_details?: { cached_tokens?: number }
}
}
export interface CommonChunk {
id: string
object: "chat.completion.chunk"
created: number
model: string
choices: Array<{
index: number
delta: {
role?: "assistant"
content?: string
tool_calls?: Array<{
index: number
id?: string
type?: "function"
function?: {
name?: string
arguments?: string
}
}>
}
finish_reason: "stop" | "tool_calls" | "length" | "content_filter" | null
}>
usage?: {
prompt_tokens?: number
completion_tokens?: number
total_tokens?: number
prompt_tokens_details?: { cached_tokens?: number }
}
}
export function buildCostChunk(format: ZenData.Format, cost: string): string {
switch (format) {
case "anthropic":
return `event: ping\ndata: ${JSON.stringify({ type: "ping", cost })}\n\n`
case "openai":
return `event: ping\ndata: ${JSON.stringify({ type: "ping", cost })}\n\n`
case "oa-compat":
return `data: ${JSON.stringify({ choices: [], cost })}\n\n`
default:
return `data: ${JSON.stringify({ type: "ping", cost })}\n\n`
}
}
export function createBodyConverter(from: ZenData.Format, to: ZenData.Format) {
return (body: any): any => {
if (from === to) return body
let raw: CommonRequest
if (from === "anthropic") raw = fromAnthropicRequest(body)
else if (from === "openai") raw = fromOpenaiRequest(body)
else raw = fromOaCompatibleRequest(body)
if (to === "anthropic") return toAnthropicRequest(raw)
if (to === "openai") return toOpenaiRequest(raw)
if (to === "oa-compat") return toOaCompatibleRequest(raw)
}
}
export function createStreamPartConverter(from: ZenData.Format, to: ZenData.Format) {
return (part: any): any => {
if (from === to) return part
let raw: CommonChunk | string
if (from === "anthropic") raw = fromAnthropicChunk(part)
else if (from === "openai") raw = fromOpenaiChunk(part)
else raw = fromOaCompatibleChunk(part)
// If result is a string (error case), pass it through
if (typeof raw === "string") return raw
if (to === "anthropic") return toAnthropicChunk(raw)
if (to === "openai") return toOpenaiChunk(raw)
if (to === "oa-compat") return toOaCompatibleChunk(raw)
}
}
export function createResponseConverter(from: ZenData.Format, to: ZenData.Format) {
return (response: any): any => {
if (from === to) return response
let raw: CommonResponse
if (from === "anthropic") raw = fromAnthropicResponse(response)
else if (from === "openai") raw = fromOpenaiResponse(response)
else raw = fromOaCompatibleResponse(response)
if (to === "anthropic") return toAnthropicResponse(raw)
if (to === "openai") return toOpenaiResponse(raw)
if (to === "oa-compat") return toOaCompatibleResponse(raw)
}
}
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