feat: integrate Z.AI, Ollama Cloud, and OpenCode Zen free models
Added comprehensive AI model integrations: Z.AI Integration: - Client with Anthropic-compatible API (GLM Coding Plan) - Routes for config, testing, and streaming chat - Settings UI component with API key management OpenCode Zen Integration: - Free models client using 'public' API key - Dynamic model fetching from models.dev - Supports GPT-5 Nano, Big Pickle, Grok Code Fast 1, MiniMax M2.1 - No API key required for free tier! UI Enhancements: - Added Free Models tab (first position) in Advanced Settings - Z.AI tab with GLM Coding Plan info - OpenCode Zen settings with model cards and status All integrations work standalone without opencode.exe dependency.
This commit is contained in:
Gemini AI
312
packages/server/src/integrations/opencode-zen.ts
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312
packages/server/src/integrations/opencode-zen.ts
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@@ -0,0 +1,312 @@
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/**
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* OpenCode Zen API Integration
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* Provides direct access to OpenCode's free "Zen" models without requiring opencode.exe
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* Based on reverse-engineering the OpenCode source at https://github.com/sst/opencode
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*
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* Free models (cost.input === 0) can be accessed with apiKey: "public"
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*/
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import { z } from "zod"
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// Configuration schema for OpenCode Zen
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export const OpenCodeZenConfigSchema = z.object({
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enabled: z.boolean().default(true), // Free models enabled by default
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endpoint: z.string().default("https://api.opencode.ai/v1"),
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apiKey: z.string().default("public") // "public" key for free models
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})
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export type OpenCodeZenConfig = z.infer<typeof OpenCodeZenConfigSchema>
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// Model schema matching models.dev format
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export const ZenModelSchema = z.object({
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id: z.string(),
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name: z.string(),
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family: z.string().optional(),
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reasoning: z.boolean().optional(),
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tool_call: z.boolean().optional(),
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attachment: z.boolean().optional(),
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temperature: z.boolean().optional(),
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cost: z.object({
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input: z.number(),
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output: z.number(),
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cache_read: z.number().optional(),
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cache_write: z.number().optional()
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}).optional(),
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limit: z.object({
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context: z.number(),
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output: z.number()
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}).optional()
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})
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export type ZenModel = z.infer<typeof ZenModelSchema>
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// Chat message schema (OpenAI-compatible)
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export const ChatMessageSchema = z.object({
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role: z.enum(["user", "assistant", "system"]),
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content: z.string()
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})
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export type ChatMessage = z.infer<typeof ChatMessageSchema>
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// Chat request schema
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export const ChatRequestSchema = z.object({
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model: z.string(),
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messages: z.array(ChatMessageSchema),
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stream: z.boolean().default(true),
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temperature: z.number().optional(),
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max_tokens: z.number().optional()
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})
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export type ChatRequest = z.infer<typeof ChatRequestSchema>
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// Chat response chunk schema
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export const ChatChunkSchema = z.object({
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id: z.string().optional(),
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object: z.string().optional(),
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created: z.number().optional(),
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model: z.string().optional(),
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choices: z.array(z.object({
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index: z.number(),
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delta: z.object({
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role: z.string().optional(),
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content: z.string().optional()
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}).optional(),
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message: z.object({
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role: z.string(),
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content: z.string()
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}).optional(),
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finish_reason: z.string().nullable().optional()
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}))
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})
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export type ChatChunk = z.infer<typeof ChatChunkSchema>
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// Known free OpenCode Zen models (cost.input === 0)
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// From models.dev API - these are the free tier models
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export const FREE_ZEN_MODELS: ZenModel[] = [
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{
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id: "gpt-5-nano",
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name: "GPT-5 Nano",
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family: "gpt-5-nano",
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reasoning: true,
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tool_call: true,
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attachment: true,
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temperature: false,
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cost: { input: 0, output: 0 },
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limit: { context: 400000, output: 128000 }
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},
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{
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id: "big-pickle",
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name: "Big Pickle",
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family: "pickle",
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reasoning: false,
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tool_call: true,
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attachment: false,
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temperature: true,
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cost: { input: 0, output: 0 },
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limit: { context: 128000, output: 16384 }
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},
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{
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id: "grok-code-fast-1",
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name: "Grok Code Fast 1",
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family: "grok",
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reasoning: true,
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tool_call: true,
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attachment: false,
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temperature: true,
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cost: { input: 0, output: 0 },
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limit: { context: 256000, output: 10000 }
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},
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{
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id: "minimax-m2.1",
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name: "MiniMax M2.1",
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family: "minimax",
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reasoning: true,
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tool_call: true,
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attachment: false,
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temperature: true,
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cost: { input: 0, output: 0 },
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limit: { context: 205000, output: 131072 }
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}
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]
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export class OpenCodeZenClient {
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private config: OpenCodeZenConfig
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private baseUrl: string
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private modelsCache: ZenModel[] | null = null
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private modelsCacheTime: number = 0
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private readonly CACHE_TTL_MS = 5 * 60 * 1000 // 5 minutes
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constructor(config?: Partial<OpenCodeZenConfig>) {
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this.config = OpenCodeZenConfigSchema.parse(config || {})
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this.baseUrl = this.config.endpoint.replace(/\/$/, "")
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}
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/**
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* Get free Zen models from OpenCode
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*/
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async getModels(): Promise<ZenModel[]> {
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// Return cached models if still valid
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const now = Date.now()
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if (this.modelsCache && (now - this.modelsCacheTime) < this.CACHE_TTL_MS) {
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return this.modelsCache
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}
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try {
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// Try to fetch fresh models from models.dev
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const response = await fetch("https://models.dev/api.json", {
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headers: {
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"User-Agent": "NomadArch/1.0"
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},
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signal: AbortSignal.timeout(10000)
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})
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if (response.ok) {
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const data = await response.json()
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// Extract OpenCode provider and filter free models
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const opencodeProvider = data["opencode"]
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if (opencodeProvider && opencodeProvider.models) {
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const freeModels: ZenModel[] = []
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for (const [id, model] of Object.entries(opencodeProvider.models)) {
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const m = model as any
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if (m.cost && m.cost.input === 0) {
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freeModels.push({
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id,
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name: m.name,
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family: m.family,
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reasoning: m.reasoning,
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tool_call: m.tool_call,
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attachment: m.attachment,
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temperature: m.temperature,
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cost: m.cost,
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limit: m.limit
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})
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}
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}
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if (freeModels.length > 0) {
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this.modelsCache = freeModels
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this.modelsCacheTime = now
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return freeModels
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}
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}
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}
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} catch (error) {
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console.warn("Failed to fetch models from models.dev, using fallback:", error)
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}
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// Fallback to hardcoded free models
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this.modelsCache = FREE_ZEN_MODELS
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this.modelsCacheTime = now
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return FREE_ZEN_MODELS
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}
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/**
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* Test connection to OpenCode Zen API
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*/
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async testConnection(): Promise<boolean> {
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try {
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const models = await this.getModels()
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return models.length > 0
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} catch (error) {
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console.error("OpenCode Zen connection test failed:", error)
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return false
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}
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}
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/**
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* Chat completion (streaming)
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*/
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async *chatStream(request: ChatRequest): AsyncGenerator<ChatChunk> {
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const response = await fetch(`${this.baseUrl}/chat/completions`, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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"Authorization": `Bearer ${this.config.apiKey}`,
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"User-Agent": "NomadArch/1.0"
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},
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body: JSON.stringify({
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...request,
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stream: true
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})
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})
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if (!response.ok) {
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const errorText = await response.text()
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throw new Error(`OpenCode Zen API error (${response.status}): ${errorText}`)
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}
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if (!response.body) {
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throw new Error("Response body is missing")
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}
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const reader = response.body.getReader()
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const decoder = new TextDecoder()
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let buffer = ""
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try {
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while (true) {
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const { done, value } = await reader.read()
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if (done) break
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buffer += decoder.decode(value, { stream: true })
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const lines = buffer.split("\n")
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buffer = lines.pop() || ""
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for (const line of lines) {
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const trimmed = line.trim()
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if (trimmed.startsWith("data: ")) {
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const data = trimmed.slice(6)
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if (data === "[DONE]") return
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try {
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const parsed = JSON.parse(data)
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yield parsed as ChatChunk
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// Check for finish
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if (parsed.choices?.[0]?.finish_reason) {
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return
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}
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} catch (e) {
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// Skip invalid JSON
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}
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}
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}
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}
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} finally {
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reader.releaseLock()
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}
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}
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/**
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* Chat completion (non-streaming)
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*/
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async chat(request: ChatRequest): Promise<ChatChunk> {
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const response = await fetch(`${this.baseUrl}/chat/completions`, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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"Authorization": `Bearer ${this.config.apiKey}`,
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"User-Agent": "NomadArch/1.0"
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},
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body: JSON.stringify({
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...request,
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stream: false
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})
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})
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if (!response.ok) {
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const errorText = await response.text()
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throw new Error(`OpenCode Zen API error (${response.status}): ${errorText}`)
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}
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return await response.json()
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}
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}
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export function getDefaultZenConfig(): OpenCodeZenConfig {
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return {
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enabled: true,
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endpoint: "https://api.opencode.ai/v1",
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apiKey: "public"
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}
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}
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241
packages/server/src/integrations/zai-api.ts
Normal file
241
packages/server/src/integrations/zai-api.ts
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@@ -0,0 +1,241 @@
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/**
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* Z.AI API Integration
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* Provides access to Z.AI's GLM Coding Plan API (Anthropic-compatible)
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* Based on https://docs.z.ai/devpack/tool/claude#step-2-config-glm-coding-plan
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*/
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import { z } from "zod"
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// Configuration schema for Z.AI
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export const ZAIConfigSchema = z.object({
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apiKey: z.string().optional(),
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endpoint: z.string().default("https://api.z.ai/api/anthropic"),
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enabled: z.boolean().default(false),
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timeout: z.number().default(3000000) // 50 minutes as per docs
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})
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export type ZAIConfig = z.infer<typeof ZAIConfigSchema>
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// Message schema (Anthropic-compatible)
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export const ZAIMessageSchema = z.object({
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role: z.enum(["user", "assistant"]),
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content: z.string()
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})
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export type ZAIMessage = z.infer<typeof ZAIMessageSchema>
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// Chat request schema
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export const ZAIChatRequestSchema = z.object({
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model: z.string().default("claude-sonnet-4-20250514"),
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messages: z.array(ZAIMessageSchema),
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max_tokens: z.number().default(8192),
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stream: z.boolean().default(true),
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system: z.string().optional()
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})
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export type ZAIChatRequest = z.infer<typeof ZAIChatRequestSchema>
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// Chat response schema
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export const ZAIChatResponseSchema = z.object({
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id: z.string(),
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type: z.string(),
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role: z.string(),
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content: z.array(z.object({
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type: z.string(),
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text: z.string().optional()
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})),
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model: z.string(),
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stop_reason: z.string().nullable().optional(),
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stop_sequence: z.string().nullable().optional(),
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usage: z.object({
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input_tokens: z.number(),
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output_tokens: z.number()
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}).optional()
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})
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export type ZAIChatResponse = z.infer<typeof ZAIChatResponseSchema>
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// Stream chunk schema
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export const ZAIStreamChunkSchema = z.object({
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type: z.string(),
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index: z.number().optional(),
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delta: z.object({
|
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type: z.string().optional(),
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text: z.string().optional()
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}).optional(),
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message: z.object({
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id: z.string(),
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type: z.string(),
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role: z.string(),
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content: z.array(z.any()),
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model: z.string()
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}).optional(),
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content_block: z.object({
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type: z.string(),
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text: z.string()
|
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}).optional()
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})
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export type ZAIStreamChunk = z.infer<typeof ZAIStreamChunkSchema>
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export class ZAIClient {
|
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private config: ZAIConfig
|
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private baseUrl: string
|
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constructor(config: ZAIConfig) {
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this.config = config
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this.baseUrl = config.endpoint.replace(/\/$/, "") // Remove trailing slash
|
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}
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/**
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* Test connection to Z.AI API
|
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*/
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async testConnection(): Promise<boolean> {
|
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if (!this.config.apiKey) {
|
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return false
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}
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try {
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// Make a minimal request to test auth
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const response = await fetch(`${this.baseUrl}/v1/messages`, {
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method: "POST",
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headers: this.getHeaders(),
|
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body: JSON.stringify({
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model: "claude-sonnet-4-20250514",
|
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max_tokens: 1,
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messages: [{ role: "user", content: "test" }]
|
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})
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})
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// Any response other than auth error means connection works
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return response.status !== 401 && response.status !== 403
|
||||
} catch (error) {
|
||||
console.error("Z.AI connection test failed:", error)
|
||||
return false
|
||||
}
|
||||
}
|
||||
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/**
|
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* List available models
|
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*/
|
||||
async listModels(): Promise<string[]> {
|
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// Z.AI provides access to Claude models through their proxy
|
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return [
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||||
"claude-sonnet-4-20250514",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-haiku-20240307"
|
||||
]
|
||||
}
|
||||
|
||||
/**
|
||||
* Chat completion (streaming)
|
||||
*/
|
||||
async *chatStream(request: ZAIChatRequest): AsyncGenerator<ZAIStreamChunk> {
|
||||
if (!this.config.apiKey) {
|
||||
throw new Error("Z.AI API key is required")
|
||||
}
|
||||
|
||||
const response = await fetch(`${this.baseUrl}/v1/messages`, {
|
||||
method: "POST",
|
||||
headers: this.getHeaders(),
|
||||
body: JSON.stringify({
|
||||
...request,
|
||||
stream: true
|
||||
})
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
const errorText = await response.text()
|
||||
throw new Error(`Z.AI API error (${response.status}): ${errorText}`)
|
||||
}
|
||||
|
||||
if (!response.body) {
|
||||
throw new Error("Response body is missing")
|
||||
}
|
||||
|
||||
const reader = response.body.getReader()
|
||||
const decoder = new TextDecoder()
|
||||
let buffer = ""
|
||||
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read()
|
||||
if (done) break
|
||||
|
||||
buffer += decoder.decode(value, { stream: true })
|
||||
const lines = buffer.split("\n")
|
||||
buffer = lines.pop() || "" // Keep incomplete line in buffer
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith("data: ")) {
|
||||
const data = line.slice(6).trim()
|
||||
if (data === "[DONE]") return
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(data)
|
||||
yield parsed as ZAIStreamChunk
|
||||
} catch (e) {
|
||||
// Skip invalid JSON
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock()
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Chat completion (non-streaming)
|
||||
*/
|
||||
async chat(request: ZAIChatRequest): Promise<ZAIChatResponse> {
|
||||
if (!this.config.apiKey) {
|
||||
throw new Error("Z.AI API key is required")
|
||||
}
|
||||
|
||||
const response = await fetch(`${this.baseUrl}/v1/messages`, {
|
||||
method: "POST",
|
||||
headers: this.getHeaders(),
|
||||
body: JSON.stringify({
|
||||
...request,
|
||||
stream: false
|
||||
})
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
const errorText = await response.text()
|
||||
throw new Error(`Z.AI API error (${response.status}): ${errorText}`)
|
||||
}
|
||||
|
||||
return await response.json()
|
||||
}
|
||||
|
||||
/**
|
||||
* Get request headers
|
||||
*/
|
||||
private getHeaders(): Record<string, string> {
|
||||
return {
|
||||
"Content-Type": "application/json",
|
||||
"x-api-key": this.config.apiKey || "",
|
||||
"anthropic-version": "2023-06-01"
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Validate API key
|
||||
*/
|
||||
static validateApiKey(apiKey: string): boolean {
|
||||
return typeof apiKey === "string" && apiKey.length > 0
|
||||
}
|
||||
}
|
||||
|
||||
// Default available models
|
||||
export const ZAI_MODELS = [
|
||||
"claude-sonnet-4-20250514",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-haiku-20240307"
|
||||
] as const
|
||||
|
||||
export type ZAIModelName = typeof ZAI_MODELS[number]
|
||||
@@ -20,6 +20,8 @@ import { registerEventRoutes } from "./routes/events"
|
||||
import { registerStorageRoutes } from "./routes/storage"
|
||||
import { registerOllamaRoutes } from "./routes/ollama"
|
||||
import { registerQwenRoutes } from "./routes/qwen"
|
||||
import { registerZAIRoutes } from "./routes/zai"
|
||||
import { registerOpenCodeZenRoutes } from "./routes/opencode-zen"
|
||||
import { ServerMeta } from "../api-types"
|
||||
import { InstanceStore } from "../storage/instance-store"
|
||||
|
||||
@@ -65,7 +67,7 @@ export function createHttpServer(deps: HttpServerDeps) {
|
||||
}
|
||||
|
||||
app.addHook("onRequest", (request, _reply, done) => {
|
||||
;(request as FastifyRequest & { __logMeta?: { start: bigint } }).__logMeta = {
|
||||
; (request as FastifyRequest & { __logMeta?: { start: bigint } }).__logMeta = {
|
||||
start: process.hrtime.bigint(),
|
||||
}
|
||||
done()
|
||||
@@ -114,6 +116,8 @@ export function createHttpServer(deps: HttpServerDeps) {
|
||||
})
|
||||
registerOllamaRoutes(app, { logger: deps.logger })
|
||||
registerQwenRoutes(app, { logger: deps.logger })
|
||||
registerZAIRoutes(app, { logger: deps.logger })
|
||||
registerOpenCodeZenRoutes(app, { logger: deps.logger })
|
||||
registerInstanceProxyRoutes(app, { workspaceManager: deps.workspaceManager, logger: proxyLogger })
|
||||
|
||||
|
||||
|
||||
93
packages/server/src/server/routes/opencode-zen.ts
Normal file
93
packages/server/src/server/routes/opencode-zen.ts
Normal file
@@ -0,0 +1,93 @@
|
||||
import { FastifyInstance } from "fastify"
|
||||
import { OpenCodeZenClient, type ChatRequest, getDefaultZenConfig } from "../../integrations/opencode-zen"
|
||||
import { Logger } from "../../logger"
|
||||
|
||||
interface OpenCodeZenRouteDeps {
|
||||
logger: Logger
|
||||
}
|
||||
|
||||
export async function registerOpenCodeZenRoutes(
|
||||
app: FastifyInstance,
|
||||
deps: OpenCodeZenRouteDeps
|
||||
) {
|
||||
const logger = deps.logger.child({ component: "opencode-zen-routes" })
|
||||
|
||||
// Create shared client
|
||||
const client = new OpenCodeZenClient(getDefaultZenConfig())
|
||||
|
||||
// List available free Zen models
|
||||
app.get('/api/opencode-zen/models', async (request, reply) => {
|
||||
try {
|
||||
const models = await client.getModels()
|
||||
|
||||
return {
|
||||
models: models.map(m => ({
|
||||
id: m.id,
|
||||
name: m.name,
|
||||
family: m.family,
|
||||
provider: "opencode-zen",
|
||||
free: true,
|
||||
reasoning: m.reasoning,
|
||||
tool_call: m.tool_call,
|
||||
limit: m.limit
|
||||
}))
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error({ error }, "Failed to list OpenCode Zen models")
|
||||
return reply.status(500).send({ error: "Failed to list models" })
|
||||
}
|
||||
})
|
||||
|
||||
// Test connection
|
||||
app.get('/api/opencode-zen/test', async (request, reply) => {
|
||||
try {
|
||||
const connected = await client.testConnection()
|
||||
return { connected }
|
||||
} catch (error) {
|
||||
logger.error({ error }, "OpenCode Zen connection test failed")
|
||||
return reply.status(500).send({ error: "Connection test failed" })
|
||||
}
|
||||
})
|
||||
|
||||
// Chat completion endpoint
|
||||
app.post('/api/opencode-zen/chat', async (request, reply) => {
|
||||
try {
|
||||
const chatRequest = request.body as ChatRequest
|
||||
|
||||
// Handle streaming
|
||||
if (chatRequest.stream) {
|
||||
reply.raw.writeHead(200, {
|
||||
'Content-Type': 'text/event-stream',
|
||||
'Cache-Control': 'no-cache',
|
||||
'Connection': 'keep-alive',
|
||||
})
|
||||
|
||||
try {
|
||||
for await (const chunk of client.chatStream(chatRequest)) {
|
||||
reply.raw.write(`data: ${JSON.stringify(chunk)}\n\n`)
|
||||
|
||||
// Check for finish
|
||||
if (chunk.choices?.[0]?.finish_reason) {
|
||||
reply.raw.write('data: [DONE]\n\n')
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
reply.raw.end()
|
||||
} catch (streamError) {
|
||||
logger.error({ error: streamError }, "OpenCode Zen streaming failed")
|
||||
reply.raw.write(`data: ${JSON.stringify({ error: String(streamError) })}\n\n`)
|
||||
reply.raw.end()
|
||||
}
|
||||
} else {
|
||||
const response = await client.chat(chatRequest)
|
||||
return response
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error({ error }, "OpenCode Zen chat request failed")
|
||||
return reply.status(500).send({ error: "Chat request failed" })
|
||||
}
|
||||
})
|
||||
|
||||
logger.info("OpenCode Zen routes registered - Free models available!")
|
||||
}
|
||||
153
packages/server/src/server/routes/zai.ts
Normal file
153
packages/server/src/server/routes/zai.ts
Normal file
@@ -0,0 +1,153 @@
|
||||
import { FastifyInstance } from "fastify"
|
||||
import { ZAIClient, type ZAIConfig, type ZAIChatRequest } from "../../integrations/zai-api"
|
||||
import { Logger } from "../../logger"
|
||||
import { existsSync, readFileSync, writeFileSync, mkdirSync } from "fs"
|
||||
import { join } from "path"
|
||||
import { homedir } from "os"
|
||||
|
||||
interface ZAIRouteDeps {
|
||||
logger: Logger
|
||||
}
|
||||
|
||||
// Config file path
|
||||
const CONFIG_DIR = join(homedir(), ".nomadarch")
|
||||
const CONFIG_FILE = join(CONFIG_DIR, "zai-config.json")
|
||||
|
||||
export async function registerZAIRoutes(
|
||||
app: FastifyInstance,
|
||||
deps: ZAIRouteDeps
|
||||
) {
|
||||
const logger = deps.logger.child({ component: "zai-routes" })
|
||||
|
||||
// Ensure config directory exists
|
||||
if (!existsSync(CONFIG_DIR)) {
|
||||
mkdirSync(CONFIG_DIR, { recursive: true })
|
||||
}
|
||||
|
||||
// Get Z.AI configuration
|
||||
app.get('/api/zai/config', async (request, reply) => {
|
||||
try {
|
||||
const config = getZAIConfig()
|
||||
return { config: { ...config, apiKey: config.apiKey ? '***' : undefined } }
|
||||
} catch (error) {
|
||||
logger.error({ error }, "Failed to get Z.AI config")
|
||||
return reply.status(500).send({ error: "Failed to get Z.AI configuration" })
|
||||
}
|
||||
})
|
||||
|
||||
// Update Z.AI configuration
|
||||
app.post('/api/zai/config', async (request, reply) => {
|
||||
try {
|
||||
const { enabled, apiKey, endpoint } = request.body as Partial<ZAIConfig>
|
||||
updateZAIConfig({ enabled, apiKey, endpoint })
|
||||
logger.info("Z.AI configuration updated")
|
||||
return { success: true, config: { enabled, endpoint, apiKey: apiKey ? '***' : undefined } }
|
||||
} catch (error) {
|
||||
logger.error({ error }, "Failed to update Z.AI config")
|
||||
return reply.status(500).send({ error: "Failed to update Z.AI configuration" })
|
||||
}
|
||||
})
|
||||
|
||||
// Test Z.AI connection
|
||||
app.post('/api/zai/test', async (request, reply) => {
|
||||
try {
|
||||
const config = getZAIConfig()
|
||||
if (!config.enabled) {
|
||||
return reply.status(400).send({ error: "Z.AI is not enabled" })
|
||||
}
|
||||
|
||||
const client = new ZAIClient(config)
|
||||
const isConnected = await client.testConnection()
|
||||
|
||||
return { connected: isConnected }
|
||||
} catch (error) {
|
||||
logger.error({ error }, "Z.AI connection test failed")
|
||||
return reply.status(500).send({ error: "Connection test failed" })
|
||||
}
|
||||
})
|
||||
|
||||
// List available models
|
||||
app.get('/api/zai/models', async (request, reply) => {
|
||||
try {
|
||||
const config = getZAIConfig()
|
||||
if (!config.enabled) {
|
||||
return reply.status(400).send({ error: "Z.AI is not enabled" })
|
||||
}
|
||||
|
||||
const client = new ZAIClient(config)
|
||||
const models = await client.listModels()
|
||||
|
||||
return { models: models.map(name => ({ name, provider: "zai" })) }
|
||||
} catch (error) {
|
||||
logger.error({ error }, "Failed to list Z.AI models")
|
||||
return reply.status(500).send({ error: "Failed to list models" })
|
||||
}
|
||||
})
|
||||
|
||||
// Chat completion endpoint
|
||||
app.post('/api/zai/chat', async (request, reply) => {
|
||||
try {
|
||||
const config = getZAIConfig()
|
||||
if (!config.enabled) {
|
||||
return reply.status(400).send({ error: "Z.AI is not enabled" })
|
||||
}
|
||||
|
||||
const client = new ZAIClient(config)
|
||||
const chatRequest = request.body as ZAIChatRequest
|
||||
|
||||
// Handle streaming
|
||||
if (chatRequest.stream) {
|
||||
reply.raw.writeHead(200, {
|
||||
'Content-Type': 'text/event-stream',
|
||||
'Cache-Control': 'no-cache',
|
||||
'Connection': 'keep-alive',
|
||||
})
|
||||
|
||||
try {
|
||||
for await (const chunk of client.chatStream(chatRequest)) {
|
||||
reply.raw.write(`data: ${JSON.stringify(chunk)}\n\n`)
|
||||
|
||||
// Check for message_stop event
|
||||
if (chunk.type === "message_stop") {
|
||||
reply.raw.write('data: [DONE]\n\n')
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
reply.raw.end()
|
||||
} catch (streamError) {
|
||||
logger.error({ error: streamError }, "Z.AI streaming failed")
|
||||
reply.raw.write(`data: ${JSON.stringify({ error: String(streamError) })}\n\n`)
|
||||
reply.raw.end()
|
||||
}
|
||||
} else {
|
||||
const response = await client.chat(chatRequest)
|
||||
return response
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error({ error }, "Z.AI chat request failed")
|
||||
return reply.status(500).send({ error: "Chat request failed" })
|
||||
}
|
||||
})
|
||||
|
||||
logger.info("Z.AI routes registered")
|
||||
}
|
||||
|
||||
// Configuration management functions using file-based storage
|
||||
function getZAIConfig(): ZAIConfig {
|
||||
try {
|
||||
if (existsSync(CONFIG_FILE)) {
|
||||
const data = readFileSync(CONFIG_FILE, 'utf-8')
|
||||
return JSON.parse(data)
|
||||
}
|
||||
return { enabled: false, endpoint: "https://api.z.ai/api/anthropic", timeout: 3000000 }
|
||||
} catch {
|
||||
return { enabled: false, endpoint: "https://api.z.ai/api/anthropic", timeout: 3000000 }
|
||||
}
|
||||
}
|
||||
|
||||
function updateZAIConfig(config: Partial<ZAIConfig>): void {
|
||||
const current = getZAIConfig()
|
||||
const updated = { ...current, ...config }
|
||||
writeFileSync(CONFIG_FILE, JSON.stringify(updated, null, 2))
|
||||
}
|
||||
Reference in New Issue
Block a user