From cf457e8349c78f62572797e398f8b440162d3972 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Roog=20=28=E9=A1=BE=E6=96=B0=E5=9F=B9=29?= Date: Wed, 27 May 2026 11:10:40 +0800 Subject: [PATCH] =?UTF-8?q?main:=20=E5=88=9D=E5=A7=8B=E5=8C=96=20Face=20to?= =?UTF-8?q?=20API=20=E9=A1=B9=E7=9B=AE?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 添加前端抽卡台与模型配置界面 - 添加 Express API 服务与多厂商模型调用适配 - 配置本地环境示例、构建脚本和忽略规则 --- .env.example | 28 + .gitignore | 8 + README.md | 38 + index.html | 20 + package-lock.json | 3479 ++++++++++++++++++++++++++++++++++++ package.json | 36 + server/index.ts | 334 ++++ server/modelConfigStore.ts | 121 ++ server/modelRegistry.ts | 261 +++ server/providerClients.ts | 618 +++++++ server/template.ts | 22 + server/tokens.ts | 32 + src/main.tsx | 1140 ++++++++++++ src/styles.css | 1118 ++++++++++++ tsconfig.json | 20 + tsconfig.server.json | 17 + vite.config.ts | 12 + 17 files changed, 7304 insertions(+) create mode 100644 .env.example create mode 100644 .gitignore create mode 100644 README.md create mode 100644 index.html create mode 100644 package-lock.json create mode 100644 package.json create mode 100644 server/index.ts create mode 100644 server/modelConfigStore.ts create mode 100644 server/modelRegistry.ts create mode 100644 server/providerClients.ts create mode 100644 server/template.ts create mode 100644 server/tokens.ts create mode 100644 src/main.tsx create mode 100644 src/styles.css create mode 100644 tsconfig.json create mode 100644 tsconfig.server.json create mode 100644 vite.config.ts diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..e6124d0 --- /dev/null +++ b/.env.example @@ -0,0 +1,28 @@ +# Server +PORT=8787 +MODEL_CONFIG_PATH=.face-to-api/model-configs.json + +# Provider keys +OPENAI_API_KEY= +DEEPSEEK_API_KEY= +ZHIPU_API_KEY= +ANTHROPIC_API_KEY= +GEMINI_API_KEY= + +# Optional endpoint/model overrides for deployments whose IDs differ from the UI labels. +OPENAI_BASE_URL=https://api.openai.com/v1 +OPENAI_MODEL_GPT_5_5=gpt-5.5 +DEEPSEEK_BASE_URL=https://api.deepseek.com +DEEPSEEK_MODEL_V4_PRO=DeepSeekV4-pro +DEEPSEEK_MODEL_V4_FLASH=DeepSeekV4-flash +ZHIPU_BASE_URL=https://open.bigmodel.cn/api/paas/v4 +ZHIPU_MODEL_GLM_5_1=GLM5.1 +ANTHROPIC_MODEL_CLAUDE_OPUS_4_7=claude-opus-4.7 +GEMINI_MODEL_3_1_PRO=Gemini-3.1-pro +GEMINI_MODEL_3_5_FLASH=gemini3.5-flash + +# Add comma-separated OpenAI-compatible custom models. +# CUSTOM_OPENAI_NAME=Internal Gateway +# CUSTOM_OPENAI_BASE_URL=https://gateway.example.com/v1 +# CUSTOM_OPENAI_API_KEY= +# CUSTOM_OPENAI_MODEL_IDS=llama-4,moonshot-v2 diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..9d69a74 --- /dev/null +++ b/.gitignore @@ -0,0 +1,8 @@ +node_modules +dist +dist-server +artifacts +.env +.face-to-api +.DS_Store +npm-debug.log* diff --git a/README.md b/README.md new file mode 100644 index 0000000..2cdc2f3 --- /dev/null +++ b/README.md @@ -0,0 +1,38 @@ +# Face to API + +一个 Web 对话抽卡台,用统一接口连接多家模型厂商。第一期内置: + +- DeepSeekV4-pro +- DeepSeekV4-flash +- GLM5.1 +- GPT-5.5 +- Claude Opus 4.7 +- Gemini-3.1-pro +- gemini3.5-flash + +## 启动 + +```bash +npm install +cp .env.example .env +npm run dev +``` + +前端默认运行在 `http://127.0.0.1:5173`,API 默认运行在 `http://127.0.0.1:8787`。 + +## 环境变量 + +在 `.env` 中填写对应厂商的 API key。不同厂商实际模型 ID 若与界面展示名不同,可以用 `.env.example` 中的模型覆盖变量改掉。 + +也可以直接在 Web 页面点击左侧「配置」进入可视化配置台。每个模型都有独立的 API Base URL、模型 ID 和 API Key;页面保存的模型级配置会优先于 `.env` 中的厂商级配置。API Key 会写入本地 `.face-to-api/model-configs.json`,该目录已加入 `.gitignore`。 + +## 功能 + +- 系统提示词与用户提示词分窗输入,支持 `{{draw}}`、`{{model}}`、`{{provider}}`、`{{now}}`、`{{timestamp}}` 内置变量。 +- 同时选择多个模型,每个模型并发执行多次抽卡。 +- 每张卡流式展示上游返回的思考过程与输出结果,结束后再补齐输入 token、输出 token、总 token 和耗时。 +- 流式运行中可一键停止,未完成的卡片会标记为 stopped,并中断上游请求。 +- 可视化模型配置页,支持每个模型独立保存 API Base URL、实际模型 ID 和 API Key。 +- 配置页可开关每个模型是否展示在对话选择页,关闭后仍保留配置并可随时重新开启。 +- 后端统一归一化 OpenAI-compatible、Anthropic Messages、Gemini generateContent 的 usage 字段。 +- 可通过 `CUSTOM_OPENAI_*` 增加任意 OpenAI-compatible 网关模型。 diff --git a/index.html b/index.html new file mode 100644 index 0000000..6ef05f2 --- /dev/null +++ b/index.html @@ -0,0 +1,20 @@ + + + + + + + + + + Face to API + + +
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"zod": "^4.1.12" + }, + "devDependencies": { + "@types/cors": "^2.8.19", + "@types/express": "^5.0.5", + "@types/node": "^22.18.10", + "@types/react": "^19.2.2", + "@types/react-dom": "^19.2.2", + "concurrently": "^9.2.1", + "tsx": "^4.20.6", + "typescript": "^5.9.3", + "vite": "^7.1.10" + } +} + diff --git a/server/index.ts b/server/index.ts new file mode 100644 index 0000000..3252d37 --- /dev/null +++ b/server/index.ts @@ -0,0 +1,334 @@ +import "dotenv/config"; +import cors from "cors"; +import express from "express"; +import path from "node:path"; +import { fileURLToPath } from "node:url"; +import { z } from "zod"; +import { findModel, providerForModel, registry } from "./modelRegistry.js"; +import { saveModelConfig } from "./modelConfigStore.js"; +import { callProvider, streamProvider } from "./providerClients.js"; +import { renderPrompt } from "./template.js"; +import { normalizeUsage } from "./tokens.js"; + +const app = express(); +const port = Number(process.env.PORT ?? 8787); + +app.use(cors()); +app.use(express.json({ limit: "1mb" })); + +const runSchema = z.object({ + template: z.string().trim().optional(), + systemTemplate: z.string().trim().optional(), + userTemplate: z.string().trim().optional(), + modelIds: z.array(z.string()).min(1), + draws: z.number().int().min(1).max(20), + temperature: z.number().min(0).max(2).default(0.8), + maxTokens: z.number().int().min(64).max(8192).default(1024) +}).superRefine((data, context) => { + const userTemplate = data.userTemplate || data.template || ""; + if (!userTemplate.trim()) { + context.addIssue({ + code: z.ZodIssueCode.custom, + path: ["userTemplate"], + message: "User prompt template is required" + }); + } +}); + +const composePrompt = (systemPrompt: string, userPrompt: string) => + [systemPrompt, userPrompt].filter(Boolean).join("\n\n"); + +const modelConfigSchema = z.object({ + baseUrl: z.string().trim().optional(), + model: z.string().trim().optional(), + apiKey: z.string().optional(), + enabled: z.boolean().optional(), + clearApiKey: z.boolean().optional() +}); + +app.get("/api/health", (_request, response) => { + response.json({ ok: true }); +}); + +app.get("/api/models", (_request, response) => { + response.json({ models: registry() }); +}); + +app.get("/api/model-configs", (_request, response) => { + response.json({ models: registry() }); +}); + +app.put("/api/model-configs/:modelId", (request, response) => { + const model = findModel(request.params.modelId); + if (!model) { + response.status(404).json({ error: "Model not found" }); + return; + } + + const parsed = modelConfigSchema.safeParse(request.body); + if (!parsed.success) { + response.status(400).json({ error: parsed.error.flatten() }); + return; + } + + saveModelConfig(model.id, parsed.data); + const updated = findModel(model.id); + response.json({ model: updated }); +}); + +app.post("/api/runs", async (request, response) => { + const parsed = runSchema.safeParse(request.body); + if (!parsed.success) { + response.status(400).json({ error: parsed.error.flatten() }); + return; + } + + const { + systemTemplate = "", + userTemplate: explicitUserTemplate, + template: legacyTemplate, + modelIds, + draws, + temperature, + maxTokens + } = parsed.data; + const userTemplate = explicitUserTemplate || legacyTemplate || ""; + const startedAt = new Date(); + const uniqueModelIds = [...new Set(modelIds)]; + const models = uniqueModelIds.map((modelId) => findModel(modelId)); + const missing = uniqueModelIds.filter((modelId, index) => !models[index]); + + if (missing.length) { + response.status(400).json({ error: `Unknown model: ${missing.join(", ")}` }); + return; + } + + const jobs = models.flatMap((model) => + Array.from({ length: draws }, (_, index) => ({ + model: model!, + draw: index + 1 + })) + ); + + const results = await Promise.all( + jobs.map(async ({ model, draw }) => { + const context = { draw, model, startedAt }; + const systemPrompt = systemTemplate ? renderPrompt(systemTemplate, context) : ""; + const userPrompt = renderPrompt(userTemplate, context); + const prompt = composePrompt(systemPrompt, userPrompt); + const provider = providerForModel(model); + const jobStarted = Date.now(); + + try { + const result = await callProvider({ + model, + provider, + systemPrompt, + prompt: userPrompt, + temperature, + maxTokens + }); + + return { + id: `${model.id}-${draw}-${jobStarted}`, + ok: true, + draw, + prompt, + systemPrompt, + userPrompt, + output: result.output, + modelId: model.id, + modelLabel: model.label, + providerName: model.providerName, + rawModel: result.rawModel, + durationMs: Date.now() - jobStarted, + usage: result.usage + }; + } catch (error) { + const message = error instanceof Error ? error.message : "Unknown provider error"; + + return { + id: `${model.id}-${draw}-${jobStarted}`, + ok: false, + draw, + prompt, + systemPrompt, + userPrompt, + output: "", + error: message, + modelId: model.id, + modelLabel: model.label, + providerName: model.providerName, + rawModel: model.model, + durationMs: Date.now() - jobStarted, + usage: normalizeUsage(prompt, "", null) + }; + } + }) + ); + + response.json({ + startedAt: startedAt.toISOString(), + finishedAt: new Date().toISOString(), + results + }); +}); + +app.post("/api/runs/stream", async (request, response) => { + const parsed = runSchema.safeParse(request.body); + if (!parsed.success) { + response.status(400).json({ error: parsed.error.flatten() }); + return; + } + + const { + systemTemplate = "", + userTemplate: explicitUserTemplate, + template: legacyTemplate, + modelIds, + draws, + temperature, + maxTokens + } = parsed.data; + const userTemplate = explicitUserTemplate || legacyTemplate || ""; + const startedAt = new Date(); + const uniqueModelIds = [...new Set(modelIds)]; + const models = uniqueModelIds.map((modelId) => findModel(modelId)); + const missing = uniqueModelIds.filter((modelId, index) => !models[index]); + + if (missing.length) { + response.status(400).json({ error: `Unknown model: ${missing.join(", ")}` }); + return; + } + + response.setHeader("Content-Type", "application/x-ndjson; charset=utf-8"); + response.setHeader("Cache-Control", "no-cache, no-transform"); + response.setHeader("Connection", "keep-alive"); + response.setHeader("X-Accel-Buffering", "no"); + response.flushHeaders(); + + const controller = new AbortController(); + response.on("close", () => { + if (!response.writableEnded) { + controller.abort(); + } + }); + + const writeEvent = (event: Record) => { + if (!response.destroyed && !response.writableEnded) { + response.write(`${JSON.stringify(event)}\n`); + } + }; + + const jobs = models.flatMap((model) => + Array.from({ length: draws }, (_, index) => ({ + model: model!, + draw: index + 1 + })) + ); + + writeEvent({ + type: "run_start", + startedAt: startedAt.toISOString(), + totalJobs: jobs.length + }); + + await Promise.all( + jobs.map(async ({ model, draw }, jobIndex) => { + const context = { draw, model, startedAt }; + const systemPrompt = systemTemplate ? renderPrompt(systemTemplate, context) : ""; + const userPrompt = renderPrompt(userTemplate, context); + const prompt = composePrompt(systemPrompt, userPrompt); + const provider = providerForModel(model); + const jobStarted = Date.now(); + const id = `${model.id}-${draw}-${startedAt.getTime()}-${jobIndex}`; + + writeEvent({ + type: "card_start", + id, + draw, + prompt, + systemPrompt, + userPrompt, + modelId: model.id, + modelLabel: model.label, + providerName: model.providerName, + rawModel: model.model + }); + + try { + const result = await streamProvider({ + model, + provider, + systemPrompt, + prompt: userPrompt, + temperature, + maxTokens, + signal: controller.signal, + onDelta: (delta) => { + writeEvent({ + type: "delta", + id, + channel: delta.channel, + text: delta.text + }); + } + }); + + writeEvent({ + type: "card_end", + id, + ok: true, + output: result.output, + reasoning: result.reasoning ?? "", + rawModel: result.rawModel, + durationMs: Date.now() - jobStarted, + usage: result.usage + }); + } catch (error) { + const message = error instanceof Error ? error.message : "Unknown provider error"; + + writeEvent({ + type: "card_end", + id, + ok: false, + output: "", + reasoning: "", + error: message, + rawModel: model.model, + durationMs: Date.now() - jobStarted, + usage: normalizeUsage(prompt, "", null) + }); + } + }) + ); + + writeEvent({ + type: "run_end", + startedAt: startedAt.toISOString(), + finishedAt: new Date().toISOString() + }); + response.end(); +}); + +const dirname = path.dirname(fileURLToPath(import.meta.url)); +const distPath = path.resolve(dirname, "../dist"); + +app.use(express.static(distPath)); +app.use((request, response, next) => { + if (request.path.startsWith("/api")) { + next(); + return; + } + + const indexPath = path.join(distPath, "index.html"); + response.sendFile(indexPath, (error) => { + if (error) { + next(); + } + }); +}); + +app.listen(port, () => { + console.log(`Face to API server listening on http://127.0.0.1:${port}`); +}); diff --git a/server/modelConfigStore.ts b/server/modelConfigStore.ts new file mode 100644 index 0000000..28ec80e --- /dev/null +++ b/server/modelConfigStore.ts @@ -0,0 +1,121 @@ +import fs from "node:fs"; +import path from "node:path"; + +export type SavedModelConfig = { + baseUrl?: string; + model?: string; + apiKey?: string; + enabled?: boolean; + updatedAt?: string; +}; + +type ConfigFile = { + version: 1; + models: Record; +}; + +export type SaveModelConfigInput = { + baseUrl?: string; + model?: string; + apiKey?: string; + enabled?: boolean; + clearApiKey?: boolean; +}; + +const defaultConfigPath = () => + path.resolve(process.cwd(), process.env.MODEL_CONFIG_PATH?.trim() || ".face-to-api/model-configs.json"); + +let cache: ConfigFile | undefined; + +const emptyStore = (): ConfigFile => ({ version: 1, models: {} }); + +const readStore = (): ConfigFile => { + if (cache) { + return cache; + } + + const filePath = defaultConfigPath(); + if (!fs.existsSync(filePath)) { + cache = emptyStore(); + return cache; + } + + try { + const parsed = JSON.parse(fs.readFileSync(filePath, "utf-8")) as ConfigFile; + cache = { + version: 1, + models: parsed.models ?? {} + }; + return cache; + } catch { + cache = emptyStore(); + return cache; + } +}; + +const writeStore = (store: ConfigFile) => { + const filePath = defaultConfigPath(); + fs.mkdirSync(path.dirname(filePath), { recursive: true }); + fs.writeFileSync(filePath, `${JSON.stringify(store, null, 2)}\n`); + cache = store; +}; + +const trimOrUndefined = (value?: string) => { + const trimmed = value?.trim(); + return trimmed ? trimmed : undefined; +}; + +export const getSavedModelConfig = (modelId: string): SavedModelConfig | undefined => { + const saved = readStore().models[modelId]; + return saved ? { ...saved } : undefined; +}; + +export const saveModelConfig = (modelId: string, input: SaveModelConfigInput) => { + const store = readStore(); + const existing = store.models[modelId] ?? {}; + const next: SavedModelConfig = { ...existing }; + const baseUrl = trimOrUndefined(input.baseUrl); + const model = trimOrUndefined(input.model); + const apiKey = trimOrUndefined(input.apiKey); + + if (input.baseUrl !== undefined) { + if (baseUrl) { + next.baseUrl = baseUrl; + } else { + delete next.baseUrl; + } + } + + if (input.model !== undefined) { + if (model) { + next.model = model; + } else { + delete next.model; + } + } + + if (input.clearApiKey) { + delete next.apiKey; + } else if (apiKey) { + next.apiKey = apiKey; + } + + if (input.enabled !== undefined) { + next.enabled = input.enabled; + } + + next.updatedAt = new Date().toISOString(); + store.models[modelId] = next; + writeStore(store); + + return { ...next }; +}; + +export const maskApiKey = (apiKey?: string) => { + if (!apiKey) { + return ""; + } + + const tail = apiKey.slice(-4); + return `•••• ${tail}`; +}; diff --git a/server/modelRegistry.ts b/server/modelRegistry.ts new file mode 100644 index 0000000..137e816 --- /dev/null +++ b/server/modelRegistry.ts @@ -0,0 +1,261 @@ +export type ProviderKind = "openai-compatible" | "anthropic" | "gemini"; + +export type ProviderId = + | "deepseek" + | "zhipu" + | "openai" + | "anthropic" + | "gemini" + | "custom-openai"; + +export type ModelProvider = { + id: ProviderId; + name: string; + kind: ProviderKind; + baseUrl?: string; + apiKeyEnv: string; + apiKey?: string; + configured: boolean; +}; + +export type ChatModel = { + id: string; + label: string; + providerId: ProviderId; + providerName: string; + providerKind: ProviderKind; + model: string; + baseUrl: string; + enabled: boolean; + configured: boolean; + apiKeyConfigured: boolean; + apiKeyPreview: string; + apiKeySource: "model" | "provider-env" | "none"; + configUpdatedAt?: string; + accent: "red" | "green" | "blue" | "gold" | "ink"; +}; + +import { getSavedModelConfig, maskApiKey } from "./modelConfigStore.js"; + +const env = (key: string, fallback = "") => process.env[key]?.trim() || fallback; + +export const providers = (): ModelProvider[] => [ + { + id: "deepseek", + name: "DeepSeek", + kind: "openai-compatible", + baseUrl: env("DEEPSEEK_BASE_URL", "https://api.deepseek.com"), + apiKeyEnv: "DEEPSEEK_API_KEY", + configured: Boolean(env("DEEPSEEK_API_KEY")) + }, + { + id: "zhipu", + name: "Zhipu GLM", + kind: "openai-compatible", + baseUrl: env("ZHIPU_BASE_URL", "https://open.bigmodel.cn/api/paas/v4"), + apiKeyEnv: "ZHIPU_API_KEY", + configured: Boolean(env("ZHIPU_API_KEY")) + }, + { + id: "openai", + name: "OpenAI", + kind: "openai-compatible", + baseUrl: env("OPENAI_BASE_URL", "https://api.openai.com/v1"), + apiKeyEnv: "OPENAI_API_KEY", + configured: Boolean(env("OPENAI_API_KEY")) + }, + { + id: "anthropic", + name: "Anthropic", + kind: "anthropic", + baseUrl: "https://api.anthropic.com/v1", + apiKeyEnv: "ANTHROPIC_API_KEY", + configured: Boolean(env("ANTHROPIC_API_KEY")) + }, + { + id: "gemini", + name: "Google Gemini", + kind: "gemini", + baseUrl: "https://generativelanguage.googleapis.com/v1beta", + apiKeyEnv: "GEMINI_API_KEY", + configured: Boolean(env("GEMINI_API_KEY")) + } +]; + +const resolveModel = ( + model: Omit< + ChatModel, + | "providerName" + | "providerKind" + | "configured" + | "baseUrl" + | "enabled" + | "apiKeyConfigured" + | "apiKeyPreview" + | "apiKeySource" + >, + provider: ModelProvider +): ChatModel => { + const saved = getSavedModelConfig(model.id); + const envApiKey = env(provider.apiKeyEnv); + const apiKey = saved?.apiKey || envApiKey; + const apiKeySource = saved?.apiKey ? "model" : envApiKey ? "provider-env" : "none"; + + return { + ...model, + providerName: provider.name, + providerKind: provider.kind, + model: saved?.model || model.model, + baseUrl: saved?.baseUrl || provider.baseUrl || "", + enabled: saved?.enabled ?? true, + configured: Boolean(apiKey), + apiKeyConfigured: Boolean(apiKey), + apiKeyPreview: maskApiKey(apiKey), + apiKeySource, + configUpdatedAt: saved?.updatedAt + }; +}; + +export const registry = (): ChatModel[] => { + const providerMap = new Map(providers().map((provider) => [provider.id, provider])); + const baseModels: Array< + Omit< + ChatModel, + | "providerName" + | "providerKind" + | "configured" + | "baseUrl" + | "enabled" + | "apiKeyConfigured" + | "apiKeyPreview" + | "apiKeySource" + > + > = [ + { + id: "deepseek-v4-pro", + label: "DeepSeekV4-pro", + providerId: "deepseek", + model: env("DEEPSEEK_MODEL_V4_PRO", "DeepSeekV4-pro"), + accent: "red" + }, + { + id: "deepseek-v4-flash", + label: "DeepSeekV4-flash", + providerId: "deepseek", + model: env("DEEPSEEK_MODEL_V4_FLASH", "DeepSeekV4-flash"), + accent: "red" + }, + { + id: "glm-5-1", + label: "GLM5.1", + providerId: "zhipu", + model: env("ZHIPU_MODEL_GLM_5_1", "GLM5.1"), + accent: "green" + }, + { + id: "gpt-5-5", + label: "GPT-5.5", + providerId: "openai", + model: env("OPENAI_MODEL_GPT_5_5", "gpt-5.5"), + accent: "blue" + }, + { + id: "claude-opus-4-7", + label: "Claude Opus 4.7", + providerId: "anthropic", + model: env("ANTHROPIC_MODEL_CLAUDE_OPUS_4_7", "claude-opus-4.7"), + accent: "gold" + }, + { + id: "gemini-3-1-pro", + label: "Gemini-3.1-pro", + providerId: "gemini", + model: env("GEMINI_MODEL_3_1_PRO", "Gemini-3.1-pro"), + accent: "ink" + }, + { + id: "gemini-3-5-flash", + label: "gemini3.5-flash", + providerId: "gemini", + model: env("GEMINI_MODEL_3_5_FLASH", "gemini3.5-flash"), + accent: "ink" + } + ]; + + const models = baseModels.map((model) => { + const provider = providerMap.get(model.providerId); + if (!provider) { + throw new Error(`Missing provider for ${model.id}`); + } + + return resolveModel(model, provider); + }); + + const customIds = env("CUSTOM_OPENAI_MODEL_IDS") + .split(",") + .map((value) => value.trim()) + .filter(Boolean); + + if (customIds.length && env("CUSTOM_OPENAI_BASE_URL")) { + const customConfigured = Boolean(env("CUSTOM_OPENAI_API_KEY")); + models.push( + ...customIds.map((modelId) => + resolveModel( + { + id: `custom-${modelId.toLowerCase().replace(/[^a-z0-9]+/g, "-")}`, + label: modelId, + providerId: "custom-openai" as const, + model: modelId, + configUpdatedAt: undefined, + accent: "blue" as const + }, + { + id: "custom-openai", + name: env("CUSTOM_OPENAI_NAME", "Custom OpenAI-compatible"), + kind: "openai-compatible", + baseUrl: env("CUSTOM_OPENAI_BASE_URL"), + apiKeyEnv: "CUSTOM_OPENAI_API_KEY", + configured: customConfigured + } + ) + ) + ); + } + + return models; +}; + +export const findModel = (modelId: string) => registry().find((model) => model.id === modelId); + +export const providerForModel = (model: ChatModel): ModelProvider => { + const saved = getSavedModelConfig(model.id); + + if (model.providerId === "custom-openai") { + const envApiKey = env("CUSTOM_OPENAI_API_KEY"); + return { + id: "custom-openai", + name: env("CUSTOM_OPENAI_NAME", "Custom OpenAI-compatible"), + kind: "openai-compatible", + baseUrl: saved?.baseUrl || env("CUSTOM_OPENAI_BASE_URL"), + apiKeyEnv: "CUSTOM_OPENAI_API_KEY", + apiKey: saved?.apiKey, + configured: Boolean(saved?.apiKey || envApiKey) + }; + } + + const provider = providers().find((item) => item.id === model.providerId); + if (!provider) { + throw new Error(`Provider not found for ${model.label}`); + } + + const envApiKey = env(provider.apiKeyEnv); + + return { + ...provider, + baseUrl: saved?.baseUrl || provider.baseUrl, + apiKey: saved?.apiKey, + configured: Boolean(saved?.apiKey || envApiKey) + }; +}; + +export const apiKeyForProvider = (provider: ModelProvider) => provider.apiKey || env(provider.apiKeyEnv); diff --git a/server/providerClients.ts b/server/providerClients.ts new file mode 100644 index 0000000..6497b1a --- /dev/null +++ b/server/providerClients.ts @@ -0,0 +1,618 @@ +import type { ChatModel, ModelProvider } from "./modelRegistry.js"; +import { apiKeyForProvider } from "./modelRegistry.js"; +import { normalizeUsage, type Usage } from "./tokens.js"; + +export type ChatRequest = { + model: ChatModel; + provider: ModelProvider; + systemPrompt?: string; + prompt: string; + temperature: number; + maxTokens: number; +}; + +export type ChatResponse = { + output: string; + reasoning?: string; + usage: Usage; + rawModel: string; +}; + +export type StreamDelta = { + channel: "reasoning" | "output"; + text: string; +}; + +export type ChatStreamRequest = ChatRequest & { + onDelta: (delta: StreamDelta) => void; + signal?: AbortSignal; +}; + +type OpenAIResponse = { + choices?: Array<{ message?: { content?: string }; text?: string }>; + usage?: { + prompt_tokens?: number; + completion_tokens?: number; + total_tokens?: number; + input_tokens?: number; + output_tokens?: number; + }; +}; + +type OpenAIStreamDelta = { + content?: string; + reasoning?: string; + reasoning_content?: string; + thinking?: string; + reasoning_details?: Array<{ text?: string; content?: string }>; +}; + +type OpenAIStreamChunk = { + choices?: Array<{ + delta?: OpenAIStreamDelta; + }>; + usage?: OpenAIResponse["usage"]; +}; + +type AnthropicResponse = { + content?: Array<{ type?: string; text?: string }>; + usage?: { + input_tokens?: number; + output_tokens?: number; + }; +}; + +type AnthropicStreamEvent = { + type?: string; + content_block?: { + type?: string; + text?: string; + thinking?: string; + }; + delta?: { + type?: string; + text?: string; + thinking?: string; + }; + message?: { + usage?: { + input_tokens?: number; + output_tokens?: number; + }; + }; + usage?: { + input_tokens?: number; + output_tokens?: number; + }; +}; + +type GeminiResponse = { + candidates?: Array<{ + content?: { + parts?: Array<{ text?: string }>; + }; + }>; + usageMetadata?: { + promptTokenCount?: number; + candidatesTokenCount?: number; + totalTokenCount?: number; + }; +}; + +type GeminiStreamChunk = GeminiResponse; + +const readErrorBody = async (response: Response) => { + const text = await response.text(); + if (!text) { + return response.statusText; + } + + try { + const json = JSON.parse(text) as { error?: { message?: string }; message?: string }; + return json.error?.message ?? json.message ?? text; + } catch { + return text; + } +}; + +const postJson = async ( + url: string, + headers: Record, + body: unknown +): Promise => { + const response = await fetch(url, { + method: "POST", + headers: { + "content-type": "application/json", + ...headers + }, + body: JSON.stringify(body) + }); + + if (!response.ok) { + throw new Error(await readErrorBody(response)); + } + + return (await response.json()) as T; +}; + +const postJsonStream = async ( + url: string, + headers: Record, + body: unknown, + signal?: AbortSignal +) => { + const response = await fetch(url, { + method: "POST", + headers: { + "content-type": "application/json", + ...headers + }, + body: JSON.stringify(body), + signal + }); + + if (!response.ok) { + throw new Error(await readErrorBody(response)); + } + + if (!response.body) { + throw new Error("Provider returned an empty stream"); + } + + return response; +}; + +const readSse = async ( + response: Response, + onEvent: (event: { event?: string; data: string }) => void +) => { + const reader = response.body?.getReader(); + if (!reader) { + throw new Error("Provider stream is not readable"); + } + + const decoder = new TextDecoder(); + let buffer = ""; + let eventName = ""; + let dataLines: string[] = []; + + const flush = () => { + if (!dataLines.length) { + eventName = ""; + return; + } + + onEvent({ + event: eventName || undefined, + data: dataLines.join("\n") + }); + eventName = ""; + dataLines = []; + }; + + const handleLine = (rawLine: string) => { + const line = rawLine.endsWith("\r") ? rawLine.slice(0, -1) : rawLine; + if (!line) { + flush(); + return; + } + + if (line.startsWith("event:")) { + eventName = line.slice(6).trim(); + return; + } + + if (line.startsWith("data:")) { + dataLines.push(line.slice(5).trimStart()); + return; + } + + if (line.trim().startsWith("{")) { + onEvent({ data: line.trim() }); + } + }; + + while (true) { + const { value, done } = await reader.read(); + if (done) { + break; + } + + buffer += decoder.decode(value, { stream: true }); + const lines = buffer.split("\n"); + buffer = lines.pop() ?? ""; + for (const line of lines) { + handleLine(line); + } + } + + buffer += decoder.decode(); + if (buffer) { + handleLine(buffer); + } + flush(); +}; + +const endpoint = (provider: ModelProvider, path: string) => { + const baseUrl = provider.baseUrl?.replace(/\/$/, ""); + if (!baseUrl) { + throw new Error(`${provider.name} base URL is not configured`); + } + + return `${baseUrl}${path}`; +}; + +const composePrompt = (systemPrompt: string | undefined, prompt: string) => + [systemPrompt, prompt].filter(Boolean).join("\n\n"); + +const openAICompatibleMessages = (systemPrompt: string | undefined, prompt: string) => [ + ...(systemPrompt ? [{ role: "system", content: systemPrompt }] : []), + { role: "user", content: prompt } +]; + +export const callOpenAICompatible = async ({ + provider, + model, + systemPrompt, + prompt, + temperature, + maxTokens +}: ChatRequest): Promise => { + const apiKey = apiKeyForProvider(provider); + if (!apiKey) { + throw new Error(`${provider.name} API key is not configured (${provider.apiKeyEnv})`); + } + + const json = await postJson( + endpoint(provider, "/chat/completions"), + { authorization: `Bearer ${apiKey}` }, + { + model: model.model, + messages: openAICompatibleMessages(systemPrompt, prompt), + temperature, + max_tokens: maxTokens + } + ); + + const output = json.choices?.[0]?.message?.content ?? json.choices?.[0]?.text ?? ""; + const usage = normalizeUsage(composePrompt(systemPrompt, prompt), output, { + inputTokens: json.usage?.prompt_tokens ?? json.usage?.input_tokens, + outputTokens: json.usage?.completion_tokens ?? json.usage?.output_tokens, + totalTokens: json.usage?.total_tokens, + estimated: !json.usage + }); + + return { output, usage, rawModel: model.model }; +}; + +const reasoningTextFromDelta = (delta?: OpenAIStreamDelta) => { + const details = delta?.reasoning_details + ?.map((detail) => detail.text ?? detail.content ?? "") + .join(""); + return delta?.reasoning_content ?? delta?.reasoning ?? delta?.thinking ?? details ?? ""; +}; + +export const streamOpenAICompatible = async ({ + provider, + model, + systemPrompt, + prompt, + temperature, + maxTokens, + onDelta, + signal +}: ChatStreamRequest): Promise => { + const apiKey = apiKeyForProvider(provider); + if (!apiKey) { + throw new Error(`${provider.name} API key is not configured (${provider.apiKeyEnv})`); + } + + let output = ""; + let reasoning = ""; + let usage: OpenAIResponse["usage"] | undefined; + + const response = await postJsonStream( + endpoint(provider, "/chat/completions"), + { authorization: `Bearer ${apiKey}` }, + { + model: model.model, + messages: openAICompatibleMessages(systemPrompt, prompt), + temperature, + max_tokens: maxTokens, + stream: true, + stream_options: { include_usage: true } + }, + signal + ); + + await readSse(response, ({ data }) => { + if (data === "[DONE]") { + return; + } + + const chunk = JSON.parse(data) as OpenAIStreamChunk; + usage = chunk.usage ?? usage; + const delta = chunk.choices?.[0]?.delta; + const reasoningDelta = reasoningTextFromDelta(delta); + const outputDelta = delta?.content ?? ""; + + if (reasoningDelta) { + reasoning += reasoningDelta; + onDelta({ channel: "reasoning", text: reasoningDelta }); + } + + if (outputDelta) { + output += outputDelta; + onDelta({ channel: "output", text: outputDelta }); + } + }); + + return { + output, + reasoning, + usage: normalizeUsage(composePrompt(systemPrompt, prompt), output, { + inputTokens: usage?.prompt_tokens ?? usage?.input_tokens, + outputTokens: usage?.completion_tokens ?? usage?.output_tokens, + totalTokens: usage?.total_tokens, + estimated: !usage + }), + rawModel: model.model + }; +}; + +export const callAnthropic = async ({ + provider, + model, + systemPrompt, + prompt, + temperature, + maxTokens +}: ChatRequest): Promise => { + const apiKey = apiKeyForProvider(provider); + if (!apiKey) { + throw new Error(`${provider.name} API key is not configured (${provider.apiKeyEnv})`); + } + + const json = await postJson( + endpoint(provider, "/messages"), + { + "x-api-key": apiKey, + "anthropic-version": "2023-06-01" + }, + { + model: model.model, + system: systemPrompt || undefined, + messages: [{ role: "user", content: prompt }], + temperature, + max_tokens: maxTokens + } + ); + + const output = json.content?.map((part) => part.text ?? "").join("\n").trim() ?? ""; + const usage = normalizeUsage(composePrompt(systemPrompt, prompt), output, { + inputTokens: json.usage?.input_tokens, + outputTokens: json.usage?.output_tokens, + estimated: !json.usage + }); + + return { output, usage, rawModel: model.model }; +}; + +export const streamAnthropic = async ({ + provider, + model, + systemPrompt, + prompt, + temperature, + maxTokens, + onDelta, + signal +}: ChatStreamRequest): Promise => { + const apiKey = apiKeyForProvider(provider); + if (!apiKey) { + throw new Error(`${provider.name} API key is not configured (${provider.apiKeyEnv})`); + } + + let output = ""; + let reasoning = ""; + let inputTokens: number | undefined; + let outputTokens: number | undefined; + + const response = await postJsonStream( + endpoint(provider, "/messages"), + { + "x-api-key": apiKey, + "anthropic-version": "2023-06-01" + }, + { + model: model.model, + system: systemPrompt || undefined, + messages: [{ role: "user", content: prompt }], + temperature, + max_tokens: maxTokens, + stream: true + }, + signal + ); + + await readSse(response, ({ data }) => { + const event = JSON.parse(data) as AnthropicStreamEvent; + inputTokens = event.message?.usage?.input_tokens ?? event.usage?.input_tokens ?? inputTokens; + outputTokens = event.message?.usage?.output_tokens ?? event.usage?.output_tokens ?? outputTokens; + + const startText = + event.type === "content_block_start" && event.content_block?.type === "text" + ? event.content_block.text ?? "" + : ""; + const startThinking = + event.type === "content_block_start" && event.content_block?.type === "thinking" + ? event.content_block.thinking ?? "" + : ""; + const outputDelta = event.delta?.type === "text_delta" ? event.delta.text ?? "" : ""; + const reasoningDelta = + event.delta?.type === "thinking_delta" ? event.delta.thinking ?? "" : ""; + + if (startThinking || reasoningDelta) { + const text = startThinking || reasoningDelta; + reasoning += text; + onDelta({ channel: "reasoning", text }); + } + + if (startText || outputDelta) { + const text = startText || outputDelta; + output += text; + onDelta({ channel: "output", text }); + } + }); + + return { + output, + reasoning, + usage: normalizeUsage(composePrompt(systemPrompt, prompt), output, { + inputTokens, + outputTokens, + estimated: inputTokens === undefined && outputTokens === undefined + }), + rawModel: model.model + }; +}; + +export const callGemini = async ({ + provider, + model, + systemPrompt, + prompt, + temperature, + maxTokens +}: ChatRequest): Promise => { + const apiKey = apiKeyForProvider(provider); + if (!apiKey) { + throw new Error(`${provider.name} API key is not configured (${provider.apiKeyEnv})`); + } + + const baseUrl = provider.baseUrl?.replace(/\/$/, ""); + const url = `${baseUrl}/models/${encodeURIComponent(model.model)}:generateContent?key=${encodeURIComponent(apiKey)}`; + const json = await postJson( + url, + {}, + { + systemInstruction: systemPrompt ? { parts: [{ text: systemPrompt }] } : undefined, + contents: [{ role: "user", parts: [{ text: prompt }] }], + generationConfig: { + temperature, + maxOutputTokens: maxTokens + } + } + ); + + const output = + json.candidates?.[0]?.content?.parts?.map((part) => part.text ?? "").join("\n").trim() ?? ""; + const usage = normalizeUsage(composePrompt(systemPrompt, prompt), output, { + inputTokens: json.usageMetadata?.promptTokenCount, + outputTokens: json.usageMetadata?.candidatesTokenCount, + totalTokens: json.usageMetadata?.totalTokenCount, + estimated: !json.usageMetadata + }); + + return { output, usage, rawModel: model.model }; +}; + +export const streamGemini = async ({ + provider, + model, + systemPrompt, + prompt, + temperature, + maxTokens, + onDelta, + signal +}: ChatStreamRequest): Promise => { + const apiKey = apiKeyForProvider(provider); + if (!apiKey) { + throw new Error(`${provider.name} API key is not configured (${provider.apiKeyEnv})`); + } + + const baseUrl = provider.baseUrl?.replace(/\/$/, ""); + const url = `${baseUrl}/models/${encodeURIComponent(model.model)}:streamGenerateContent?alt=sse&key=${encodeURIComponent(apiKey)}`; + let output = ""; + let reasoning = ""; + let usage: GeminiResponse["usageMetadata"] | undefined; + + const response = await postJsonStream( + url, + {}, + { + systemInstruction: systemPrompt ? { parts: [{ text: systemPrompt }] } : undefined, + contents: [{ role: "user", parts: [{ text: prompt }] }], + generationConfig: { + temperature, + maxOutputTokens: maxTokens + } + }, + signal + ); + + await readSse(response, ({ data }) => { + const chunk = JSON.parse(data) as GeminiStreamChunk; + usage = chunk.usageMetadata ?? usage; + const parts = chunk.candidates?.[0]?.content?.parts ?? []; + + for (const part of parts) { + const text = part.text ?? ""; + if (!text) { + continue; + } + + if ("thought" in part && part.thought === true) { + reasoning += text; + onDelta({ channel: "reasoning", text }); + } else { + output += text; + onDelta({ channel: "output", text }); + } + } + }); + + return { + output, + reasoning, + usage: normalizeUsage(composePrompt(systemPrompt, prompt), output, { + inputTokens: usage?.promptTokenCount, + outputTokens: usage?.candidatesTokenCount, + totalTokens: usage?.totalTokenCount, + estimated: !usage + }), + rawModel: model.model + }; +}; + +export const callProvider = async (request: ChatRequest): Promise => { + switch (request.provider.kind) { + case "openai-compatible": + return callOpenAICompatible(request); + case "anthropic": + return callAnthropic(request); + case "gemini": + return callGemini(request); + default: { + const provider: never = request.provider.kind; + throw new Error(`Unsupported provider kind: ${provider}`); + } + } +}; + +export const streamProvider = async (request: ChatStreamRequest): Promise => { + switch (request.provider.kind) { + case "openai-compatible": + return streamOpenAICompatible(request); + case "anthropic": + return streamAnthropic(request); + case "gemini": + return streamGemini(request); + default: { + const provider: never = request.provider.kind; + throw new Error(`Unsupported provider kind: ${provider}`); + } + } +}; diff --git a/server/template.ts b/server/template.ts new file mode 100644 index 0000000..4130df1 --- /dev/null +++ b/server/template.ts @@ -0,0 +1,22 @@ +import type { ChatModel } from "./modelRegistry.js"; + +export type TemplateContext = { + draw: number; + model: ChatModel; + startedAt: Date; +}; + +export const renderPrompt = (template: string, context: TemplateContext) => { + const values: Record = { + draw: String(context.draw), + model: context.model.label, + provider: context.model.providerName, + now: context.startedAt.toLocaleString("zh-CN", { hour12: false }), + timestamp: context.startedAt.toISOString() + }; + + return template.replace(/\{\{\s*([a-zA-Z0-9_-]+)\s*\}\}/g, (match, key: string) => { + return values[key] ?? match; + }); +}; + diff --git a/server/tokens.ts b/server/tokens.ts new file mode 100644 index 0000000..996ab17 --- /dev/null +++ b/server/tokens.ts @@ -0,0 +1,32 @@ +export type Usage = { + inputTokens: number; + outputTokens: number; + totalTokens: number; + estimated: boolean; +}; + +export const estimateTokens = (text: string) => { + if (!text.trim()) { + return 0; + } + + const ascii = text.match(/[\x00-\x7F]/g)?.length ?? 0; + const nonAscii = text.length - ascii; + return Math.max(1, Math.ceil(ascii / 4 + nonAscii / 1.7)); +}; + +export const normalizeUsage = ( + prompt: string, + output: string, + usage?: Partial | null +): Usage => { + const inputTokens = usage?.inputTokens ?? estimateTokens(prompt); + const outputTokens = usage?.outputTokens ?? estimateTokens(output); + + return { + inputTokens, + outputTokens, + totalTokens: usage?.totalTokens ?? inputTokens + outputTokens, + estimated: usage?.estimated ?? !usage + }; +}; diff --git a/src/main.tsx b/src/main.tsx new file mode 100644 index 0000000..aa8ee94 --- /dev/null +++ b/src/main.tsx @@ -0,0 +1,1140 @@ +import React from "react"; +import { createRoot } from "react-dom/client"; +import { + Activity, + AlertTriangle, + BadgeCheck, + Check, + Clipboard, + Clock3, + Copy, + Gauge, + KeyRound, + Layers3, + Loader2, + MessageSquare, + Play, + RefreshCcw, + Save, + Settings2, + ShieldCheck, + SlidersHorizontal, + Square, + TerminalSquare, + Trash2, + Zap +} from "lucide-react"; +import "./styles.css"; + +type Accent = "red" | "green" | "blue" | "gold" | "ink"; + +type ChatModel = { + id: string; + label: string; + providerId: string; + providerName: string; + providerKind: string; + model: string; + baseUrl: string; + enabled: boolean; + configured: boolean; + apiKeyConfigured: boolean; + apiKeyPreview: string; + apiKeySource: "model" | "provider-env" | "none"; + configUpdatedAt?: string; + accent: Accent; +}; + +type Usage = { + inputTokens: number; + outputTokens: number; + totalTokens: number; + estimated: boolean; +}; + +type RunResult = { + id: string; + ok: boolean; + status: "streaming" | "done" | "error" | "stopped"; + draw: number; + prompt: string; + systemPrompt: string; + userPrompt: string; + reasoning: string; + output: string; + error?: string; + modelId: string; + modelLabel: string; + providerName: string; + rawModel: string; + durationMs: number; + usage: Usage; +}; + +type RunResponse = { + startedAt: string; + finishedAt: string; + results: RunResult[]; +}; + +type RunStreamEvent = + | { + type: "run_start"; + startedAt: string; + totalJobs: number; + } + | { + type: "card_start"; + id: string; + draw: number; + prompt: string; + systemPrompt?: string; + userPrompt?: string; + modelId: string; + modelLabel: string; + providerName: string; + rawModel: string; + } + | { + type: "delta"; + id: string; + channel: "reasoning" | "output"; + text: string; + } + | { + type: "card_end"; + id: string; + ok: boolean; + output: string; + reasoning: string; + error?: string; + rawModel: string; + durationMs: number; + usage: Usage; + } + | { + type: "run_end"; + startedAt: string; + finishedAt: string; + }; + +type ViewMode = "chat" | "config"; + +type ConfigDraft = { + baseUrl: string; + model: string; + apiKey: string; + enabled: boolean; +}; + +const defaultSystemTemplate = "你是一个严谨但有创造力的产品策略助手。"; + +const defaultUserTemplate = + "请基于第 {{draw}} 次抽卡,为 {{model}} 输出一个 AI 对话系统的首屏功能建议。要求:\n1. 先给一句结论\n2. 列出 3 个关键界面模块\n3. 给出一个容易忽略的风险"; + +const numberFormat = new Intl.NumberFormat("zh-CN"); + +function App() { + const [models, setModels] = React.useState([]); + const [selectedModelIds, setSelectedModelIds] = React.useState([]); + const [view, setView] = React.useState("chat"); + const [systemTemplate, setSystemTemplate] = React.useState(defaultSystemTemplate); + const [userTemplate, setUserTemplate] = React.useState(defaultUserTemplate); + const [draws, setDraws] = React.useState(3); + const [temperature, setTemperature] = React.useState(0.8); + const [maxTokens, setMaxTokens] = React.useState(1024); + const [configDrafts, setConfigDrafts] = React.useState>({}); + const [results, setResults] = React.useState([]); + const [runWindow, setRunWindow] = React.useState<{ startedAt: string; finishedAt: string }>(); + const [loading, setLoading] = React.useState(false); + const [savingModelId, setSavingModelId] = React.useState(""); + const [savedModelId, setSavedModelId] = React.useState(""); + const [loadError, setLoadError] = React.useState(""); + const [copiedId, setCopiedId] = React.useState(""); + const runAbortRef = React.useRef(null); + + React.useEffect(() => { + void loadModels(); + }, []); + + const configuredCount = models.filter((model) => model.configured).length; + const visibleModels = models.filter((model) => model.enabled); + const selectedModels = visibleModels.filter((model) => selectedModelIds.includes(model.id)); + const selectedConfiguredCount = selectedModels.filter((model) => model.configured).length; + const totalJobs = selectedModelIds.length * draws; + const tokenTotals = results.reduce( + (accumulator, item) => { + accumulator.input += item.usage.inputTokens; + accumulator.output += item.usage.outputTokens; + accumulator.total += item.usage.totalTokens; + return accumulator; + }, + { input: 0, output: 0, total: 0 } + ); + const okCount = results.filter((item) => item.ok && item.status === "done").length; + const runningCount = results.filter((item) => item.status === "streaming").length; + + async function loadModels(options?: { preserveSelection?: boolean }) { + setLoadError(""); + try { + const response = await fetch("/api/models"); + if (!response.ok) { + throw new Error("模型列表加载失败"); + } + + const data = (await response.json()) as { models: ChatModel[] }; + setModels(data.models); + setConfigDrafts((current) => { + const next: Record = {}; + for (const model of data.models) { + next[model.id] = { + baseUrl: model.baseUrl, + model: model.model, + enabled: model.enabled, + apiKey: current[model.id]?.apiKey ?? "" + }; + } + return next; + }); + + if (options?.preserveSelection) { + setSelectedModelIds((current) => + current.filter((modelId) => + data.models.some((model) => model.id === modelId && model.enabled) + ) + ); + } else { + const enabledModels = data.models.filter((model) => model.enabled); + const preferred = enabledModels.filter((model) => model.configured).map((model) => model.id); + setSelectedModelIds( + preferred.length ? preferred : enabledModels.slice(0, 3).map((model) => model.id) + ); + } + } catch (error) { + setLoadError(error instanceof Error ? error.message : "模型列表加载失败"); + } + } + + const updateConfigDraft = (modelId: string, patch: Partial) => { + setConfigDrafts((current) => { + const existing = current[modelId] ?? { baseUrl: "", model: "", apiKey: "", enabled: true }; + return { + ...current, + [modelId]: { + ...existing, + ...patch + } + }; + }); + }; + + const saveConfig = async ( + modelId: string, + clearApiKey = false, + overrides: Partial = {} + ) => { + const draftBase = configDrafts[modelId]; + if (!draftBase) { + return; + } + const draft = { ...draftBase, ...overrides }; + + setSavingModelId(modelId); + setSavedModelId(""); + setLoadError(""); + + try { + const response = await fetch(`/api/model-configs/${encodeURIComponent(modelId)}`, { + method: "PUT", + headers: { "content-type": "application/json" }, + body: JSON.stringify({ + baseUrl: draft.baseUrl, + model: draft.model, + enabled: draft.enabled, + apiKey: clearApiKey ? undefined : draft.apiKey, + clearApiKey + }) + }); + + if (!response.ok) { + const text = await response.text(); + throw new Error(text || "配置保存失败"); + } + + const data = (await response.json()) as { model: ChatModel }; + setModels((current) => + current.map((model) => (model.id === data.model.id ? data.model : model)) + ); + setConfigDrafts((current) => ({ + ...current, + [data.model.id]: { + baseUrl: data.model.baseUrl, + model: data.model.model, + enabled: data.model.enabled, + apiKey: "" + } + })); + if (!data.model.enabled) { + setSelectedModelIds((current) => current.filter((modelId) => modelId !== data.model.id)); + } + setSavedModelId(data.model.id); + window.setTimeout(() => setSavedModelId(""), 1400); + } catch (error) { + setLoadError(error instanceof Error ? error.message : "配置保存失败"); + } finally { + setSavingModelId(""); + } + }; + + const toggleModel = (modelId: string) => { + if (!visibleModels.some((model) => model.id === modelId)) { + return; + } + + setSelectedModelIds((current) => + current.includes(modelId) ? current.filter((id) => id !== modelId) : [...current, modelId] + ); + }; + + const selectProvider = (providerName: string) => { + const providerModelIds = visibleModels + .filter((model) => model.providerName === providerName) + .map((model) => model.id); + const allSelected = providerModelIds.every((modelId) => selectedModelIds.includes(modelId)); + setSelectedModelIds((current) => + allSelected + ? current.filter((modelId) => !providerModelIds.includes(modelId)) + : [...new Set([...current, ...providerModelIds])] + ); + }; + + const runDraws = async () => { + if (!userTemplate.trim() || !selectedModelIds.length) { + return; + } + + runAbortRef.current?.abort(); + const controller = new AbortController(); + runAbortRef.current = controller; + setLoading(true); + setLoadError(""); + setResults([]); + setRunWindow(undefined); + + try { + const response = await fetch("/api/runs/stream", { + method: "POST", + signal: controller.signal, + headers: { "content-type": "application/json" }, + body: JSON.stringify({ + systemTemplate, + userTemplate, + modelIds: selectedModelIds, + draws, + temperature, + maxTokens + }) + }); + + if (!response.ok) { + const text = await response.text(); + throw new Error(text || "抽卡请求失败"); + } + + if (!response.body) { + throw new Error("流式响应为空"); + } + + const reader = response.body.getReader(); + const decoder = new TextDecoder(); + let buffer = ""; + + const handleEvent = (event: RunStreamEvent) => { + if (controller.signal.aborted) { + return; + } + + switch (event.type) { + case "run_start": + setRunWindow({ startedAt: event.startedAt, finishedAt: "" }); + return; + case "card_start": + setResults((current) => [ + ...current, + { + id: event.id, + ok: true, + status: "streaming", + draw: event.draw, + prompt: event.prompt, + systemPrompt: event.systemPrompt ?? "", + userPrompt: event.userPrompt ?? event.prompt, + reasoning: "", + output: "", + modelId: event.modelId, + modelLabel: event.modelLabel, + providerName: event.providerName, + rawModel: event.rawModel, + durationMs: 0, + usage: { + inputTokens: 0, + outputTokens: 0, + totalTokens: 0, + estimated: true + } + } + ]); + return; + case "delta": + setResults((current) => + current.map((item) => + item.id === event.id + ? { + ...item, + status: "streaming", + reasoning: + event.channel === "reasoning" ? item.reasoning + event.text : item.reasoning, + output: event.channel === "output" ? item.output + event.text : item.output + } + : item + ) + ); + return; + case "card_end": + setResults((current) => + current.map((item) => + item.id === event.id + ? { + ...item, + ok: event.ok, + status: event.ok ? "done" : "error", + reasoning: event.reasoning, + output: event.output, + error: event.error, + rawModel: event.rawModel, + durationMs: event.durationMs, + usage: event.usage + } + : item + ) + ); + return; + case "run_end": + setRunWindow({ startedAt: event.startedAt, finishedAt: event.finishedAt }); + return; + default: { + const neverEvent: never = event; + throw new Error(`未知流事件: ${JSON.stringify(neverEvent)}`); + } + } + }; + + const handleLine = (line: string) => { + const trimmed = line.trim(); + if (!trimmed) { + return; + } + + handleEvent(JSON.parse(trimmed) as RunStreamEvent); + }; + + while (true) { + const { value, done } = await reader.read(); + if (controller.signal.aborted) { + break; + } + + if (done) { + break; + } + + buffer += decoder.decode(value, { stream: true }); + const lines = buffer.split("\n"); + buffer = lines.pop() ?? ""; + for (const line of lines) { + handleLine(line); + } + } + + buffer += decoder.decode(); + handleLine(buffer); + } catch (error) { + if (controller.signal.aborted) { + markStreamingStopped(); + } else { + setLoadError(error instanceof Error ? error.message : "抽卡请求失败"); + } + } finally { + if (runAbortRef.current === controller) { + runAbortRef.current = null; + setLoading(false); + } + } + }; + + const markStreamingStopped = () => { + const stoppedAt = new Date().toISOString(); + setRunWindow((current) => + current ? { startedAt: current.startedAt, finishedAt: stoppedAt } : current + ); + setResults((current) => + current.map((item) => + item.status === "streaming" + ? { + ...item, + ok: false, + status: "stopped", + error: "已停止" + } + : item + ) + ); + }; + + const stopRun = () => { + if (!runAbortRef.current) { + return; + } + + runAbortRef.current.abort(); + runAbortRef.current = null; + setLoading(false); + markStreamingStopped(); + }; + + const copyResult = async (item: RunResult) => { + await navigator.clipboard.writeText(item.output || item.error || ""); + setCopiedId(item.id); + window.setTimeout(() => setCopiedId(""), 1200); + }; + + const providers = [...new Set(visibleModels.map((model) => model.providerName))]; + + return ( +
+
+
+
+

Face to API

+

模型抽卡台

+
+
+ + {configuredCount} +
+
+ +
+ + +
+ + {view === "chat" ? ( + <> +
+
+ 提示词模板 +
+
+