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"simple-concat": "^1.0.0" } }, + "node_modules/smart-buffer": { + "version": "4.2.0", + "resolved": "https://registry.npmjs.org/smart-buffer/-/smart-buffer-4.2.0.tgz", + "integrity": "sha512-94hK0Hh8rPqQl2xXc3HsaBoOXKV20MToPkcXvwbISWLEs+64sBq5kFgn2kJDHb1Pry9yrP0dxrCI9RRci7RXKg==", + "license": "MIT", + "engines": { + "node": ">= 6.0.0", + "npm": ">= 3.0.0" + } + }, + "node_modules/socks": { + "version": "2.8.8", + "resolved": "https://registry.npmjs.org/socks/-/socks-2.8.8.tgz", + "integrity": "sha512-NlGELfPrgX2f1TAAcz0WawlLn+0r3FyhhCRpFFK2CemXenPYvzMWWZINv3eDNo9ucdwme7oCHRY0Jnbs4aIkog==", + "license": "MIT", + "dependencies": { + "ip-address": "^10.1.1", + "smart-buffer": "^4.2.0" + }, + "engines": { + "node": ">= 10.0.0", + "npm": ">= 3.0.0" + } + }, + "node_modules/socks-proxy-agent": { + "version": "8.0.5", + "resolved": "https://registry.npmjs.org/socks-proxy-agent/-/socks-proxy-agent-8.0.5.tgz", + "integrity": 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"sha512-ums3KNd42PGyx5xaoVTO1mjU1bH3NpY4vsrVlnv9PNGqQj8wd7rJ6nEypLrJ7z5vxK5RP0yMLo6J/Gsm62DI5Q==", + "funding": [ + { + "type": "github", + "url": "https://github.com/sponsors/NaturalIntelligence" + } + ], + "license": "MIT" + }, "node_modules/supports-color": { "version": "8.1.1", "resolved": "https://registry.npmjs.org/supports-color/-/supports-color-8.1.1.tgz", @@ -2373,7 +4614,6 @@ "version": "2.8.1", "resolved": "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz", "integrity": "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==", - "dev": true, "license": "0BSD" }, "node_modules/tsx": { @@ -2421,6 +4661,12 @@ "node": ">= 0.6" } }, + "node_modules/typebox": { + "version": "1.1.38", + "resolved": "https://registry.npmjs.org/typebox/-/typebox-1.1.38.tgz", + "integrity": "sha512-pZ0aQPmMmXoUvSbeuWf/Hzsc+avNw/Zd6VeE8CFgkVGWyuHPJvqeJJDeJqLve+K70LvjYIoleGcoJHPT17cWoA==", + "license": "MIT" + }, "node_modules/typedarray": { "version": "0.0.6", "resolved": "https://registry.npmjs.org/typedarray/-/typedarray-0.0.6.tgz", @@ -2441,6 +4687,15 @@ "node": ">=14.17" } }, + "node_modules/undici": { + "version": "7.25.0", + "resolved": "https://registry.npmjs.org/undici/-/undici-7.25.0.tgz", + "integrity": "sha512-xXnp4kTyor2Zq+J1FfPI6Eq3ew5h6Vl0F/8d9XU5zZQf1tX9s2Su1/3PiMmUANFULpmksxkClamIZcaUqryHsQ==", + "license": "MIT", + "engines": { + "node": ">=20.18.1" + } + }, "node_modules/undici-types": { "version": "7.19.2", "resolved": "https://registry.npmjs.org/undici-types/-/undici-types-7.19.2.tgz", @@ -2480,6 +4735,15 @@ "node": ">= 0.8" } }, + "node_modules/web-streams-polyfill": { + "version": "3.3.3", + "resolved": "https://registry.npmjs.org/web-streams-polyfill/-/web-streams-polyfill-3.3.3.tgz", + "integrity": "sha512-d2JWLCivmZYTSIoge9MsgFCZrt571BikcWGYkjC1khllbTeDlGqZ2D8vD8E/lJa8WGWbb7Plm8/XJYV7IJHZZw==", + "license": "MIT", + "engines": { + "node": ">= 8" + } + }, "node_modules/wrap-ansi": { "version": "7.0.0", "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz", @@ -2569,11 +4833,18 @@ "resolved": "https://registry.npmjs.org/zod/-/zod-3.25.76.tgz", "integrity": "sha512-gzUt/qt81nXsFGKIFcC3YnfEAx5NkunCfnDlvuBSSFS02bcXu4Lmea0AFIUwbLWxWPx3d9p8S5QoaujKcNQxcQ==", "license": "MIT", - "optional": true, - "peer": true, "funding": { "url": "https://github.com/sponsors/colinhacks" } + }, + "node_modules/zod-to-json-schema": { + "version": "3.25.2", + "resolved": "https://registry.npmjs.org/zod-to-json-schema/-/zod-to-json-schema-3.25.2.tgz", + "integrity": "sha512-O/PgfnpT1xKSDeQYSCfRI5Gy3hPf91mKVDuYLUHZJMiDFptvP41MSnWofm8dnCm0256ZNfZIM7DSzuSMAFnjHA==", + "license": "ISC", + "peerDependencies": { + "zod": "^3.25.28 || ^4" + } } } } diff --git a/web/package.json b/web/package.json index 9257e68..4e8d533 100644 --- a/web/package.json +++ b/web/package.json @@ -12,6 +12,8 @@ }, "dependencies": { "@anthropic-ai/sdk": "^0.95.0", + "@earendil-works/pi-agent-core": "^0.74.0", + "@earendil-works/pi-ai": "^0.74.0", "@types/multer": "^2.1.0", "better-sqlite3": "^11.6.0", "cors": "^2.8.5", diff --git a/web/server/agent/index.ts b/web/server/agent/index.ts index 96baaac..b41725a 100644 --- a/web/server/agent/index.ts +++ b/web/server/agent/index.ts @@ -1,102 +1,12 @@ -import Anthropic from '@anthropic-ai/sdk'; -import OpenAI from 'openai'; -import { tools, ToolDefinition } from './tools/index'; -import { getDb } from '../db'; import fs from 'fs'; import path from 'path'; import { fileURLToPath } from 'url'; const __filename = fileURLToPath(import.meta.url); const __dirname = path.dirname(__filename); -const PROJECT_ROOT = path.resolve(__dirname, '..', '..', '..', '..'); - -export type Protocol = 'anthropic' | 'openai'; - -interface ApiConfig { - protocol: Protocol; - apiKey: string; - baseURL: string | undefined; - model: string; -} - -function getApiConfig(): ApiConfig { - const configRow = getDb().prepare('SELECT value FROM configs WHERE key = ?').get('api_keys') as { value: string } | undefined; - - let apiKey = process.env.ANTHROPIC_API_KEY || ''; - let baseURL: string | undefined; - let model = process.env.ANTHROPIC_MODEL || 'claude-sonnet-4-6'; - let protocol: Protocol = 'anthropic'; - - if (configRow) { - try { - const cfg = JSON.parse(configRow.value); - if (cfg.ANTHROPIC_AUTH_TOKEN) apiKey = cfg.ANTHROPIC_AUTH_TOKEN; - if (cfg.ANTHROPIC_BASE_URL) baseURL = cfg.ANTHROPIC_BASE_URL; - if (cfg.ANTHROPIC_MODEL) model = cfg.ANTHROPIC_MODEL; - if (cfg.PROTOCOL === 'openai') protocol = 'openai'; - } catch {} - } - - return { protocol, apiKey, baseURL, model }; -} - -function getAnthropicClient(): Anthropic { - const { apiKey, baseURL } = getApiConfig(); - return new Anthropic({ apiKey, baseURL }); -} - -function getOpenAIClient(): OpenAI { - const { apiKey, baseURL } = getApiConfig(); - return new OpenAI({ apiKey, baseURL: baseURL || 'https://api.openai.com/v1' }); -} +const PROJECT_ROOT = path.resolve(__dirname, '..', '..', '..'); export class VideoAgent { - private tools: ToolDefinition[]; - - constructor() { - this.tools = tools; - } - - getProtocol(): Protocol { - return getApiConfig().protocol; - } - - getModel(): string { - return getApiConfig().model; - } - - getAnthropicClient(): Anthropic { - return getAnthropicClient(); - } - - getOpenAIClient(): OpenAI { - return getOpenAIClient(); - } - - getAnthropicTools(): Anthropic.Tool[] { - return this.tools.map((t) => ({ - name: t.name, - description: t.description, - input_schema: t.input_schema, - })); - } - - getOpenAITools(): OpenAI.ChatCompletionTool[] { - return this.tools.map((t) => ({ - type: 'function' as const, - function: { - name: t.name, - description: t.description, - parameters: t.input_schema, - }, - })); - } - - async executeTool(name: string, params: Record): Promise { - const tool = this.tools.find((t) => t.name === name); - if (!tool) throw new Error(`Unknown tool: ${name}`); - return tool.execute(params); - } getSystemPrompt(): string { const accountsDir = path.join(PROJECT_ROOT, 'accounts'); diff --git a/web/server/agent/pi-bridge.ts b/web/server/agent/pi-bridge.ts new file mode 100644 index 0000000..45a53f6 --- /dev/null +++ b/web/server/agent/pi-bridge.ts @@ -0,0 +1,117 @@ +import { Agent } from '@earendil-works/pi-agent-core'; +import type { AgentEvent } from '@earendil-works/pi-agent-core'; +import { streamSimple } from '@earendil-works/pi-ai'; +import type { AssistantMessage } from '@earendil-works/pi-ai'; +import { WebSocket } from 'ws'; +import { createPiModel } from './pi-model'; +import { createPiTools } from './pi-tools'; +import { tools } from './tools/index'; +import { videoAgent } from './index'; +import { dbToPiMessages, saveUserMessage, saveAssistantMessage, saveToolResult, type DbMessage } from './pi-persist'; +import { getDb } from '../db'; + +interface RunContext { + currentAssistantMsgId: string | null; +} + +export async function runAgentChat(ws: WebSocket, convId: string, userContent: string) { + const userMsgId = saveUserMessage(convId, userContent); + ws.send(JSON.stringify({ type: 'message', data: { id: userMsgId, role: 'user', content: userContent } })); + + const msgCount = getDb().prepare('SELECT COUNT(*) as count FROM messages WHERE conversation_id = ?').get(convId) as { count: number }; + if (msgCount.count <= 1) { + const title = userContent.slice(0, 30) + (userContent.length > 30 ? '...' : ''); + getDb().prepare("UPDATE conversations SET title = ?, updated_at = datetime('now') WHERE id = ?").run(title, convId); + } + getDb().prepare("UPDATE conversations SET updated_at = datetime('now') WHERE id = ?").run(convId); + + const history = getDb().prepare( + 'SELECT * FROM messages WHERE conversation_id = ? AND id != ? ORDER BY created_at' + ).all(convId, userMsgId) as DbMessage[]; + const piMessages = dbToPiMessages(history); + + const { model, apiKey } = createPiModel(); + const piTools = createPiTools(tools); + + const agent = new Agent({ + initialState: { + systemPrompt: videoAgent.getSystemPrompt(), + model, + thinkingLevel: 'off', + tools: piTools, + messages: piMessages, + }, + streamFn: streamSimple, + getApiKey: () => apiKey, + }); + + const ctx: RunContext = { currentAssistantMsgId: null }; + + agent.subscribe((event: AgentEvent) => { + handleAgentEvent(ws, convId, event, ctx); + }); + + ws.send(JSON.stringify({ type: 'status', data: { status: 'thinking' } })); + + try { + await agent.prompt(userContent); + } catch (err) { + const errMsg = (err as Error).message; + console.error('[pi-bridge] Agent error:', errMsg); + ws.send(JSON.stringify({ + type: 'message', + data: { id: '', role: 'assistant', content: `抱歉，出错了：${errMsg}` }, + })); + } +} + +function handleAgentEvent(ws: WebSocket, convId: string, event: AgentEvent, ctx: RunContext) { + switch (event.type) { + case 'message_start': { + if (event.message.role === 'assistant') { + const id = crypto.randomUUID(); + ctx.currentAssistantMsgId = id; + ws.send(JSON.stringify({ type: 'message_start', data: { id } })); + } + break; + } + + case 'message_update': { + const piEvent = event.assistantMessageEvent; + const id = ctx.currentAssistantMsgId || ''; + + if (piEvent.type === 'text_delta') { + ws.send(JSON.stringify({ type: 'text_delta', data: { id, text: piEvent.delta } })); + } else if (piEvent.type === 'thinking_delta') { + ws.send(JSON.stringify({ type: 'reasoning_delta', data: { id, text: piEvent.delta } })); + } + break; + } + + case 'message_end': { + if (event.message.role === 'assistant') { + const id = ctx.currentAssistantMsgId || ''; + ws.send(JSON.stringify({ type: 'message_end', data: { id } })); + saveAssistantMessage(convId, event.message as AssistantMessage); + ctx.currentAssistantMsgId = null; + } + break; + } + + case 'tool_execution_start': { + ws.send(JSON.stringify({ type: 'tool_start', data: { tool: event.toolName, input: event.args } })); + break; + } + + case 'tool_execution_end': { + const resultText = event.result?.content?.map((c: any) => c.text || '').join('') || ''; + if (event.isError) { + ws.send(JSON.stringify({ type: 'tool_error', data: { tool: event.toolName, error: resultText } })); + } else { + ws.send(JSON.stringify({ type: 'tool_result', data: { tool: event.toolName, result: resultText.slice(0, 1000) } })); + } + saveToolResult(convId, event.toolCallId, event.toolName, resultText, event.isError); + break; + } + } +} diff --git a/web/server/agent/pi-model.ts b/web/server/agent/pi-model.ts new file mode 100644 index 0000000..1aa42ff --- /dev/null +++ b/web/server/agent/pi-model.ts @@ -0,0 +1,57 @@ +import { registerBuiltInApiProviders } from '@earendil-works/pi-ai'; +import type { Model } from '@earendil-works/pi-ai'; +import { getDb } from '../db'; + +registerBuiltInApiProviders(); + +export interface PiModelConfig { + model: Model; + apiKey: string; +} + +export function createPiModel(): PiModelConfig { + const row = getDb().prepare('SELECT value FROM configs WHERE key = ?').get('api_keys') as { value: string } | undefined; + + let apiKey = process.env.ANTHROPIC_API_KEY || ''; + let baseURL: string | undefined; + let modelId = process.env.ANTHROPIC_MODEL || 'claude-sonnet-4-6'; + let protocol: 'anthropic' | 'openai' = 'anthropic'; + + if (row) { + try { + const cfg = JSON.parse(row.value); + if (cfg.ANTHROPIC_AUTH_TOKEN) apiKey = cfg.ANTHROPIC_AUTH_TOKEN; + if (cfg.ANTHROPIC_BASE_URL) baseURL = cfg.ANTHROPIC_BASE_URL; + if (cfg.ANTHROPIC_MODEL) modelId = cfg.ANTHROPIC_MODEL; + if (cfg.PROTOCOL === 'openai') protocol = 'openai'; + } catch {} + } + + const model: Model = protocol === 'openai' + ? { + id: modelId, + name: modelId, + api: 'openai-completions', + provider: 'openai', + baseUrl: baseURL || 'https://api.openai.com/v1', + reasoning: false, + input: ['text'] as ('text' | 'image')[], + cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 }, + contextWindow: 128000, + maxTokens: 8192, + } + : { + id: modelId, + name: modelId, + api: 'anthropic-messages', + provider: 'anthropic', + baseUrl: baseURL || 'https://api.anthropic.com', + reasoning: true, + input: ['text', 'image'] as ('text' | 'image')[], + cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 }, + contextWindow: 200000, + maxTokens: 8192, + }; + + return { model, apiKey }; +} diff --git a/web/server/agent/pi-persist.ts b/web/server/agent/pi-persist.ts new file mode 100644 index 0000000..ed02333 --- /dev/null +++ b/web/server/agent/pi-persist.ts @@ -0,0 +1,164 @@ +import { randomUUID } from 'crypto'; +import { getDb } from '../db'; +import type { Message, AssistantMessage, TextContent, ToolCall } from '@earendil-works/pi-ai'; + +export interface DbMessage { + id: string; + conversation_id: string; + role: string; + content: string; + tool_calls: string | null; + created_at: string; +} + +export function dbToPiMessages(dbMessages: DbMessage[]): Message[] { + const sanitized = sanitizeHistory(dbMessages); + return sanitized.map(dbToPiMessage); +} + +function dbToPiMessage(msg: DbMessage): Message { + if (msg.role === 'user') { + return { role: 'user', content: msg.content, timestamp: Date.parse(msg.created_at) || Date.now() }; + } + + if (msg.role === 'assistant') { + const content: (TextContent | ToolCall)[] = []; + const textContent = msg.content && msg.content !== '(调用工具)' ? msg.content : ''; + if (textContent) { + content.push({ type: 'text', text: textContent }); + } + + if (msg.tool_calls) { + try { + const parsed = JSON.parse(msg.tool_calls); + const blocks = Array.isArray(parsed) ? parsed : parsed.content_blocks; + if (Array.isArray(blocks)) { + for (const b of blocks) { + if (b.type === 'tool_use') { + content.push({ + type: 'toolCall', + id: b.id, + name: b.name, + arguments: b.input || b.arguments || {}, + }); + } + } + } + } catch {} + } + + return { + role: 'assistant', + content, + api: 'unknown' as any, + provider: 'unknown', + model: 'unknown', + usage: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, totalTokens: 0, cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 } }, + stopReason: 'stop', + timestamp: Date.parse(msg.created_at) || Date.now(), + }; + } + + if (msg.role === 'tool') { + try { + const { tool_use_id, content: resultContent } = JSON.parse(msg.content); + return { + role: 'toolResult', + toolCallId: tool_use_id, + toolName: '', + content: [{ type: 'text', text: resultContent }], + isError: false, + timestamp: Date.parse(msg.created_at) || Date.now(), + }; + } catch { + return { + role: 'toolResult', + toolCallId: 'unknown', + toolName: '', + content: [{ type: 'text', text: msg.content }], + isError: true, + timestamp: Date.parse(msg.created_at) || Date.now(), + }; + } + } + + return { role: 'user', content: msg.content, timestamp: Date.now() }; +} + +function sanitizeHistory(messages: DbMessage[]): DbMessage[] { + const cleaned = messages.filter((m) => { + if (m.role === 'assistant' && m.content.startsWith('抱歉，出错了：')) return false; + return true; + }); + + const result: DbMessage[] = []; + for (const msg of cleaned) { + if (msg.role === 'tool') { + let hasPrecedingToolCall = false; + for (let j = result.length - 1; j >= 0; j--) { + const prev = result[j]; + if (prev.role === 'assistant') { + if (prev.tool_calls) { + try { + const parsed = JSON.parse(prev.tool_calls); + const blocks = Array.isArray(parsed) ? parsed : parsed.content_blocks; + if (blocks?.some((b: any) => b.type === 'tool_use')) { + hasPrecedingToolCall = true; + } + } catch {} + } + break; + } + if (prev.role === 'tool') continue; + break; + } + if (!hasPrecedingToolCall) continue; + } + result.push(msg); + } + + return result; +} + +export function saveUserMessage(convId: string, content: string): string { + const id = randomUUID(); + getDb().prepare( + 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' + ).run(id, convId, 'user', content); + return id; +} + +export function saveAssistantMessage(convId: string, msg: AssistantMessage): string { + const id = randomUUID(); + const textParts = msg.content.filter((c): c is TextContent => c.type === 'text'); + const text = textParts.map((c) => c.text).join(''); + + const toolCalls = msg.content.filter((c): c is ToolCall => c.type === 'toolCall'); + + if (toolCalls.length > 0) { + const dbToolCalls = toolCalls.map((tc) => ({ + type: 'tool_use', + id: tc.id, + name: tc.name, + input: tc.arguments, + })); + const contentBlocks = text ? [{ type: 'text', text }, ...dbToolCalls] : dbToolCalls; + getDb().prepare( + 'INSERT INTO messages (id, conversation_id, role, content, tool_calls) VALUES (?, ?, ?, ?, ?)' + ).run(id, convId, 'assistant', text || '(调用工具)', JSON.stringify(contentBlocks)); + } else { + getDb().prepare( + 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' + ).run(id, convId, 'assistant', text); + } + + return id; +} + +export function saveToolResult(convId: string, toolCallId: string, toolName: string, result: string, isError: boolean): string { + const id = randomUUID(); + getDb().prepare( + 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' + ).run(id, convId, 'tool', JSON.stringify({ tool_use_id: toolCallId, tool_name: toolName, content: result })); + return id; +} diff --git a/web/server/agent/pi-tools.ts b/web/server/agent/pi-tools.ts new file mode 100644 index 0000000..5fc3dd2 --- /dev/null +++ b/web/server/agent/pi-tools.ts @@ -0,0 +1,18 @@ +import type { AgentTool, AgentToolResult } from '@earendil-works/pi-agent-core'; +import type { ToolDefinition } from './tools/types'; + +export function createPiTools(tools: ToolDefinition[]): AgentTool[] { + return tools.map((t): AgentTool => ({ + name: t.name, + description: t.description, + parameters: t.input_schema as any, + label: t.name, + execute: async (_toolCallId: string, params: any): Promise> => { + const result = await t.execute(params); + return { + content: [{ type: 'text' as const, text: result }], + details: null, + }; + }, + })); +} diff --git a/web/server/routes/accounts.ts b/web/server/routes/accounts.ts index 404694b..743a21f 100644 --- a/web/server/routes/accounts.ts +++ b/web/server/routes/accounts.ts @@ -2,8 +2,11 @@ import { Router } from 'express'; import fs from 'fs/promises'; import fss from 'fs'; import path from 'path'; +import { fileURLToPath } from 'url'; import multer from 'multer'; +const __filename = fileURLToPath(import.meta.url); +const __dirname = path.dirname(__filename); const ACCOUNTS_DIR = path.resolve(__dirname, '..', '..', '..', 'accounts'); export const accountsRouter = Router(); diff --git a/web/server/routes/prompts.ts b/web/server/routes/prompts.ts index aea356b..7c517bb 100644 --- a/web/server/routes/prompts.ts +++ b/web/server/routes/prompts.ts @@ -1,7 +1,10 @@ import { Router } from 'express'; import fs from 'fs/promises'; import path from 'path'; +import { fileURLToPath } from 'url'; +const __filename = fileURLToPath(import.meta.url); +const __dirname = path.dirname(__filename); const PROJECT_ROOT = path.resolve(__dirname, '..', '..', '..'); export const promptsRouter = Router(); diff --git a/web/server/ws/chat.ts b/web/server/ws/chat.ts index a30a767..00d35b7 100644 --- a/web/server/ws/chat.ts +++ b/web/server/ws/chat.ts @@ -1,54 +1,7 @@ import { WebSocket } from 'ws'; import { randomUUID } from 'crypto'; import { getDb } from '../db'; -import { videoAgent } from '../agent'; -import type Anthropic from '@anthropic-ai/sdk'; -import type OpenAI from 'openai'; - -type MessageParam = Anthropic.MessageParam; -type ContentBlock = Anthropic.ContentBlock; - -interface DbMessage { - id: string; - conversation_id: string; - role: string; - content: string; - tool_calls: string | null; - created_at: string; -} - -function filterContent(blocks: ContentBlock[]): ContentBlock[] { - return blocks.filter((b) => b.type === 'text' || b.type === 'tool_use'); -} - -function dbToAnthropic(msg: DbMessage): MessageParam { - if (msg.role === 'user') { - return { role: 'user', content: msg.content }; - } - if (msg.role === 'assistant') { - if (msg.tool_calls) { - try { - const parsed = JSON.parse(msg.tool_calls) as ContentBlock[]; - return { role: 'assistant', content: filterContent(parsed) }; - } catch { - return { role: 'assistant', content: msg.content }; - } - } - return { role: 'assistant', content: msg.content }; - } - if (msg.role === 'tool') { - try { - const { tool_use_id, content } = JSON.parse(msg.content); - return { - role: 'user', - content: [{ type: 'tool_result' as const, tool_use_id, content }], - }; - } catch { - return { role: 'user', content: msg.content }; - } - } - return { role: 'user', content: msg.content }; -} +import { runAgentChat } from '../agent/pi-bridge'; export function handleChat(ws: WebSocket) { let conversationId: string | null = null; @@ -61,7 +14,7 @@ export function handleChat(ws: WebSocket) { conversationId = msg.conversationId || randomUUID(); const history = getDb().prepare( 'SELECT * FROM messages WHERE conversation_id = ? ORDER BY created_at' - ).all(conversationId) as DbMessage[]; + ).all(conversationId); ws.send(JSON.stringify({ type: 'history', data: { conversationId, messages: history } })); return; } @@ -81,7 +34,7 @@ export function handleChat(ws: WebSocket) { ws.send(JSON.stringify({ type: 'error', data: { message: '没有活跃对话，请先创建或选择一个对话' } })); return; } - await handleChatMessage(ws, conversationId, msg.content); + await runAgentChat(ws, conversationId, msg.content); } } catch (e) { console.error('WebSocket error:', e); @@ -91,381 +44,3 @@ export function handleChat(ws: WebSocket) { ws.on('close', () => {}); } - -// Helper: convert DB messages to OpenAI format -function extractToolCalls(blocks: ContentBlock[]): OpenAI.ChatCompletionMessageToolCall[] { - return blocks - .filter((b) => b.type === 'tool_use') - .map((b) => ({ - id: (b as { id: string }).id, - type: 'function' as const, - function: { - name: (b as { name: string }).name, - arguments: JSON.stringify((b as { input: unknown }).input), - }, - })); -} - -function dbToOpenAI(msg: DbMessage): OpenAI.ChatCompletionMessageParam { - if (msg.role === 'user') { - return { role: 'user', content: msg.content }; - } - if (msg.role === 'assistant') { - const result: Record = { role: 'assistant', content: msg.content || null }; - - if (!msg.tool_calls) return result as unknown as OpenAI.ChatCompletionMessageParam; - - let parsed: unknown; - try { parsed = JSON.parse(msg.tool_calls); } catch { return result as unknown as OpenAI.ChatCompletionMessageParam; } - - // Legacy format: parsed is ContentBlock[] (array) - if (Array.isArray(parsed)) { - const toolCalls = extractToolCalls(parsed); - if (toolCalls.length > 0) { - result.tool_calls = toolCalls; - const textBlocks = parsed.filter((b) => b.type === 'text'); - result.content = textBlocks.map((b) => (b as { text: string }).text).join('') || null; - } - return result as unknown as OpenAI.ChatCompletionMessageParam; - } - - // New format: parsed is { reasoning_content?, content_blocks? } - const meta = parsed as { reasoning_content?: string; content_blocks?: ContentBlock[] }; - if (meta.reasoning_content) { - result.reasoning_content = meta.reasoning_content; - } - if (meta.content_blocks) { - const toolCalls = extractToolCalls(meta.content_blocks); - if (toolCalls.length > 0) { - result.tool_calls = toolCalls; - const textBlocks = meta.content_blocks.filter((b) => b.type === 'text'); - result.content = textBlocks.map((b) => (b as { text: string }).text).join('') || null; - } - } - - return result as unknown as OpenAI.ChatCompletionMessageParam; - } - if (msg.role === 'tool') { - try { - const { tool_use_id, content } = JSON.parse(msg.content); - return { role: 'tool', tool_call_id: tool_use_id, content }; - } catch { - return { role: 'tool', tool_call_id: 'unknown', content: msg.content }; - } - } - return { role: 'user', content: msg.content }; -} - -// --- Anthropic protocol streaming --- -async function streamAnthropic( - ws: WebSocket, - convId: string, - messages: MessageParam[], -): Promise { - const client = videoAgent.getAnthropicClient(); - const model = videoAgent.getModel(); - const systemPrompt = videoAgent.getSystemPrompt(); - - let currentMessages = messages; - let maxLoops = 10; - - while (maxLoops-- > 0) { - console.log(`[chat:anthropic] Loop ${9 - maxLoops}, messages: ${currentMessages.length}`); - const stream = client.messages.stream({ - model, - max_tokens: 4096, - system: systemPrompt, - tools: videoAgent.getAnthropicTools(), - messages: currentMessages, - }); - - const assistantMsgId = randomUUID(); - ws.send(JSON.stringify({ type: 'message_start', data: { id: assistantMsgId } })); - - for await (const event of stream) { - if (event.type === 'content_block_delta') { - if (event.delta.type === 'text_delta') { - ws.send(JSON.stringify({ - type: 'text_delta', - data: { id: assistantMsgId, text: event.delta.text }, - })); - } - } - } - - const finalMsg = await stream.finalMessage(); - ws.send(JSON.stringify({ type: 'message_end', data: { id: assistantMsgId } })); - - const toolUses = finalMsg.content.filter((b): b is Anthropic.ToolUseBlock => b.type === 'tool_use'); - const textBlocks = finalMsg.content.filter((b): b is Anthropic.TextBlock => b.type === 'text'); - const finalText = textBlocks.map((b) => b.text).join(''); - - if (toolUses.length === 0) { - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' - ).run(assistantMsgId, convId, 'assistant', finalText); - return; - } - - // Save assistant with tool calls - const cleanContent = filterContent(finalMsg.content as ContentBlock[]); - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content, tool_calls) VALUES (?, ?, ?, ?, ?)' - ).run(assistantMsgId, convId, 'assistant', finalText || '(调用工具)', JSON.stringify(cleanContent)); - - currentMessages.push({ role: 'assistant', content: cleanContent }); - - // Execute tools - const toolResults: Anthropic.ToolResultBlockParam[] = []; - for (const tool of toolUses) { - ws.send(JSON.stringify({ type: 'tool_start', data: { tool: tool.name, input: tool.input } })); - console.log(`[chat:anthropic] Executing tool: ${tool.name}`); - - try { - const result = await videoAgent.executeTool(tool.name, tool.input as Record); - toolResults.push({ type: 'tool_result', tool_use_id: tool.id, content: result }); - - const toolMsgId = randomUUID(); - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' - ).run(toolMsgId, convId, 'tool', JSON.stringify({ tool_use_id: tool.id, content: result })); - - ws.send(JSON.stringify({ type: 'tool_result', data: { tool: tool.name, result: result.slice(0, 1000) } })); - } catch (err) { - const errMsg = (err as Error).message; - toolResults.push({ type: 'tool_result', tool_use_id: tool.id, content: `Error: ${errMsg}` }); - - const toolMsgId = randomUUID(); - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' - ).run(toolMsgId, convId, 'tool', JSON.stringify({ tool_use_id: tool.id, content: `Error: ${errMsg}` })); - - ws.send(JSON.stringify({ type: 'tool_error', data: { tool: tool.name, error: errMsg } })); - } - } - - currentMessages.push({ role: 'user', content: toolResults }); - } -} - -// --- OpenAI protocol streaming --- -async function streamOpenAI( - ws: WebSocket, - convId: string, - dbMessages: DbMessage[], -): Promise { - const client = videoAgent.getOpenAIClient(); - const model = videoAgent.getModel(); - const systemPrompt = videoAgent.getSystemPrompt(); - - const openaiTools = videoAgent.getOpenAITools(); - - let currentDbMessages = [...dbMessages]; - let maxLoops = 10; - - while (maxLoops-- > 0) { - const openaiMessages: OpenAI.ChatCompletionMessageParam[] = [ - { role: 'system', content: systemPrompt }, - ...currentDbMessages.map(dbToOpenAI), - ]; - - console.log(`[chat:openai] Loop ${9 - maxLoops}, messages: ${openaiMessages.length}`); - - const assistantMsgId = randomUUID(); - ws.send(JSON.stringify({ type: 'message_start', data: { id: assistantMsgId } })); - - let fullText = ''; - let reasoningContent = ''; - let toolCallsAcc: Array<{ id: string; name: string; arguments: string }> = []; - - const stream = await client.chat.completions.create({ - model, - messages: openaiMessages, - tools: openaiTools.length > 0 ? openaiTools : undefined, - stream: true, - }); - - for await (const chunk of stream) { - const delta = chunk.choices[0]?.delta; - if (delta?.content) { - fullText += delta.content; - ws.send(JSON.stringify({ - type: 'text_delta', - data: { id: assistantMsgId, text: delta.content }, - })); - } - // DeepSeek thinking mode: capture reasoning_content - if ((delta as Record)?.reasoning_content) { - const chunk = (delta as Record).reasoning_content as string; - reasoningContent += chunk; - ws.send(JSON.stringify({ - type: 'reasoning_delta', - data: { id: assistantMsgId, text: chunk }, - })); - } - if (delta?.tool_calls) { - for (const tc of delta.tool_calls) { - if (tc.index !== undefined) { - while (toolCallsAcc.length <= tc.index) { - toolCallsAcc.push({ id: '', name: '', arguments: '' }); - } - if (tc.id) toolCallsAcc[tc.index].id = tc.id; - if (tc.function?.name) toolCallsAcc[tc.index].name = tc.function.name; - if (tc.function?.arguments) toolCallsAcc[tc.index].arguments += tc.function.arguments; - } - } - } - } - - ws.send(JSON.stringify({ type: 'message_end', data: { id: assistantMsgId } })); - - // Store extra metadata (reasoning_content, tool_calls) in tool_calls column as JSON - const extraMeta: Record = {}; - if (reasoningContent) extraMeta.reasoning_content = reasoningContent; - - // No tool calls — save and done - if (toolCallsAcc.length === 0) { - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content, tool_calls) VALUES (?, ?, ?, ?, ?)' - ).run(assistantMsgId, convId, 'assistant', fullText, Object.keys(extraMeta).length > 0 ? JSON.stringify(extraMeta) : null); - return; - } - - // Save assistant with tool calls in Anthropic-compatible format for DB - const dbToolCalls = toolCallsAcc.map((tc) => ({ - type: 'tool_use', - id: tc.id, - name: tc.name, - input: JSON.parse(tc.arguments || '{}'), - })); - const cleanContent = fullText - ? [{ type: 'text', text: fullText }, ...dbToolCalls] - : dbToolCalls; - extraMeta.content_blocks = cleanContent; - - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content, tool_calls) VALUES (?, ?, ?, ?, ?)' - ).run(assistantMsgId, convId, 'assistant', fullText || '(调用工具)', JSON.stringify(extraMeta)); - - // Execute tools and collect results - for (const tc of toolCallsAcc) { - ws.send(JSON.stringify({ type: 'tool_start', data: { tool: tc.name, input: JSON.parse(tc.arguments || '{}') } })); - console.log(`[chat:openai] Executing tool: ${tc.name}`); - - try { - const params = JSON.parse(tc.arguments || '{}'); - const result = await videoAgent.executeTool(tc.name, params); - - const toolMsgId = randomUUID(); - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' - ).run(toolMsgId, convId, 'tool', JSON.stringify({ tool_use_id: tc.id, content: result })); - - ws.send(JSON.stringify({ type: 'tool_result', data: { tool: tc.name, result: result.slice(0, 1000) } })); - } catch (err) { - const errMsg = (err as Error).message; - - const toolMsgId = randomUUID(); - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' - ).run(toolMsgId, convId, 'tool', JSON.stringify({ tool_use_id: tc.id, content: `Error: ${errMsg}` })); - - ws.send(JSON.stringify({ type: 'tool_error', data: { tool: tc.name, error: errMsg } })); - } - } - - // Reload all messages for next loop - currentDbMessages = getDb().prepare( - 'SELECT * FROM messages WHERE conversation_id = ? ORDER BY created_at' - ).all(convId) as DbMessage[]; - } -} - -// Clean and validate message history before sending to API -function sanitizeHistory(messages: DbMessage[]): DbMessage[] { - // 1. Filter out error messages stored in DB - const cleaned = messages.filter((m) => { - if (m.role === 'assistant' && m.content.startsWith('抱歉，出错了：')) return false; - return true; - }); - - // 2. Validate sequence: tool messages must follow assistant with tool_calls - const result: DbMessage[] = []; - for (let i = 0; i < cleaned.length; i++) { - const msg = cleaned[i]; - - // Tool message: check if preceding assistant has tool_calls - if (msg.role === 'tool') { - let hasPrecedingToolCall = false; - for (let j = result.length - 1; j >= 0; j--) { - const prev = result[j]; - if (prev.role === 'assistant') { - if (prev.tool_calls) { - try { - const parsed = JSON.parse(prev.tool_calls); - const blocks = Array.isArray(parsed) ? parsed : parsed.content_blocks; - if (blocks?.some((b: ContentBlock) => b.type === 'tool_use')) { - hasPrecedingToolCall = true; - } - } catch {} - } - break; // stop at nearest assistant - } - if (prev.role === 'tool') continue; // skip consecutive tool messages - break; - } - if (!hasPrecedingToolCall) continue; // skip orphan tool message - } - - result.push(msg); - } - - return result; -} - -async function handleChatMessage(ws: WebSocket, convId: string, content: string) { - const userMsgId = randomUUID(); - getDb().prepare( - 'INSERT INTO messages (id, conversation_id, role, content) VALUES (?, ?, ?, ?)' - ).run(userMsgId, convId, 'user', content); - ws.send(JSON.stringify({ type: 'message', data: { id: userMsgId, role: 'user', content } })); - - const msgCount = getDb().prepare( - 'SELECT COUNT(*) as count FROM messages WHERE conversation_id = ?' - ).get(convId) as { count: number }; - if (msgCount.count <= 1) { - const title = content.slice(0, 30) + (content.length > 30 ? '...' : ''); - getDb().prepare('UPDATE conversations SET title = ?, updated_at = datetime(\'now\') WHERE id = ?') - .run(title, convId); - } - getDb().prepare('UPDATE conversations SET updated_at = datetime(\'now\') WHERE id = ?').run(convId); - - const rawHistory = getDb().prepare( - 'SELECT * FROM messages WHERE conversation_id = ? AND id != ? ORDER BY created_at' - ).all(convId, userMsgId) as DbMessage[]; - const history = sanitizeHistory(rawHistory); - - ws.send(JSON.stringify({ type: 'status', data: { status: 'thinking' } })); - - try { - const protocol = videoAgent.getProtocol(); - - if (protocol === 'openai') { - // OpenAI protocol - await streamOpenAI(ws, convId, history); - } else { - // Anthropic protocol (default) - const messages: MessageParam[] = history.map(dbToAnthropic); - await streamAnthropic(ws, convId, messages); - } - } catch (err) { - const errMsg = (err as Error).message; - console.error('[chat] LLM error:', errMsg); - const errId = randomUUID(); - // Don't store error in DB to avoid polluting history - ws.send(JSON.stringify({ - type: 'message', - data: { id: errId, role: 'assistant', content: `抱歉，出错了：${errMsg}` }, - })); - } -}