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| 1 | +import { NextRequest, NextResponse } from 'next/server'; |
| 2 | +import path from 'path'; |
| 3 | +import { SkillRetriever } from '@/lib/retriever'; |
| 4 | +import { callAI, AgentLoop } from '@/lib/ai-sdk'; |
| 5 | +import { |
| 6 | + TOOLS, |
| 7 | + toolListReferences, |
| 8 | + toolReadSkills, |
| 9 | + buildSystemPrompt |
| 10 | +} from '@/lib/skill-tools'; |
| 11 | +import { |
| 12 | + detectIntent, |
| 13 | + buildMessages, |
| 14 | + extractCodeFromMarkdown |
| 15 | +} from '@/lib/intent'; |
| 16 | +import ProviderRegistry, { PROVIDERS } from '@/lib/provider-registry'; |
| 17 | + |
| 18 | +// Initialize retriever |
| 19 | +const retriever = new SkillRetriever(); |
| 20 | + |
| 21 | +// Load skills index on first request |
| 22 | +let skillsLoaded = false; |
| 23 | +function ensureSkillsLoaded() { |
| 24 | + if (!skillsLoaded) { |
| 25 | + try { |
| 26 | + const { skills } = retriever.loadIndex(); |
| 27 | + console.log(`✅ Loaded ${skills.length} skills from index`); |
| 28 | + skillsLoaded = true; |
| 29 | + } catch (e) { |
| 30 | + console.error( |
| 31 | + '❌ Skills index not found. Run: node cli/skills-antv.js build' |
| 32 | + ); |
| 33 | + } |
| 34 | + } |
| 35 | +} |
| 36 | + |
| 37 | +// Resolve provider and model from request |
| 38 | +function resolveProviderModel( |
| 39 | + reqProvider?: string, |
| 40 | + reqModel?: string |
| 41 | +): { provider: string; model: string } { |
| 42 | + const provider = reqProvider || process.env.AI_PROVIDER || 'qwen'; |
| 43 | + const model = |
| 44 | + reqModel || |
| 45 | + process.env.AI_MODEL || |
| 46 | + PROVIDERS[provider]?.defaultModel || |
| 47 | + 'qwen3-coder-480b-a35b-instruct'; |
| 48 | + return { provider, model }; |
| 49 | +} |
| 50 | + |
| 51 | +// BM25 mode generation |
| 52 | +async function generateWithBM25( |
| 53 | + query: string, |
| 54 | + library: string, |
| 55 | + currentCode: string | null, |
| 56 | + provider: string, |
| 57 | + model: string |
| 58 | +) { |
| 59 | + const selectedLibrary = |
| 60 | + library === 'auto' ? retriever.detectLibrary(query) : library; |
| 61 | + |
| 62 | + const { systemPrompt, primarySkills, extraSkills } = retriever.buildPrompt( |
| 63 | + query, |
| 64 | + { library: selectedLibrary, topK: 5, maxExtra: 2 } |
| 65 | + ); |
| 66 | + const retrievedSkills = [...primarySkills, ...extraSkills]; |
| 67 | + const intent = detectIntent(query, currentCode); |
| 68 | + const messages = buildMessages(query, systemPrompt, intent, currentCode); |
| 69 | + |
| 70 | + const response = await callAI({ |
| 71 | + provider, |
| 72 | + model, |
| 73 | + messages, |
| 74 | + temperature: 0.3, |
| 75 | + maxTokens: 4000 |
| 76 | + }); |
| 77 | + |
| 78 | + return { |
| 79 | + code: extractCodeFromMarkdown(response.content), |
| 80 | + selectedLibrary, |
| 81 | + retrievedSkills, |
| 82 | + intent |
| 83 | + }; |
| 84 | +} |
| 85 | + |
| 86 | +// Tool-call mode generation |
| 87 | +async function generateWithToolCall( |
| 88 | + query: string, |
| 89 | + library: string, |
| 90 | + currentCode: string | null, |
| 91 | + provider: string, |
| 92 | + model: string |
| 93 | +) { |
| 94 | + const selectedLibrary = |
| 95 | + library === 'auto' ? retriever.detectLibrary(query) : library; |
| 96 | + |
| 97 | + const systemPrompt = buildSystemPrompt(selectedLibrary); |
| 98 | + const intent = detectIntent(query, currentCode); |
| 99 | + |
| 100 | + let userMessage = `请根据以下描述生成 AntV ${selectedLibrary.toUpperCase()} 代码，只输出一个完整的 javascript 代码块：\n\n${query}`; |
| 101 | + if (intent === 'tune') { |
| 102 | + userMessage = |
| 103 | + `当前图表代码：\n\`\`\`javascript\n${currentCode}\n\`\`\`\n\n` + |
| 104 | + `请基于上面的代码，${query}。只输出修改后的完整 javascript 代码块。`; |
| 105 | + } |
| 106 | + |
| 107 | + const agent = new AgentLoop({ |
| 108 | + provider, |
| 109 | + model, |
| 110 | + tools: TOOLS, |
| 111 | + maxRounds: 6, |
| 112 | + debug: false, |
| 113 | + toolHandlers: { |
| 114 | + list_references: toolListReferences, |
| 115 | + read_skills: toolReadSkills |
| 116 | + } |
| 117 | + }); |
| 118 | + |
| 119 | + const result = await agent.run(systemPrompt, userMessage); |
| 120 | + const code = extractCodeFromMarkdown(result.content); |
| 121 | + const loadedSkillPaths = result.toolCallsLog |
| 122 | + .filter((l) => l.tool === 'read_skills') |
| 123 | + .flatMap((l) => l.args.paths || []); |
| 124 | + |
| 125 | + console.log( |
| 126 | + ` Tool calls: ${result.toolCallsLog.length}, loaded: ${loadedSkillPaths.map((p) => path.basename(p, '.md')).join(', ')}` |
| 127 | + ); |
| 128 | + |
| 129 | + return { |
| 130 | + code, |
| 131 | + selectedLibrary, |
| 132 | + toolCallsLog: result.toolCallsLog, |
| 133 | + loadedSkillPaths |
| 134 | + }; |
| 135 | +} |
| 136 | + |
| 137 | +export async function POST(request: NextRequest) { |
| 138 | + ensureSkillsLoaded(); |
| 139 | + |
| 140 | + const body = await request.json(); |
| 141 | + const { |
| 142 | + query, |
| 143 | + library = 'auto', |
| 144 | + currentCode = null, |
| 145 | + mode = 'bm25', |
| 146 | + provider: reqProvider, |
| 147 | + model: reqModel |
| 148 | + } = body; |
| 149 | + |
| 150 | + if (!query) { |
| 151 | + return NextResponse.json({ error: 'Query is required' }, { status: 400 }); |
| 152 | + } |
| 153 | + |
| 154 | + const { provider, model } = resolveProviderModel(reqProvider, reqModel); |
| 155 | + |
| 156 | + if (!ProviderRegistry.hasProvider(provider)) { |
| 157 | + return NextResponse.json( |
| 158 | + { error: `Unknown provider: ${provider}` }, |
| 159 | + { status: 400 } |
| 160 | + ); |
| 161 | + } |
| 162 | + if (!ProviderRegistry.hasApiKey(provider)) { |
| 163 | + return NextResponse.json( |
| 164 | + { error: `Missing API key for provider: ${provider}` }, |
| 165 | + { status: 400 } |
| 166 | + ); |
| 167 | + } |
| 168 | + |
| 169 | + console.log( |
| 170 | + `\n[${mode}] "${query.substring(0, 60)}" (${library}) | ${provider}/${model}` |
| 171 | + ); |
| 172 | + |
| 173 | + try { |
| 174 | + if (mode === 'tool-call') { |
| 175 | + const { code, selectedLibrary, toolCallsLog, loadedSkillPaths } = |
| 176 | + await generateWithToolCall( |
| 177 | + query, |
| 178 | + library, |
| 179 | + currentCode, |
| 180 | + provider, |
| 181 | + model |
| 182 | + ); |
| 183 | + |
| 184 | + return NextResponse.json({ |
| 185 | + code, |
| 186 | + library: selectedLibrary, |
| 187 | + mode: 'tool-call', |
| 188 | + provider, |
| 189 | + model, |
| 190 | + skills: loadedSkillPaths.map((p) => ({ |
| 191 | + id: path.basename(p, '.md'), |
| 192 | + title: path.basename(p, '.md') |
| 193 | + })), |
| 194 | + toolCallsCount: toolCallsLog.length |
| 195 | + }); |
| 196 | + } |
| 197 | + |
| 198 | + const { code, selectedLibrary, retrievedSkills, intent } = |
| 199 | + await generateWithBM25(query, library, currentCode, provider, model); |
| 200 | + |
| 201 | + console.log( |
| 202 | + `[bm25] ${selectedLibrary.toUpperCase()} [${intent}], skills: ${retrievedSkills.length}` |
| 203 | + ); |
| 204 | + |
| 205 | + return NextResponse.json({ |
| 206 | + code, |
| 207 | + library: selectedLibrary, |
| 208 | + mode: 'bm25', |
| 209 | + provider, |
| 210 | + model, |
| 211 | + skills: retrievedSkills.map((s) => ({ id: s.id, title: s.title })), |
| 212 | + intent |
| 213 | + }); |
| 214 | + } catch (error) { |
| 215 | + console.error('Generation error:', error); |
| 216 | + const message = error instanceof Error ? error.message : 'Unknown error'; |
| 217 | + return NextResponse.json({ error: message }, { status: 500 }); |
| 218 | + } |
| 219 | +} |
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