perplexity-reference-architecture
Implement Perplexity reference architecture with best-practice project layout. Use when designing new Perplexity integrations, reviewing project structure, or establishing architecture standards for Perplexity applications. Trigger with phrases like "perplexity architecture", "perplexity best practices", "perplexity project structure", "how to organize perplexity", "perplexity layout".
Install
mkdir -p .claude/skills/perplexity-reference-architecture && curl -L -o skill.zip "https://mcp.directory/api/skills/download/5344" && unzip -o skill.zip -d .claude/skills/perplexity-reference-architecture && rm skill.zipInstalls to .claude/skills/perplexity-reference-architecture
About this skill
Perplexity Reference Architecture
Overview
Production architecture for AI-powered search with Perplexity Sonar API. Three tiers: search service (model routing + caching), citation pipeline (extract, validate, store), and research orchestrator (multi-query synthesis).
Architecture
┌─────────────────────────────────────────────┐
│ Application Layer │
│ (Search Widget, Research Agent, Fact Check) │
└──────────────────────┬──────────────────────┘
│
┌──────────────────────▼──────────────────────┐
│ Search Service Layer │
│ ┌──────────┐ ┌──────────┐ ┌─────────────┐ │
│ │ Model │ │ Query │ │ Response │ │
│ │ Router │ │ Cache │ │ Parser │ │
│ └──────────┘ └──────────┘ └─────────────┘ │
└──────────────────────┬──────────────────────┘
│
┌──────────────────────▼──────────────────────┐
│ api.perplexity.ai/chat/completions │
│ sonar | sonar-pro | sonar-reasoning-pro │
└─────────────────────────────────────────────┘
Prerequisites
- Perplexity API key with Sonar access
- OpenAI-compatible client library (
openaipackage) - Redis for production caching (LRU for development)
Instructions
Step 1: Search Service with Model Routing
// src/perplexity/search-service.ts
import OpenAI from "openai";
import { createHash } from "crypto";
type SearchDepth = "quick" | "standard" | "deep" | "reasoning";
const MODEL_MAP: Record<SearchDepth, { model: string; maxTokens: number; timeout: number }> = {
quick: { model: "sonar", maxTokens: 256, timeout: 10000 },
standard: { model: "sonar", maxTokens: 1024, timeout: 15000 },
deep: { model: "sonar-pro", maxTokens: 4096, timeout: 30000 },
reasoning: { model: "sonar-reasoning-pro", maxTokens: 4096, timeout: 45000 },
};
export class SearchService {
constructor(
private client: OpenAI,
private cache: Map<string, { result: any; expiry: number }> = new Map()
) {}
async search(query: string, depth: SearchDepth = "standard", opts: {
recencyFilter?: "hour" | "day" | "week" | "month";
domainFilter?: string[];
systemPrompt?: string;
} = {}) {
const config = MODEL_MAP[depth];
const cacheKey = this.hashQuery(query, config.model, opts);
// Check cache
const cached = this.cache.get(cacheKey);
if (cached && cached.expiry > Date.now()) {
return { ...cached.result, cached: true };
}
const response = await this.client.chat.completions.create({
model: config.model,
messages: [
...(opts.systemPrompt ? [{ role: "system" as const, content: opts.systemPrompt }] : []),
{ role: "user" as const, content: query },
],
max_tokens: config.maxTokens,
...(opts.recencyFilter && { search_recency_filter: opts.recencyFilter }),
...(opts.domainFilter && { search_domain_filter: opts.domainFilter }),
} as any);
const result = {
answer: response.choices[0].message.content || "",
citations: (response as any).citations || [],
searchResults: (response as any).search_results || [],
model: response.model,
usage: response.usage,
};
// Cache with TTL based on query type
const ttl = opts.recencyFilter === "hour" ? 900_000 : 3600_000;
this.cache.set(cacheKey, { result, expiry: Date.now() + ttl });
return { ...result, cached: false };
}
private hashQuery(query: string, model: string, opts: any): string {
return createHash("sha256")
.update(JSON.stringify({ query: query.toLowerCase().trim(), model, ...opts }))
.digest("hex");
}
}
Step 2: Citation Pipeline
// src/perplexity/citation-pipeline.ts
export interface Citation {
url: string;
domain: string;
index: number;
}
export function extractCitations(answer: string, citationUrls: string[]): Citation[] {
return citationUrls.map((url, i) => ({
url,
domain: new URL(url).hostname,
index: i + 1,
}));
}
export function renderCitationsAsMarkdown(answer: string, citations: Citation[]): string {
let rendered = answer;
for (const c of citations) {
rendered = rendered.replaceAll(`[${c.index}]`, `[${c.index}](${c.url})`);
}
return rendered;
}
export function deduplicateCitations(citations: Citation[]): Citation[] {
const seen = new Set<string>();
return citations.filter((c) => {
const normalized = c.url.split("?")[0].replace(/\/$/, "");
if (seen.has(normalized)) return false;
seen.add(normalized);
return true;
});
}
Step 3: Research Orchestrator
// src/perplexity/research-orchestrator.ts
export class ResearchOrchestrator {
constructor(private searchService: SearchService) {}
async research(topic: string): Promise<{
sections: Array<{ question: string; answer: string; citations: string[] }>;
bibliography: string[];
}> {
// Phase 1: Decompose topic (fast model)
const overview = await this.searchService.search(
`Break "${topic}" into 4-5 key research questions. List one per line.`,
"quick"
);
const questions = overview.answer.split("\n").filter((q) => q.trim().length > 10);
// Phase 2: Deep dive each question
const sections = [];
const allCitations = new Set<string>();
for (const question of questions.slice(0, 5)) {
const result = await this.searchService.search(question, "deep", {
systemPrompt: `Research context: ${topic}. Provide detailed, well-cited answer.`,
});
sections.push({
question: question.trim(),
answer: result.answer,
citations: result.citations,
});
result.citations.forEach((url: string) => allCitations.add(url));
// Rate limit protection
await new Promise((r) => setTimeout(r, 2000));
}
return { sections, bibliography: [...allCitations] };
}
}
Step 4: Fact-Check Service
export async function factCheck(
claim: string,
searchService: SearchService
): Promise<{ verdict: string; confidence: string; sources: string[] }> {
const result = await searchService.search(
`Verify this claim with sources. State whether it is accurate, partially accurate, or inaccurate: "${claim}"`,
"deep",
{ systemPrompt: "You are a fact-checker. Be precise and cite sources." }
);
return {
verdict: result.answer,
confidence: result.citations.length > 3 ? "high" : result.citations.length > 1 ? "medium" : "low",
sources: result.citations,
};
}
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| No citations returned | Using sonar for complex query | Upgrade to sonar-pro |
| Stale information | No recency filter | Add search_recency_filter |
| High cost | sonar-pro for simple queries | Route by depth |
| Rate limit on research | Too many sequential queries | Add 2s delay between calls |
Output
- Search service with model routing by query depth
- Citation extraction and rendering pipeline
- Multi-query research orchestrator
- Fact-checking service
Resources
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