Execute Perplexity secondary workflow: Core Workflow B. Use when implementing secondary use case, or complementing primary workflow. Trigger with phrases like "perplexity secondary workflow", "secondary task with perplexity".
npxskills add jeremylongshore/claude-code-plugins-plus-skills--skill perplexity-core-workflow-bLoading…
Multi-turn research workflow using Perplexity Sonar API. Decomposes a broad topic into focused sub-queries, runs them with context continuity, deduplicates citations, and synthesizes a structured research document. Use sonar for fast passes and sonar-pro for deep dives.
perplexity-install-auth setupperplexity-core-workflow-aPERPLEXITY_API_KEY setimport OpenAI from "openai";
const perplexity = new OpenAI({
apiKey: process.env.PERPLEXITY_API_KEY,
baseURL: "https://api.perplexity.ai",
});
type Message = OpenAI.ChatCompletionMessageParam;
class ResearchSession {
private messages: Message[] = [];
private allCitations: Set<string> = new Set();
constructor(systemPrompt: string = "You are a research assistant. Provide thorough, cited answers.") {
this.messages.push({ role: "system", content: systemPrompt });
}
async ask(question: string, model: "sonar" | "sonar-pro" = "sonar"): Promise<{
answer: string;
citations: string[];
}> {
this.messages.push({ role: "user", content: question });
const response = await perplexity.chat.completions.create({
model,
messages: this.messages,
} as any);
const answer = response.choices[0].message.content || "";
const citations = (response as any).citations || [];
// Maintain conversation context
this.messages.push({ role: "assistant", content: answer });
// Accumulate all citations across the session
citations.forEach((url: string) => this.allCitations.add(url));
return { answer, citations };
}
getAllCitations(): string[] {
return [...this.allCitations];
}
// Keep context manageable (Perplexity searches per turn)
trimHistory(keepLast: number = 6) {
const system = this.messages[0];
const recent = this.messages.slice(-(keepLast * 2));
this.messages = [system, ...recent];
}
}
interface ResearchPlan {
topic: string;
questions: string[];
}
interface ResearchReport {
topic: string;
sections: Array<{ question: string; answer: string; citations: string[] }>;
allCitations: string[];
totalTokens: number;
}
async function conductResearch(plan: ResearchPlan): Promise<ResearchReport> {
const sections: ResearchReport["sections"] = [];
const allCitations = new Set<string>();
let totalTokens = 0;
for (const question of plan.questions) {
const response = await perplexity.chat.completions.create({
model: "sonar-pro", // deeper research for each sub-question
messages: [
{ role: "system", content: `Research context: ${plan.topic}` },
{ role: "user", content: question },
],
} as any);
const answer = response.choices[0].message.content || "";
const citations = (response as any).citations || [];
sections.push({ question, answer, citations });
citations.forEach((url: string) => allCitations.add(url));
totalTokens += response.usage?.total_tokens || 0;
// Rate limit protection: 50 RPM for most tiers
await new Promise((r) => setTimeout(r, 1500));
}
return {
topic: plan.topic,
sections,
allCitations: [...allCitations],
totalTokens,
};
}
async function decomposeTopic(topic: string): Promise<string[]> {
const response = await perplexity.chat.completions.create({
model: "sonar",
messages: [
{
role: "system",
content: "Break this research topic into 4-6 specific, focused questions. Return one question per line, no numbering.",
},
{ role: "user", content: topic },
],
max_tokens: 500,
});
return (response.choices[0].message.content || "")
.split("\n")
.map((q) => q.trim())
.filter((q) => q.length > 10);
}
function compileReport(report: ResearchReport): string {
let md = `# Research: ${report.topic}\n\n`;
for (const section of report.sections) {
md += `## ${section.question}\n\n`;
md += `${section.answer}\n\n`;
}
md += `## Bibliography\n\n`;
report.allCitations.forEach((url, i) => {
md += `${i + 1}. ${url}\n`;
});
md += `\n---\n`;
md += `*${report.sections.length} queries | ${report.allCitations.length} unique sources | ${report.totalTokens} tokens*\n`;
return md;
}
async function researchTopic(topic: string): Promise<string> {
console.log(`Decomposing: ${topic}`);
const questions = await decomposeTopic(topic);
console.log(`Generated ${questions.length} sub-questions`);
const report = await conductResearch({ topic, questions });
console.log(`Found ${report.allCitations.length} unique sources`);
return compileReport(report);
}
// Usage
const markdown = await researchTopic("Impact of AI on drug discovery in 2025");
console.log(markdown);
import asyncio, os
from openai import OpenAI
client = OpenAI(api_key=os.environ["PERPLEXITY_API_KEY"], base_url="https://api.perplexity.ai")
def research_topic(topic: str, questions: list[str]) -> dict:
sections = []
all_citations = set()
for q in questions:
r = client.chat.completions.create(
model="sonar-pro",
messages=[
{"role": "system", "content": f"Research context: {topic}"},
{"role": "user", "content": q},
],
)
raw = r.model_dump()
citations = raw.get("citations", [])
sections.append({"question": q, "answer": r.choices[0].message.content, "citations": citations})
all_citations.update(citations)
return {"topic": topic, "sections": sections, "citations": list(all_citations)}
| Error | Cause | Solution |
|---|---|---|
429 Too Many Requests | Batch queries too fast | Add 1-2s delay between queries |
| Context overflow | Too many conversation turns | Call trimHistory() to keep last 6 turns |
| Contradictory answers | Different sources disagree | Flag contradictions for manual review |
| High cost | Using sonar-pro for all queries | Use sonar for decomposition, sonar-pro for deep dives |
For common errors, see perplexity-common-errors.
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