reverse-engineer（逆向工程师）

Reverse Engineering Perplexity AI APIs

Discover, document, and implement undocumented Perplexity AI endpoints for pplx-sdk.

When to use

Use this skill when:

• Discovering new API endpoints from perplexity.ai browser traffic
• Decoding request/response payloads from captured cURL commands
• Mapping SSE event types from streaming endpoints
• Extracting auth flows (cookies, tokens, session management)
• Adding new endpoint support to the SDK

Instructions

Step 1: Capture Traffic

DevTools (F12) → Network → XHR/Fetch
1. Perform action on perplexity.ai
2. Right-click request → Copy as cURL
3. Paste cURL for analysis

Step 2: Decode Payload

Extract from the captured request:

• URL path (e.g., /rest/sse/perplexity.ask)
• Method (GET, POST, PUT, DELETE)
• Auth (Bearer token from cookie pplx.session-id)
• Request body (JSON payload with field names and types)
• Response format (JSON, SSE stream, etc.)

Step 3: Document Schema

For each field in the payload:

• Name, type, required/optional, default value
• What it controls (e.g., mode: "concise" = shorter answers)
• Discovered values (e.g., model_preference = "pplx-70b-chat" | "pplx-70b-deep")

Step 4: Map to SDK Architecture

Step 5: Implement

Create the SDK implementation following the layered architecture:

1. Model in domain/models.py
2. Service in domain/<service>.py
3. Tests in tests/test_<service>.py

Known API Surface

Implemented

• POST /rest/sse/perplexity.ask — Main query endpoint (SSE streaming)

Discovered (not yet implemented)

• Thread management (/rest/threads/)
• Collections (/rest/collections/)
• User profile (/rest/user/)
• File upload (/rest/upload)
• Sharing (/rest/share/)

Anti-Detection Notes

• Use realistic User-Agent headers matching Chrome/Safari
• Include Referer: https://www.perplexity.ai/ and Origin headers
• Consider TLS fingerprinting via curl_cffi with impersonate="chrome120"
• Rate limit requests to avoid detection