Perplexica Search

AI-powered search using your local Perplexica instance. Runs deep research (quality mode) with web search and LLM reasoning; returns answers with cited sources in OpenClaw while keeping search/RAG state in Perplexica. Use when the user asks to "search with Perplexica", "ask Perplexica", "deep search", "research with sources", or wants AI search with citations. Local-only; no data exfiltration.

Perplexica Search Skill

AI-powered search using your local Perplexica instance. This skill calls Perplexica's search API for deep research (quality mode), returns the answer and cited sources in OpenClaw, and leaves search/RAG state in Perplexica. Local-only: only localhost, 127.0.0.1, ::1, or host.docker.internal (Docker) are allowed; remote URLs are rejected. HTTP redirects are not followed, so the client cannot be sent to a non-local host.

When to Use

Use this skill when the user wants to:

• Search the web with AI-powered reasoning
• Get answers with cited sources
• Perform deep research on a topic (use --mode quality)
• Search academic papers or discussions
• Use a local, privacy-focused search engine
• Get structured search results with metadata

Prerequisites

• python3 (required to run the script)
• Perplexica running locally (default: http://localhost:3000)
• At least one chat model provider configured in Perplexica
• At least one embedding model configured

Usage

Run the script by path; do not rely on cd to the skill directory. The script finds its config from its own location. Use the skill directory your environment provides (e.g. {baseDir} or the path where this skill is installed).

bash

# Basic search (replace <SKILL_DIR> with the actual skill path, e.g. ~/.openclaw/skills/perplexica-search or {baseDir})
python3 <SKILL_DIR>/scripts/perplexica_search.py "What is quantum computing?"

# Specify optimization mode
python3 <SKILL_DIR>/scripts/perplexica_search.py "Latest AI developments" --mode quality

# Search specific sources
python3 <SKILL_DIR>/scripts/perplexica_search.py "Machine learning papers" --sources academic

# Different local port or Docker host (allowed: localhost, 127.0.0.1, ::1, host.docker.internal)
python3 <SKILL_DIR>/scripts/perplexica_search.py "Climate change research" --url http://127.0.0.1:3000
python3 <SKILL_DIR>/scripts/perplexica_search.py "Query" --url http://host.docker.internal:3000

# JSON output for programmatic use
python3 <SKILL_DIR>/scripts/perplexica_search.py "Python best practices" --json

# Deep research (allow slow chunks, e.g. 5 min between chunks)
python3 <SKILL_DIR>/scripts/perplexica_search.py "Comprehensive review of X" --mode quality --timeout 300

# With conversation history
python3 <SKILL_DIR>/scripts/perplexica_search.py "Explain more" --history '[["human", "What is Python?"], ["assistant", "Python is a programming language..."]]'

# Custom system instructions
python3 <SKILL_DIR>/scripts/perplexica_search.py "Explain Rust" --instructions "Focus on memory safety and performance"

# Minimal output (answer + sources only), e.g. for OpenClaw/agents
python3 <SKILL_DIR>/scripts/perplexica_search.py "Your query" --quiet

If the agent has a skill base path variable (e.g. {baseDir}), use it: python3 {baseDir}/scripts/perplexica_search.py "query". Do not cd into the skill directory first; run the script by full path so it works regardless of current working directory and install location.

Minimal output in OpenClaw: To avoid extra decorative headers when the runner adds its own messages (e.g. "Exec running/finished", "An async command you ran earlier has completed..."), use --quiet or -q. That prints only the answer and a compact sources list. The "System: Exec...", "Handle the result internally", and timestamp lines are from OpenClaw, not this skill; they cannot be disabled from the skill.

CLI Flags

Flag	Short	Default	Description
query		(required)	The search query
--url	-u	http://localhost:3000	Local Perplexica base URL only (localhost, 127.0.0.1, ::1, or host.docker.internal)
--mode	-m	balanced	Optimization mode: speed, balanced, quality
--sources	-s	web	Search sources: web, academic, discussions (comma-separated)
--chat-model		auto	Chat model key (e.g., gpt-4o-mini, llama3.1:latest)
--embedding-model		auto	Embedding model key (e.g., text-embedding-3-large)
--instructions	-i	None	Custom system instructions
--history		None	Conversation history as JSON array
--json	-j	off	Output raw JSON instead of formatted summary
--quiet	-q	off	Minimal output: answer and sources only (no decorative headers). Use from OpenClaw/agents to reduce clutter.
--timeout		180	Seconds to wait between stream chunks (increase if the LLM is slow)

How It Works

1. Validate URL: Ensures the Perplexica base URL is local only (localhost, 127.0.0.1, ::1, or host.docker.internal); exits with error if not. Redirects are rejected so the client never follows a redirect to a remote host.
2. Fetch Providers: Calls /api/providers to get available chat and embedding models
3. Auto-Select Models: If not specified, selects the first available chat and embedding models
4. Execute Search: POSTs to /api/search with streaming (same as the Perplexica web UI), so chunks arrive as they’re generated and long-running quality/deep research does not time out
5. Format Results: Displays answer with sources and citations in OpenClaw; search/RAG state remains in Perplexica

Library / past chats in the Perplexica web UI

Searches run via this skill (API) are not saved to Perplexica’s “library of past chats and sources.” The Perplexica API uses in-memory sessions only and does not write to the same database the web UI uses for the library. So you will not see those API searches in the web UI’s history. To have a search appear in the library, run it in the Perplexica web UI. The skill still returns the full answer and sources in OpenClaw.

Output Structure

Human-Readable Summary

text

🔍 Query: What is Perplexica?
⚡ Mode: balanced | Sources: web

📄 Answer:
Perplexica is an AI-powered search engine that...

📚 Sources:
[1] Title - https://example.com/page1
[2] Title - https://example.com/page2

JSON Output

json

{
  "query": "What is Perplexica?",
  "mode": "balanced",
  "sources": ["web"],
  "answer": "Perplexica is...",
  "sources_used": [
    {
      "title": "Page Title",
      "url": "https://example.com",
      "content": "Snippet..."
    }
  ],
  "model_used": "gpt-4o-mini",
  "took_ms": 1234
}

Configuration

Optional: create a config.json in the skill directory. perplexica_url must be a local URL only (localhost, 127.0.0.1, ::1, or host.docker.internal); remote URLs are rejected.

json

{
  "perplexica_url": "http://localhost:3000",
  "default_chat_model": "llama3.1:latest",
  "default_embedding_model": "nomic-embed-text",
  "default_mode": "balanced",
  "default_sources": ["web"]
}

API Endpoints

Endpoint	Method	Purpose
/api/providers	GET	List available model providers
/api/search	POST	Execute search query

Error Handling

• Connection Error: Perplexica instance unreachable — check URL and that it's running. If the agent runs in Docker, try --url http://host.docker.internal:3000 or --url http://127.0.0.1:3000.
• No Providers: No chat models configured — configure at least one provider in Perplexica settings
• Invalid Model: Specified model not found — use --json to see available models
• Timeout: The skill uses streaming (like the web UI); --timeout is the max seconds to wait between chunks (default 180). If the LLM is slow, use e.g. --timeout 300.

Troubleshooting: "failed 2m" or step failing after curl

• Do not cd into the skill directory. Some runners run cd ~/.openclaw/skills/perplexica-search and then the script; if the skill is installed elsewhere (e.g. by ClawHub under a different path), cd can fail or the path may be wrong. Invoke the script by full path instead: python3 /path/to/perplexica-search/scripts/perplexica_search.py "query" (use whatever path or variable your environment gives for the skill directory, e.g. {baseDir}/scripts/perplexica_search.py).
• Runner timeout: If the runner has a 2-minute (or other) limit for a single step, a long search can be killed. Use --mode speed for faster results, or increase the runner’s tool/step timeout if possible.
• Check where the skill is installed: Run ls ~/.openclaw/skills/ or your ClawHub/OpenClaw skills path; then use that directory in the script path.

Examples

Quick Fact Check

bash

python3 scripts/perplexica_search.py "Who won the 2024 Nobel Prize in Physics?"

Research with Academic Sources

bash

python3 scripts/perplexica_search.py "Transformer architecture improvements 2024" --sources academic --mode quality

Technical Documentation Search

bash

python3 scripts/perplexica_search.py "Python async await best practices" --instructions "Focus on Python 3.10+ examples"

Publishing to ClawHub

To publish this skill to ClawHub:

bash

cd ~/.openclaw/skills/perplexica-search
clawhub publish . --slug perplexica-search --name "Perplexica Search" --version 1.0.0 --changelog "Initial release"

Security & Privacy

• Local only: The script accepts only local Perplexica URLs (localhost, 127.0.0.1, ::1, or host.docker.internal for Docker). Remote URLs are rejected. HTTP redirects are not followed. Resolved IPs are validated: the hostname is resolved and every address must be loopback (127.x, ::1) or private (RFC 1918); if DNS or /etc/hosts points a allowed hostname to a public IP, the script exits with an error. The script uses a request-scoped URL opener (no global install_opener), so it is safe to run as a subprocess and does not affect other code if imported.
• No API keys in skill: Uses Perplexica's configured providers; API keys are configured in Perplexica, not in this skill.

Limitations

• Requires Perplexica to be running locally
• Search quality depends on configured models and SearXNG setup
• Streaming mode requires additional client-side handling

External Endpoints

Endpoint	Data Sent	Purpose
http://localhost:3000/api/providers	None	Fetch available model providers
http://localhost:3000/api/search	Query, model selections, sources	Execute AI-powered search

All requests go to your local Perplexica instance. Perplexica itself may make external requests to search engines (SearXNG, Tavily, Exa) and LLM providers based on your configuration.

Implementation notes

• Run as subprocess: Invoke the script with python3 path/to/perplexica_search.py (not by importing it). The script uses a request-scoped URL opener only; it does not call install_opener, so it does not modify global urllib state.
• Resolved IP check: Before connecting, the script resolves the hostname and ensures every address is loopback (127.x, ::1) or private (RFC 1918). If DNS or /etc/hosts maps an allowed hostname to a public IP, the script exits with an error. Verify that localhost and your Perplexica host resolve to local or private IPs.
• Sandboxing: For higher assurance, run the skill in a network-restricted or sandboxed environment so that only localhost (or your Perplexica host) is reachable.

Trust Statement

By installing this skill, you trust that: (1) the skill will make HTTP requests only to a local Perplexica instance (URLs are validated to localhost, 127.0.0.1, ::1, or host.docker.internal); (2) resolved IPs are checked (loopback or private only) to mitigate DNS/hosts tampering; (3) HTTP redirects are rejected; (4) the script does not install a global urllib opener (intended to be run as a subprocess: python3 path/to/perplexica_search.py). Only install if you are running Perplexica locally. For higher assurance, run in a sandboxed or network-restricted environment.