Parallel

调用 Parallel.ai 搜索 API（one-shot/fast/agentic 三种模式），通过 Python SDK 及 scripts 下的 search.py 等脚本执行搜索、深度研究、实体查找、监控与报告任务，输出含 URL、标题、摘录、发布日期与引用的结构化结果；需要 PARALLEL_API_KEY 并联网。

mvanhorn

热度 73.07

最近更新 2026-05-18 11:53:20

分类：搜索依赖：代码执行 / 第三方 API应用场景：研究 / 报告撰写 / 市场分析 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add parallel

Metadata

name: parallel
version: 1.1.0
description: High-accuracy web search and research via Parallel.ai API. Optimized for AI agents with rich excerpts and citations. Supports agentic mode for token-efficient multi-step reasoning.
author: mvanhorn
license: MIT
repository: https://github.com/mvanhorn/clawdbot-skill-parallel
homepage: https://parallel.ai
triggers: ["parallel","deep search","research"]
metadata: {"openclaw":{"emoji":"🔬","requires":{"env":["PARALLEL_API_KEY"]},"primaryEnv":"PARALLEL_API_KEY","tags":["search","research","web","parallel","citations"]}}

Parallel.ai 🔬

High-accuracy web search API built for AI agents. Outperforms Perplexity/Exa on research benchmarks.

Setup

pip install parallel-web

API key is configured. Uses Python SDK.

from parallel import Parallel
client = Parallel(api_key="YOUR_KEY")
response = client.beta.search(
    mode="one-shot",  # or "fast" for lower latency/cost, "agentic" for multi-hop
    max_results=10,
    objective="your query"
)

Modes

Mode	Use Case	Tradeoff
`one-shot`	Default, balanced accuracy	Best for most queries
`fast` ⚡	Quick lookups, cost-sensitive	Lower latency/cost, may sacrifice some accuracy
`agentic`	Complex multi-hop research	Higher accuracy, more expensive

Quick Usage

# Default search (one-shot mode)
{baseDir}/.venv/bin/python {baseDir}/scripts/search.py "Who is the CEO of Anthropic?" --max-results 5

# Fast mode - lower latency/cost ⚡
{baseDir}/.venv/bin/python {baseDir}/scripts/search.py "latest AI news" --mode fast

# Agentic mode - complex research
{baseDir}/.venv/bin/python {baseDir}/scripts/search.py "compare transformer architectures" --mode agentic

# JSON output
{baseDir}/.venv/bin/python {baseDir}/scripts/search.py "latest AI news" --json

Response Format

Returns structured results with:

search_id - unique search identifier
results[] - array of results with:
- url - source URL
- title - page title
- excerpts[] - relevant text excerpts
- publish_date - when available
usage - API usage stats

When to Use

Deep research requiring cross-referenced facts
Company/person research with citations
Fact-checking with evidence-based outputs
Complex queries that need multi-hop reasoning
Higher accuracy than traditional search for research tasks

API Reference

Docs: https://docs.parallel.ai Platform: https://platform.parallel.ai