RomainGRAS42/web-search

Web Search & Extraction

Search the web and extract content via inference.sh CLI.

Quick Start

curl -fsSL https://cli.inference.sh | sh && infsh login

# Search the web
infsh app run tavily/search-assistant --input '{"query": "latest AI developments 2024"}'

Available Apps

Tavily

| App | App ID | Description | |-----|--------|-------------| | Search Assistant | tavily/search-assistant | AI-powered search with answers | | Extract | tavily/extract | Extract content from URLs |

Exa

| App | App ID | Description | |-----|--------|-------------| | Search | exa/search | Smart web search with AI | | Answer | exa/answer | Direct factual answers | | Extract | exa/extract | Extract and analyze web content |

Examples

Tavily Search

infsh app run tavily/search-assistant --input '{
  "query": "What are the best practices for building AI agents?"
}'

Returns AI-generated answers with sources and images.

Tavily Extract

infsh app run tavily/extract --input '{
  "urls": ["https://example.com/article1", "https://example.com/article2"]
}'

Extracts clean text and images from multiple URLs.

Exa Search

infsh app run exa/search --input '{
  "query": "machine learning frameworks comparison"
}'

Returns highly relevant links with context.

Exa Answer

infsh app run exa/answer --input '{
  "question": "What is the population of Tokyo?"
}'

Returns direct factual answers.

Exa Extract

infsh app run exa/extract --input '{
  "url": "https://example.com/research-paper"
}'

Extracts and analyzes web page content.

Workflow: Research + LLM

# 1. Search for information
infsh app run tavily/search-assistant --input '{
  "query": "latest developments in quantum computing"
}' > search_results.json

# 2. Analyze with Claude
infsh app run openrouter/claude-sonnet-45 --input '{
  "prompt": "Based on this research, summarize the key trends: <search-results>"
}'

Workflow: Extract + Summarize

# 1. Extract content from URL
infsh app run tavily/extract --input '{
  "urls": ["https://example.com/long-article"]
}' > content.json

# 2. Summarize with LLM
infsh app run openrouter/claude-haiku-45 --input '{
  "prompt": "Summarize this article in 3 bullet points: <content>"
}'

Use Cases

• Research: Gather information on any topic
• RAG: Retrieval-augmented generation
• Fact-checking: Verify claims with sources
• Content aggregation: Collect data from multiple sources
• Agents: Build research-capable AI agents

Related Skills

# Full platform skill (all 150+ apps)
npx skills add inferencesh/skills@inference-sh

# LLM models (combine with search for RAG)
npx skills add inferencesh/skills@llm-models

# Image generation
npx skills add inferencesh/skills@ai-image-generation

Browse all apps: infsh app list

Documentation

• Adding Tools to Agents - Equip agents with search
• Building a Research Agent - LLM + search integration guide
• Tool Integration Tax - Why pre-built tools matter