AI RAG Pipeline Build RAG (Retrieval Augmented Generation) pipelines via inference.sh CLI. Quick Start Requires inference.sh CLI ( infsh ). Get installation instructions: npx skills add inference-sh/skills@agent-tools infsh login
Simple RAG: Search + LLM
SEARCH
- $(
- infsh app run tavily/search-assistant
- --input
- '{"query": "latest AI developments 2024"}'
- )
- infsh app run openrouter/claude-sonnet-45
- --input
- "{
- \"
- prompt
- \"
- :
- \"
- Based on this research, summarize the key trends:
- $SEARCH
- \"
- }"
- What is RAG?
- RAG combines:
- Retrieval
-
- Fetch relevant information from external sources
- Augmentation
-
- Add retrieved context to the prompt
- Generation
- LLM generates response using the context This produces more accurate, up-to-date, and verifiable AI responses. RAG Pipeline Patterns Pattern 1: Simple Search + Answer [User Query] -> [Web Search] -> [LLM with Context] -> [Answer] Pattern 2: Multi-Source Research [Query] -> [Multiple Searches] -> [Aggregate] -> [LLM Analysis] -> [Report] Pattern 3: Extract + Process [URLs] -> [Content Extraction] -> [Chunking] -> [LLM Summary] -> [Output] Available Tools Search Tools Tool App ID Best For Tavily Search tavily/search-assistant AI-powered search with answers Exa Search exa/search Neural search, semantic matching Exa Answer exa/answer Direct factual answers Extraction Tools Tool App ID Best For Tavily Extract tavily/extract Clean content from URLs Exa Extract exa/extract Analyze web content LLM Tools Model App ID Best For Claude Sonnet 4.5 openrouter/claude-sonnet-45 Complex analysis Claude Haiku 4.5 openrouter/claude-haiku-45 Fast processing GPT-4o openrouter/gpt-4o General purpose Gemini 2.5 Pro openrouter/gemini-25-pro Long context Pipeline Examples Basic RAG Pipeline
1. Search for information
SEARCH_RESULT
$( infsh app run tavily/search-assistant --input '{ "query": "What are the latest breakthroughs in quantum computing 2024?" }' )
2. Generate grounded response
infsh app run openrouter/claude-sonnet-45 --input "{ \" prompt \" : \" You are a research assistant. Based on the following search results, provide a comprehensive summary with citations. Search Results: $SEARCH_RESULT Provide a well-structured summary with source citations. \" }" Multi-Source Research
Search multiple sources
TAVILY
$( infsh app run tavily/search-assistant --input '{"query": "electric vehicle market trends 2024"}' ) EXA = $( infsh app run exa/search --input '{"query": "EV market analysis latest reports"}' )
Combine and analyze
infsh app run openrouter/claude-sonnet-45 --input "{ \" prompt \" : \" Analyze these research results and identify common themes and contradictions. Source 1 (Tavily): $TAVILY Source 2 (Exa): $EXA Provide a balanced analysis with sources. \" }" URL Content Analysis
1. Extract content from specific URLs
CONTENT
$( infsh app run tavily/extract --input '{ "urls": [ "https://example.com/research-paper", "https://example.com/industry-report" ] }' )
2. Analyze extracted content
infsh app run openrouter/claude-sonnet-45 --input "{ \" prompt \" : \" Analyze these documents and extract key insights: $CONTENT Provide: 1. Key findings 2. Data points 3. Recommendations \" }" Fact-Checking Pipeline
Claim to verify
CLAIM
"AI will replace 50% of jobs by 2030"
1. Search for evidence
EVIDENCE
$( infsh app run tavily/search-assistant --input "{ \" query \" : \" $CLAIM evidence studies research \" }" )
2. Verify claim
infsh app run openrouter/claude-sonnet-45 --input "{ \" prompt \" : \" Fact-check this claim: ' $CLAIM ' Based on the following evidence: $EVIDENCE Provide: 1. Verdict (True/False/Partially True/Unverified) 2. Supporting evidence 3. Contradicting evidence 4. Sources \" }" Research Report Generator TOPIC = "Impact of generative AI on creative industries"
1. Initial research
OVERVIEW
$( infsh app run tavily/search-assistant --input "{ \" query \" : \" $TOPIC overview \" }" ) STATISTICS = $( infsh app run exa/search --input "{ \" query \" : \" $TOPIC statistics data \" }" ) OPINIONS = $( infsh app run tavily/search-assistant --input "{ \" query \" : \" $TOPIC expert opinions \" }" )
2. Generate comprehensive report
infsh app run openrouter/claude-sonnet-45 --input "{ \" prompt \" : \" Generate a comprehensive research report on: $TOPIC Research Data: == Overview == $OVERVIEW == Statistics == $STATISTICS == Expert Opinions == $OPINIONS Format as a professional report with: - Executive Summary - Key Findings - Data Analysis - Expert Perspectives - Conclusion - Sources \" }" Quick Answer with Sources
Use Exa Answer for direct factual questions
infsh app run exa/answer --input '{ "question": "What is the current market cap of NVIDIA?" }' Best Practices 1. Query Optimization
Bad: Too vague
"AI news"
Good: Specific and contextual
"latest developments in large language models January 2024" 2. Context Management
Summarize long search results before sending to LLM
SEARCH
$( infsh app run tavily/search-assistant --input '{"query": "..."}' )
If too long, summarize first
SUMMARY
$( infsh app run openrouter/claude-haiku-45 --input "{ \" prompt \" : \" Summarize these search results in bullet points: $SEARCH \" }" )
Then use summary for analysis
infsh app run openrouter/claude-sonnet-45 --input "{ \" prompt \" : \" Based on this research summary, provide insights: $SUMMARY \" }" 3. Source Attribution Always ask the LLM to cite sources: infsh app run openrouter/claude-sonnet-45 --input '{ "prompt": "... Always cite sources in Source Name format." }' 4. Iterative Research
First pass: broad search
INITIAL
$( infsh app run tavily/search-assistant --input '{"query": "topic overview"}' )
Second pass: dive deeper based on findings
DEEP
$( infsh app run tavily/search-assistant --input '{"query": "specific aspect from initial search"}' ) Pipeline Templates Agent Research Tool
!/bin/bash
research.sh - Reusable research function
research ( ) { local query = " $1 "
Search
local results = $( infsh app run tavily/search-assistant --input "{ \" query \" : \" $query \" }" )
Analyze
infsh app run openrouter/claude-haiku-45 --input "{ \" prompt \" : \" Summarize: $results \" }" } research "your query here"