Ai Rag Pipeline

AI RAG Pipeline

Build RAG (Retrieval Augmented Generation) pipelines via inference.sh CLI.

Quick Start

curl -fsSL https://cli.inference.sh | sh && 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\" }" Install note: The install script only detects your OS/architecture, downloads the matching binary from dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.

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.

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]

Search Tools

ToolApp IDBest ForTavily Searchtavily/search-assistantAI-powered search with answersExa Searchexa/searchNeural search, semantic matchingExa Answerexa/answerDirect factual answers

Extraction Tools

ToolApp IDBest ForTavily Extracttavily/extractClean content from URLsExa Extractexa/extractAnalyze web content

LLM Tools

ModelApp IDBest ForClaude Sonnet 4.5openrouter/claude-sonnet-45Complex analysisClaude Haiku 4.5openrouter/claude-haiku-45Fast processingGPT-4oopenrouter/gpt-4oGeneral purposeGemini 2.5 Proopenrouter/gemini-25-proLong context

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?" }'

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](URL) 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"}')

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"

Related Skills

# Web search tools npx skills add inference-sh/skills@web-search # LLM models npx skills add inference-sh/skills@llm-models # Content pipelines npx skills add inference-sh/skills@ai-content-pipeline # Full platform skill npx skills add inference-sh/skills@inference-sh Browse all apps: infsh app list

Documentation

Adding Tools to Agents - Agent tool integration Building a Research Agent - Full guide