RAG & AI Pipelines Prompt Library for AI Tools

About This Product

Stop wasting hours crafting prompts for your RAG pipelines from scratch – this library delivers production-ready templates that actually work.

This prompt library solves the biggest pain in RAG: inconsistent response quality due to untested prompts. It provides 50+ pre-optimized templates for query decomposition, context compression, re-ranking, and answer generation, all designed to integrate seamlessly with LangChain, LlamaIndex, and custom AI tools. Save weeks of trial and error and start building reliable, accurate pipelines today.

## What's Included

- 50+ pre-built prompt templates for every RAG stage: query, retrieval, re-rank, generation - Optimized for top LM providers (OpenAI, Anthropic, Cohere, open-source models) - Ready-to-use within LangChain, LlamaIndex, and custom Python frameworks - Includes advanced patterns: multi-hop retrieval, self-querying, and adaptive context windows - Detailed documentation with use-case examples and customization guides

Key Features

• Stop wasting hours crafting prompts for your RAG pipelines from scratch – this library delivers production-ready templates that actually work
• This prompt library solves the biggest pain in RAG: inconsistent response quality due to untested prompts
• It provides 50+ pre-optimized templates for query decomposition, context compression, re-ranking, and answer generation, all designed to integrate seamlessly with LangChain, LlamaIndex, and custom AI tools
• Save weeks of trial and error and start building reliable, accurate pipelines today
• ## What's Included - 50+ pre-built prompt templates for every RAG stage: query, retrieval, re-rank, generation - Optimized for top LM providers (OpenAI, Anthropic, Cohere, open-source models) - Ready-to-use within LangChain, LlamaIndex, and custom Python frameworks - Includes advanced patterns: multi-hop retrieval, self-querying, and adaptive context windows - Detailed documentation with use-case examples and customization guides ## Who Is This For - AI developers building RAG-based chatbots or document QA systems - Data scientists tired of prompt engineering guesswork in retrieval pipelines - Prompt engineers needing a structured starting point for complex RAG workflows - Tech teams launching automated customer support or knowledge retrieval tools ## How It Works Download the ZIP file containing all prompt templates as plain text and JSON files
• Import any template into your codebase, adjust variables like model name or temperature, and plug it into your RAG pipeline