AgentIndex icon
AgentIndex
haiku.rag logo
haiku.rag
★ 634
vs
turbo-flow logo
turbo-flow
★ 176

haiku.rag vs turbo-flow

haiku.rag: Haiku RAG is an agentic retrieval-augmented generation (RAG) system built with LanceDB, Pydantic AI, and Docling. It offers advanced features like hybrid search, multi-agent workflows for research, complex analytical tasks via code execution, and conversational RAG with session memory.; turbo-flow: Turbo Flow is a complete agentic development environment integrating Claude Flow V3 and RuVector, designed to streamline AI-powered development. It provides a comprehensive stack with 36 built-in skills, 15 plugins, and a robust memory system for advanced agent orchestration and intelligence.

01

TL;DR

haiku.rag logo
haiku.ragRAG / Knowledge Base · ★ 634

Indexing various document types (e.g., PDFs, URLs) for search and retrieval.

Read haiku.rag full review →
turbo-flow logo
turbo-flowRAG / Knowledge Base · ★ 176

Agentic AI Development and Orchestration

Read turbo-flow full review →
02

Side-by-Side Comparison

Field
haiku.rag logohaiku.rag
turbo-flow logoturbo-flow
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 634
★ 176
License
MIT
MIT
Install Command
pip install haiku.rag
devpod up https://github.com/marcuspat/turbo-flow-claude --ide vscode
Updated
1d ago
6d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
RAG, Agentic AI, Hybrid Search
Agentic AI, Multi-Agent System, Vector Database
03

Features

haiku.rag logohaiku.rag
01Hybrid search — Vector + full-text with Reciprocal Rank Fusion
02Research agents — Multi-agent workflows via pydantic-graph: plan, search, evaluate, synthesize
03RLM agent — Complex analytical tasks via sandboxed Python code execution
04Conversational RAG — Chat TUI and web application for multi-turn conversations with session memory
05Local-first — Embedded LanceDB, no servers required. Also supports S3, GCS, Azure, and LanceDB Cloud
turbo-flow logoturbo-flow
01Complete Agentic Development Environment with Claude Flow V3 and RuVector
02Integrated RuVector Neural Engine for advanced vector search and GNN capabilities
0336 Built-in Skills and 15 Plugins for diverse AI-powered development tasks
04Robust Agent Orchestration with 60+ agents and 175+ MCP tools
05Advanced Memory System featuring HNSW Vector Search and AgentDB SQLite
04

Use Cases

haiku.rag logohaiku.rag
↳Indexing various document types (e.g., PDFs, URLs) for search and retrieval.
↳Performing question answering with source citations to verify information.
↳Executing complex analytical tasks using sandboxed Python code (RLM mode).
↳Engaging in multi-turn conversations with memory for contextual understanding.
↳Integrating as a tool for AI assistants (e.g., Claude Desktop) for document management, search, and QA.
turbo-flow logoturbo-flow
↳Agentic AI Development and Orchestration
↳Automated Quality Engineering and Test Generation
↳Advanced Code Intelligence and Refactoring
↳Domain-Specific AI Applications (e.g., Financial, Healthcare, Legal)
↳Multi-agent Collaboration and Swarm Coordination
FAQ

FAQ

What is the difference between haiku.rag and turbo-flow?
Both haiku.rag and turbo-flow are in the RAG / Knowledge Base category. haiku.rag has 634 stars, while turbo-flow has 176 stars.
Which is better, haiku.rag or turbo-flow?
The best choice depends on your use case. Choose haiku.rag if Indexing various document types (e.g., PDFs, URLs) for search and retrieval., and turbo-flow if Agentic AI Development and Orchestration.
Is haiku.rag free or open source?
Yes, haiku.rag is open source on GitHub (MIT).
Is turbo-flow free or open source?
Yes, turbo-flow is open source on GitHub (MIT).
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