🤖
AIllowpages
AI + Yellow Pages · The AI Tools Search Engine
🤖

Rivet

Framework Free

Rivet is an open-source visual AI programming environment developed by Ironclad for building complex LLM pipelines through a node-based graph editor. It supports multi-model workflows, parallel execution, conditional branching, and live debugging of running pipelines, making it powerful enough for production use cases while remaining accessible through its visual interface. AI engineers and product teams building sophisticated agent workflows and prompt chains use Rivet to design, test, and debug LLM applications with full visual observability.

💰 Pricing
Free
📂 Category
Framework
🏷️ Tags
framework, visual, llm
↗ Visit Tool 🔍 Similar Tools ← Back to All Tools
🔗 Related Tools
LlamaIndex
Framework
LlamaIndex is a data framework for building LLM-powered applications that provides the tools to ingest, structure, and access private or domain-specific data for use with large language models in RAG pipelines, agents, and query engines. It offers hundreds of data connectors, multiple index types optimized for different query patterns, and query engine abstractions that handle retrieval, reranking, and response synthesis. AI engineers and full-stack developers building knowledge-intensive LLM applications use LlamaIndex as the go-to framework for connecting LLMs to custom data sources efficiently and reliably.
LangChain
Framework
LangChain is a cutting-edge framework empowering developers to design, build, and deploy sophisticated LLM-powered applications, ideal for data scientists, researchers, and businesses seeking to unlock the full potential of language models. With its robust tools for prompt chaining and seamless API integration, users can create scalable, production-ready AI agents for various industries, including customer service, content generation, and more. Its flexibility and ease of use make it an invaluable resource for companies and individuals looking to integrate AI into their products and services.
Gradio
Framework
Gradio is a versatile framework that empowers data scientists to effortlessly create and share user interfaces for machine learning models, facilitating seamless model demonstration and collaboration. Used by researchers, developers, and data enthusiasts alike, Gradio's customizable and shareable web-based interfaces enable the rapid prototyping and deployment of ML applications. Ideal for UI and ML prototyping, Gradio excels in simple model sharing and demonstration, as well as in more complex applications.