Dust

DUST: Empowering Language Model App Creation and Deployment

Unlock the potential of building robust workflows on LLMs (Large Language Models) and Semantic Search with DUST. Seamlessly deploy to API or utilize directly from DUST, complete with version control, cached interactions, and connectivity to diverse Data Sources.

Pricing: Free
Semrush rank: 4.9m

Features

  • Chained LLM Apps: Create intricate workflows by chaining calls between models, code execution, and queries to external services.
  • Multiple Inputs: Enhance LLM app design by iterating on several inputs simultaneously to prevent overfitting and ensure versatility.
  • Model Choice: Design applications against models served by OpenAI, Cohere, AI21, and more, with the ability to switch seamlessly between them.
  • Version History: Retrieve iterations, model outputs, and few-shot examples effortlessly with DUST’s automatically saved version history.
  • Caching: Accelerate iterations and reduce costs by leveraging cached model interactions within the DUST platform.
  • Easy Deployment & Use: Deploy applications to an API endpoint or utilize them directly from the DUST interface, ensuring a hassle-free experience.
  • Data Sources: Access fully managed semantic search engines seamlessly integrated for querying within your workflows.
  • Community Example Apps: Explore and learn from a variety of apps created by the community, providing inspiration and a quick start with DUST.

Use Cases:

  • Semantic Search for IPCC AR6 Report: Utilize semantic search to answer questions and gain insights into the IPCC AR6 report.
  • Wedding Thank You Notes: Effortlessly overcome the blank page problem by generating personalized content for wedding thank you notes.
  • Web Search Assistant: Achieve high factual accuracy in responses by utilizing DUST as a web search assistant, searching online and compiling content-based responses.
  • Generating Code for Maths Questions: Efficiently generate code to answer mathematical questions, simplifying complex problem-solving.
  • Teaching LLM to Teach Itself: Teach the language model to instruct itself in new tasks by providing few-shot examples based on high-level task descriptions.

DUST stands as a potent tool for anyone venturing into the realm of language model app development and deployment. With a rich feature set, user-friendly deployment, and access to managed data sources, DUST opens up endless possibilities.

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