LlamaIndex AI technology page Top Builders

Explore the top contributors showcasing the highest number of LlamaIndex AI technology page app submissions within our community.

LlamaIndex: a Data Framework for LLM Applications

LlamaIndex is an open source data framework that allows you to connect custom data sources to large language models (LLMs) like GPT-4, Claude, Cohere LLMs or AI21 Studio. It provides tools for ingesting, indexing, and querying data to build powerful AI applications augmented by your own knowledge.

TypeData framework for LLM applications

Key Features of LlamaIndex

  • Data Ingestion: Easily connect to existing data sources like APIs, documents, databases, etc. and ingest data in various formats.
  • Data Indexing: Store and structure ingested data for optimized retrieval and usage with LLMs. Integrate with vector stores and databases.
  • Query Interface: LlamaIndex provides a simple prompt-based interface to query your indexed data. Ask a question in natural language and get an LLM-powered response augmented with your data.
  • Flexible & Customizable: LlamaIndex is designed to be highly flexible. You can customize data connectors, indices, retrieval, and other components to fit your use case.

How to Get Started with LlamaIndex

LlamaIndex is open source and available on GitHub. Visit the repo to install the Python package, access documentation, guides, examples, and join the community:

AI Tutorials

LlamaIndex Libraries

A curated list of libraries and technologies to help you build great projects with LlamaIndex.

LlamaIndex AI technology page Hackathon projects

Discover innovative solutions crafted with LlamaIndex AI technology page, developed by our community members during our engaging hackathons.

Zang Beto

Zang Beto

Zhang Beto: Revolutionizing Communication and Tourism in Benin Zhang Beto is the first-ever native application supporting speech-to-text and text-to-speech functionalities exclusively in Fan, Zhang Beto is set to transform how locals and tourists interact and explore the rich cultural heritage of Benin. Fan Language Speech-to-Text: Effortlessly convert spoken Fan into written text. Whether you're a local needing to transcribe conversations or a tourist trying to jot down phrases, Zhang Beto ensures accuracy and ease of use. Fan Language Text-to-Speech: Type in Fan and let the app speak for you. Perfect for learning pronunciation, practicing conversations, or communicating with locals when you don't feel confident speaking the language yourself. Tourism Enhancement: Discover Benin's hidden gems with AI-driven recommendations. Zhang Beto utilizes advanced algorithms to suggest tourist spots, cultural landmarks, and activities tailored to your interests, making your visit to Benin memorable and enriching. Cultural Insights: Learn about Benin's traditions, history, and customs through the app's curated content. Zhang Beto is not just a communication tool but also an educational resource, helping users gain a deeper understanding of the Fan-speaking community. User-Friendly Interface: Designed with simplicity and functionality in mind, Zhang Beto offers an intuitive user experience that caters to both tech-savvy individuals and those less familiar with digital applications. Boosting Tourism: With tourism contributing only 0.7% to Benin's economy, Zhang Beto aims to invigorate this sector by making it easier for tourists to navigate and appreciate the country's attractions through the Fan language. Cultural Preservation: Zhang Beto plays a crucial role in documenting and preserving the Fan language, ensuring that it remains a vibrant part of Benin's cultural landscape for future generations. Zhang Beto - Connecting People, Discovering Benin.

Cricket Video Analyzer - 12 labs RAG

Cricket Video Analyzer - 12 labs RAG

Cricket VIDEO ANALYZER to understand a batsman using 12 labs API +llama index + GPT 4 Solution: Choose 1 batsman (Glenn Maxwell of Australia) (Source 1) : Use 12 labs API to understand their playing style - Understand the video Generate the text (Source 2 for additional augmentation) : Use cricinfo.com APIs to get ball by ball commentary of the batsman Build a vector store of the dataset built using (2) and (3) Use GPT-4 to answer questions on this dataset (RAG application) Global Popularity and Demand: The immense popularity of cricket has led to a high demand for video analysis tools. Coaches, players, and teams use these tools to analyze player performance, match strategies, and opponent weaknesses. The ability to break down every aspect of a game, from batting techniques to bowling actions, has become crucial for success. As cricket leagues (such as the Indian Premier League) and international tournaments continue to grow, the demand for sophisticated video analysis software has skyrocketed. Advanced Technology and Data Insights: Cricket video analysis tools have evolved significantly over the years. High-speed cameras, ball-tracking systems, and AI algorithms allow for precise analysis of player movements, ball trajectories, and field placements. Coaches can identify patterns, assess player fitness, and make data-driven decisions. For example, analyzing a batsman’s scoring zones or a bowler’s release point can provide valuable insights.