Aquiles-ai
Aquiles-ai is a company that creates advanced Retrieval-Augmented Generation (RAG) solutions. Their main project, Aquiles-RAG, is built on Redis and offers a user-friendly interface through FastAPI REST APIs. This solution improves document indexing and query answering by combining semantic search with powerful language models like GPT-4.1.
Aquiles-ai provides several repositories to support and demonstrate the capabilities of Aquiles-RAG:
Aquiles-RAG: The main repository for the high-performance RAG solution built on Redis, providing a robust interface through FastAPI.
aquiles-example-deploy: This repository offers an example of how to deploy Aquiles-RAG, including its folder structure, to help users implement the solution effectively.
Aquiles-RAG-JS: A JavaScript variant of Aquiles-RAG, developed using Fastify, which continues the high-performance philosophy of the Python version with FastAPI.
aquiles-chat-demo: A demo chatbot that utilizes Aquiles-RAG as a RAG server to index documents and answer queries by combining semantic search with GPT-4.1, showcasing the practical applications of the technology.
aqRAG-docs: This repository likely contains documentation and additional resources related to Aquiles-RAG, although specific details are not provided.
These repositories collectively demonstrate Aquiles-ai's commitment to advancing RAG technology and providing practical tools and examples for users to implement and benefit from their solutions.
This content is either user submitted or generated using AI technology (including, but not limited to, Google Gemini API, Llama, Grok, and Mistral), based on automated research and analysis of public data sources from search engines like DuckDuckGo, Google Search, and SearXNG, and directly from the tool's own website and with minimal to no human editing/review. THEJO AI is not affiliated with or endorsed by the AI tools or services mentioned. This is provided for informational and reference purposes only, is not an endorsement or official advice, and may contain inaccuracies or biases. Please verify details with original sources.
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