'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker
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Updated
Jun 28, 2024 - HTML
'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker
CodeRAG-Bench: Can Retrieval Augment Code Generation?
Open source implementation of Sova - RAG-based Web search engine using power of LLMs. Using Langchain, Ollama, HuggingFace Embeddings and scraping google search results.
This is a RAG based chatbot in which semantic cache and guardrails have been incorporated.
AI-based search engine done right
Source code for the Gilded Age Gourmet, a cooking chat app based on the Boston Cooking-School Cook Book.
This example repository illustrates the usage of LLMs with Quarkus by using the quarkus-langchain4j extension to build integrations with ChatGPT or Hugging Face. The code dives into simple conversations, retrieval augmented generation (RAG) and building agents.
This is a RAG implementation using Open Source stack. BioMistral 7B has been used to build this app along with PubMedBert as an embedding model, Qdrant as a self hosted Vector DB, and Langchain & Llama CPP as an orchestration frameworks.
An Art-Deco bot that utilizes RAG. Benchmarking of RAG vs. LLMs on QA and timing
Retrieval-Augmented Generation using Azure OpenAI
a sophisticated recommendation system for CNC machines, leveraging state-of-the-art AI technology, and integrating the capabilities of Google's Gemini 1.0 API
Source code for the Gilded Age Gourmet, a cooking chat app based on the Boston Cooking-School Cook Book
Just training on langchain to improve RAG skills
Advancing the next generation of Retrieval Augmented Generation (RAG): A dynamic exploration of RAG technology's evolving landscape. This repository is the go-to resource for state-of-the-art developments, conceptual advancements, and the future trajectory of AI-driven information retrieval and generation.
Build an efficient Python-based Retrieval-Augmented Generation (RAG) system for contextual query answering over personal data, all with natural language using ChatGoogleGenerativeAI (gemini-pro).
This application aims to provide users with a convenient way to interact with Langchain documentation through a chat interface powered by advanced Generative AI technologies
💬🤖 Build a better chatbot 🤖💬
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