Sophora - AI Reasoning, Function-calling & Knowledge Retrieval
-
Updated
Feb 28, 2025 - Pascal
Sophora - AI Reasoning, Function-calling & Knowledge Retrieval
Stateful AI Agent for Knowledge Extraction
PromptWeaver: RAG Edition helps design effective prompts for Traditional, Hybrid, and Agentic RAG systems. It offers templates, system prompts, and best practices to improve accuracy, context use, and LLM reasoning.
Notebook examples for using OpenAI's Assistants API with the file search (knowledge retrieval) functionality.
⚡️ Local RAG API using FastAPI + LangChain + Ollama | Upload PDFs, DOCX, CSVs, XLSX and ask questions using your own documents — fully offline!
CareConnect uses state-of-the-art large language models (LLMs) to provide rapid, reliable medical guidance. This project addresses increasing wait times and health misinformation, offering timely assistance and supporting informed decision-making to alleviate the burden on the healthcare system.
Code to make any AI have unlimited context persistent memory. In the example, a software for any AI to read the Uniform Commercial Code of Michigan. A document of 220,000 tokens
Local Retrieval-Augmented Generation (RAG) system built with FastAPI, integrating vector search, Elasticsearch, and optional web search to power LLM-based intelligent question answering using models like Mistral or GPT-4.
A local Retrieval-Augmented Generation (RAG) system for answering questions about TouchDesigner using wiki pages, tutorials, and other structured or semi-structured content. Powered by FAISS and local LLMs via Ollama.
A Streamlit-based application that leverages Retrieval Augmented Generation (RAG) to provide accurate answers from Wikipedia content.
Scientific Agent: A Retrieval-Augmented Generation (RAG) System for Domain-Aware Literature Review Automation
QueryVault is a robust RAG system for structured Q&A data. It ingests JSON files, embeds content via ChromaDB, and serves context-aware answers using FastAPI and Google Gemini. With a modular design and CLI tools, it's built for scalable, secure AI-powered knowledge retrieval.
🚀 Revolutionize your data interaction with a cutting-edge chatbot built on Retrieval-Augmented Generation (RAG) and OpenAI’s GPT-4. Upload documents, create custom knowledge bases, and get precise, contextual answers. Ideal for research, business operations, customer support, and more!
An end-to-end multi-source knowledge retrieval system using LangChain, FAISS, and OpenAI embeddings. This Retrieval-Augmented Generation (RAG) pipeline intelligently searches across Wikipedia, arXiv, and custom websites, optimizing source selection and delivering precise, real-time results based on query relevance.
Add a description, image, and links to the knowledge-retrieval topic page so that developers can more easily learn about it.
To associate your repository with the knowledge-retrieval topic, visit your repo's landing page and select "manage topics."