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Local Deep Researcher is a fully local web research assistant that uses any LLM hosted by Ollama or LMStudio. Give it a topic and it will generate a web search query, gather web search results, summarize the results of web search, reflect on the summary to examine knowledge gaps, generate a new…

This project is a reference implementation and application template for Retrieval-Augmented Generation (RAG). It integrates Azure OpenAI with Azure AI Search to enable conversational chat interfaces that provide grounded responses based on private enterprise data. The system is distinguished by its multimodal AI interface, allowing it to process and reason over combined text, image, and PDF content. It employs a hybrid search architecture that combines vector and keyword retrieval with semantic reranking to prioritize the most relevant documents for prompt augmentation. The project covers a

Open-deep-research is an autonomous research orchestrator and language model-based agent designed to execute multi-step investigations and automated web research workflows. It explores complex topics systematically by generating targeted search queries, processing multiple sources simultaneously, and recursively feeding synthesized findings back into search planning loops to expand its research scope. The system coordinates these tasks through a graph-based agent orchestration model that routes state between modular nodes for searching, reading, and reasoning. It accelerates data collection v