OpenDeepSearch - An AI search tool that supports deep web search and information retrieval.
OpenDeepSearch is an open-source deep search tool that improves search performance based on open-source inference models and inference agents. It is specifically optimized for seamless integration with Hugging Face's SmolAgents and supports deep web search and...
What is OpenDeepSearch?
OpenDeepSearch is an open-source deep search tool that improves search performance based on open-source inference models and inference agents. It is optimized for seamless integration with Hugging Face's SmolAgents and supports deep web search and information retrieval. OpenDeepSearch consists of two core components: the Open Search Tool, which provides high-quality web search results, optimizing retrieval performance based on semantic reordering and multi-source integration; and the Open Reasoning Agent, which interprets user queries and invokes the tool to complete complex tasks. OpenDeepSearch supports various models and APIs, allowing for easy expansion.
Main functions of OpenDeepSearch
- Semantic searchIt provides in-depth search results based on a semantic reorderer, understanding the semantics of the query.
- Default modeFast and efficient, suitable for simple queries, with a short response time.
- Professional Mode (Depth Search)It provides deeper and more accurate results, making it suitable for complex multi-hop queries and problems requiring cross-reference verification.
- Seamless integration with AI agentsCompatible with Hugging Face's SmolAgents ecosystem, supporting code generation and inference tasks.
- ScalabilityIt supports multiple models and APIs, allowing users to configure them flexibly according to their needs.
OpenDeepSearch's technical principles
- Open Search ToolThis approach improves the coverage and diversity of search results by generating multiple semantically related queries. It retrieves relevant context from the Search Engine Results Page (SERP) API, formats it, and prioritizes reliable sources. Relevant paragraphs are extracted from the retrieved web pages, and content is filtered using a semantic reordering tool to ensure all relevant context is included.
- Open Reasoning AgentBased on the ReAct agent (ODS-v1), it uses Chain-of-Thought (CoT) reasoning and the ReAct framework to solve problems step by step, combining thinking, action, and observation steps. It supports tool calls such as web search, mathematical calculation (via the Wolfram Alpha API), and continued thinking.
- CodeAct-based proxy (ODS-v2)It uses Chain-of-Code (CoC) inference to solve complex problems by generating and executing code. It supports code generation and execution, making it suitable for tasks requiring precise computation.
- Plug and play frameUsers can choose any base LLM (such as DeepSeek-R1 or Llama3.1-70B) to use in conjunction with the ODS framework for optimal performance.
OpenDeepSearch project address
- GitHub repository:https://github.com/sentient-agi/OpenDeepSearch
- HuggingFace model library:https://huggingface.co/papers/2503.20201
- arXiv technical paper:https://arxiv.org/pdf/2503.20201
Application scenarios of OpenDeepSearch
- Solutions to complex problemsSolve multi-hop queries and cross-domain issues by gradually decomposing and integrating the answers.
- Real-time information retrievalGet the latest news, dynamic data (such as weather, flights) and other real-time information.
- Education and Research:It supports academic research and online learning, enabling users to find literature and interpret knowledge.
- Business AnalysisAnalyze market trends and competitor information to improve decision-making efficiency.
- Personal productivityQuickly find answers to everyday questions, automate tasks, and save time and effort.