What is OpenDeepSearch
OpenDeepSearch is an open-source deep search tool that improves search performance based on open-source reasoning models and reasoning agents. It is specifically optimized for seamless integration with Hugging Face's SmolAgents and supports deep web search and information retrieval. OpenDeepSearch includes two core components: Open Search Tool provides high-quality web search results, optimizing retrieval effectiveness based on semantic reranking and multi-source integration. Open Reasoning Agent is responsible for interpreting user queries and invoking tools to complete complex tasks. OpenDeepSearch supports multiple models and APIs, making extension easy.
Main Features of OpenDeepSearch
- Semantic Search: Provides deep search results based on a semantic reranker, understanding query semantics.
- Default Mode: Fast and efficient, suitable for simple queries, with short response times.
- Professional Mode (Deep Search): More in-depth and accurate, suitable for complex multi-hop queries and questions requiring cross-reference verification.
- Seamless Integration with AI Agents: Compatible with Hugging Face's SmolAgents ecosystem, supporting code generation and reasoning tasks.
- Scalability: Supports multiple models and APIs, allowing users to flexibly configure according to their needs.
Technical Principles of OpenDeepSearch
- Open Search Tool: Based on generating multiple semantically related queries, improving the coverage and diversity of retrieval results. Retrieves relevant context from search engine results page (SERP) APIs, formats it, and prioritizes reliable sources. Extracts relevant passages from retrieved web pages, filters content based on a semantic reranker, and ensures all relevant context is included.
- Open Reasoning Agent: A ReAct-based agent (ODS-v1) that uses Chain-of-Thought (CoT) reasoning and the ReAct framework, combining thought, action, and observation steps to solve problems step by step. Supports tool invocation, such as web search, mathematical computation (via the Wolfram Alpha API), and continued thinking.
- CodeAct-based Agent (ODS-v2): Uses Chain-of-Code (CoC) reasoning to solve complex problems based on generated and executed code. Supports code generation and execution, suitable for tasks requiring precise computation.
- Plug-and-Play Framework: Users can choose any base LLM (such as DeepSeek-R1 or Llama3.1-70B) and combine it with the ODS framework to achieve optimal performance.
Project Address of OpenDeepSearch
- 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
- Complex Question Answering: Solves multi-hop queries and cross-domain problems, breaking them down step by step and integrating answers.
- Real-Time Information Retrieval: Obtains real-time information such as the latest news and dynamic data (e.g., weather, flights).
- Education and Research:Supports academic research and online learning, finding literature and explaining knowledge.
- Business Analysis: Analyzes market trends and competitor information to improve decision-making efficiency.
- Personal Productivity: Quickly queries everyday questions and automates tasks, saving time and effort.