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MiroThinker is a deep research agent optimized for complex research and prediction tasks. Our latest models, MiroThinker-1.7, achieves 74.0 and 75.3 on the BrowseComp and BrowseComp Zh, respectively.
🔍 The hardest search benchmark in the wild — vague, multi-turn, proactive. 200 long-horizon tasks with persona-driven progressive disclosure, scored by verifiable schema-free knowledge-graph evaluation. No vibes, just triplet F1.
🔍 OpenSearch-VL provides a fully open recipe for training strong multimodal deep search agents through high-quality data curation, diverse visual/search tools, and fatal-aware agentic reinforcement learning.
A self-contained AI project that runs a quantized Large Language Model (Qwen2.5-0.5B) entirely on your local machine. Built with FastAPI and llama-cpp-python, this agent intelligently switches between standard chat and "Search Mode" to fetch real-time data from the internet. The project features a responsive HTML/CSS/JS frontend and is fully Docker
AI tool discovery Agent Skill for finding existing software tools across GitHub, npm, MCP servers, Agent Skills, VS Code Marketplace, Open VSX, and web search before building from scratch.