PokeeResearchOSS provides an open-source, agentic “deep research” model centered on a 7B backbone that can browse, read, and synthesize current information from the web. Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. The repository includes evaluation results on multi-step QA and research benchmarks, illustrating how web-time context boosts accuracy. Because the system is modular, you can swap the search component, reader, or policy to fit private deployments or different data domains. It’s aimed at developers who want a transparent, hackable research agent they can run locally or wire into existing workflows.

Features

  • 7B deep-research agent with integrated search and page reading
  • Multi-step planning to decompose complex questions into sub-tasks
  • Evidence-aware synthesis that cites or grounds to gathered content
  • Configurable browsing and extraction modules for custom stacks
  • Benchmarked on research-style QA tasks with reproducible scripts
  • Designed for local use or service deployment with straightforward APIs

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Categories

AI Agents, AI Models

License

Apache License V2.0

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PokeeResearch-7B Web Site

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Additional Project Details

Programming Language

Python

Related Categories

Python AI Agents, Python AI Models

Registered

2025-10-27