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Agentic Reasoning

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Basic Information

Agentic Reasoning is an open-source research framework that explores integrating agentic tools into large language model (LLM) reasoning. The repository is aimed at researchers and developers who want to experiment with augmenting LLMs with external tools and pipelines for deeper, multi-step research workflows. The project includes environment setup instructions, a main run script, and references an associated arXiv preprint. It supports using remote LLMs and third-party services through API keys, and it explicitly cautions that the code is still in active development and may require updates to run. The README lists a short todo list and acknowledges code reuse from other projects. The overall purpose is to provide a practical, extensible starting point for prototyping agentic reasoning approaches in deep research contexts.

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App URL
https://github.com/theworldofagents/Agentic-Reasoning
Github Repository
https://github.com/theworldofagents/Agentic-Reasoning/blob/main/README.md

App Details

Features
The repository documents key runnable pieces and integrations rather than a polished product. It provides an environment.yml for Conda-based installation and a scripts/run_agentic_reason.py entrypoint with flags to enable components. Supported integrations mentioned include remote LLMs (example model names given), OpenAI API key support, you.com deep research via a YDC_API_KEY, optional Jina integration with a jina_api_key, and optional Bing support via a bing_subscription_key. Runtime flags include toggles for mind map output and deep research mode. The README includes a citation to an arXiv paper that describes the approach. The codebase is presented as experimental with a short todo list for features like auto research and cleanup.
Use Cases
For researchers and developers studying tool-augmented LLM reasoning, this repository provides a concrete prototype to run experiments and connect LLMs to agentic tools. The included environment file and run script lower the barrier to reproducing the authors" setup, and the command-line flags let users enable or disable components such as Jina retrieval, Bing search, or a deep research mode. By requiring API keys for external services, experiments can be conducted with real remote models and search backends. The project is helpful as a starting scaffold for exploring multi-step, tool-enabled reasoning and for iterating on research ideas, while the README warns that the codebase is still evolving and may need maintenance to be fully operational.

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