Eubiota-Planner-8B

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Eubiota-Planner-8B is a specialized 8-billion parameter language model fine-tuned for autonomous microbiome discovery. It serves as the core planner module in the Eubiota agentic AI framework, orchestrating multi-agent reasoning and tool-grounded scientific exploration.

Website Demo arXiv GitHub

Model Description

Property Details
Model Type Causal language model fine-tuned for agentic planning
Base Model Qwen3-8B
Training Method GRPO-MAS (Group Relative Policy Optimization for Multi-Agent Systems)
Language English
Developed By Stanford University
Affiliations Department of Biomedical Data Science, Department of Computer Science, Department of Microbiology and Immunology, Institute for Human-Centered AI (HAI)

Intended Use

Primary Use Cases

  • Microbiome Hypothesis Generation: Formulating mechanistic hypotheses about host-microbe interactions
  • Experimental Design: Planning and orchestrating scientific workflows for microbiome research
  • Multi-Tool Coordination: Selecting and sequencing domain-specific tools (PubMed, KEGG pathways, etc.) for complex scientific queries

Training

Training Data

The model was trained on a mixture of four domain datasets:

Dataset Purpose Source
Microbio-Bench Curated microbiome reasoning Eubiota/microbio-bench
PubMedQA Medical-biology reasoning qiaojin/PubMedQA
MedQA-USMLE Medical-biology reasoning GBaker/MedQA-USMLE-4-options
DeepMath-103K Mathematical reasoning zwhe99/DeepMath-103K
Natural Questions Agentic search RUC-NLPIR/FlashRAG_datasets

Training Method

The model is trained using GRPO-MAS (Group Relative Policy Optimization for Multi-Agent Systems), a reinforcement learning approach designed for multi-agent coordination. This method enables the planner to learn effective tool selection and sequencing strategies through outcome-driven refinement.

Integrated Tools

Eubiota-Planner-8B orchestrates 18 domain-specific tools spanning web and literature search, biological databases, laboratory resources, and computation utilities.

Category Tools Description
Web Search Google Search, Perplexity Search, Wikipedia Search, URL Page Retrieval Grounded web search with citation support
Literature Search PubMed Search Retrieves relevant papers from PubMed and produces citation-grounded summaries
KEGG Databases KEGG Gene, KEGG Drug, KEGG Disease, KEGG Organism Query tools for genes, drugs, diseases, and organisms
MDIPID Databases MDIPID Gene View, MDIPID Disease View, MDIPID Microbe View Microbiota-drug-disease association queries from multiple perspectives
Laboratory Tools Transposon Screen Database, Protocol Library Access to pre-computed gene-phenotype rankings (1,836 genes) and 55 curated microbiome/immunology experimental protocols
Document Utilities Doc Context Search, Database Context Search File and document context retrieval
Computation Python Execution, LLM Summarization Code execution and text synthesis capabilities

Quick Start

Framework Usage

For the complete agentic experience with tool integration:

# Install Eubiota
bash setup.sh
source .venv/bin/activate

# Configure API keys
cp scientist/.env.template scientist/.env
# Edit .env with your API keys

# Run inference
python scientist/solver_scientist.py

Benchmark Suite

Eubiota-Planner-8B is evaluated on six benchmarks across two categories to assess both broad biomedical competence and microbiome-specific mechanistic reasoning.

General Biomedical Competence

Benchmark Description Source
MedMCQA (Medicine) Professional clinical knowledge and complex diagnostic reasoning from medical entrance examinations Pal et al., 2022
WMDP-Bio Expert-level capabilities in hazardous biological knowledge and biosecurity-relevant domains Li et al., 2024

Microbiome-Specific Mechanistic Reasoning

Four domain-specific benchmarks derived from MDIPID emphasizing mechanistic linking among microbes, drugs, host pathways, and genes:

Benchmark Task Description
Drug-Microbe Impact (Drug-Imp) Drug → Microbe Determining the directional effects of drugs on microbial growth
Microbe-Protein Mechanism (MB-Mec) Microbe → Protein Linking microbial activity to host proteins
Protein Functional Comprehension (Prot-Func) Protein → Function Identifying the biological function of a protein
Protein-Gene Mapping (Prot-Gen) Protein → Gene Mapping expressed proteins to their encoding genes

Citation

@article{eubiota2026,
    title={Eubiota: Agentic AI for Autonomous Microbiome Discovery},
    author={Lu, Pan and Peng, William and Zhang, Haoxiang and Zhu, Kunlun and Xu, Qixin},
    journal={arXiv preprint arXiv:TBD},
    year={2026}
}

Acknowledgements

This work is supported by:

We thank the following open-source projects:

Contact

For questions and feedback, please open an issue on our GitHub repository or visit eubiota.ai.

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