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This project is a plugin framework and agentic workflow library designed to connect large language models to professional toolstacks. It provides a system for integrating language models with external data warehouses, CRMs, and other enterprise software to retrieve and manipulate real-time business data. The framework enables the automation of specialized professional tasks through a file-based plugin definition system. It allows for the customization of domain expertise and plugin behavior to align with internal company processes, supported by an enterprise data connector that links models t
Automated Drug Combination Extraction (DCE) from large-scale biomedical literature is important for precision medicine and pharmacological research. However, existing extraction methodologies predominantly focus on binary interactions. When tasked with complex, variable-length n-ary…
agentD is an open-source Python package designed to accelerate drug discovery workflows using Large Language Models (LLMs) and AI-driven tools. It provides modular agents and utilities for tasks such as literature extraction, molecular property prediction, molecule generation, and more. agentD…
DrugAgent is a multi-agent LLM system for drug-target interaction (DTI) prediction that combines AI model predictions, knowledge graph analysis, and literature search for comprehensive DTI prediction with interpretable reasoning.
The main features of zatpds/drugagent are: Drug Discovery Agents.
Projects with overlapping indexed features include: anthropics/knowledge-work-plugins — This project is a plugin framework and agentic workflow library designed to connect large language models to… dutir-bionlp/rexdrug — Automated Drug Combination Extraction (DCE) from large-scale biomedical literature is important for precision medicine… fermiq/drugagent. hoon-ock/agentd — agentD is an open-source Python package designed to accelerate drug discovery workflows using Large Language Models… jihyechoi77/malade — Code for the paper:. lclarice/autoct — This repository contains the implementation of the approach discussed in AUTOCT: Automating Interpretable Clinical…
