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OpenAgents is an open-source platform for deploying, managing, and interacting with language agents through a conversational interface. Agents on this platform can analyze data by generating and executing Python and SQL code, invoke external plugins, browse the web autonomously, and perform tasks like flight search, map directions, and social media posting—all driven by natural language. What distinguishes the platform is its architecture for persistent agent lifecycle management, isolated code execution via a sandbox, multi-agent coordination for complex workflows, and automatic plugin disco
This project is an LLM research orchestrator and autonomous AI agent framework designed to automate the scientific lifecycle. It functions as an end-to-end research pipeline and model training toolkit, managing everything from initial literature reviews and hypothesis testing to the final drafting of academic papers. The system is distinguished by its ability to convert unstructured academic PDFs into machine-executable knowledge layers, allowing agents to reproduce and extend research findings. It employs a two-loop orchestration architecture and a specialized research engineering skill libr
EvoScientist is an autonomous AI scientist and multi-agent research framework designed to plan, code, and execute end-to-end scientific research workflows. It functions as an agentic workflow orchestrator that uses a state-machine to coordinate specialized agents through iterative phases of planning, execution, and verification. The system is distinguished by a persistent knowledge graph memory that distills agent interactions into reusable skills and a hub for integrating external tools via the Model Context Protocol. It features a provider-agnostic model layer for switching between language
TinyLlama is a compact 1.1B parameter language model pretrained on a dataset of 3 trillion tokens. It is an edge AI model designed for high-performance text generation on memory-constrained devices. The project provides a distributed pretraining framework for training small language models across multiple GPUs and nodes. It also includes a finetuning toolkit for full-parameter weight adjustments to adapt the base model for chat and specific tasks. The system supports distributed large language model training and on-device text generation. Its architectural components include rotary positiona
Chemcrow
The main features of ur-whitelab/chemcrow-public are: Language Models, Molecular Discovery, Scientific Research Agents, Task Automation Agents, Tool Use And Integration.
Projects with overlapping indexed features include: xlang-ai/openagents — OpenAgents is an open-source platform for deploying, managing, and interacting with language agents through a… evoscientist/evoscientist — EvoScientist is an autonomous AI scientist and multi-agent research framework designed to plan, code, and execute… orchestra-research/ai-research-skills — This project is an LLM research orchestrator and autonomous AI agent framework designed to automate the scientific… k-dense-ai/scientific-agent-skills — This project is a collection of specialized toolkits and an agent skill library designed to equip large language model… jzhang38/tinyllama — TinyLlama is a compact 1.1B parameter language model pretrained on a dataset of 3 trillion tokens. It is an edge AI… aiming-lab/autoresearchclaw — AutoResearchClaw is an agentic system designed to automate the scientific research process. It functions as an…