WrenAI is a platform designed to enable natural language interaction with relational and analytical databases. By combining a text-to-SQL engine with semantic data modeling, it allows users to explore structured data through plain language questions, removing the requirement for manual code generation. The system functions by grounding natural language requests in a predefined business logic layer rather than raw database schemas. This semantic approach, supported by context-aware prompt engineering, ensures that generated queries remain consistent and accurate across an organization. The pla
Develop and deploy smart contracts using natural language.
This is an LLM agent framework and symbolic learning system designed for building self-evolving autonomous agents. It functions as a computational graph orchestrator that organizes agent interactions and tool sequences as a trainable graph of nodes. The framework focuses on data-centric agent optimization, allowing agent pipelines and prompts to be upgraded through data-driven training rather than manual engineering. It utilizes a symbolic learning process that applies language-based loss and textual reflections to refine the operational logic and symbolic components of an agent. The system
Les fonctionnalités principales de ltzheng/synapse sont : Task Automation Agents.
Les alternatives open-source à ltzheng/synapse incluent : xlang-ai/osworld — OSWorld is an evaluation framework and multimodal agent benchmark designed to test the ability of large language… canner/wrenai — WrenAI is a platform designed to enable natural language interaction with relational and analytical databases. By… craftjarvis/mc-planner. markeljan/web3gpt — Develop and deploy smart contracts using natural language. microsoft/ufo — UFO is a multi-device task orchestrator and LLM agent orchestration framework designed to decompose natural language… posgnu/rci-agent — Welcome to the codebase for our paper, "Language Models can Solve Computer Tasks". In this codebase, you will find the…