Ultimate IA explicativa Solutions for Everyone

Discover all-in-one IA explicativa tools that adapt to your needs. Reach new heights of productivity with ease.

IA explicativa

  • An open-source ReAct-based AI agent built with DeepSeek for dynamic question-answering and knowledge retrieval from custom data sources.
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    What is ReAct AI Agent from Scratch using DeepSeek?
    The repository provides a step-by-step tutorial and reference implementation for creating a ReAct-based AI agent that uses DeepSeek for high-dimensional vector retrieval. It covers environment setup, dependency installation, and configuration of vector stores for custom data. The agent employs the ReAct pattern to combine reasoning traces with external knowledge searches, resulting in transparent and explainable responses. Users can extend the system by integrating additional document loaders, fine-tuning prompt templates, or swapping vector databases. This flexible framework enables developers and researchers to prototype powerful conversational agents that reason, retrieve, and interact seamlessly with various knowledge sources in a few lines of Python code.
  • AI-driven contract review platform offering over 90% accuracy.
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    What is LLM Sandbox by Dioptra?
    Dioptra AI offers a sophisticated platform for contract review, harnessing artificial intelligence to achieve lawyer-level accuracy. Trusted by numerous legal professionals, the platform aims to streamline the process of contract review, making it faster and more accurate. The AI's explainability ensures users can trust and understand the decision-making process, while the high accuracy rate makes it a vital tool for legal teams seeking efficiency and precision.
  • An open-source Python framework offering diverse multi-agent reinforcement learning environments for training and benchmarking AI agents.
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    What is multiagent_envs?
    multiagent_envs delivers a modular set of Python-based environments tailored for multi-agent reinforcement learning research and development. It includes scenarios like cooperative navigation, predator-prey, social dilemmas, and competitive arenas. Each environment lets you define the number of agents, observation features, reward functions, and collision dynamics. The framework integrates seamlessly with popular RL libraries such as Stable Baselines and RLlib, allowing vectorized training loops, parallel execution, and easy logging. Users can extend existing scenarios or create new ones by following a simple API, accelerating experimentation with algorithms like MADDPG, QMIX, and PPO in a consistent, reproducible setup.
  • An open-source AI agent combining Mistral-7B with Delphi for interactive moral and ethical question answering.
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    What is DelphiMistralAI?
    DelphiMistralAI is an open-source Python toolkit that integrates the powerful Mistral-7B LLM with the Delphi moral reasoning model. It offers both a command-line interface and a RESTful API for delivering reasoned ethical judgments on user-supplied scenarios. Users can deploy the agent locally, customize judgment criteria, and inspect generated rationales for each moral decision. This tool aims to accelerate AI ethics research, educational demonstrations, and safe, explainable decision support systems.
  • Bosch AI enhances products with advanced AI technologies.
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    What is bosch-ai.com?
    Bosch AI aims to elevate the digitalized world using advanced AI to make life easier and safer. They leverage data from over 230 Bosch plants, conducting secure, robust, and explainable AI research. They focus on real-world applications across various sectors and foster collaborations with industry and academic leaders to expand their research network.
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