Showing 7 open source projects for "self learning"

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  • 1
    AgentEvolver

    AgentEvolver

    Towards Efficient Self-Evolving Agent System

    AgentEvolver is an open-source research framework for building self-evolving AI agents powered by large language models. The system focuses on improving the efficiency and scalability of training autonomous agents by allowing them to generate tasks, explore environments, and refine strategies without heavy reliance on manually curated datasets. Its architecture combines reinforcement learning with LLM-driven reasoning mechanisms to guide exploration and learning.
    Downloads: 1 This Week
    Last Update:
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    SwanLab

    SwanLab

    An open-source, modern-design AI training tracking and visualization

    ...SwanLab supports both cloud and self-hosted deployments, allowing organizations to run the system privately or integrate it into shared development environments. The platform integrates with a wide range of machine learning frameworks including PyTorch, Transformers, Keras, and other widely used training ecosystems.
    Downloads: 5 This Week
    Last Update:
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  • 3
    OpenOutreach

    OpenOutreach

    Linkedin Automation Tool

    ...According to the repository, it combines large language model classification with a Bayesian machine learning layer based on profile embeddings, which helps it shift from broad exploration to more confident qualification as it gathers more decisions. It is designed to automate personalized outreach as well, including connection requests and follow-up messaging, while keeping deployment under the user’s control through a local or self-hosted setup.
    Downloads: 1 This Week
    Last Update:
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  • 4
    AudioMuse-AI

    AudioMuse-AI

    AudioMuse-AI is an Open Source Dockerized environment

    ...By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal music libraries and generate curated playlists for different moods or listening contexts. AudioMuse-AI integrates with several popular self-hosted music servers including Jellyfin, Navidrome, and Emby, allowing users to extend existing media servers with advanced AI-powered recommendation capabilities. The system uses machine learning and audio analysis tools such as Librosa and ONNX models to extract features directly from audio tracks.
    Downloads: 10 This Week
    Last Update:
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  • 5
    hCaptcha Challenger

    hCaptcha Challenger

    Gracefully face hCaptcha challenge with multimodal llms

    hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks...
    Downloads: 16 This Week
    Last Update:
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  • 6
    Agentic Context Engine

    Agentic Context Engine

    Make your agents learn from experience

    Agentic Context Engine (ACE) is an open-source framework designed to help AI agents improve their performance by learning from their own execution history. Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and...
    Downloads: 0 This Week
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  • 7
    Agents 2.0

    Agents 2.0

    An Open-source Framework for Data-centric Language Agents

    Agents is an open-source framework designed to build and train autonomous language agents through a data-centric and learning-oriented architecture. The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During...
    Downloads: 0 This Week
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