Repository History
96 repositories tagged with Machine Learning
Agentarium: A Python Framework for AI Agent Simulations
Agentarium is an open-source Python framework designed for creating and managing simulations with AI-powered agents. It offers an intuitive platform for designing complex, interactive environments where agents can act, learn, and evolve. This powerful tool simplifies the orchestration of multiple AI agents and their interactions.
Observers: A Lightweight Library for AI Observability in Python
Observers is a Python library designed for AI observability, enabling developers to track and store interactions with generative AI APIs. It provides a flexible framework with various observers for popular LLM providers and multiple storage backends. This tool helps in monitoring, debugging, and analyzing AI model behavior effectively.
JailbreakEval: An Integrated Toolkit for Evaluating LLM Jailbreak Attempts
JailbreakEval is an award-winning collection of automated evaluators designed to assess jailbreak attempts against large language models. It addresses the impracticality of manual inspection for large-scale analysis by unifying various evaluation tools. This toolkit is invaluable for both jailbreak researchers and evaluator developers, offering a robust framework for creating and benchmarking new evaluators.
Hiring Agent: An AI Agent for Resume Evaluation and Scoring
Hiring Agent is an open-source AI agent designed to evaluate and score resumes objectively. It extracts structured data from PDF resumes, enriches it with GitHub profile signals, and provides a fair, explainable evaluation with detailed scores and evidence. This tool supports both local LLMs via Ollama and cloud-based options like Google Gemini.
AuditNLG: Auditing Generative AI for Trustworthiness
AuditNLG is an open-source library from Salesforce designed to enhance the trustworthiness of generative AI language models. It provides state-of-the-art techniques to detect and improve factualness, safety, and constraint adherence in AI-generated text. This library simplifies the process of auditing AI outputs, offering explanations and alternative suggestions for problematic content.
spacy-llm: Integrating LLMs into Structured NLP Pipelines with spaCy
spacy-llm seamlessly integrates Large Language Models (LLMs) into spaCy, offering a modular system for rapid prototyping and transforming unstructured LLM responses into robust outputs for various NLP tasks. It supports a wide range of LLMs, including OpenAI, Cohere, Anthropic, and open-source models, enabling users to combine the power of LLMs with spaCy's production-ready capabilities. This package allows for quick experimentation and the creation of efficient, reliable, and controlled NLP systems.
Dexter: An Autonomous Agent for Deep Financial Research
Dexter is an autonomous financial research agent designed to think, plan, and learn while performing analysis. It leverages task planning, self-reflection, and real-time market data to tackle complex financial questions. This project provides a powerful tool for in-depth financial exploration, emphasizing its educational and informational purposes.
Loop Library: Practical Repeatable AI-Agent Workflows
The Loop Library is a GitHub repository offering reusable AI agent workflows for various domains like engineering, content, and design. It introduces the concept of "loops," which are structured, repeatable instructions that guide AI agents through multi-step tasks. This skill enables agents to learn from results, adapt, and complete complex tasks more reliably than with one-shot prompts.
GLM-5: Flagship Models for Long-Horizon Agentic Engineering
GLM-5 is a series of flagship models, including GLM-5.2, GLM-5.1, and GLM-5, developed by zai-org for complex systems engineering and long-horizon agentic tasks. These models offer advanced coding capabilities, impressive context lengths, and state-of-the-art performance on various benchmarks. They are designed to sustain effective problem-solving over extended sessions through iterative reasoning and strategy revision.
AutoHedge: Build Your Autonomous AI Hedge Fund with Swarm Intelligence
AutoHedge is an enterprise-grade autonomous agent hedge fund that leverages swarm intelligence and specialized AI agents. This powerful Python project automates end-to-end market analysis, risk management, and trade execution. It allows users to build and deploy their own AI-driven trading strategies with minimal human intervention.
Feynman: The Open Source AI Research Agent
Feynman is an open-source AI research agent designed to automate and streamline complex research tasks. Built with TypeScript, it leverages multiple agents and tools to conduct in-depth investigations, literature reviews, and even experiment replications, providing source-grounded outputs.
autoresearch: AI Agents for Autonomous LLM Training Research
autoresearch, by Andrej Karpathy, pioneers autonomous AI research by enabling agents to experiment with LLM training on a single GPU. The system allows an AI agent to modify code, train a model for a fixed 5-minute duration, and iteratively optimize for improved performance. This innovative approach aims to automate the experimental cycle of AI research, fostering continuous discovery and optimization.