Search Results for "python framework" - Page 6
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Showing 2013 open source projects for "python framework"
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Jittor
Jittor is a high-performance deep learning framework
...The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. -
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Agent Squad
Flexible and powerful framework for managing multiple AI agents
Agent-Squad is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries and maintains context across interactions, offering pre-built components for quick deployment and easy integration of custom agents. -
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NNCF
Neural Network Compression Framework for enhanced OpenVINO
NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency. -
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NVIDIA Isaac Lab
Unified framework for robot learning built on NVIDIA Isaac Sim
Isaac Lab is an open-source modular robotics learning framework built atop Isaac Sim. It simplifies research workflows across reinforcement learning, imitation learning, and motion planning by offering robust, GPU-accelerated simulation with realistic sensor and physics fidelity—ideal for sim-to-real robot training. Compatible and optimized for use with Isaac Sim versions (e.g., Sim 5.0 and 4.5). GPU-accelerated, high-fidelity physics and sensor simulation suitable for complex learning... -
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Rasa
Open source machine learning framework to automate text conversations
Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual assistants on Facebook Messenger, Slack, Google Hangouts, Webex Teams, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram, and Twilio or on your own custom conversational channels. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forths. -
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LitServe
Minimal Python framework for scalable AI inference servers fast
LitServe is a minimal Python framework designed for building custom AI inference servers with full control over how models are executed and served. It allows developers to define their own inference logic, making it suitable for complex systems such as multi-model pipelines, agents, and retrieval-augmented generation workflows. Unlike traditional serving tools that enforce rigid abstractions, LitServe focuses on flexibility by letting users control request handling, batching strategies, and output processing directly in Python. ... -
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NVIDIA Earth2Studio
Open-source deep-learning framework
NVIDIA Earth2Studio is an open-source Python package and framework designed to accelerate the development and deployment of AI-driven weather and climate science workflows. It provides a unified API that lets researchers, data scientists, and engineers build complex forecasting and analysis pipelines by combining modular prognostic and diagnostic AI models with a diverse range of real-world data sources such as global forecast systems, reanalysis datasets, and satellite feeds. ... -
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DeerFlow
Deep Research framework, combining language models with tools
DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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PyOpenCL
OpenCL integration for Python, plus shiny features
PyOpenCL is a Python wrapper for the OpenCL framework, providing seamless access to parallel computing on CPUs, GPUs, and other accelerators. It enables developers to harness the full power of heterogeneous computing directly from Python, combining Python’s ease of use with the performance benefits of OpenCL. PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and machine learning workflows that demand acceleration. -
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Perceval
An open source framework for programming photonic quantum computers
An open-source framework for programming photonic quantum computers. Through a simple object-oriented Python API, Perceval provides tools for composing circuits from linear optical components, defining single-photon sources, manipulating Fock states, running simulations, reproducing published experimental papers and experimenting with a new generation of quantum algorithms. -
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Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
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robosuite
A Modular Simulation Framework and Benchmark for Robot Learning
Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning. -
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caveman
Why use many token when few token do trick
Caveman is a lightweight and experimental project focused on simplifying backend or full-stack development workflows through minimalistic abstractions and rapid prototyping principles. It is designed to reduce the complexity of modern frameworks by offering a stripped-down approach that prioritizes speed, clarity, and ease of use. The project often serves as a foundation for developers who want to build applications quickly without being constrained by heavy conventions or extensive... -
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OmAgent
Build multimodal language agents for fast prototype and production
OmAgent is an open-source Python framework designed to simplify the development of multimodal language agents that can reason, plan, and interact with different types of data sources. The framework provides abstractions and infrastructure for building AI agents that operate on text, images, video, and audio while maintaining a relatively simple interface for developers. -
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HunyuanVideo
HunyuanVideo: A Systematic Framework For Large Video Generation Model
HunyuanVideo is a cutting-edge framework designed for large-scale video generation, leveraging advanced AI techniques to synthesize videos from various inputs. It is implemented in PyTorch, providing pre-trained model weights and inference code for efficient deployment. The framework aims to push the boundaries of video generation quality, incorporating multiple innovative approaches to improve the realism and coherence of the generated content. Release of FP8 model weights to reduce GPU... -
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AI Berkshire
AI-era Berkshire: a value investing research framework
AI Berkshire is an AI-assisted value investing research framework designed for Claude Code and Codex workflows. It turns the investment methods of Warren Buffett, Charlie Munger, Duan Yongping, and Li Lu into structured research agents. The project is meant to improve research depth, decision discipline, and analytical consistency compared with asking a general AI model for a one-off stock opinion. It uses parallel agent analysis, adversarial viewpoints, financial rigor checks, and... -
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Opsdroid
An open source chat-ops bot framework
Designed to take messages from chat services and execute Python functions (skills) based on their contents. Connector modules transfer messages between opsdroid and a particular chat service. Database modules allow opsdroid to persist information in a database of your choice. Parsers/Matchers modules gather the meaning of what was said and match a skill. Skills are what make opsdroid tick. They define how opsdroid should respond and what actions to take. -
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kotaemon
An open-source RAG-based tool for chatting with your documents
An open-source clean & customizable RAG UI for chatting with your documents. Built with both end users and developers in mind. This project serves as a functional RAG UI for both end users who want to do QA on their documents and developers who want to build their own RAG pipeline. -
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Agent Reinforcement Trainer
Train multi-step agents for real-world tasks using GRPO
...The framework is designed to integrate easily with Python applications, abstracting much of the RL infrastructure so developers can train agents without deep RL expertise or heavy infrastructure overhead. ART also supports scalable training patterns, observability tools, and integration with hosted platforms like Weights & Biases, and it provides notebooks that demonstrate training on standard benchmarks and tasks. -
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SGR Agent Core
Schema-Guided Reasoning (SGR) has agentic system design
SGR Agent Core is an open-source framework for building intelligent AI research agents based on a methodology known as Schema-Guided Reasoning (SGR). The framework provides a core library that allows developers to design autonomous agents capable of structured reasoning and complex task execution. Instead of relying solely on free-form prompts, the system organizes reasoning processes around schemas that guide how agents analyze problems, gather information, and generate outputs. This... -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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FastMCP
The fast, Pythonic way to build Model Context Protocol servers
FastMCP is a fast, Pythonic framework for building servers and clients using the Model Context Protocol (MCP). It abstracts away protocol complexity like serialization, validation, and error handling, letting developers focus entirely on their business logic. With simple decorators, you can expose Python functions as tools, resources, or prompts that AI agents can safely and efficiently use. -
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flair
A very simple framework for state-of-the-art NLP
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. A powerful NLP library. Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), sentiment analysis, part-of-speech tagging (PoS), special support for biomedical texts, sense disambiguation and classification, with support for a rapidly growing number of languages. A text embedding library. Flair has... -
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Hephaestus
Semi-Structured Agentic Framework. Workflows build themselves
Hephaestus is an open-source semi-structured agentic framework designed to orchestrate multiple AI agents working together on complex tasks. Instead of relying entirely on predefined workflows, the framework allows agents to dynamically create tasks as they explore a problem space. Developers define high-level phases such as analysis, implementation, and testing, while agents generate specific subtasks within those phases. The system continuously monitors agent behavior and task progression,...
