Search Results for "python framework" - Page 7
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Showing 1690 open source projects for "python framework"
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Django-CRM
Open Source CRM based on Django
Django CRM is opensource CRM developed on django framework. It has all the basic features of CRM to start with. We welcome code contributions and feature requests via github. Create and activate a virtual environment. Install the project's dependency after activating env. -
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Zendriver
A blazing fast, async-first, undetectable webscraping
Zendriver is a modern Python web automation and scraping framework that leverages the Chrome DevTools Protocol to provide fast, asynchronous control over real browser instances. Unlike traditional tools that rely on Selenium or WebDriver, Zendriver communicates directly with the browser through CDP, enabling higher performance and more precise control over browser behavior. -
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Cosmos-RL
Cosmos-RL is a flexible and scalable Reinforcement Learning framework
Cosmos-RL is a scalable reinforcement learning framework designed specifically for physical AI systems such as robotics, autonomous agents, and multimodal models. It provides a distributed training architecture that separates policy learning and environment rollout processes, enabling efficient and asynchronous reinforcement learning at scale. The framework supports multiple parallelism strategies, including tensor, pipeline, and data parallelism, allowing it to leverage large GPU clusters... -
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NErlNet
Nerlnet is a framework for research and development
NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices. -
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DINOv3
Reference PyTorch implementation and models for DINOv3
DINOv3 is the third-generation iteration of Meta’s self-supervised visual representation learning framework, building upon the ideas from DINO and DINOv2. It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while... -
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DrissionPage
Python based web automation tool. Powerful and elegant
DrissionPage is a Python-based automation framework that blends the capabilities of Selenium for browser automation with Requests-HTML for fast, headless web data extraction. It enables seamless switching between browser-controlled and headless HTTP sessions within the same interface. Ideal for web scraping, testing, and automation, DrissionPage is lightweight and highly efficient, offering more flexibility than standard Selenium or Requests usage alone. -
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uvicorn
An ASGI web server, for Python
Uvicorn is an ASGI web server implementation for Python. Until recently Python has lacked a minimal low-level server/application interface for async frameworks. The ASGI specification fills this gap, and means we're now able to start building a common set of tooling usable across all async frameworks. Uvicorn currently supports HTTP/1.1 and WebSockets. -
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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,... -
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AIDE ML
AI-Driven Exploration in the Space of Code
...The system repeatedly improves its generated code by exploring different implementation paths and selecting the best-performing solutions. AIDE ML is packaged as a Python toolkit with built-in utilities such as command-line tools, configuration presets, and visualization interfaces that allow researchers to observe how the search process evolves. The framework is designed for experimentation and academic research into automated programming and machine learning optimization. -
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Tequila
A High-Level Abstraction Framework for Quantum Algorithms
Tequila is an abstraction framework for (variational) quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices. -
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Griptape
Python framework for AI workflows and pipelines with chain of thought
The Griptape framework provides developers with the ability to create AI systems that operate across two dimensions: predictability and creativity. For predictability, Griptape enforces structures like sequential pipelines, DAG-based workflows, and long-term memory. To facilitate creativity, Griptape safely prompts LLMs with tools (keeping output data off prompt by using short-term memory), which connects them to external APIs and data stores. The framework allows developers to transition... -
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Checkov
Prevent cloud misconfigurations during build-time for Terraform
...Checkov uses a common command-line interface to manage and analyze infrastructure as code (IaC) scan results across platforms such as Terraform, CloudFormation, Kubernetes, Helm, ARM Templates and Serverless framework. Verify changes to hundreds of supported resource types in all major cloud providers. Checkov supports developers using Terraform, Terraform plan, CloudFormation, Kubernetes, ARM Templates, Serverless, Helm, and AWS CDK. Scan cloud resources in build-time for misconfigured attributes with a simple Python policy-as-code framework. ... -
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MiniMind
Train a 26M-parameter GPT from scratch in just 2h
minimind is a framework that enables users to train a 26-million-parameter GPT (Generative Pre-trained Transformer) model from scratch in approximately two hours. It provides a streamlined process for data preparation, model training, and evaluation, making it accessible for individuals and organizations to develop their own language models without extensive computational resources. -
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TapeAgents
A framework that facilitates all stages of LLM development
TapeAgents is a framework that facilitates all stages of the Large Language Model (LLM) agent development lifecycle, providing tools for building, testing, and deploying AI agents. -
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socketify.py
Bringing Http/Https and WebSockets High Performance servers for PyPy3
Socketify.py is a reliable, high-performance Python web framework for building large-scale app backends and microservices. With no precedents websocket performance and a really fast HTTP server that can delivery encrypted TLS 1.3 quicker than most alternative servers can do even unencrypted, cleartext messaging. -
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Behaviour Suite Reinforcement Learning
bsuite is a collection of carefully-designed experiments
bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each... -
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Django Two-Factor Authentication
Complete Two-Factor Authentication for Django
Complete Two-Factor Authentication for Django. Built on top of the one-time password framework django-otp and Django's built-in authentication framework django.contrib.auth for providing the easiest integration into most Django projects. Inspired by the user experience of Google's Two-Step Authentication, allowing users to authenticate through call, text messages (SMS), by using a token generator app like Google Authenticator or a YubiKey hardware token generator (optional). If you run into... -
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GeoAI
GeoAI: Artificial Intelligence for Geospatial Data
GeoAI is a comprehensive open-source Python package designed to integrate artificial intelligence techniques with geospatial data analysis, enabling users to perform advanced geographic modeling and visualization tasks with ease. It provides a unified framework that combines machine learning libraries such as PyTorch and Transformers with geospatial tools, allowing users to process satellite imagery, aerial photos, and vector datasets in a streamlined workflow. -
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NVIDIA AgentIQ
The NVIDIA AgentIQ toolkit is an open-source library
NVIDIA AgentIQ is an open-source toolkit designed to efficiently connect, evaluate, and accelerate teams of AI agents. It provides a framework-agnostic platform that integrates seamlessly with various data sources and tools, enabling developers to build composable and reusable agentic workflows. By treating agents, tools, and workflows as simple function calls, AgentIQ facilitates rapid development and optimization of AI-driven applications, enhancing collaboration and efficiency in complex... -
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TNT
A lightweight library for PyTorch training tools and utilities
TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps... -
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uvloop
Ultra fast asyncio event loop
uvloop is an ultra-fast, drop-in replacement of the built-in asyncio event loop. Together with asyncio and the power of async/await in Python 3.5, uvloop makes it easier than ever to write high-performance Python networking code. uvloop makes asyncio incredibly fast-- 2 to 4 times faster than nodejs, or any other Python asynchronous framework. The performance of asyncio when it is uvloop-based is almost comparable to that of Go programs. uvloop is written in Cython and is built on top of libuv, a high performance, fast and stable multiplatform asynchronous I/O library used by nodejs. -
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Evennia
Python MUD/MUX/MUSH/MU* development system
Evennia is a mature, open-source framework written in Python — specifically designed to build text-based, online multiplayer games such as MUDs, MUCKs, MUSHes, MUXes, and other “MU-style” virtual worlds. Rather than prescribing a rigid game structure, Evennia gives you a bare-bones but powerful foundation: default systems handle networking, database/storage, server management, user accounts, characters, rooms, items, chat channels, and basic commands — but you define the gameplay rules, content, and game logic yourself in pure Python modules. ... -
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SLM Lab
Modular Deep Reinforcement Learning framework in PyTorch
SLM Lab is a modular and extensible deep reinforcement learning framework designed for research and practical applications. It provides implementations of various state-of-the-art RL algorithms and emphasizes reproducibility, scalability, and detailed experiment tracking. SLM Lab is structured around a flexible experiment management system, allowing users to define, run, and analyze RL experiments efficiently. -
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LOTUS
AI-Powered Data Processing: Use LOTUS to process all of your datasets
LOTUS is an open-source framework and query engine designed to enable efficient processing of structured and unstructured datasets using large language models. The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. ... -
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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...
