Search Results for "python framework"
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363 projects for "python framework" with 2 filters applied:
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Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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Agent Framework
Framework for building, orchestrating, and deploying AI agents
Microsoft Agent Framework is an open source framework designed to help developers build, orchestrate, and deploy AI agents and multi-agent systems. It provides a unified programming model that supports both Python and .NET implementations, allowing developers to create agent-driven applications in multiple programming environments. It includes tools and abstractions for constructing simple conversational agents as well as complex workflows where multiple agents collaborate to complete tasks. ... -
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TypeAgent Python
Structured RAG: ingest, index, query
TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. -
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BeeAI Framework
Build production-ready AI agents in both Python and Typescript
...The framework supports both Python and TypeScript with full feature parity, making it accessible to a wide range of developers and teams. It includes a unified backend layer that connects seamlessly to multiple large language model providers, allowing flexible deployment across different AI infrastructures without vendor lock-in. BeeAI also provides orchestration tools for designing dynamic workflows, enabling multiple agents to coordinate tasks through structured execution flows, retries, and parallel processing. -
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python-whatsapp-bot
Build AI WhatsApp Bots with Pure Python
python-whatsapp-bot is an open-source framework that demonstrates how to build AI-powered WhatsApp bots using pure Python and the official WhatsApp Cloud API. The project provides a practical implementation of a messaging automation system using the Flask web framework to handle webhook events and process incoming messages in real time. -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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Open AEA Framework
A framework for open autonomous economic agent (AEA) development
open-aea is an open-source framework for building autonomous software agents that can operate and interact independently on decentralized networks. Developed by Valory, it facilitates creating agents capable of economic transactions, communication, and smart contract interactions in Web3 ecosystems. -
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Dynamiq
An orchestration framework for agentic AI and LLM applications
Dynamiq is an open-source orchestration framework designed to streamline the development of generative AI applications that rely on large language models and autonomous agents. The framework focuses on simplifying the creation of complex AI workflows that involve multiple agents, retrieval systems, and reasoning steps. Instead of building each component manually, developers can use Dynamiq’s structured APIs and modular architecture to connect language models, vector databases, and external... -
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. -
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OpenManus
Open-source AI agent framework
OpenManus is an open-source AI agent framework designed to autonomously execute complex, multi-step tasks by combining reasoning, planning, and tool use. It enables developers to build agents that can think, act, and iterate toward goals rather than simply responding to prompts. The platform emphasizes task decomposition, allowing agents to break down objectives into smaller steps and execute them sequentially or recursively. OpenManus supports integration with external tools, APIs, and... -
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PyTensor
Python library for defining and optimizing mathematical expressions
...Implements an extensible graph transpilation framework that currently provides compilation via C, JAX, and Numba. Based on one of the most widely-used Python tensor libraries: Theano. -
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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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TensorFlow Quantum
Open-source Python framework for hybrid quantum-classical ml learning
TensorFlow Quantum is an open-source software framework designed for building and training hybrid quantum-classical machine learning models within the TensorFlow ecosystem. The framework enables researchers and developers to represent quantum circuits as data and integrate them directly into machine learning workflows. By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages... -
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference pipelines for models that combine data-driven learning with physics-based constraints. ... -
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. -
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skfolio
Python library for portfolio optimization built on top of scikit-learn
skfolio is a Python library designed for portfolio optimization and financial risk management that integrates closely with the scikit-learn ecosystem. The project provides a unified machine learning-style framework for building, validating, and comparing portfolio allocation strategies using financial data. By following the familiar scikit-learn API design, the library allows quantitative researchers and developers to apply techniques such as model selection, cross-validation, and hyperparameter tuning to portfolio construction workflows. ... -
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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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FuzzyAI Fuzzer
A powerful tool for automated LLM fuzzing
FuzzyAI is an open-source fuzzing framework designed to test the security and reliability of large language model applications. The tool automates the process of generating adversarial prompts and input variations to identify vulnerabilities such as jailbreaks, prompt injections, or unsafe model responses. It allows developers and security researchers to systematically evaluate the robustness of LLM-based systems by simulating a wide range of malicious or unexpected inputs. The framework can... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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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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SWIFT LLM
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs
SWIFT LLM is a comprehensive framework developed within the ModelScope ecosystem for training, fine-tuning, evaluating, and deploying large language models and multimodal models. The platform provides a full machine learning pipeline that supports tasks ranging from model pre-training to reinforcement learning alignment techniques. It integrates with popular inference engines such as vLLM and LMDeploy to accelerate deployment and runtime performance. The framework also includes support for... -
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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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LightLLM
LightLLM is a Python-based LLM (Large Language Model) inference
LightLLM is a high-performance inference and serving framework designed specifically for large language models, focusing on lightweight architecture, scalability, and efficient deployment. The framework enables developers to run and serve modern language models with significantly improved speed and resource efficiency compared to many traditional inference systems. Built primarily in Python, the project integrates optimization techniques and ideas from several leading open-source implementations, including FasterTransformer, vLLM, and FlashAttention, to accelerate token generation and reduce latency. ... -
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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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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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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
...Because the library integrates machine learning algorithms with signal processing tools, it enables researchers to develop complete audio analysis pipelines using a single framework.
