Search Results for "code framework" - Page 9
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Showing 310 open source projects for "code framework"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Step1X-Edit
A SOTA open-source image editing model
Step1X-Edit is a state-of-the-art open-source image editing model/framework that uses a multimodal large language model (LLM) together with a diffusion-based image decoder to let users edit images simply via natural-language instructions plus a reference image. You supply an existing image and a textual command — e.g. “add a ruby pendant on the girl’s neck” or “make the background a sunset over mountains” — and the model interprets the instruction, computes a latent embedding combining the... -
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mlforecast
Scalable machine learning for time series forecasting
mlforecast is a time-series forecasting framework built around machine-learning models, designed to make forecasting both efficient and scalable. It lets you apply any regressor that follows the typical scikit-learn API, for example, gradient-boosted trees or linear models, to time-series data by automating much of the messy feature engineering and data preparation. Instead of writing custom code to build lagged features, rolling statistics, and date-based predictors, mlforecast generates those automatically based on a simple configuration. ... -
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning... -
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HunyuanVideo-I2V
A Customizable Image-to-Video Model based on HunyuanVideo
HunyuanVideo-I2V is a customizable image-to-video generation framework developed by Tencent, extending the capabilities of HunyuanVideo. It allows for high-quality video creation from still images, using PyTorch and providing pre-trained model weights, inference code, and customizable training options. The system includes a LoRA training code for adding special effects and enhancing video realism, aiming to offer versatile and scalable solutions for generating videos from static image inputs. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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TaskWeaver
A code-first agent framework for seamlessly planning analytics tasks
TaskWeaver is a multi-agent AI framework designed for orchestrating autonomous agents that collaborate to complete complex tasks. -
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AIConfig
AIConfig is a config-based framework to build generative AI apps
AIConfig is an open-source framework designed to simplify the development and management of generative AI applications by separating AI logic from application code. The framework allows prompts, model configurations, and parameters to be stored as structured configuration files that can be version controlled and managed independently from the rest of the software system. -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. ... -
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ToRA
Tool-integrated Reasoning LLM Agents
...This approach allows the model to reason step by step in natural language and then execute precise calculations or code through tool calls, creating a hybrid reasoning workflow. The framework was designed to address known weaknesses of large language models in mathematical problem solving and formal reasoning tasks. Training data includes tool-use trajectories that teach the model when to reason verbally and when to delegate tasks to specialized tools. -
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telegraf.js
Modern Telegram Bot Framework for Node.js
Bots are special Telegram accounts designed to handle messages automatically. Users can interact with bots by sending them command messages in private or group chats. These accounts serve as an interface for code running somewhere on your server. Telegraf is a library that makes it simple for you to develop your own Telegram bots using JavaScript or TypeScript. You can see in every example is a Context instance. Telegraf creates one for each incoming update and passes it to your middleware.... -
AI Agents That Actually Do the WorkClickUp's Super Agents run 24/7 inside your workspace: triaging bugs, drafting content, updating statuses, and routing tasks without being told twice. Connect them to 500+ tools and let them execute, not just suggest. Build custom agents in minutes that understand your workflows and act on them autonomously.
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Obsei
Obsei is a low code AI powered automation tool
Obsei is an automated no-code/low-code AI-powered text observation and analysis framework, designed for extracting insights from unstructured text data such as social media, reviews, and logs. -
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CommandDash
AI assist to integrate APIs and SDKs without reading docs
Integrate any package, SDK, or framework with expert AI agents. Get contextualized code for your use case within the IDE. Modern software is built on top of 3rd party APIs and SDKs. However integrating them is time-consuming, requiring to manually read docs and copy-paste snippets. CommandDash enables you to skip reading documentation and integrate any API or SDK with an IDE agent up to date with the latest documentation, examples, and issues. -
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Exposure Correction
Learning multi-scale deep model correcting over- and under- exposed
...The repository focuses on correcting poorly exposed photographs, handling both underexposure and overexposure using a deep learning approach. The method employs a multi-scale framework that learns to enhance images by adjusting exposure levels across different spatial resolutions. This allows the model to preserve fine details while correcting global lighting inconsistencies. The repository includes pre-trained models, datasets, and training/testing code to enable reproducibility and experimentation. By leveraging this framework, researchers and developers can apply exposure correction to a wide range of natural images, improving visual quality without manual editing. ... -
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Mr. Ranedeer
GPT-4 AI Tutor Prompt for customizable personalized learning
Unlock the potential of GPT-4 with Mr. Ranedeer AI Tutor, a customizable prompt that delivers personalized learning experiences for users with diverse needs and interests. -
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Feishu ChatGPT
Voice dialogue, role-playing, multi-topic discussion, picture creation
...Easily control Docker containerization technology and deploy code as you like! With some experience in payment function development, it really makes money fly! Understand some Linux scripting and socket programming. -
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TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing models
...It aims to implement the complete Tensorflow API in C# which allows .NET developers to develop, train and deploy Machine Learning models with the cross-platform .NET Standard framework. TensorFlow.NET has built-in Keras high-level interface and is released as an independent package TensorFlow.Keras. SciSharp STACK's mission is to bring popular data science technology into the .NET world and to provide .NET developers with a powerful Machine Learning tool set without reinventing the wheel. Since the APIs are kept as similar as possible you can immediately adapt any existing TensorFlow code in C# or F# with a zero learning curve. ... -
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D2L.ai
Interactive deep learning book with multi-framework code
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge. This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. ... -
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Demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. The... -
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fastquant
Backtest and optimize your ML trading strategies with only 3 lines
fastquant is a Python library designed to simplify quantitative financial analysis and algorithmic trading strategy development. The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common strategies such as moving average crossovers, momentum trading, and custom indicators on historical stock data. By automating data retrieval, strategy evaluation, and result visualization, the library reduces the barrier to entry for individuals interested in quantitative finance. ... -
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Lightning-Hydra-Template
PyTorch Lightning + Hydra. A very user-friendly template
...Not fitted for data engineering - the template configuration setup is not designed for building data processing pipelines that depend on each other. PyTorch Lightning, a lightweight PyTorch wrapper for high-performance AI research. Think of it as a framework for organizing your PyTorch code. Hydra, a framework for elegantly configuring complex applications. The key feature is the ability to dynamically create a hierarchical configuration by composition and override it through config files and the command line. -
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LangChain Apps on Production with Jina
Langchain Apps on Production with Jina & FastAPI
Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own... -
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EasyRL
Reinforcement learning (RL) tutorial series
easy-rl is a beginner-friendly reinforcement learning (RL) tutorial series and framework developed by Datawhale China. It provides educational resources and implementations of various RL algorithms to help new researchers and practitioners learn RL concepts. -
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PromptAppGPT
A rapid prompt app development framework based on GPT
PromptAppGPT is a low-code prompt-based rapid app development framework. PromptAppGPT contains features such as low-code prompt-based development, GPT text generation, DALLE image generation, online prompt editer+compiler+runer, automatic user interface generation, support for plug-in extensions, etc. PromptAppGPT aims to enable natural language app development based on GPT. -
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TaskMatrix
Enable sending and receiving images during chatting
...The project expands beyond traditional chatbot behavior by enabling AI systems to process, generate, edit, and reason about images while coordinating multiple specialized models simultaneously. Originally introduced alongside the Visual ChatGPT concept, TaskMatrix acts as an orchestration framework where a central language model delegates subtasks to domain-specific AI systems such as image generators, segmentation tools, or recognition models. The architecture focuses on modularity, allowing new APIs and foundation models to be integrated as interchangeable task-solving components. The project also explores low-code human-AI interaction workflows that improve controllability and transparency during complex task execution. -
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aqueduct LLM
Aqueduct allows you to run LLM and ML workloads on any infrastructure
Aqueduct is an MLOps framework that allows you to define and deploy machine learning and LLM workloads on any cloud infrastructure. Aqueduct is an open-source MLOps framework that allows you to write code in vanilla Python, run that code on any cloud infrastructure you'd like to use, and gain visibility into the execution and performance of your models and predictions. -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
...Start scaling your model training with just a few lines of Python code. Scale up to hundreds of GPUs with upwards of 90% scaling efficiency.
