Search Results for "python programming language" - Page 52
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Showing 5506 open source projects for "python programming language"
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Sov.ai
A curated list of practical financial machine learning tools and apps
Financial Machine Learning is a curated directory of practical tools, repositories, datasets, papers, and educational resources for quantitative finance. It organizes material across trading, forecasting, portfolio construction, risk, alternative data, and financial machine learning techniques. Dedicated sections cover supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, and time-series analysis. Entries include descriptions, popularity... -
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Kirara AI
DIY multimodal AI chatbot
Kirara AI is a chatbot framework designed to connect large language models with mainstream chat platforms. It supports multi-turn conversation, persona presets, keyword-triggered replies, administrator commands, and conditional automation. The project can work with model providers such as OpenAI, DeepSeek, Claude, Gemini, Qwen, Mistral, Kimi, Minimax, and others. It also supports image generation models, voice replies, cross-platform message sending, and custom workflows. A WebUI helps users... -
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ChatRWKV
ChatRWKV is like ChatGPT but powered by RWKV
ChatRWKV is a chat-oriented inference project built around the RWKV language model. It is designed to provide a ChatGPT-like conversational experience while using RWKV’s recurrent, attention-free architecture. The project focuses on making RWKV usable for interactive prompting, assistant behavior, developer demos, and local experimentation. It connects to the broader RWKV ecosystem, including newer RWKV model versions and compatible weights. ChatRWKV is useful for developers who want to test... -
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NeuTTS Air
NeuTTS model built from small LLM backbones
NeuTTS Air is an open-source collection of on-device text-to-speech speech language models from Neuphonic. It is built for natural-sounding voice generation that can run locally instead of relying on a remote web API. The project emphasizes instant voice cloning, real-time performance, and deployment on smaller devices such as phones, laptops, and Raspberry Pi-class hardware. Its LLM-based architecture is intended to bring more expressive and flexible speech generation to local applications.... -
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NeuTTS Nano
On-device TTS model by Neuphonic
NeuTTS Nano is an open-source collection of on-device text-to-speech speech language models from Neuphonic. It is built for natural-sounding voice generation that can run locally instead of relying on a remote web API. The project emphasizes instant voice cloning, real-time performance, and deployment on smaller devices such as phones, laptops, and Raspberry Pi-class hardware. Its LLM-based architecture is intended to bring more expressive and flexible speech generation to local... -
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LitGPT
20+ high-performance LLMs with recipes to pretrain, finetune at scale
LitGPT is a collection of over 20 high-performance large language models (LLMs) accompanied by recipes to pretrain, finetune, and deploy them at scale. It provides implementations without abstractions, making it beginner-friendly while offering advanced features like flash attention and support for various precision levels. LitGPT is designed to run efficiently across multiple GPUs or TPUs, catering to both small-scale and large-scale deployments. -
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FastAgency
The fastest way to bring multi-agent workflows to production
FastAgency is a framework that simplifies the creation and deployment of AI-driven automation agents. It provides a structured environment for developing AI assistants capable of handling various business and technical tasks. -
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Ragas
Supercharge Your LLM Application Evaluations
Objective metrics, intelligent test generation, and data-driven insights for LLM apps. Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye to time-consuming, subjective assessments and hello to data-driven, efficient evaluation workflows. Don't have a test dataset ready? We also do production-aligned test set generation. -
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ReMe
Memory Management Kit for Agents
ReMe is a memory management kit for AI agents that gives them structured, persistent memory capabilities, enabling agents to extract, store, and reuse information across sessions, tasks, and interactions. It is designed to support long-running agent workflows where context matters and working memory alone isn’t enough, helping agents remember user preferences, task histories, and relevant past observations. The toolkit provides APIs to offload large, ephemeral outputs to external storage and... -
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VibeVoice
Open-source multi-speaker long-form text-to-speech model
VibeVoice-1.5B is Microsoft’s frontier open-source text-to-speech (TTS) model designed for generating expressive, long-form, multi-speaker conversational audio such as podcasts. Unlike traditional TTS systems, it excels in scalability, speaker consistency, and natural turn-taking for up to 90 minutes of continuous speech with as many as four distinct speakers. A key innovation is its use of continuous acoustic and semantic speech tokenizers operating at an ultra-low frame rate of 7.5 Hz,... -
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CWhy
Explains and suggests fixes for compile-time errors for C, C++, C#, Go
Explains and suggests fixes for compiler error messages for a wide range of programming languages, including C, C++, C#, Go, Java, LaTeX, PHP, Python, Ruby, Rust, Swift, and TypeScript. CWhy needs to be connected to an OpenAI account or an Amazon Web Services account. Your account will need to have a positive balance for this to work (check your OpenAI balance). CWhy currently defaults to GPT-4, and falls back to GPT-3.5-turbo if a request error occurs. -
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GLM-TTS
Controllable & emotion-expressive zero-shot TTS
GLM-TTS is an advanced text-to-speech synthesis system built on large language model technologies that focuses on producing high-quality, expressive, and controllable spoken output, including features like emotion modulation and zero-shot voice cloning. It uses a two-stage architecture where a generative LLM first converts text into intermediate speech token sequences and then a Flow-based neural model converts those tokens into natural audio waveforms, enabling rich prosody and voice... -
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cuML
RAPIDS Machine Learning Library
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU equivalents. For details on performance, see the cuML Benchmarks Notebook. -
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CounterfactualExplanations.jl
A package for Counterfactual Explanations and Algorithmic Recourse
...Both CE and AR are related tools for explainable artificial intelligence (XAI). While the package is written purely in Julia, it can be used to explain machine learning algorithms developed and trained in other popular programming languages like Python and R. See below for a short introduction and other resources or dive straight into the docs. -
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AWS CodeBuild curated Docker images
AWS CodeBuild repository for managed Docker images
When you call AWS CodeBuild to run a build, you must provide information about the build environment. A build environment represents a combination of operating system, programming language runtime, and tools that CodeBuild uses to run a build. The master branch will sometimes have changes that are still in the process of being released in AWS CodeBuild. When you provide information to CodeBuild about the build environment, you specify the identifier of a Docker image in a supported repository type. These include the CodeBuild Docker image repository, publicly available images in Docker Hub, and Amazon Elastic Container Registry (Amazon ECR) repositories that your AWS account has permission to access. ... -
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CS-Books
Collection of computer science textbooks, learning materials
CS-Books is a massive curated collection of computer science textbooks, learning materials, and resource links that covers a wide range of topics from programming languages like C/C++ and Python to core subjects such as data structures, algorithms, operating systems, databases, networks, and design patterns. The repository aggregates over a thousand classic reference books and educational resources into a single index, making it a valuable starting point for self-learners, students preparing for technical interviews, and professionals deepening their knowledge across different CS domains. ... -
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GLM-4.6V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.6V represents the latest generation of the GLM-V family and marks a major step forward in multimodal AI by combining advanced vision-language understanding with native “tool-call” capabilities, long-context reasoning, and strong generalization across domains. Unlike many vision-language models that treat images and text separately or require intermediate conversions, GLM-4.6V allows inputs such as images, screenshots or document pages directly as part of its reasoning pipeline — and... -
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pmd
An extensible multilanguage static code analyzer
PMD is a source code analyzer. It finds common programming flaws like unused variables, empty catch blocks, unnecessary object creation, and so forth. It supports Java, JavaScript, Salesforce.com Apex and Visualforce, PLSQL, Apache Velocity, XML, and XSL. Additionally, it includes CPD, the copy-paste-detector. CPD finds duplicated code in Java, C, C++, C#, Groovy, PHP, Ruby, Fortran, JavaScript, PLSQL, Apache Velocity, Scala, Objective C, Matlab, Python, Go, Swift and Salesforce.com Apex, and Visualforce. ... -
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Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector... -
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Learn AI Engineering
Learn AI and LLMs from scratch using free resources
Learn AI Engineering is a learning path for AI engineering that consolidates high-quality, free resources across the full stack: math, Python foundations, machine learning, deep learning, LLMs, agents, tooling, and deployment. Rather than a loose bookmark list, it organizes topics into a progression so learners can start from fundamentals and move toward practical, production-oriented skills. It mixes courses, articles, code labs, and videos, emphasizing materials that teach both concepts... -
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Gemini Fullstack LangGraph Quickstart
Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph
gemini-fullstack-langgraph-quickstart is a fullstack reference application from Google DeepMind’s Gemini team that demonstrates how to build a research-augmented conversational AI system using LangGraph and Google Gemini models. The project features a React (Vite) frontend and a LangGraph/FastAPI backend designed to work together seamlessly for real-time research and reasoning tasks. The backend agent dynamically generates search queries based on user input, retrieves information via the... -
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OpenAI Agents JS
A lightweight, powerful framework for multi-agent workflows
...The repo includes examples showing how to build agents that call local functions, chain between agents, validate input/output, stream responses, and interact in real time (e.g. voice agents via WebRTC). It also has tracing and debugging support so you can introspect how agents executed their workflows. Because it aligns closely with the Python Agents SDK, it aims for cross-language parity so that JS/TS devs can adopt similar agent architectures. -
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Tongyi DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
DeepResearch (Tongyi DeepResearch) is an open-source “deep research agent” developed by Alibaba’s Tongyi Lab designed for long-horizon, information-seeking tasks. It’s built to act like a research agent: synthesizing, reasoning, retrieving information via the web and documents, and backing its outputs with evidence. The model is about 30.5 billion parameters in size, though at any given token only ~3.3B parameters are active. It uses a mix of synthetic data generation, fine-tuning and... -
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AWS MCP Servers
Helping you get the most out of AWS, wherever you use MCP
AWS MCP Servers are a collection of remotely hosted, fully-managed Model Context Protocol (MCP) servers by AWS, providing AI applications with real-time access to AWS documentation, API references, best practices, and infrastructure-management capabilities via natural-language workflows. An MCP Server is a lightweight program that exposes specific capabilities through the standardized Model Context Protocol. Host applications (such as chatbots, IDEs, and other AI tools) have MCP clients that... -
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marqo
Tensor search for humans
A tensor-based search and analytics engine that seamlessly integrates with your applications, websites, and workflows. Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and...
