Search Results for "python" - Page 45
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Showing 22535 open source projects for "python"
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Strands Agents
A model-driven approach to building AI agents in just a few lines
Strands Agents SDK is a model-driven approach to building and running AI agents. It enables the creation of simple conversational assistants to complex autonomous workflows, scaling from local development to production deployment. The SDK is designed to be simple yet powerful, catering to various AI agent development needs. -
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ContextGem
ContextGem: Effortless LLM extraction from documents
ContextGem is an open-source framework designed to simplify the extraction of structured data and insights from documents using large language models (LLMs). It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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HACS Integration
HACS gives you a UI to handle downloads of all your custom needs
HACS is an integration for Home Assistant that simplifies the management of custom components, themes, and other community-driven content. It provides a user-friendly interface within Home Assistant for browsing, installing, and updating custom add-ons, enhancing the customization and extensibility of Home Assistant setups. -
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MCP Server Qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. -
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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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Splunk Attack Range
A tool that allows you to create vulnerable environments
The Splunk Attack Range is an open-source project maintained by the Splunk Threat Research Team. It builds instrumented cloud (AWS, Azure) and local environments (Virtualbox), simulates attacks, and forwards the data into a Splunk instance. This environment can then be used to develop and test the effectiveness of detections. -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
MiniSom is a minimalistic and Numpy-based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial Neural Network able to convert complex, nonlinear statistical relationships between high-dimensional data items into simple geometric relationships on a low-dimensional display. Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation of... -
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BudouX
Standalone, small, language-neutral
Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training... -
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Metacrafter
Metadata and data identification tool and Python library
Python command line tool and Python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifiable information (PII). Metacrafter is a rule-based tool that helps to label fields of the tables in databases. It scans table and finds person names, surnames, midnames, PII data, basic identifiers like UUID/GUID. -
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AudioLM - Pytorch
Implementation of AudioLM audio generation model in Pytorch
Implementation of AudioLM, a Language Modeling Approach to Audio Generation out of Google Research, in Pytorch It also extends the work for conditioning with classifier free guidance with T5. This allows for one to do text-to-audio or TTS, not offered in the paper. Yes, this means VALL-E can be trained from this repository. It is essentially the same. This repository now also contains a MIT licensed version of SoundStream. It is also compatible with EnCodec, however, be aware that it... -
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Cascadia Code
A fun, new monospaced font that includes programming ligatures
This project contains the source code for Cascadia Code, a fun yet modern monospaced font that includes programming ligatures. Cascadia was designed to enhance the look and feel of the Windows Terminal, with three variants: Cascadia Code, the standard version of the font; Cascadia Mono, which is the version without Ligatures; and Cascadia PL, the version embedded with Powerline symbols. For Windows or any other OS that employs TrueType hinting, it is recommended to use the TTF version to... -
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Kindle_download_helper
Download all your kindle books script
Kindle_download_helper is a Python script for downloading Kindle books and personal documents from a user’s Amazon content library. It supports several Amazon regions, including Amazon, Amazon.cn, Amazon.de, Amazon.co.uk, and Amazon.co.jp. The workflow requires the user to log in through the browser, retrieve a CSRF token, and then run the script with the correct regional option. -
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xiaogpt
Play ChatGPT and other LLM with Xiaomi AI Speaker
xiaogpt is a Python project that connects Xiaomi AI speakers with ChatGPT and other large language models. It lets users turn compatible XiaoAI speaker devices into conversational AI assistants beyond the default built-in voice capabilities. The project works by listening for user interactions, forwarding prompts to supported model providers, and sending generated responses back through the speaker. -
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CommunityScrapers
This is a public repository containing scrapers
Stash Community Scrapers is a large open-source collection of metadata extraction tools designed to work with the Stash media management platform, enabling automated scraping of content information from various online sources. The repository contains hundreds of scraper definitions written primarily in YAML and Python, each tailored to extract structured metadata such as titles, performers, tags, and media details from specific websites. These scrapers integrate directly into Stash, allowing users to enrich their media libraries with accurate and detailed information without manual entry. The project supports both automatic installation through in-app feeds and manual configuration for advanced use cases. ... -
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WhatsApp MCP Server
WhatsApp MCP server enabling AI access to chats and messaging
...It acts as a bridge between WhatsApp and large language models, allowing controlled access to messages, chats, and contacts. whatsapp-mcp is composed of two main components: a Go-based bridge that connects to the WhatsApp Web API and stores data locally, and a Python-based MCP server that exposes tools for AI interaction. All message data is stored in a local SQLite database and is only accessed when explicitly requested through defined tools, giving users control over how their data is used. It supports both sending and receiving messages, including various media types such as images, audio, videos, and documents. ... -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
...It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters and notebooks progress from tiny toy models to more capable transformer stacks, including sampling strategies and evaluation hooks. The focus is on readability, correctness, and experimentation, making it ideal for students and practitioners transitioning from theory to working systems. ... -
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ImageReward
[NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences
...Trained on 137k expert-annotated image pairs, ImageReward significantly outperforms existing scoring methods like CLIP, Aesthetic, and BLIP in capturing human visual preferences. It is provided as a Python package (image-reward) that enables quick scoring of generated images against textual prompts, with APIs for ranking, scoring, and filtering outputs. Beyond evaluation, ImageReward supports Reward Feedback Learning (ReFL), a method for directly fine-tuning diffusion models such as Stable Diffusion using human-preference feedback, leading to demonstrable improvements in image quality. -
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minted
minted is a LaTeX package that provides syntax highlighting
minted is a LaTeX package that enables advanced syntax highlighting of source code using the Pygments library. It supports customization via LaTeX and Python integration, allowing fine-grained control over code snippets in documents. -
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towncrier
Manage the release notes for your project
towncrier is a changelog management tool that automates the generation of release notes from fragments stored during development. It encourages developers to document changes incrementally and reduces the burden of writing changelogs at release time. Designed for Python projects, it integrates well with tools like setuptools and tox. -
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GPflow
Gaussian processes in TensorFlow
GPflow is a package for building Gaussian process models in Python. It implements modern Gaussian process inference for composable kernels and likelihoods. GPflow builds on TensorFlow 2.4+ and TensorFlow Probability for running computations, which allows fast execution on GPUs. -
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auto-cpufreq
Automatic CPU speed & power optimizer for Linux
Automatic CPU speed & power optimizer for Linux. Actively monitors laptop battery state, CPU usage, CPU temperature, and system load, ultimately allowing you to improve battery life without making any compromises. -
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Genv
GPU environment management and cluster orchestration
Genv is an open-source environment and cluster management system for GPUs. Genv lets you easily control, configure, monitor and enforce the GPU resources that you are using in a GPU machine or cluster. It is intended to ease up the process of GPU allocation for data scientists without code changes. -
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Jupytext
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
...Only the notebook inputs (and optionally, the metadata) are included. Text notebooks are well suited for version control. You can also edit or refactor them in an IDE - the .py notebook above is a regular Python file. Text notebooks with a .py or .md extension are well suited for version control. They can be edited or authored conveniently in an IDE. You can open and run them as notebooks in Jupyter Lab with a right click. However, the notebook outputs are lost when the notebook is closed, as only the notebook inputs are saved in text notebooks. -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
...Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. Validate the functions that produce your data by automatically generating test cases for them. Integrate seamlessly with the Python ecosystem. Overcome the initial hurdle of defining a schema by inferring one from clean data, then refine it over time. Identify the critical points in your data pipeline, and validate data going in and out of them. Build confidence in the quality of your data by defining schemas for complex data objects.
