Tag: Python

The product is a Python script that leverages the Gemini API to fetch and summarize research papers from arXiv. It helps researchers, students, and enthusiasts quickly extract key information, saving time from reading lengthy literature. This tool is not only suitable for individual users, but can also automate daily literature searches and improve research efficiency. The product is available free of charge and is easy to install and configure.

Atom of Thoughts (AoT) is a new reasoning framework that transforms the reasoning process into a Markov process by representing solutions as combinations of atomic problems. This framework significantly improves the performance of large language models on inference tasks through the decomposition and contraction mechanism, while reducing the waste of computing resources. AoT can not only be used as an independent inference method, but also as a plug-in for existing test-time extension methods, flexibly combining the advantages of different methods. The framework is open source and implemented in Python, making it suitable for researchers and developers to conduct experiments and applications in the fields of natural language processing and large language models.

Cliprun is a browser-based Python programming tool that allows users to run Python code directly on any web page through a Chrome plug-in. It leverages Pyodide technology to enable on-the-fly code execution without local environment configuration. The main advantages of this tool include no need to install a Python environment, support for a variety of commonly used Python libraries (such as pandas, numpy, matplotlib, etc.), provision of code snippet saving functions, and support for data visualization and automated script running. Cliprun is mainly aimed at developers, data analysts and programming learners. It aims to provide a convenient and efficient online programming environment to help users quickly implement code testing, data analysis and automation tasks.

Smallpond is a high-performance data processing framework designed for large-scale data processing. It is built on DuckDB and 3FS and can efficiently handle petabyte-scale data sets without the need for long-running services. Smallpond provides a simple and easy-to-use API, supporting Python 3.8 to 3.12, suitable for data scientists and engineers to quickly develop and deploy data processing tasks. Its open source nature allows developers to freely customize and extend functions.

Probly is an innovative desktop client application that combines the convenience of spreadsheets with the powerful data analysis capabilities of Python. By running Python code in the browser (using WebAssembly technology), users can perform efficient data analysis locally while leveraging AI technology to obtain intelligent recommendations and automated analysis. This product is mainly aimed at users who need to perform complex data analysis but want to maintain operational convenience, such as data analysts, researchers and enterprise users. Probly ensures data privacy and high performance through a locally running architecture design, while providing rich functions and flexible scalability.

Crawl4LLM is an open source web crawler project that aims to provide efficient data crawling solutions for the pre-training of large language models (LLM). It helps researchers and developers obtain high-quality training corpus by intelligently selecting and crawling web page data. The tool supports multiple document scoring methods and can flexibly adjust crawling strategies according to configuration to meet different pre-training needs. The project is developed based on Python, has good scalability and ease of use, and is suitable for use in academic research and industrial applications.

KET-RAG (Knowledge-Enhanced Text Retrieval Augmented Generation) is a powerful retrieval-enhanced generation framework that combines knowledge graph technology. It achieves efficient knowledge retrieval and generation through multi-granularity indexing frameworks such as knowledge graph skeleton and text-keyword bipartite graph. This framework significantly improves retrieval and generation quality while reducing indexing costs, and is suitable for large-scale RAG application scenarios. KET-RAG is developed based on Python, supports flexible configuration and expansion, and is suitable for developers and researchers who need efficient knowledge retrieval and generation.

LangGraph Multi-Agent Supervisor is a Python library built on the LangGraph framework for creating hierarchical multi-agent systems. It allows developers to coordinate multiple professional agents through a centralized supervisory agent to achieve dynamic assignment of tasks and communication management. The importance of this technology lies in its ability to efficiently organize complex multi-agent tasks and improve the flexibility and scalability of the system. It is suitable for scenarios that require multi-agent collaboration, such as automated task processing, complex problem solving, etc. The product is positioned for advanced developers and enterprise-level applications. The price has not yet been disclosed, but its open source feature allows users to customize and expand it according to their own needs.

Dria-Agent-α is a large language model (LLM) tool interaction framework launched by Hugging Face. It calls tools through Python code. Compared with the traditional JSON mode, it can more fully utilize the reasoning capabilities of LLM, allowing the model to solve complex problems in a way that is closer to human natural language. The framework leverages Python’s popularity and near-pseudocode syntax to make LLM perform better in agency scenarios. Dria-Agent-α was developed using the synthetic data generation tool Dria, which uses a multi-stage pipeline to generate realistic scenes and train models for complex problem solving. Currently, two models, Dria-Agent-α-3B and Dria-Agent-α-7B, have been released on Hugging Face.

RAG over excel sheets is an artificial intelligence project that combines LlamaIndex and IBM's Docling technology, focusing on implementing retrieval question answering (RAG) on Excel sheets. This project can not only be applied to Excel, but can also be extended to PPTs and other complex documents. It greatly improves the efficiency of data analysis and document management by providing efficient information retrieval and processing capabilities.

radio-llm is a platform for integrating long language models (LLMs) with Meshtastic mesh communication networks. It allows users on the mesh network to interact with LLM for concise, automated responses. Additionally, the platform allows users to perform tasks through LLM such as calling emergency services, sending messages, and retrieving sensor information. Product background information shows that currently only demonstration tools for emergency services are supported, and more tools will be launched in the future.

Ollama-OCR is an OCR tool that uses the latest visual language model. It is technically supported by Ollama and can extract text from images. It supports multiple output formats, including Markdown, plain text, JSON, structured data and key-value pairs, and supports batch processing functions. This project is provided in the form of Python package and Streamlit network application, which is convenient for users to use in different scenarios.

The Semantic Kernel OpenAPI plug-in is a plug-in designed for Semantic Kernel. It allows developers to easily integrate existing APIs as plug-ins to enhance the capabilities of AI agents and make them more diverse in practical applications. The release of this plug-in means that developers can use existing API functions and convert them into plug-ins in AI solutions, simplifying the process and improving development efficiency.

Sudoku-RWKV is a Sudoku problem-solving tool based on the RWKV model, which uses deep learning technology to solve Sudoku problems. This model has been specially trained to handle a large number of Sudoku samples and has a high problem-solving accuracy. Product background information shows that the model used about 2M Sudoku samples during training, covering about 39.2B tokens, with a parameter size of about 12.7M, a vocabulary of 133, and an 8-layer architecture with 320 dimensions per layer. The main advantages of this model are its high efficiency and accuracy, being able to solve any solvable Sudoku puzzle.

Marimo is an open source Python reactive notebook that is reproducible, git-friendly, executable as a script, and shareable as an application. It responds to cell changes by automatically running affected cells, eliminating the tedious work of managing notebook state. Marimo's UI elements such as data frame GUIs and charts make data processing fast, futuristic and intuitive. Marimo notebooks are stored as .py files and can be used with git version control, run as Python scripts, or import symbols into other notebooks or Python files and lint or format them using your favorite tools. All in a modern, AI-powered editor.

ComfyUI-GIMM-VFI is a frame interpolation tool based on the GIMM-VFI algorithm, which enables users to achieve high-quality frame interpolation effects in image and video processing. This technology increases the frame rate of a video by inserting new frames between consecutive frames, making the action look smoother. This is especially important for video games, film post-production, and other applications that require high frame rate video. Product background information shows that it is developed based on Python and relies on the CuPy library, which is particularly suitable for scenarios that require high-performance computing.

browser-use is an open source web page automation library that allows large language models (LLM) to interact with websites and implement complex web page operations through a simple interface. The main advantages of this technology include universal support for multiple language models, automatic detection of interactive elements, multi-tab management, XPath extraction, visual model support, etc. It solves some pain points in traditional web page automation, such as dynamic content processing, long task solving, etc. With its flexibility and ease of use, browser-use provides developers with a powerful tool to build more intelligent and automated web interaction experiences.

Claude Vision Object Detection is a Python-based tool that utilizes the Claude 3.5 Sonnet Vision API to detect and visualize objects in images. The tool automatically draws bounding boxes around detected objects, labels them, and displays confidence scores. It supports processing a single image or an entire catalog of images, and features highly accurate confidence scores using bright and different colors for each detected object. Additionally, it can save annotated images with detection results.

Data Formulator is an AI-driven data visualization tool developed by the Microsoft research team. It helps users quickly create rich data visualization charts by combining user interface interaction and natural language input. The tool automatically handles data conversion, allowing users to focus on chart design. Data Formulator supports installation and running locally via Python, or can be quickly started in GitHub Codespaces. It represents technological progress in the field of data analysis and visualization, improving the efficiency and ease of use of data visualization through AI technology.

ComfyUI-MochiWrapper is a wrapper node for the Mochi video generator, which allows users to interact with Mochi models through the ComfyUI interface. The main advantage of this project is that it can use Mochi models to generate video content and simplify the operation process through ComfyUI. It is developed based on Python and is completely open source, allowing developers to use and modify it freely. The project is currently under active development and already has some basic functions, but has not yet officially released a version.

joy-caption-batch is a programming model that uses the Joytag Caption tool to batch generate descriptive captions for image files. This tool is currently in the Alpha stage. It analyzes the image content and uses artificial intelligence technology to generate corresponding text descriptions to help users quickly understand the image content. Key benefits of this tool include batch processing capabilities, support for custom image directories, and support for low-video memory mode, allowing it to run on devices with low video memory. In addition, the tool also provides detailed installation and usage instructions to facilitate users to get started quickly.

AgentStack is a command line tool for quickly creating AI agent projects. It is based on Python 3.10+, supports a variety of popular agent frameworks, such as CrewAI, Autogen and LiteLLM, and integrates a variety of tools to simplify the development process. The design concept of AgentStack is to simplify the process of building AI agents from scratch, so that agent projects can be quickly up and running without complex configuration. It also provides an interactive test runner, live development server, and production build scripts. AgentStack is open source and follows the MIT license. It is suitable for developers who want to quickly enter AI agent development.

Swarm is an experimental framework managed by the OpenAI Solutions team for building, orchestrating, and deploying multi-agent systems. It achieves coordination and execution between agents by defining the abstract concepts of agents and handoffs. The Swarm framework emphasizes lightweight, high controllability, and ease of testing. It is suitable for scenarios that require a large number of independent functions and instructions, allowing developers to have complete transparency and fine-grained control over context, steps, and tool calls. The Swarm framework is currently in the experimental stage and is not recommended for use in production environments.

promptic is a lightweight, decorator-based Python library that simplifies the process of interacting with large language models (LLMs) through litellm. Using prompt, you can easily create prompts, handle input parameters, and receive structured output from LLMs with just a few lines of code.

Chat With Your Docs is a Python application that allows users to chat with multiple document formats such as PDFs, web pages, and YouTube videos. Users can ask questions using natural language and the application will provide relevant answers based on the document content. The app uses language models to generate accurate answers. Note that the app only responds to questions related to loaded documents.

Briefer is an open source data platform that allows users to run SQL and Python code and transform notebooks into dashboards and data applications. It supports connecting to multiple data sources, such as Postgres, BigQuery, Redshift, etc., and query results can be used directly in Python code blocks. Additionally, it provides pre-installed libraries and built-in AI assistants to help users write code faster. Briefer's dashboard and data application capabilities allow users to create interactive pages for data exploration and decision support.

iText2KG is a Python package designed to leverage large language models to extract entities and relationships from text documents and incrementally build consistent knowledge graphs. It has zero-shot capabilities, allowing knowledge extraction across different domains without specific training. The package includes document distillation, entity extraction, and relationship extraction modules, ensuring entities and relationships are resolved and unique. It provides visual representation of knowledge graphs through Neo4j, supporting interactive exploration and analysis of structured data.

Parsera is a lightweight Python library specifically designed to be combined with large language models (LLMs) to simplify the process of website data scraping. It makes data scraping more efficient and cost-effective by using minimal tokens to increase speed and reduce costs. Parsera supports multiple chat models and can be customized to use different models, such as OpenAI or Azure.

LLaMA Assistant for Mac is a desktop client developed based on the llama-cpp-python library and is designed to assist users with predefined requirements. It uses a lot of code from other projects, but replaces the ollama parts with llama-cpp-python to achieve a solution more consistent with Python programming style.

Scrape It Now! is an open source web scraping tool that provides a complete set of automated web scraping and indexing solutions. The tool is written in Python and supports a variety of functions, including dynamic JavaScript content loading, ad blocking, random user agents, automatic creation of AI search indexes, etc., to improve crawling efficiency and data quality. It is suitable for users who need to extract information from web pages and perform further analysis or storage.

SuperCoder 2.0 is an open source autonomous software development system that utilizes large language models (LLMs) and large action models (LAMs) to fine-tune Python code generation to achieve higher-precision one-time or less-time programming. It combines software guardrails specific to development frameworks, such as Flask and Django, with SuperAGI's general intelligent development agents to deliver complex real-world software systems. SuperCoder 2.0 also ensures that your intellectual property and code are protected from AI-related abuse and is deeply integrated with existing development stacks such as Jira, Github or Gitlab, Jenkins, CSPs, and QA solutions such as BrowserStack/Selenium Clouds to ensure a seamless software development experience.

Datalore is an AI-driven data analysis tool that integrates Anthropic's Claude API and multiple data analysis libraries. It provides an interactive interface that enables users to perform data analysis tasks using natural language commands.

Great Tables is a Python library for creating beautiful and feature-rich tables. It supports Pandas or Polars DataFrame as data source, provides a variety of formatting options and customization functions, and is ideal for data analysis and report generation. The library is mainly maintained by Rich Iannone and Michael Chow, adopts the MIT license, and emphasizes a simple and powerful design philosophy.

RAGElo is a toolset that uses the Elo scoring system to help select the best retrieval-augmented generation (RAG)-based large language model (LLM) agents. As generative LLM becomes easier to prototype and integrate in production, evaluation remains the most challenging part of the solution. RAGElo provides a good overview of which settings work and which don't by comparing answers to multiple questions from different RAG pipelines and prompts, calculating rankings for different settings.

ComfyUI-LuminaWrapper is an open source Python wrapper for simplifying the loading and use of Lumina models. It supports custom nodes and workflows, making it easier for developers to integrate Lumina models into their projects. This plug-in is mainly aimed at developers who want to use Lumina models for deep learning or machine learning in a Python environment.

AI Math Notes is an open source interactive drawing application that allows users to draw mathematical equations on canvas. The application utilizes a multimodal large language model (LLM) to calculate and display the results. The application was developed in Python, utilizing the Tkinter library to create the graphical user interface and PIL for image processing. Inspired by Apple's 'Math Notes' showcase at the 2024 Worldwide Developers Conference (WWDC).

Abstra is a Python and AI-based business process automation platform that allows users to create powerful workflows by dragging and dropping components and binding Python code. The platform provides a variety of automation tools such as smart forms, scheduled tasks, and event triggers, supports one-click deployment to the cloud, and can be integrated with Git. Abstra emphasizes transparency and auditability, providing SSO or SAML authentication and fine-grained access control, making it suitable for enterprise teams that require highly customized automation solutions.

prettygraph is a Python-based web application developed by @yoheinakajima that showcases a new UI pattern for dynamically converting text input into a knowledge graph. This project is a rapid prototype that aims to provide a simple UI idea to generate a knowledge graph by updating text highlighting in the UI in real time.

Snorkell.ai is a tool that automatically generates documentation. It can automatically generate and update the documentation of a GitHub project every time a pull request is merged, ensuring that the documentation is always consistent with the code base. It supports programming languages ​​such as Python, Java, TypeScript, JavaScript, and Kotlin to generate human-readable and understandable documentation.

SunoAPI is an unofficial Suno API based on Python and FastAPI. It supports functions such as generating songs, lyrics, etc., and comes with built-in token maintenance and keep-alive functions, so you don’t have to worry about token expiration. SunoAPI adopts a fully asynchronous design, runs quickly, and is suitable for subsequent expansion. Users can easily use the API to generate a variety of music content.

DataDreamer is a powerful open source Python library for prompting, generating synthetic data and training workflows. It is designed to be simple to use, extremely efficient, and of research-grade quality. DataDreamer supports creating prompt workflows, generating synthetic datasets, aligning models, fine-tuning models, command-tuning models, and model distillation. It is simple, research-grade, efficient, reproducible, and simplifies the sharing of data sets and models.

Quadratic is an infinite canvas spreadsheet that runs in the browser, integrating artificial intelligence, Python and SQL. It can help users perform data analysis, processing and visualization, and provides powerful data processing functions and intelligent suggestions. At the same time, Quadratic also provides rich Python and SQL programming capabilities, allowing users to use customized Python scripts and SQL queries for data processing in tables. Quadratic is positioned to provide an efficient, flexible and intelligent data processing tool.

React Flow is an open source visual editor that allows users to create agent workgroups through drag-and-drop for customizing business logic. Users can drag and drop agents from the gallery into the workspace, connect them, define initial tasks, and export Python scripts to run on the local machine. We provide cloud support for enterprises through customized operating systems so that they can run LLM. Feel free to contact our Enterprise Support team for more information.

UniRef is a unified model for reference object segmentation in images and videos. It supports various tasks such as semantic reference image segmentation (RIS), few-shot segmentation (FSS), semantic reference video object segmentation (RVOS), and video object segmentation (VOS). The core of UniRef is the UniFusion module, which can efficiently inject various reference information into the basic network. UniRef can be used as a plug-in component for basic models such as SAM. UniRef provides models trained on multiple benchmark data sets, and also opens source code for research use.

Streamlit is an open source Python library that allows data scientists and machine learning engineers to quickly create beautiful, custom machine learning applications and data applications in a web browser. There is no need to learn front-end web development, Streamlit applications can be built from simple scripts in minutes. Streamlit provides simple APIs to create various interactive widgets such as text, images, tables, charts, videos, etc., making data exploration and presentation easy. It has built-in support for data frameworks such as Pandas, Numpy, Matplotlib, etc. It is compatible with most Python machine learning libraries, such as Scikit-learn, TensorFlow, etc.

NewsNerd HackerBot is your ultimate companion for the latest tech news on Hacker News! It provides access to Hacker News stories in the Hot, Best, Latest, Q&A, Showcase, and Recruitment categories. You can also filter stories by keyword, such as "Give me 20 stories about Sam Altman and OpenAI." In the future, we plan to add tools to analyze comments on stories as well as analyze URL content (e.g. blog posts, etc.).

SuperDuperDB is a tool that can integrate and train AI directly into your favorite database. Just use Python, no complex MLOps processes and specialized vector databases required. It allows you to perform real-time inference and model training in the database, convert existing databases into fully functional vector databases, and integrate seamlessly with various machine learning frameworks and AI APIs. Please visit the official website for more information.

NLTK is a leading Python platform for processing human language data. It provides an easy-to-use interface for accessing more than 50 corpora and lexical resources such as WordNet, and a set of text processing libraries for classification, tagging, parsing, and semantic reasoning. It also provides wrappers for industrial-grade NLP libraries and has an active discussion forum. NLTK is intended for linguists, engineers, students, educators, researchers, and industry users. NLTK is free to use and is an open source, community-driven project.

Langroid is a lightweight, extensible and principled Python framework that makes it easy to build LLM-based applications. You can set up agents, equip them with optional components (LLMs, vector stores, and methods), assign them tasks, and let them collaborate to solve problems by exchanging messages. This multi-agent paradigm is inspired by the Actor framework (but you don't need to know anything about this!). Langroid offers a completely new way of developing LLM applications that is thoughtfully thought out in simplifying the developer experience; it does not use Langchain. We welcome contributions - see the contributions documentation for contribution ideas.

scikit-learn is a simple and efficient machine learning library that provides a rich set of machine learning algorithms and tools that can be used for classification, regression, clustering, dimensionality reduction and other tasks. It is built on NumPy, SciPy and matplotlib and features ease of use, superior performance and reusability. scikit-learn is open source and available for commercial use under the BSD license.

CHATGPT AI is a writing summary tool based on AI and Python models. It can generate corresponding summaries based on the input Arxiv paper link and the selected AI/Python model. CHATGPT AI provides high-quality automatic summarization services to help users quickly understand the content of the paper.

PyCaret is an open source, low-code Python machine learning library that automates machine learning workflows. PyCaret allows you to spend less time writing code and more time analyzing. PyCaret has a modular design, and each module encapsulates a specific machine learning task. A consistent set of functions in PyCaret can perform tasks in workflows. There are many data preprocessing functions to choose from in PyCaret, from scaling to feature engineering. There are tons of interesting tutorials to help you learn PyCaret, you can start with our official tutorials. PyCaret makes machine learning easy and fun.