An LLM-powered code generation tool that relies on the built-in Node.js API Typescript Template Project to easily generate clean, well-structured CRUD module code from text description. It orchestrates 3 LLM micro-agents (`Developer`, `Troubleshooter` and `TestsFixer`) to generate code, fix compilation errors, and ensure passing E2E tests. The process includes module code generation, DB migration creation, seeding data, and running tests to validate output. By cycling through these steps, it guarantees consistent and production-ready CRUD code aligned with vertical slicing architecture.

OramaCore is a database designed for AI projects, answer engines, copilots, and search functionalities. It offers features such as a full-text search engine, vector database, LLM interface, and various utilities. The tool is currently under active development and not recommended for production use due to potential API changes. OramaCore aims to provide a comprehensive solution for managing data and enabling advanced AI capabilities in projects.

Kaytu is an AI platform that enhances cloud efficiency by analyzing historical usage data and providing intelligent recommendations for optimizing instance sizes. Users can pay for only what they need without compromising the performance of their applications. The platform is easy to use with a one-line command, allows customization for specific requirements, and ensures security by extracting metrics from the client side. Kaytu is open-source and supports AWS services, with plans to expand to GCP, Azure, GPU optimization, and observability data from Prometheus in the future.

DistillKitPlus is an open-source toolkit designed for knowledge distillation (KLD) in low computation resource settings. It supports logit distillation, pre-computed logits for memory-efficient training, LoRA fine-tuning integration, and model quantization for faster inference. The toolkit utilizes a JSON configuration file for project, dataset, model, tokenizer, training, distillation, LoRA, and quantization settings. Users can contribute to the toolkit and contact the developers for technical questions or issues.

AutoAgent is a fully-automated and zero-code framework that enables users to create and deploy LLM agents through natural language alone. It is a top performer on the GAIA Benchmark, equipped with a native self-managing vector database, and allows for easy creation of tools, agents, and workflows without any coding. AutoAgent seamlessly integrates with a wide range of LLMs and supports both function-calling and ReAct interaction modes. It is designed to be dynamic, extensible, customized, and lightweight, serving as a personal AI assistant.

PearAI Landing Page is an open-source AI-powered code editor managed by Nang and Pan. It is built with Next.js, Vercel, Tailwind CSS, and TypeScript. The project requires setting up environment variables for proper configuration. Users can run the project locally by starting the development server and visiting the specified URL in the browser. Recommended extensions include Prettier, ESLint, and JavaScript and TypeScript Nightly. Contributions to the project are welcomed and appreciated.

AI Context is a CLI tool that generates AI-friendly markdown files from GitHub repos, local code, YouTube videos, or webpages. It supports processing local directories, GitHub repositories, YouTube transcripts, and webpages, converting them to markdown format. The tool simplifies interactions with LLMs like ChatGPT and Claude by providing a text-first context creation approach. It offers features for installation, usage, and acknowledgments, with options to process single paths, URLs, or lists of paths concurrently.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

Trieve is an advanced relevance API for hybrid search, recommendations, and RAG. It offers a range of features including self-hosting, semantic dense vector search, typo tolerant full-text/neural search, sub-sentence highlighting, recommendations, convenient RAG API routes, the ability to bring your own models, hybrid search with cross-encoder re-ranking, recency biasing, tunable popularity-based ranking, filtering, duplicate detection, and grouping. Trieve is designed to be flexible and customizable, allowing users to tailor it to their specific needs. It is also easy to use, with a simple API and well-documented features.

NoLabs is an open-source biolab that provides easy access to state-of-the-art models for bio research. It supports various tasks, including drug discovery, protein analysis, and small molecule design. NoLabs aims to accelerate bio research by making inference models accessible to everyone.

Scalene is a high-performance CPU, GPU, and memory profiler for Python that provides detailed information and runs faster than many other profilers. It incorporates AI-powered proposed optimizations, allowing users to generate optimization suggestions by clicking on specific lines or regions of code. Scalene separates time spent in Python from native code, highlights hotspots, and identifies memory usage per line. It supports GPU profiling on NVIDIA-based systems and detects memory leaks. Users can generate reduced profiles, profile specific functions using decorators, and suspend/resume profiling for background processes. Scalene is available as a pip or conda package and works on various platforms. It offers features like profiling at the line level, memory trends, copy volume reporting, and leak detection.

BentoML is an open-source model serving library for building performant and scalable AI applications with Python. It comes with everything you need for serving optimization, model packaging, and production deployment.

RainbowGPT is a versatile tool that offers a range of functionalities, including Stock Analysis for financial decision-making, MySQL Management for database navigation, and integration of AI technologies like GPT-4 and ChatGlm3. It provides a user-friendly interface suitable for all skill levels, ensuring seamless information flow and continuous expansion of emerging technologies. The tool enhances adaptability, creativity, and insight, making it a valuable asset for various projects and tasks.

Open Computer Use is a secure cloud Linux computer powered by E2B Desktop Sandbox and controlled by open-source LLMs. It allows users to operate the computer via keyboard, mouse, and shell commands, live stream the display of the sandbox on the client computer, and pause or prompt the agent at any time. The tool is designed to work with any operating system and supports integration with various LLMs and providers following the OpenAI API specification.

The LLM-Aided OCR Project is an advanced system that enhances Optical Character Recognition (OCR) output by leveraging natural language processing techniques and large language models. It offers features like PDF to image conversion, OCR using Tesseract, error correction using LLMs, smart text chunking, markdown formatting, duplicate content removal, quality assessment, support for local and cloud-based LLMs, asynchronous processing, detailed logging, and GPU acceleration. The project provides detailed technical overview, text processing pipeline, LLM integration, token management, quality assessment, logging, configuration, and customization. It requires Python 3.12+, Tesseract OCR engine, PDF2Image library, PyTesseract, and optional OpenAI or Anthropic API support for cloud-based LLMs. The installation process involves setting up the project, installing dependencies, and configuring environment variables. Users can place a PDF file in the project directory, update input file path, and run the script to generate post-processed text. The project optimizes processing with concurrent processing, context preservation, and adaptive token management. Configuration settings include choosing between local or API-based LLMs, selecting API provider, specifying models, and setting context size for local LLMs. Output files include raw OCR output and LLM-corrected text. Limitations include performance dependency on LLM quality and time-consuming processing for large documents.

Lihil is a performant, productive, and professional web framework designed to make Python the mainstream programming language for web development. It is 100% test covered and strictly typed, offering fast performance, ergonomic API, and built-in solutions for common problems. Lihil is suitable for enterprise web development, delivering robust and scalable solutions with best practices in microservice architecture and related patterns. It features dependency injection, OpenAPI docs generation, error response generation, data validation, message system, testability, and strong support for AI features. Lihil is ASGI compatible and uses starlette as its ASGI toolkit, ensuring compatibility with starlette classes and middlewares. The framework follows semantic versioning and has a roadmap for future enhancements and features.

An LLM-powered code generation tool that relies on the built-in Node.js API Typescript Template Project to easily generate clean, well-structured CRUD module code from text description. It orchestrates 3 LLM micro-agents (`Developer`, `Troubleshooter` and `TestsFixer`) to generate code, fix compilation errors, and ensure passing E2E tests. The process includes module code generation, DB migration creation, seeding data, and running tests to validate output. By cycling through these steps, it guarantees consistent and production-ready CRUD code aligned with vertical slicing architecture.

ChatDBG is an AI-based debugging assistant for C/C++/Python/Rust code that integrates large language models into a standard debugger (`pdb`, `lldb`, `gdb`, and `windbg`) to help debug your code. With ChatDBG, you can engage in a dialog with your debugger, asking open-ended questions about your program, like `why is x null?`. ChatDBG will _take the wheel_ and steer the debugger to answer your queries. ChatDBG can provide error diagnoses and suggest fixes. As far as we are aware, ChatDBG is the _first_ debugger to automatically perform root cause analysis and to provide suggested fixes.

Dravid (DRD) is an advanced, AI-powered CLI coding framework designed to follow user instructions until the job is completed, including fixing errors. It can generate code, fix errors, handle image queries, manage file operations, integrate with external APIs, and provide a development server with error handling. Dravid is extensible and requires Python 3.7+ and CLAUDE_API_KEY. Users can interact with Dravid through CLI commands for various tasks like creating projects, asking questions, generating content, handling metadata, and file-specific queries. It supports use cases like Next.js project development, working with existing projects, exploring new languages, Ruby on Rails project development, and Python project development. Dravid's project structure includes directories for source code, CLI modules, API interaction, utility functions, AI prompt templates, metadata management, and tests. Contributions are welcome, and development setup involves cloning the repository, installing dependencies with Poetry, setting up environment variables, and using Dravid for project enhancements.

AiR is an AI tool built entirely in Rust that delivers blazing speed and efficiency. It features accurate translation and seamless text rewriting to supercharge productivity. AiR is designed to assist non-native speakers by automatically fixing errors and polishing language to sound like a native speaker. The tool is under heavy development with more features on the horizon.

Thread is an AI-powered Jupyter alternative that integrates an AI copilot into your editing experience. It offers a familiar Jupyter Notebook editing experience with features like natural language code edits, generating cells to answer questions, context-aware chat sidebar, and automatic error explanations or fixes. The tool aims to enhance code editing and data exploration by providing a more interactive and intuitive experience for users. Thread can be used for free with Ollama or your own API key, and it runs locally for convenience and privacy.

ChatGPT-Arcana is an Emacs package that allows users to interact with ChatGPT directly from Emacs, enabling tasks such as chatting with GPT, operating on code or text, generating eshell commands from natural language, fixing errors, writing commit messages, and creating agents for web search and code evaluation. The package requires an API key from OpenAI's GPT-3 model and offers various interactive functions for enhancing productivity within Emacs.

Aide is an Open Source AI-native code editor that combines the powerful features of VS Code with advanced AI capabilities. It provides a combined chat + edit flow, proactive agents for fixing errors, inline editing widget, intelligent code completion, and AST navigation. Aide is designed to be an intelligent coding companion, helping users write better code faster while maintaining control over the development process.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Resonance is a framework designed to facilitate interoperability and messaging between services in your infrastructure and beyond. It provides AI capabilities and takes full advantage of asynchronous PHP, built on top of Swoole. With Resonance, you can: * Chat with Open-Source LLMs: Create prompt controllers to directly answer user's prompts. LLM takes care of determining user's intention, so you can focus on taking appropriate action. * Asynchronous Where it Matters: Respond asynchronously to incoming RPC or WebSocket messages (or both combined) with little overhead. You can set up all the asynchronous features using attributes. No elaborate configuration is needed. * Simple Things Remain Simple: Writing HTTP controllers is similar to how it's done in the synchronous code. Controllers have new exciting features that take advantage of the asynchronous environment. * Consistency is Key: You can keep the same approach to writing software no matter the size of your project. There are no growing central configuration files or service dependencies registries. Every relation between code modules is local to those modules. * Promises in PHP: Resonance provides a partial implementation of Promise/A+ spec to handle various asynchronous tasks. * GraphQL Out of the Box: You can build elaborate GraphQL schemas by using just the PHP attributes. Resonance takes care of reusing SQL queries and optimizing the resources' usage. All fields can be resolved asynchronously.

Aiogram bot template is a boilerplate for creating Telegram bots using Aiogram framework. It provides a solid foundation for building robust and scalable bots with a focus on code organization, database integration, and localization.

Pluto is a development tool dedicated to helping developers **build cloud and AI applications more conveniently** , resolving issues such as the challenging deployment of AI applications and open-source models. Developers are able to write applications in familiar programming languages like **Python and TypeScript** , **directly defining and utilizing the cloud resources necessary for the application within their code base** , such as AWS SageMaker, DynamoDB, and more. Pluto automatically deduces the infrastructure resource needs of the app through **static program analysis** and proceeds to create these resources on the specified cloud platform, **simplifying the resources creation and application deployment process**.

The official Node.js client for Pinecone, written in TypeScript. This client library provides a high-level interface for interacting with the Pinecone vector database service. With this client, you can create and manage indexes, upsert and query vector data, and perform other operations related to vector search and retrieval. The client is designed to be easy to use and provides a consistent and idiomatic experience for Node.js developers. It supports all the features and functionality of the Pinecone API, making it a comprehensive solution for building vector-powered applications in Node.js.

Aiohttp pydantic is an aiohttp view to easily parse and validate requests. You define using function annotations what your methods for handling HTTP verbs expect, and Aiohttp pydantic parses the HTTP request for you, validates the data, and injects the parameters you want. It provides features like query string, request body, URL path, and HTTP headers validation, as well as Open API Specification generation.

This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.

aioconsole is a Python package that provides asynchronous console and interfaces for asyncio. It offers asynchronous equivalents to input, print, exec, and code.interact, an interactive loop running the asynchronous Python console, customization and running of command line interfaces using argparse, stream support to serve interfaces instead of using standard streams, and the apython script to access asyncio code at runtime without modifying the sources. The package requires Python version 3.8 or higher and can be installed from PyPI or GitHub. It allows users to run Python files or modules with a modified asyncio policy, replacing the default event loop with an interactive loop. aioconsole is useful for scenarios where users need to interact with asyncio code in a console environment.

aiosqlite is a Python library that provides a friendly, async interface to SQLite databases. It replicates the standard sqlite3 module but with async versions of all the standard connection and cursor methods, along with context managers for automatically closing connections and cursors. It allows interaction with SQLite databases on the main AsyncIO event loop without blocking execution of other coroutines while waiting for queries or data fetches. The library also replicates most of the advanced features of sqlite3, such as row factories and total changes tracking.