Cookiecutter-fastapi is a CLI tool for creating FastAPI projects. It allows users to generate application boilerplate from a template using Jinja2 templating system. Users can easily install the tool with 'pip install cookiecutter' and generate a FastAPI project by running 'cookiecutter gh:arthurhenrique/cookiecutter-fastapi'. The tool simplifies the process of setting up FastAPI projects by automating the creation of folder structures and file contents.

Album AI is an experimental project that uses GPT-4o-mini to automatically identify metadata from image files in the album. It leverages RAG technology to enable conversations with the album, serving as a photo album or image knowledge base to assist in content generation. The tool provides APIs for search and chat functionalities, supports one-click deployment to platforms like Render, and allows for integration and modification under a permissive open-source license.

Library for connecting AI agents to Todoist, enabling them to access and modify a Todoist account on the user's behalf. Tools can be used through an MCP server or integrated into other projects for AI conversational interfaces. Reusable tools allow for complete workflows, balancing flexibility and efficiency for LLMs. Early-stage project with more tools planned. Designed to provide a small set of tools for various AI interfaces.

Hashbrown is a lightweight and efficient hashing library for Python, designed to provide easy-to-use cryptographic hashing functions for secure data storage and transmission. It supports a variety of hashing algorithms, including MD5, SHA-1, SHA-256, and SHA-512, allowing users to generate hash values for strings, files, and other data types. With Hashbrown, developers can quickly implement data integrity checks, password hashing, digital signatures, and other security features in their Python applications.

This repository contains a Rest-Backend for a Conversational Agent that allows embedding documents, semantic search, QA based on documents, and document processing with Large Language Models. It uses Aleph Alpha and OpenAI Large Language Models to generate responses to user queries, includes a vector database, and provides a REST API built with FastAPI. The project also features semantic search, secret management for API keys, installation instructions, and development guidelines for both backend and frontend components.

Dione is a tool that simplifies the installation of complex applications by providing a user-friendly interface for users. It also offers developers a seamless way to distribute apps using a JSON file. With Dione, app installation becomes effortless, eliminating the need for technical knowledge or command-line usage.

This repository provides AI tools for developers through Docker containers, enabling agentic workflows. It allows users to create complex workflows using Dockerized tools and Markdown, leveraging various LLM models. The core features include Dockerized tools, conversation loops, multi-model agents, project-first design, and trackable prompts stored in a git repo.

This project enables users to create story videos by inputting a story theme, utilizing a large language model to generate AI-generated images, story content, audio, and subtitles. The backend is built with Python and FastAPI, while the frontend utilizes React, Ant Design, and Vite.

sitefetch is a tool designed to fetch an entire website and save it as a text file, primarily intended for use with AI models. It provides a simple and efficient way to download website content for further analysis or processing. The tool supports fetching multiple pages concurrently and offers both one-off and global installation options for ease of use.

Discover the journey of building a generative AI application using LangChain.js and Azure. This demo explores the development process from idea to production, using a RAG-based approach for a Q&A system based on YouTube video transcripts. The application allows to ask text-based questions about a YouTube video and uses the transcript of the video to generate responses. The code comes in two versions: local prototype using FAISS and Ollama with LLaMa3 model for completion and all-minilm-l6-v2 for embeddings, and Azure cloud version using Azure AI Search and GPT-4 Turbo model for completion and text-embedding-3-large for embeddings. Either version can be run as an API using the Azure Functions runtime.

Decipher is a tool that utilizes AI-generated transcription subtitles to automatically add subtitles to videos. It eliminates the need for manual transcription, making videos more accessible. The tool uses OpenAI's Whisper, a State-of-the-Art speech recognition system trained on a large dataset for improved robustness to accents, background noise, and technical language.

VectorVein is a no-code AI workflow software inspired by LangChain and langflow, aiming to combine the powerful capabilities of large language models and enable users to achieve intelligent and automated daily workflows through simple drag-and-drop actions. Users can create powerful workflows without the need for programming, automating all tasks with ease. The software allows users to define inputs, outputs, and processing methods to create customized workflow processes for various tasks such as translation, mind mapping, summarizing web articles, and automatic categorization of customer reviews.

BlinkID SDK wrapper for React Native provides best-in-class ID scanning software for cross-platform apps built with React Native. It offers complete guidance on installing and linking BlinkID library with iOS and Android apps. The SDK requires a valid license key for scanning, with offline data extraction. It supports React Native v0.71.2 and includes installation and linking instructions for iOS and Android. The repository also contains a script to create a sample React Native project and dependencies. Video tutorials demonstrate using documentVerificationOverlay and CombinedRecognizer for scanning various document types.

Build your dream team with Autogen is a repository that leverages Microsoft Autogen 0.4, Azure OpenAI, and Streamlit to create an end-to-end multi-agent application. It provides an advanced multi-agent framework based on Magentic One, with features such as a friendly UI, single-line deployment, secure code execution, managed identities, and observability & debugging tools. Users can deploy Azure resources and the app with simple commands, work locally with virtual environments, install dependencies, update configurations, and run the application. The repository also offers resources for learning more about building applications with Autogen.

The devdocs-to-llm repository is a work-in-progress tool that aims to convert documentation from DevDocs format to Long Language Model (LLM) format. This tool is designed to streamline the process of converting documentation for use with LLMs, making it easier for developers to leverage large language models for various tasks. By automating the conversion process, developers can quickly adapt DevDocs content for training and fine-tuning LLMs, enabling them to create more accurate and contextually relevant language models.

Mastra is an opinionated Typescript framework designed to help users quickly build AI applications and features. It provides primitives such as workflows, agents, RAG, integrations, syncs, and evals. Users can run Mastra locally or deploy it to a serverless cloud. The framework supports various LLM providers, offers tools for building language models, workflows, and accessing knowledge bases. It includes features like durable graph-based state machines, retrieval-augmented generation, integrations, syncs, and automated tests for evaluating LLM outputs.

Cookiecutter-fastapi is a CLI tool for creating FastAPI projects. It allows users to generate application boilerplate from a template using Jinja2 templating system. Users can easily install the tool with 'pip install cookiecutter' and generate a FastAPI project by running 'cookiecutter gh:arthurhenrique/cookiecutter-fastapi'. The tool simplifies the process of setting up FastAPI projects by automating the creation of folder structures and file contents.

API Improvement Proposals (AIPs) are design documents that provide high-level, concise documentation for API development at Google. The goal of AIPs is to serve as the source of truth for API-related documentation and to facilitate discussion and consensus among API teams. AIPs are similar to Python's enhancement proposals (PEPs) and are organized into different areas within Google to accommodate historical differences in customs, styles, and guidance.

Kong, or Kong API Gateway, is a cloud-native, platform-agnostic, scalable API Gateway distinguished for its high performance and extensibility via plugins. It also provides advanced AI capabilities with multi-LLM support. By providing functionality for proxying, routing, load balancing, health checking, authentication (and more), Kong serves as the central layer for orchestrating microservices or conventional API traffic with ease. Kong runs natively on Kubernetes thanks to its official Kubernetes Ingress Controller.

Speakeasy is a tool that helps developers create production-quality SDKs, Terraform providers, documentation, and more from OpenAPI specifications. It supports a wide range of languages, including Go, Python, TypeScript, Java, and C#, and provides features such as automatic maintenance, type safety, and fault tolerance. Speakeasy also integrates with popular package managers like npm, PyPI, Maven, and Terraform Registry for easy distribution.

ApiCat is an API documentation management tool that is fully compatible with the OpenAPI specification. With ApiCat, you can freely and efficiently manage your APIs. It integrates the capabilities of LLM, which not only helps you automatically generate API documentation and data models but also creates corresponding test cases based on the API content. Using ApiCat, you can quickly accomplish anything outside of coding, allowing you to focus your energy on the code itself.

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.

Ain is a terminal HTTP API client designed for scripting input and processing output via pipes. It allows flexible organization of APIs using files and folders, supports shell-scripts and executables for common tasks, handles url-encoding, and enables sharing the resulting curl, wget, or httpie command-line. Users can put things that change in environment variables or .env-files, and pipe the API output for further processing. Ain targets users who work with many APIs using a simple file format and uses curl, wget, or httpie to make the actual calls.

OllamaKit is a Swift library designed to simplify interactions with the Ollama API. It handles network communication and data processing, offering an efficient interface for Swift applications to communicate with the Ollama API. The library is optimized for use within Ollamac, a macOS app for interacting with Ollama models.

Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.