This repository provides a template for easy asynchronous bot development for Telegram using Aiogram library. It includes setup instructions using Docker Compose, migration commands for TortoiseORM, and examples for working with TortoiseORM. The template aims to simplify the process of creating Telegram bots with features like FastAPI integration and Docker Compose setup. The repository also includes a list of tasks to be completed, such as changing SQLAlchemy to TortoiseORM, adding FastAPI for webhook, and setting up CI/CD examples.

EmotiVoice is a powerful and modern open-source text-to-speech engine that supports emotional synthesis, enabling users to create speech with a wide range of emotions such as happy, excited, sad, and angry. It offers over 2000 different voices in both English and Chinese. Users can access EmotiVoice through an easy-to-use web interface or a scripting interface for batch generation of results. The tool is continuously evolving with new features and updates, prioritizing community input and user feedback.

Eidos is an extensible framework for managing personal data in one place. It runs inside the browser as a PWA with offline support. It integrates AI features for translation, summarization, and data interaction. Users can customize Eidos with Prompt extension, JavaScript for Formula functions, TypeScript/JavaScript for data processing logic, and build apps using any framework. Eidos is developer-friendly with API & SDK, and uses SQLite standardization for data tables.

The stability-sdk is a Python package that provides a client implementation for interacting with the Stability API. This API allows users to generate images, upscale images, and animate images using a variety of different models and settings. The stability-sdk makes it easy to use the Stability API from Python code, and it provides a number of helpful features such as command line usage, support for multiple models, and the ability to filter artifacts by type.

ChatterUI is a mobile app that allows users to manage chat files and character cards, and to interact with Large Language Models (LLMs). It supports multiple backends, including local, koboldcpp, text-generation-webui, Generic Text Completions, AI Horde, Mancer, Open Router, and OpenAI. ChatterUI provides a mobile-friendly interface for interacting with LLMs, making it easy to use them for a variety of tasks, such as generating text, translating languages, writing code, and answering questions.

LangPort is an open-source platform for serving large language models. It aims to provide a super fast LLM inference service with core features including Huggingface transformers support, distributed serving system, streaming generation, batch inference, and support for various model architectures. It offers compatibility with OpenAI, FauxPilot, HuggingFace, and Tabby APIs. The project supports model architectures like LLaMa, GLM, GPT2, and GPT Neo, and has been tested with models such as NingYu, Vicuna, ChatGLM, and WizardLM. LangPort also provides features like dynamic batch inference, int4 quantization, and generation logprobs parameter.

PySpur is a graph-based editor designed for LLM workflows, offering modular building blocks for easy workflow creation and debugging at node level. It allows users to evaluate final performance and promises self-improvement features in the future. PySpur is easy-to-hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies, making it a versatile tool for workflow management in the field of AI and machine learning.

DemoGPT is an all-in-one agent library that provides tools, prompts, frameworks, and LLM models for streamlined agent development. It leverages GPT-3.5-turbo to generate LangChain code, creating interactive Streamlit applications. The tool is designed for creating intelligent, interactive, and inclusive solutions in LLM-based application development. It offers model flexibility, iterative development, and a commitment to user engagement. Future enhancements include integrating Gorilla for autonomous API usage and adding a publicly available database for refining the generation process.

KIVI is a plug-and-play 2bit KV cache quantization algorithm optimizing memory usage by quantizing key cache per-channel and value cache per-token to 2bit. It enables LLMs to maintain quality while reducing memory usage, allowing larger batch sizes and increasing throughput in real LLM inference workloads.

Holmes-VAD is a framework for unbiased and explainable Video Anomaly Detection using multimodal instructions. It addresses biased detection in challenging events by leveraging precise temporal supervision and rich multimodal instructions. The framework includes a largescale VAD instruction-tuning benchmark, VAD-Instruct50k, created with single-frame annotations and a robust video captioner. It offers accurate anomaly localization and comprehensive explanations through a customized solution for interpretable video anomaly detection.

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.

Instructor is a tool designed to structure outputs from OpenAI and other OSS LLMs by coaxing them to return JSON that maps to a provided Ecto schema. It allows for defining validation logic to guide LLMs in making corrections, and supports automatic retries. Instructor is primarily used with the OpenAI API but can be extended to work with other platforms. The tool simplifies usage by creating an ecto schema, defining a validation function, and making calls to chat_completion with instructions for the LLM. It also offers features like max_retries to fix validation errors iteratively.

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.

eShopSupport is a sample .NET application showcasing common use cases and development practices for building AI solutions in .NET, specifically Generative AI. It demonstrates a customer support application for an e-commerce website using a services-based architecture with .NET Aspire. The application includes support for text classification, sentiment analysis, text summarization, synthetic data generation, and chat bot interactions. It also showcases development practices such as developing solutions locally, evaluating AI responses, leveraging Python projects, and deploying applications to the Cloud.

ComfyUI-IF_AI_tools is a set of custom nodes for ComfyUI that allows you to generate prompts using a local Large Language Model (LLM) via Ollama. This tool enables you to enhance your image generation workflow by leveraging the power of language models.

This repository contains the code for HOLD, a method that jointly reconstructs hands and objects from monocular videos without assuming a pre-scanned object template. It can reconstruct 3D geometries of novel objects and hands, enabling template-free bimanual hand-object reconstruction, textureless object interaction with hands, and multiple objects interaction with hands. The repository provides instructions to download in-the-wild videos from HOLD, preprocess and train on custom videos, a volumetric rendering framework, a generalized codebase for single and two hand interaction with objects, a viewer to interact with predictions, and code to evaluate and compare with HOLD in HO3D. The repository also includes documentation for setup, training, evaluation, visualization, preprocessing custom sequences, and using HOLD on ARCTIC.

This repository provides a template for easy asynchronous bot development for Telegram using Aiogram library. It includes setup instructions using Docker Compose, migration commands for TortoiseORM, and examples for working with TortoiseORM. The template aims to simplify the process of creating Telegram bots with features like FastAPI integration and Docker Compose setup. The repository also includes a list of tasks to be completed, such as changing SQLAlchemy to TortoiseORM, adding FastAPI for webhook, and setting up CI/CD examples.

This repository provides a template for easy asynchronous bot development for Telegram using Aiogram library. It includes setup instructions using Docker Compose, migration commands for TortoiseORM, and examples for working with TortoiseORM. The template aims to simplify the process of creating Telegram bots with features like FastAPI integration and Docker Compose setup. The repository also includes a list of tasks to be completed, such as changing SQLAlchemy to TortoiseORM, adding FastAPI for webhook, and setting up CI/CD examples.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

XLICON-V2-MD is a versatile Multi-Device WhatsApp bot developed by Salman Ahamed. It offers a wide range of features, making it an advanced and user-friendly bot for various purposes. The bot supports multi-device operation, AI photo enhancement, downloader commands, hidden NSFW commands, logo generation, anime exploration, economic activities, games, and audio/video editing. Users can deploy the bot on platforms like Heroku, Replit, Codespace, Okteto, Railway, Mongenius, Coolify, and Render. The bot is maintained by Salman Ahamed and Abraham Dwamena, with contributions from various developers and testers. Misusing the bot may result in a ban from WhatsApp, so users are advised to use it at their own risk.

Tock is an open conversational AI platform for building bots. It offers a natural language processing open source stack compatible with various tools, a user interface for building stories and analytics, a conversational DSL for different programming languages, built-in connectors for text/voice channels, toolkits for custom web/mobile integration, and the ability to deploy anywhere in the cloud or on-premise with Docker.

aiogram is a modern and fully asynchronous framework for Telegram Bot API written in Python 3.8+ using asyncio and aiohttp. It helps users create faster and more powerful bots. The framework supports features such as asynchronous operations, type hints, PyPy support, Telegram Bot API integration, router updates, Finite State Machine, magic filters, middlewares, webhook replies, and I18n/L10n support with GNU Gettext or Fluent. Prior experience with asyncio is recommended before using aiogram.

A Telegram LLM bot that allows users to deploy their own Telegram bot in 3 simple steps by creating a flow function, configuring access to the Telegram bot, and connecting to an LLM backend. Users need to sign into flows.network, have a bot token from Telegram, and an OpenAI API key. The bot can be customized with ChatGPT prompts and integrated with OpenAI and Telegram for various functionalities.

The ChatBotKit Node SDK is a JavaScript-based platform for building conversational AI bots and agents. It offers easy setup, serverless compatibility, modern framework support, customizability, and multi-platform deployment. With capabilities like multi-modal and multi-language support, conversation management, chat history review, custom datasets, and various integrations, this SDK enables users to create advanced chatbots for websites, mobile apps, and messaging platforms.

This repository contains a Telegram bot built with Golang that integrates with DeepSeek API to provide AI-powered responses. The bot supports streaming replies, making interactions feel more natural and dynamic. It offers features like AI responses, streaming output, command handling, and easy deployment. Users can configure the bot via environment variables for customization. The bot can be deployed locally or on a cloud server, and it supports custom commands and real-time responses.