Best AI tools for< Create Virtual Environment >

Immersim AI is an interactive platform that allows users to explore infinite worlds, scripts, scenarios, and characters. It serves as a creative partner, adapting and growing with the user's imagination. The platform offers immersive experiences that transcend physical boundaries, enabling users to connect and interact with others in virtual environments.

TryNectar is an AI application that allows users to create their perfect virtual companion, known as an AI girlfriend. With just a few clicks, users can customize their dream AI girlfriend to suit their preferences and interact with her in a virtual environment. The application leverages artificial intelligence to provide a personalized and engaging experience for users seeking companionship and emotional support.

Luma AI is a 3D capture platform that allows users to create interactive 3D scenes from videos. With Luma AI, users can capture 3D models of people, objects, and environments, and then use those models to create interactive experiences such as virtual tours, product demonstrations, and training simulations.

Chirper AI is an AI life simulation tool that allows users to create and interact with virtual characters in a simulated world. Users can customize their characters, engage in conversations, and explore various virtual environments. The tool aims to provide a creative and interactive platform for users to express themselves and connect with others through their virtual avatars.

AI.TOWN is an interactive platform where users can engage with various AI personalities, chat, interact, and create their own characters. The website offers a unique experience of connecting with AI neighbors, participating in conversations, and shaping the future of AI personalities through Discord. Users can explore different neighborhoods, meet diverse characters, and even role-play with AI entities. AI.TOWN provides a fun and engaging environment for users to interact with AI in a creative and entertaining way.

MagikKraft is an AI-powered platform that simplifies complex controls by enabling users to create personalized sequences and actions for programmable devices like drones, automated appliances, and self-driving vehicles. Users can craft, simulate, and deploy customized recipes through the AI-powered tool, enhancing the potential of technology while prioritizing privacy, user control, and creative freedom.

VoxCraft is a free 3D AI generator that allows users to create realistic 3D models using artificial intelligence technology. With VoxCraft, users can easily generate detailed 3D models without the need for advanced design skills or software. The application leverages AI algorithms to streamline the modeling process and produce high-quality results. Whether you are a beginner or an experienced designer, VoxCraft offers a user-friendly platform to bring your creative ideas to life in the world of 3D modeling.

CharacterGen is an advanced AI tool for efficient 3D character generation from single images. It utilizes cutting-edge multi-view pose calibration technology and deep learning algorithms to create detailed and realistic 3D models in seconds. The platform offers real-time processing, customizable outputs, and seamless integration capabilities, making it a valuable tool for professionals and beginners in gaming, animation, and virtual reality industries.

Fams.ai is an AI-powered platform that allows users to create, roleplay, and chat in a virtual environment. It leverages artificial intelligence to provide a unique and interactive experience for users to engage in storytelling, character development, and social interactions. With Fams.ai, users can immerse themselves in creative scenarios, collaborate with others, and explore their imagination through dynamic storytelling tools and features.

Spicy Chat AI is an innovative AI application that allows users to engage in uncensored adult-themed conversations with lifelike NSFW Character AI. Users can create virtual personas, enjoy uninhibited chats, and experience emotional depth in a safe and expressive environment. The platform prioritizes user privacy with SSL encryption and compliance with data protection standards. Spicy Chat AI offers both free and premium plans, supporting multiple languages and unique features like AI voice response and chat-based image generation.

AI Mock Interview is an AI-powered platform designed to help users practice and improve their interview skills. It offers realistic interview scenarios with advanced AI technology, providing instant personalized feedback and comprehensive reports to enhance performance. Users can benefit from the service by gaining confidence and improving their answers through the feedback received. The platform aims to assist individuals in preparing for real interviews by simulating the experience in a virtual environment.

Synthesis AI is a synthetic data platform that enables more capable and ethical computer vision AI. It provides on-demand labeled images and videos, photorealistic images, and 3D generative AI to help developers build better models faster. Synthesis AI's products include Synthesis Humans, which allows users to create detailed images and videos of digital humans with rich annotations; Synthesis Scenarios, which enables users to craft complex multi-human simulations across a variety of environments; and a range of applications for industries such as ID verification, automotive, avatar creation, virtual fashion, AI fitness, teleconferencing, visual effects, and security.

Refabric is an AI-powered design platform at the intersection of AI and fashion design. It offers innovative solutions for the fashion industry by leveraging advanced technologies such as machine learning and data analytics. Refabric helps fashion retailers achieve carbon neutrality, adhere to environmental standards, and transform the way fashion is designed, produced, and consumed. The platform provides trend forecasting, creative support, and sustainability solutions to address the evolving challenges in the global fashion industry.

Koko AI is an innovative AI tool that serves as a 3D playground for users of all ages. It offers a unique and interactive experience where users can create, explore, and interact with various 3D environments. With its user-friendly interface and advanced AI technology, Koko AI provides a platform for unleashing creativity and imagination in a fun and engaging way.

Seance AI is an innovative application that combines artificial intelligence (AI) technology with immersive storytelling to create a captivating and interactive experience centered around seances and the supernatural. It offers users a unique opportunity to engage with a simulated virtual environment where they can participate in fictionalized seances, communicate with fictional spirits, and explore the mysteries of the spirit world. The application allows users to create and share seances with loved ones using AI, providing a platform where AI meets the afterlife and love endures beyond the veil.

MagicSoul.ai is an AI-powered platform that allows users to chat with AI characters in a virtual environment. The platform leverages advanced natural language processing and machine learning algorithms to create engaging conversations with AI entities. Users can interact with a variety of AI characters, each with unique personalities and traits, providing an immersive and entertaining experience. MagicSoul.ai aims to push the boundaries of AI technology by offering a novel way for users to engage with artificial intelligence.

Sunset.ia is an AI tool that utilizes JavaScript to provide users with a unique experience. It offers a range of features and functionalities to enhance user interaction and engagement. The tool is designed to help users explore the concept of sunset through an AI-driven interface, enabling them to visualize and experience the beauty of sunsets in a virtual environment. Sunset.ia aims to create a seamless and immersive experience for users, allowing them to appreciate the natural beauty of sunsets in a digital space.

Blendbox and Skybox AI are AI applications that offer immersive art generation experiences. Blendbox allows users to create and control AI artwork with full control, while Skybox AI enables the creation of virtual reality environments and 3D world meshes. These applications provide users with innovative tools for artistic expression and creativity.

Artfully Inspiring AI Photos and Video is an AI-powered platform that allows users to create realistic, unique avatars for themselves. The platform offers a variety of different styles to choose from, so users can create an avatar that represents their ideal self. The avatars can be used in a variety of different contexts, such as social media, gaming, or even virtual reality environments.

Splash is an AI-powered platform that offers a unique and immersive experience for music creation and performance. Users can access a vast library of sound packs and beatmaker instruments to create music, perform live, and interact with fans in a virtual music festival environment. The platform utilizes proprietary AI technology for features like Text-to-Singing, Text-to-Rap, Generative Text-to-Music, Composition, Melody, Voice Transfer, Lyrics, and Mastering. Splash inspires endless creativity in a digital playground, catering to a new generation of creators.

FlowGen is a tool built for AutoGen, a great agent framework from Microsoft and a lot of contributors. It provides intuitive visual tools that streamline the construction and oversight of complex agent-based workflows, simplifying the process for creators and developers. Users can create Autoflows, chat with agents, and share flow templates. The tool is fully dockerized and supports deployment on Railway.app. Contributions to the project are welcome, and the platform uses semantic-release for versioning and releases.

Pipecat Flows is a framework designed for building structured conversations in AI applications. It allows users to create both predefined conversation paths and dynamically generated flows, handling state management and LLM interactions. The framework includes a Python module for building conversation flows and a visual editor for designing and exporting flow configurations. Pipecat Flows is suitable for scenarios such as customer service scripts, intake forms, personalized experiences, and complex decision trees.

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.

The Electronic Component Classifier is a project that uses machine learning and artificial intelligence to automate the identification and classification of electrical and electronic components. It features component classification into seven classes, user-friendly design, and integration with Flask for a user-friendly interface. The project aims to reduce human error in component identification, make the process safer and more reliable, and potentially help visually impaired individuals in identifying electronic components.

LangGraph Expense tracker is a small project that explores the possibilities of LangGraph. It allows users to send pictures of invoices, which are then structured and categorized into expenses and stored in a database. The project includes functionalities for invoice extraction, database setup, and API configuration. It consists of various modules for categorizing expenses, creating database tables, and running the API. The database schema includes tables for categories, payment methods, and expenses, each with specific columns to track transaction details. The API documentation is available for reference, and the project utilizes LangChain for processing expense data.

LLM-FuzzX is an open-source user-friendly fuzz testing tool for large language models (e.g., GPT, Claude, LLaMA), equipped with advanced task-aware mutation strategies, fine-grained evaluation, and jailbreak detection capabilities. It helps researchers and developers quickly discover potential security vulnerabilities and enhance model robustness. The tool features a user-friendly web interface for visual configuration and real-time monitoring, supports various advanced mutation methods, integrates RoBERTa model for real-time jailbreak detection and evaluation, supports multiple language models like GPT, Claude, LLaMA, provides visualization analysis with seed flowcharts and experiment data statistics, and offers detailed logging support for main, mutation, and jailbreak logs.

Aider Composer is a VSCode extension that integrates Aider into your development workflow. It allows users to easily add and remove files, toggle between read-only and editable modes, review code changes, use different chat modes, and reference files in the chat. The extension supports multiple models, code generation, code snippets, and settings customization. It has limitations such as lack of support for multiple workspaces, Git repository features, linting, testing, voice features, in-chat commands, and configuration options.

Solo Server is a lightweight server designed for managing hardware-aware inference. It provides seamless setup through a simple CLI and HTTP servers, an open model registry for pulling models from platforms like Ollama and Hugging Face, cross-platform compatibility for effortless deployment of AI models on hardware, and a configurable framework that auto-detects hardware components (CPU, GPU, RAM) and sets optimal configurations.

Well-Architected Infrastructure as Code (IaC) Analyzer is a project demonstrating how generative AI can evaluate infrastructure code for alignment with best practices. It features a modern web application allowing users to upload IaC documents, complete IaC projects, or architecture diagrams for assessment. The tool provides insights into infrastructure code alignment with AWS best practices, offers suggestions for improving cloud architecture designs, and can generate IaC templates from architecture diagrams. Users can analyze CloudFormation, Terraform, or AWS CDK templates, architecture diagrams in PNG or JPEG format, and complete IaC projects with supporting documents. Real-time analysis against Well-Architected best practices, integration with AWS Well-Architected Tool, and export of analysis results and recommendations are included.

LiteLLM is a tool that allows you to call all LLM APIs using the OpenAI format. This includes Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, and more. LiteLLM manages translating inputs to provider's `completion`, `embedding`, and `image_generation` endpoints, providing consistent output, and retry/fallback logic across multiple deployments. It also supports setting budgets and rate limits per project, api key, and model.

Sparrow is an innovative open-source solution for efficient data extraction and processing from various documents and images. It seamlessly handles forms, invoices, receipts, and other unstructured data sources. Sparrow stands out with its modular architecture, offering independent services and pipelines all optimized for robust performance. One of the critical functionalities of Sparrow - pluggable architecture. You can easily integrate and run data extraction pipelines using tools and frameworks like LlamaIndex, Haystack, or Unstructured. Sparrow enables local LLM data extraction pipelines through Ollama or Apple MLX. With Sparrow solution you get API, which helps to process and transform your data into structured output, ready to be integrated with custom workflows. Sparrow Agents - with Sparrow you can build independent LLM agents, and use API to invoke them from your system. **List of available agents:** * **llamaindex** - RAG pipeline with LlamaIndex for PDF processing * **vllamaindex** - RAG pipeline with LLamaIndex multimodal for image processing * **vprocessor** - RAG pipeline with OCR and LlamaIndex for image processing * **haystack** - RAG pipeline with Haystack for PDF processing * **fcall** - Function call pipeline * **unstructured-light** - RAG pipeline with Unstructured and LangChain, supports PDF and image processing * **unstructured** - RAG pipeline with Weaviate vector DB query, Unstructured and LangChain, supports PDF and image processing * **instructor** - RAG pipeline with Unstructured and Instructor libraries, supports PDF and image processing. Works great for JSON response generation

GPT Home is a project that allows users to build their own home assistant using Raspberry Pi and OpenAI API. It serves as a guide for setting up a smart home assistant similar to Google Nest Hub or Amazon Alexa. The project integrates various components like OpenAI, Spotify, Philips Hue, and OpenWeatherMap to provide a personalized home assistant experience. Users can follow the detailed instructions provided to build their own version of the home assistant on Raspberry Pi, with optional components for customization. The project also includes system configurations, dependencies installation, and setup scripts for easy deployment. Overall, GPT Home offers a DIY solution for creating a smart home assistant using Raspberry Pi and OpenAI technology.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=