FFAIVideo

FFAIVideo is a lightweight node.js project that utilizes popular AI LLM to intelligently generate short videos. It supports multiple AI LLM models such as OpenAI, Moonshot, Azure, g4f, Google Gemini, etc. Users can input text to automatically synthesize exciting video content with subtitles, background music, and customizable settings. The project integrates Microsoft Edge's online text-to-speech service for voice options and uses Pexels website for video resources. Installation of FFmpeg is essential for smooth operation. Inspired by MoneyPrinterTurbo, MoneyPrinter, and MsEdgeTTS, FFAIVideo is designed for front-end developers with minimal dependencies and simple usage.

Knowledge Graph Builder App is a tool designed to convert PDF documents into a structured knowledge graph stored in Neo4j. It utilizes OpenAI's GPT/Diffbot LLM to extract nodes, relationships, and properties from PDF text content. Users can upload files from local machine or S3 bucket, choose LLM model, and create a knowledge graph. The app integrates with Neo4j for easy visualization and querying of extracted information.

SemanticFinder is a frontend-only live semantic search tool that calculates embeddings and cosine similarity client-side using transformers.js and SOTA embedding models from Huggingface. It allows users to search through large texts like books with pre-indexed examples, customize search parameters, and offers data privacy by keeping input text in the browser. The tool can be used for basic search tasks, analyzing texts for recurring themes, and has potential integrations with various applications like wikis, chat apps, and personal history search. It also provides options for building browser extensions and future ideas for further enhancements and integrations.

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.

TableLLM is a large language model designed for efficient tabular data manipulation tasks in real office scenarios. It can generate code solutions or direct text answers for tasks like insert, delete, update, query, merge, and chart operations on tables embedded in spreadsheets or documents. The model has been fine-tuned based on CodeLlama-7B and 13B, offering two scales: TableLLM-7B and TableLLM-13B. Evaluation results show its performance on benchmarks like WikiSQL, Spider, and self-created table operation benchmark. Users can use TableLLM for code and text generation tasks on tabular data.

**Description:** PromptFuzz is an automated tool that generates high-quality fuzz drivers for libraries via a fuzz loop constructed on mutating LLMs' prompts. The fuzz loop of PromptFuzz aims to guide the mutation of LLMs' prompts to generate programs that cover more reachable code and explore complex API interrelationships, which are effective for fuzzing. **Features:** * **Multiply LLM support** : Supports the general LLMs: Codex, Inocder, ChatGPT, and GPT4 (Currently tested on ChatGPT). * **Context-based Prompt** : Construct LLM prompts with the automatically extracted library context. * **Powerful Sanitization** : The program's syntax, semantics, behavior, and coverage are thoroughly analyzed to sanitize the problematic programs. * **Prioritized Mutation** : Prioritizes mutating the library API combinations within LLM's prompts to explore complex interrelationships, guided by code coverage. * **Fuzz Driver Exploitation** : Infers API constraints using statistics and extends fixed API arguments to receive random bytes from fuzzers. * **Fuzz engine integration** : Integrates with grey-box fuzz engine: LibFuzzer. **Benefits:** * **High branch coverage:** The fuzz drivers generated by PromptFuzz achieved a branch coverage of 40.12% on the tested libraries, which is 1.61x greater than _OSS-Fuzz_ and 1.67x greater than _Hopper_. * **Bug detection:** PromptFuzz detected 33 valid security bugs from 49 unique crashes. * **Wide range of bugs:** The fuzz drivers generated by PromptFuzz can detect a wide range of bugs, most of which are security bugs. * **Unique bugs:** PromptFuzz detects uniquely interesting bugs that other fuzzers may miss. **Usage:** 1. Build the library using the provided build scripts. 2. Export the LLM API KEY if using ChatGPT or GPT4. 3. Generate fuzz drivers using the `fuzzer` command. 4. Run the fuzz drivers using the `harness` command. 5. Deduplicate and analyze the reported crashes. **Future Works:** * **Custom LLMs suport:** Support custom LLMs. * **Close-source libraries:** Apply PromptFuzz to close-source libraries by fine tuning LLMs on private code corpus. * **Performance** : Reduce the huge time cost required in erroneous program elimination.

last_layer is a security library designed to protect LLM applications from prompt injection attacks, jailbreaks, and exploits. It acts as a robust filtering layer to scrutinize prompts before they are processed by LLMs, ensuring that only safe and appropriate content is allowed through. The tool offers ultra-fast scanning with low latency, privacy-focused operation without tracking or network calls, compatibility with serverless platforms, advanced threat detection mechanisms, and regular updates to adapt to evolving security challenges. It significantly reduces the risk of prompt-based attacks and exploits but cannot guarantee complete protection against all possible threats.

Cambrian-1 is a fully open project focused on exploring multimodal Large Language Models (LLMs) with a vision-centric approach. It offers competitive performance across various benchmarks with models at different parameter levels. The project includes training configurations, model weights, instruction tuning data, and evaluation details. Users can interact with Cambrian-1 through a Gradio web interface for inference. The project is inspired by LLaVA and incorporates contributions from Vicuna, LLaMA, and Yi. Cambrian-1 is licensed under Apache 2.0 and utilizes datasets and checkpoints subject to their respective original licenses.

CrewAI quickstart is a small project providing starter templates for an easy start with CrewAI. It includes notebooks, Python scripts, GUI with Streamlit, and Local LLMs for various tasks like web search, CSV lookup, web scraping, PDF search, and more. Contributions are welcome to enhance the project.

This project is a c++ version of the AI reasoning library that supports the reasoning of tensorrt models. It provides accelerated deployment cases of deep learning CV popular models and supports dynamic-batch image processing, inference, decode, and NMS. The project has been updated with various models and provides tutorials for model exports. It also includes a producer-consumer inference model for specific tasks. The project directory includes implementations for model inference applications, backend reasoning classes, post-processing, pre-processing, and target detection and tracking. Speed tests have been conducted on various models, and onnx downloads are available for different models.

This solution showcases how to summarize a large corpus of documents using Generative AI. It provides an end-to-end demonstration of document summarization going all the way from raw documents, detecting text in the documents and summarizing the documents on-demand using Vertex AI LLM APIs, Cloud Vision Optical Character Recognition (OCR) and BigQuery.

Dataflow-oriented robotic application (dora-rs) is a framework that makes creation of robotic applications fast and simple. Building a robotic application can be summed up as bringing together hardwares, algorithms, and AI models, and make them communicate with each others. At dora-rs, we try to: make integration of hardware and software easy by supporting Python, C, C++, and also ROS2. make communication low latency by using zero-copy Arrow messages. dora-rs is still experimental and you might experience bugs, but we're working very hard to make it stable as possible.

SimpleAICV_pytorch_training_examples is a repository that provides simple training and testing examples for various computer vision tasks such as image classification, object detection, semantic segmentation, instance segmentation, knowledge distillation, contrastive learning, masked image modeling, OCR text detection, OCR text recognition, human matting, salient object detection, interactive segmentation, image inpainting, and diffusion model tasks. The repository includes support for multiple datasets and networks, along with instructions on how to prepare datasets, train and test models, and use gradio demos. It also offers pretrained models and experiment records for download from huggingface or Baidu-Netdisk. The repository requires specific environments and package installations to run effectively.

AIP Community Registry is a collection of community-built applications and projects leveraging Palantir's AIP Platform. It showcases real-world implementations from developers using AIP in production. The registry features various solutions demonstrating practical implementations and integration patterns across different use cases.

Langtrace is an open source observability software that lets you capture, debug, and analyze traces and metrics from all your applications that leverage LLM APIs, Vector Databases, and LLM-based Frameworks. It supports Open Telemetry Standards (OTEL), and the traces generated adhere to these standards. Langtrace offers both a managed SaaS version (Langtrace Cloud) and a self-hosted option. The SDKs for both Typescript/Javascript and Python are available, making it easy to integrate Langtrace into your applications. Langtrace automatically captures traces from various vendors, including OpenAI, Anthropic, Azure OpenAI, Langchain, LlamaIndex, Pinecone, and ChromaDB.

The Portkey Python SDK is a control panel for AI apps that allows seamless integration of Portkey's advanced features with OpenAI methods. It provides features such as AI gateway for unified API signature, interoperability, automated fallbacks & retries, load balancing, semantic caching, virtual keys, request timeouts, observability with logging, requests tracing, custom metadata, feedback collection, and analytics. Users can make requests to OpenAI using Portkey SDK and also use async functionality. The SDK is compatible with OpenAI SDK methods and offers Portkey-specific methods like feedback and prompts. It supports various providers and encourages contributions through Github issues or direct contact via email or Discord.

FFAIVideo is a lightweight node.js project that utilizes popular AI LLM to intelligently generate short videos. It supports multiple AI LLM models such as OpenAI, Moonshot, Azure, g4f, Google Gemini, etc. Users can input text to automatically synthesize exciting video content with subtitles, background music, and customizable settings. The project integrates Microsoft Edge's online text-to-speech service for voice options and uses Pexels website for video resources. Installation of FFmpeg is essential for smooth operation. Inspired by MoneyPrinterTurbo, MoneyPrinter, and MsEdgeTTS, FFAIVideo is designed for front-end developers with minimal dependencies and simple usage.

InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.

Open-Sora-Plan is a project that aims to create a simple and scalable repo to reproduce Sora (OpenAI, but we prefer to call it "ClosedAI"). The project is still in its early stages, but the team is working hard to improve it and make it more accessible to the open-source community. The project is currently focused on training an unconditional model on a landscape dataset, but the team plans to expand the scope of the project in the future to include text2video experiments, training on video2text datasets, and controlling the model with more conditions.

Comflowyspace is an open-source AI image and video generation tool that aims to provide a more user-friendly and accessible experience than existing tools like SDWebUI and ComfyUI. It simplifies the installation, usage, and workflow management of AI image and video generation, making it easier for users to create and explore AI-generated content. Comflowyspace offers features such as one-click installation, workflow management, multi-tab functionality, workflow templates, and an improved user interface. It also provides tutorials and documentation to lower the learning curve for users. The tool is designed to make AI image and video generation more accessible and enjoyable for a wider range of users.

Rewind AI is a free and open-source AI-powered video editing tool that allows users to easily create and edit videos. It features a user-friendly interface, a wide range of editing tools, and support for a variety of video formats. Rewind AI is perfect for beginners and experienced video editors alike.

MoneyPrinterTurbo is a tool that can automatically generate video content based on a provided theme or keyword. It can create video scripts, materials, subtitles, and background music, and then compile them into a high-definition short video. The tool features a web interface and an API interface, supporting AI-generated video scripts, customizable scripts, multiple HD video sizes, batch video generation, customizable video segment duration, multilingual video scripts, multiple voice synthesis options, subtitle generation with font customization, background music selection, access to high-definition and copyright-free video materials, and integration with various AI models like OpenAI, moonshot, Azure, and more. The tool aims to simplify the video creation process and offers future plans to enhance voice synthesis, add video transition effects, provide more video material sources, offer video length options, include free network proxies, enable real-time voice and music previews, support additional voice synthesis services, and facilitate automatic uploads to YouTube platform.

Dough is a tool for crafting videos with AI, allowing users to guide video generations with precision using images and example videos. Users can create guidance frames, assemble shots, and animate them by defining parameters and selecting guidance videos. The tool aims to help users make beautiful and unique video creations, providing control over the generation process. Setup instructions are available for Linux and Windows platforms, with detailed steps for installation and running the app.

Ragdoll Studio is a platform offering web apps and libraries for interacting with Ragdoll, enabling users to go beyond fine-tuning and create flawless creative deliverables, rich multimedia, and engaging experiences. It provides various modes such as Story Mode for creating and chatting with characters, Vector Mode for producing vector art, Raster Mode for producing raster art, Video Mode for producing videos, Audio Mode for producing audio, and 3D Mode for producing 3D objects. Users can export their content in various formats and share their creations on the community site. The platform consists of a Ragdoll API and a front-end React application for seamless usage.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

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.

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.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.