The llmgateway repository is a tool that provides a gateway for interacting with various LLM (Large Language Model) models. It allows users to easily access and utilize pre-trained language models for tasks such as text generation, sentiment analysis, and language translation. The tool simplifies the process of integrating LLMs into applications and workflows, enabling developers to leverage the power of state-of-the-art language models for various natural language processing tasks.

Agent Squad is a flexible, lightweight open-source framework for orchestrating multiple AI agents to handle complex conversations. It intelligently routes queries, maintains context across interactions, and offers pre-built components for quick deployment. The system allows easy integration of custom agents and conversation messages storage solutions, making it suitable for various applications from simple chatbots to sophisticated AI systems, scaling efficiently.

Cerebr is an intelligent AI assistant browser extension designed to enhance work efficiency and learning experience. It integrates powerful AI capabilities from various sources to provide features such as smart sidebar, multiple API support, cross-browser API configuration synchronization, comprehensive Q&A support, elegant rendering, real-time response, theme switching, and more. With a minimalist design and focus on delivering a seamless, distraction-free browsing experience, Cerebr aims to be your second brain for deep reading and understanding.

Resume Job Matcher is a Python script that automates the process of matching resumes to a job description using AI. It leverages the Anthropic Claude API or OpenAI's GPT API to analyze resumes and provide a match score along with personalized email responses for candidates. The tool offers comprehensive resume processing, advanced AI-powered analysis, in-depth evaluation & scoring, comprehensive analytics & reporting, enhanced candidate profiling, and robust system management. Users can customize font presets, generate PDF versions of unified resumes, adjust logging level, change scoring model, modify AI provider, and adjust AI model. The final score for each resume is calculated based on AI-generated match score and resume quality score, ensuring content relevance and presentation quality are considered. Troubleshooting tips, best practices, contribution guidelines, and required Python packages are provided.

ctx is a tool designed to automatically generate organized context files from code files, GitHub repositories, Git commits, web pages, and plain text. It aims to efficiently provide necessary context to AI language models like ChatGPT and Claude, enabling users to streamline code refactoring, multiple iteration development, documentation generation, and seamless AI integration. With ctx, users can create structured markdown documents, save context files, and serve context through an MCP server for real-time assistance. The tool simplifies the process of sharing project information with AI assistants, making AI conversations smarter and easier.

MLDL.Study is a free interactive learning platform focused on simplifying Machine Learning (ML) and Deep Learning (DL) education for students and enthusiasts. It features curated roadmaps, videos, articles, and other learning materials. The platform aims to provide a comprehensive learning experience for Indian audiences, with easy-to-follow paths for ML and DL concepts, diverse resources including video tutorials and articles, and a growing community of over 6000 users. Contributors can add new resources following specific guidelines to maintain quality and relevance. Future plans include expanding content for global learners, introducing a Python programming roadmap, and creating roadmaps for fields like Generative AI and Reinforcement Learning.

Multi-Agent Orchestrator is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries to the most suitable agent based on context and content, supports dual language implementation in Python and TypeScript, offers flexible agent responses, context management across agents, extensible architecture for customization, universal deployment options, and pre-built agents and classifiers. It is suitable for various applications, from simple chatbots to sophisticated AI systems, accommodating diverse requirements and scaling efficiently.

CentralMind Gateway is an AI-first data gateway that securely connects any data source and automatically generates secure, LLM-optimized APIs. It filters out sensitive data, adds traceability, and optimizes for AI workloads. Suitable for companies deploying AI agents for customer support and analytics.

Fraim is an AI-powered toolkit designed for security engineers to enhance their workflows by leveraging AI capabilities. It offers solutions to find, detect, fix, and flag vulnerabilities throughout the development lifecycle. The toolkit includes features like Risk Flagger for identifying risks in code changes, Code Security Analysis for context-aware vulnerability detection, and Infrastructure as Code Analysis for spotting misconfigurations in cloud environments. Fraim can be run as a CLI tool or integrated into Github Actions, making it a versatile solution for security teams and organizations looking to enhance their security practices with AI technology.

Gemini Coder is a free 2M context AI coding assistant that allows users to conveniently copy folders and files for chatbots. It provides FIM completions, file refactoring, and AI-suggested changes. The extension is versatile, private, and lightweight, offering unmatched accuracy, speed, and cost in AI assistance. Users have full control over the context and coding conventions included, ensuring high performance and signal to noise ratio. Gemini Coder supports various chatbots and provides quick start guides for chat and FIM completions. It also offers commands for FIM completions, refactoring, applying changes, chat, and context copying. Users can set up custom model providers for API features and contribute to the project through pull requests or discussions. The tool is licensed under the MIT License.

LangManus is a community-driven AI automation framework that combines language models with specialized tools for tasks like web search, crawling, and Python code execution. It implements a hierarchical multi-agent system with agents like Coordinator, Planner, Supervisor, Researcher, Coder, Browser, and Reporter. The framework supports LLM integration, search and retrieval tools, Python integration, workflow management, and visualization. LangManus aims to give back to the open-source community and welcomes contributions in various forms.

This is a super customizable, concise, user-friendly, and efficient toolkit for training and aligning LLMs. It provides support for various methods such as SFT, Distillation, DPO, ORPO, CPO, SimPO, SMPO, Non-pair Reward Modeling, Special prompts basket format, Rejection Sampling, Scoring using RM, Effective FAISS Map-Reduce Deduplication, LLM scoring using RM, NER, CLIP, Classification, and STS. The toolkit offers key libraries like PyTorch, Transformers, TRL, Accelerate, FSDP, DeepSpeed, and tools for result logging with wandb or clearml. It allows mixing datasets, generation and logging in wandb/clearml, vLLM batched generation, and aligns models using the SMPO method.

The Universal Tool Calling Protocol (UTCP) Specification repository contains the official documentation for a modern and scalable standard that enables AI systems and clients to discover and interact with tools across different communication protocols. It defines tool discovery mechanisms, call formats, provider configuration, authentication methods, and response handling.

VacAIgent is an AI tool that automates and enhances trip planning by leveraging the CrewAI framework. It integrates a user-friendly Streamlit interface for interactive travel planning. Users can input preferences and receive tailored travel plans with the help of autonomous AI agents. The tool allows for collaborative decision-making on cities and crafting complete itineraries based on specified preferences, all accessible via a streamlined Streamlit user interface. VacAIgent can be customized to use different AI models like GPT-3.5 or local models like Ollama for enhanced privacy and customization.

GitDiagram is a tool that turns any GitHub repository into an interactive diagram for visualization in seconds. It offers instant visualization, interactivity, fast generation, customization, and API access. The tool utilizes a tech stack including Next.js, FastAPI, PostgreSQL, Claude 3.5 Sonnet, Vercel, EC2, GitHub Actions, PostHog, and Api-Analytics. Users can self-host the tool for local development and contribute to its development. GitDiagram is inspired by Gitingest and has future plans to use larger context models, allow user API key input, implement RAG with Mermaid.js docs, and include font-awesome icons in diagrams.

DevDocs is a platform designed to simplify the process of digesting technical documentation for software engineers and developers. It automates the extraction and conversion of web content into markdown format, making it easier for users to access and understand the information. By crawling through child pages of a given URL, DevDocs provides a streamlined approach to gathering relevant data and integrating it into various tools for software development. The tool aims to save time and effort by eliminating the need for manual research and content extraction, ultimately enhancing productivity and efficiency in the development process.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

AData is a free and open-source A-share database that focuses on transaction-related data. It provides comprehensive data on stocks, including basic information, market data, and sentiment analysis. AData is designed to be easy to use and integrate with other applications, making it a valuable tool for quantitative trading and AI training.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

Hezar is an all-in-one AI library designed specifically for the Persian community. It brings together various AI models and tools, making it easy to use AI with just a few lines of code. The library seamlessly integrates with Hugging Face Hub, offering a developer-friendly interface and task-based model interface. In addition to models, Hezar provides tools like word embeddings, tokenizers, feature extractors, and more. It also includes supplementary ML tools for deployment, benchmarking, and optimization.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

CodeProject.AI Server is a standalone, self-hosted, fast, free, and open-source Artificial Intelligence microserver designed for any platform and language. It can be installed locally without the need for off-device or out-of-network data transfer, providing an easy-to-use solution for developers interested in AI programming. The server includes a HTTP REST API server, backend analysis services, and the source code, enabling users to perform various AI tasks locally without relying on external services or cloud computing. Current capabilities include object detection, face detection, scene recognition, sentiment analysis, and more, with ongoing feature expansions planned. The project aims to promote AI development, simplify AI implementation, focus on core use-cases, and leverage the expertise of the developer community.

Spark NLP is a state-of-the-art Natural Language Processing library built on top of Apache Spark. It provides simple, performant, and accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. Spark NLP comes with 36000+ pretrained pipelines and models in more than 200+ languages. It offers tasks such as Tokenization, Word Segmentation, Part-of-Speech Tagging, Named Entity Recognition, Dependency Parsing, Spell Checking, Text Classification, Sentiment Analysis, Token Classification, Machine Translation, Summarization, Question Answering, Table Question Answering, Text Generation, Image Classification, Image to Text (captioning), Automatic Speech Recognition, Zero-Shot Learning, and many more NLP tasks. Spark NLP is the only open-source NLP library in production that offers state-of-the-art transformers such as BERT, CamemBERT, ALBERT, ELECTRA, XLNet, DistilBERT, RoBERTa, DeBERTa, XLM-RoBERTa, Longformer, ELMO, Universal Sentence Encoder, Llama-2, M2M100, BART, Instructor, E5, Google T5, MarianMT, OpenAI GPT2, Vision Transformers (ViT), OpenAI Whisper, and many more not only to Python and R, but also to JVM ecosystem (Java, Scala, and Kotlin) at scale by extending Apache Spark natively.

Scikit-LLM is a tool that seamlessly integrates powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks. It allows users to leverage large language models for various text analysis applications within the familiar scikit-learn framework. The tool simplifies the process of incorporating advanced language processing capabilities into machine learning pipelines, enabling users to benefit from the latest advancements in natural language processing.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.

This framework generates fuzz targets for real-world `C`/`C++` projects with various Large Language Models (LLM) and benchmarks them via the `OSS-Fuzz` platform. It manages to successfully leverage LLMs to generate valid fuzz targets (which generate non-zero coverage increase) for 160 C/C++ projects. The maximum line coverage increase is 29% from the existing human-written targets.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.