Best AI tools for< Relevance Engineer >
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20 - AI tool Sites
Trieve
Trieve is an AI-first infrastructure API that offers advanced search, recommendations, and RAG capabilities by combining language models with tools for fine-tuning ranking and relevance. It provides a modern API for search and RAG experiences, supporting features like semantic vector search, BM25 & SPLADE full-text search, hybrid search, merchandising, relevance tuning, sub-sentence highlighting, and more. Trieve is built on open-source models, ensuring data privacy, and offers self-hostable options for maximum performance and control over search functionalities.
Hirebase
Hirebase is an AI-powered job search engine that provides ultra-fresh job market data directly from company pages. It uses AI to scan 100,000 jobs in real-time, ensuring that every job listed is actively hiring on the internet. Users can receive email alerts for new job listings based on their preferences for job title, keywords, location, experience level, date posted, salary range, and more. Hirebase aims to 'unsuckify' the job search process by leveraging AI technology to streamline and enhance the job hunting experience.
DQLabs
DQLabs is a modern data quality platform that leverages observability to deliver reliable and accurate data for better business outcomes. It combines the power of Data Quality and Data Observability to enable data producers, consumers, and leaders to achieve decentralized data ownership and turn data into action faster, easier, and more collaboratively. The platform offers features such as data observability, remediation-centric data relevance, decentralized data ownership, enhanced data collaboration, and AI/ML-enabled semantic data discovery.
VecRank
VecRank is an AI-powered Vector Search and Reranking API service that leverages cutting-edge GenAI technologies to enhance natural language understanding and contextual relevance. It offers a scalable, AI-driven search solution for software developers and business owners. With VecRank, users can revolutionize their search capabilities with the power of AI, enabling seamless integration and powerful tools that scale with their business needs. The service allows for bulk data upload, incremental data updates, and easy integration into various programming languages and platforms, all without the hassle of setting up infrastructure for embeddings and vector search databases.
ReadRelevant.Ai
ReadRelevant.Ai is an AI-powered tool that scans thousands of websites regularly to create a personalized feed directly relevant to users' current or aspired job roles. It provides curated content free from repetitive or redundant information, helping users discover best practices, new tools, and innovative solutions for their roles. The tool aims to increase productivity, problem-solving skills, and drive innovation in users' work, ultimately accelerating career growth and keeping users relevant in their fields.
LangWatch
LangWatch is a monitoring and analytics tool for Generative AI (GenAI) solutions. It provides detailed evaluations of the faithfulness and relevancy of GenAI responses, coupled with user feedback insights. LangWatch is designed for both technical and non-technical users to collaborate and comment on improvements. With LangWatch, you can understand your users, detect issues, and improve your GenAI products.
Athina AI
Athina AI is a comprehensive platform designed to monitor, debug, analyze, and improve the performance of Large Language Models (LLMs) in production environments. It provides a suite of tools and features that enable users to detect and fix hallucinations, evaluate output quality, analyze usage patterns, and optimize prompt management. Athina AI supports integration with various LLMs and offers a range of evaluation metrics, including context relevancy, harmfulness, summarization accuracy, and custom evaluations. It also provides a self-hosted solution for complete privacy and control, a GraphQL API for programmatic access to logs and evaluations, and support for multiple users and teams. Athina AI's mission is to empower organizations to harness the full potential of LLMs by ensuring their reliability, accuracy, and alignment with business objectives.
Plato
Plato is an AI-powered platform that provides data intelligence for the digital world. It offers an immersive user experience through a proprietary hashtagging algorithm optimized for search. With over 5 million users since its beta launch in April 2020, Plato organizes public and private data sources to deliver authentic and valuable insights. The platform connects users to sector-specific applications, offering real-time data intelligence in a secure environment. Plato's vertical search and AI capabilities streamline data curation and provide contextual relevancy for users across various industries.
Software Engineer Interview Questions Generator
The Software Engineer Interview Questions Generator is an AI tool designed to help software engineers prepare for interviews by generating a wide range of technical questions related to various programming languages, frameworks, databases, and cloud services. Users can select specific topics and the number of questions they want to generate, making it a valuable resource for interview preparation. The tool leverages AI technology to provide relevant and challenging questions that cover a broad spectrum of software engineering topics.
CommandBar
CommandBar is an AI-powered user assistance tool that provides in-product help, rich help docs, and a search function that automagically connects user queries to results that contain similar concepts, not just words. It also offers personalized search suggestions, page targeting, and audience targeting to ensure that users get the most relevant help possible.
Semantic Scholar
Semantic Scholar is a free, AI-powered research tool for scientific literature. It is based at the Allen Institute for AI and provides access to over 217 million papers from all fields of science. Semantic Scholar uses AI to help users discover and explore scientific literature, and to stay up-to-date on the latest research. The tool also includes a number of features to help users manage their research, such as the ability to save papers, create bibliographies, and share research with others.
Jobright
Jobright is an AI-powered job search platform that acts as your co-pilot in finding the freshest job opportunities. With its advanced AI technology, Jobright scans the job market continuously to bring you up-to-date job listings, saving you time and effort in your job search. The platform matches jobs to your skills and experience, provides key company insights, and suggests resume tweaks to help you secure more interviews with the right employers. Jobright offers a wide range of job listings across various industries, making it a valuable tool for job seekers looking to stay ahead in their job search.
Promptstacks
Promptstacks is a community-driven platform where people can share and discover Generative AI tips and tricks. Users can also discuss prompt engineering and general industry news. The goal of prompt engineering is typically to generate more relevant, coherent or accurate output from a large language model such as ChatGPT or Bard.
Computerworld
Computerworld is a technology news website that covers topics such as artificial intelligence, productivity software, Windows, Android, Apple, augmented reality, emerging technology, mobile, remote work, and operating systems. It provides news, reviews, how-tos, and analysis on the latest technology trends and products.
Ocular
Ocular is an AI-powered search platform that allows users to search, visualize, and take action on their work and engineering tools and data on one unified platform. It is designed to help engineers work more efficiently and effectively by providing them with a single, central location to access all of their relevant information.
Inkdrop
Inkdrop is an AI-powered application that helps users visualize their cloud infrastructure by automatically generating interactive diagrams of cloud resources and dependencies. It provides a comprehensive overview of infrastructure to speed up onboarding and understand complex resource relationships for effective troubleshooting. With seamless integration, users can effortlessly update documentation via CI pipeline integration. Inkdrop aims to simplify the management of cloud resources and enhance collaboration among team members.
Error 404 Not Found
The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::jzd5h-1725561052162-b87af43bcd4a'. Users are directed to refer to the documentation for further information and troubleshooting.
SkillOk
SkillOk is an AI-powered resume builder that helps users create tailored resumes for each job application. It automates the process of customizing resumes by extracting skills from job descriptions, fine-tuning content based on targeted questions, and generating customized intros. The tool ensures that resumes are relevant to job requirements, optimized for ATS software, and aligned with industry best practices. Users can also fully customize their resumes using the drag-n-drop builder and export them in various formats. SkillOk aims to increase users' chances of getting interviews and landing their dream jobs with confidence.
Devika AI
Devika AI is an open-source AI software engineer that can understand high-level human instructions, break them down into steps, research relevant information, and generate code for particular tasks. It uses Claude 3, GPT-4, GPT-3.5, and Local LLMs via Ollama.
GoatStack
GoatStack is an AI-powered newsletter agent that delivers personalized insights from scientific papers. It reads over 4000 papers daily and handpicks the most relevant ones for you. With GoatStack, you can stay up-to-date on the latest AI breakthroughs and advancements. It offers a range of features to help you customize your newsletter, including the ability to personalize topics, generalize topics, or be specific with content.
20 - Open Source Tools
trieve
Trieve is an advanced relevance API for hybrid search, recommendations, and RAG. It offers a range of features including self-hosting, semantic dense vector search, typo tolerant full-text/neural search, sub-sentence highlighting, recommendations, convenient RAG API routes, the ability to bring your own models, hybrid search with cross-encoder re-ranking, recency biasing, tunable popularity-based ranking, filtering, duplicate detection, and grouping. Trieve is designed to be flexible and customizable, allowing users to tailor it to their specific needs. It is also easy to use, with a simple API and well-documented features.
MATLAB-Simulink-Challenge-Project-Hub
MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.
DataEngineeringPilipinas
DataEngineeringPilipinas is a repository dedicated to data engineering resources in the Philippines. It serves as a platform for data engineering professionals to contribute and access high-quality content related to data engineering. The repository provides guidelines for contributing, including forking the repository, making changes, and submitting contributions. It emphasizes the importance of quality, relevance, and respect in the contributions made to the project. By following the guidelines and contributing to the repository, users can help build a valuable resource for the data engineering community in the Philippines and beyond.
EdgeChains
EdgeChains is an open-source chain-of-thought engineering framework tailored for Large Language Models (LLMs)- like OpenAI GPT, LLama2, Falcon, etc. - With a focus on enterprise-grade deployability and scalability. EdgeChains is specifically designed to **orchestrate** such applications. At EdgeChains, we take a unique approach to Generative AI - we think Generative AI is a deployment and configuration management challenge rather than a UI and library design pattern challenge. We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure.
gollm
gollm is a Go package designed to simplify interactions with Large Language Models (LLMs) for AI engineers and developers. It offers a unified API for multiple LLM providers, easy provider and model switching, flexible configuration options, advanced prompt engineering, prompt optimization, memory retention, structured output and validation, provider comparison tools, high-level AI functions, robust error handling and retries, and extensible architecture. The package enables users to create AI-powered golems for tasks like content creation workflows, complex reasoning tasks, structured data generation, model performance analysis, prompt optimization, and creating a mixture of agents.
llm-rag-workshop
The LLM RAG Workshop repository provides a workshop on using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate and understand text in a human-like manner. It includes instructions on setting up the environment, indexing Zoomcamp FAQ documents, creating a Q&A system, and using OpenAI for generation based on retrieved information. The repository focuses on enhancing language model responses with retrieved information from external sources, such as document databases or search engines, to improve factual accuracy and relevance of generated text.
kernel-memory
Kernel Memory (KM) is a multi-modal AI Service specialized in the efficient indexing of datasets through custom continuous data hybrid pipelines, with support for Retrieval Augmented Generation (RAG), synthetic memory, prompt engineering, and custom semantic memory processing. KM is available as a Web Service, as a Docker container, a Plugin for ChatGPT/Copilot/Semantic Kernel, and as a .NET library for embedded applications. Utilizing advanced embeddings and LLMs, the system enables Natural Language querying for obtaining answers from the indexed data, complete with citations and links to the original sources. Designed for seamless integration as a Plugin with Semantic Kernel, Microsoft Copilot and ChatGPT, Kernel Memory enhances data-driven features in applications built for most popular AI platforms.
llm-course
The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod | ![Open In Colab](img/colab.svg) | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. | ![Open In Colab](img/colab.svg) | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. | ![Open In Colab](img/colab.svg) | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. | ![Open In Colab](img/colab.svg) | | 🌳 Model Family Tree | Visualize the family tree of merged models. | ![Open In Colab](img/colab.svg) | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. | ![Open In Colab](img/colab.svg) |
linkedIn_auto_jobs_applier_with_AI
LinkedIn_AIHawk is an automated tool designed to revolutionize the job search and application process on LinkedIn. It leverages automation and artificial intelligence to efficiently apply to relevant positions, personalize responses, manage application volume, filter listings, generate dynamic resumes, and handle sensitive information securely. The tool aims to save time, increase application relevance, and enhance job search effectiveness in today's competitive landscape.
griptape
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.
rag-experiment-accelerator
The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.
awesome-generative-ai
A curated list of Generative AI projects, tools, artworks, and models
awesome-ai
Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.
phoenix
Phoenix is a tool that provides MLOps and LLMOps insights at lightning speed with zero-config observability. It offers a notebook-first experience for monitoring models and LLM Applications by providing LLM Traces, LLM Evals, Embedding Analysis, RAG Analysis, and Structured Data Analysis. Users can trace through the execution of LLM Applications, evaluate generative models, explore embedding point-clouds, visualize generative application's search and retrieval process, and statistically analyze structured data. Phoenix is designed to help users troubleshoot problems related to retrieval, tool execution, relevance, toxicity, drift, and performance degradation.
CoPilot
TigerGraph CoPilot is an AI assistant that combines graph databases and generative AI to enhance productivity across various business functions. It includes three core component services: InquiryAI for natural language assistance, SupportAI for knowledge Q&A, and QueryAI for GSQL code generation. Users can interact with CoPilot through a chat interface on TigerGraph Cloud and APIs. CoPilot requires LLM services for beta but will support TigerGraph's LLM in future releases. It aims to improve contextual relevance and accuracy of answers to natural-language questions by building knowledge graphs and using RAG. CoPilot is extensible and can be configured with different LLM providers, graph schemas, and LangChain tools.
Reflection_Tuning
Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.
raga-llm-hub
Raga LLM Hub is a comprehensive evaluation toolkit for Language and Learning Models (LLMs) with over 100 meticulously designed metrics. It allows developers and organizations to evaluate and compare LLMs effectively, establishing guardrails for LLMs and Retrieval Augmented Generation (RAG) applications. The platform assesses aspects like Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails, and Vulnerability scanning, along with Metric-Based Tests for quantitative analysis. It helps teams identify and fix issues throughout the LLM lifecycle, revolutionizing reliability and trustworthiness.
redis-ai-resources
A curated repository of code recipes, demos, and resources for basic and advanced Redis use cases in the AI ecosystem. It includes demos for ArxivChatGuru, Redis VSS, Vertex AI & Redis, Agentic RAG, ArXiv Search, and Product Search. Recipes cover topics like Getting started with RAG, Semantic Cache, Advanced RAG, and Recommendation systems. The repository also provides integrations/tools like RedisVL, AWS Bedrock, LangChain Python, LangChain JS, LlamaIndex, Semantic Kernel, RelevanceAI, and DocArray. Additional content includes blog posts, talks, reviews, and documentation related to Vector Similarity Search, AI-Powered Document Search, Vector Databases, Real-Time Product Recommendations, and more. Benchmarks compare Redis against other Vector Databases and ANN benchmarks. Documentation includes QuickStart guides, official literature for Vector Similarity Search, Redis-py client library docs, Redis Stack documentation, and Redis client list.
Awesome-Interpretability-in-Large-Language-Models
This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.
llm_benchmarks
llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.
20 - OpenAI Gpts
MIL GPT
This GPT matches between system or application to it's relevant clauses in military standards. You can simply ask any question or state your system
Metaphor API Guide - Python SDK
Teaches you how to use the Metaphor Search API using our Python SDK
The Relevance Report 2024
Learn what current and future leaders in communication think about AI's impact on our industry!
Soy George Orwell
I'm George Orwell, here to discuss '1984' and its relevance to today's society.
World Watcher
I provide global news coverage with a focus on diversity, relevance, and unbiased reporting.
UK News Today
Delivers factual updates on UK news today, focusing on accuracy and relevance.
SEO Content Wizard
I assist in generating SEO content ideas, with a focus on creativity and relevance.
Chat with Tertullian
Engage with the wisdom of early Christianity through Tertullian's lens, brought to life with modern relevance.
AutoExpert (Academic)
Upon uploading a research paper, I provide a concise analysis covering its authors, key findings, methodology, and relevance. I also critique the work, highlight its strengths, and identify any open questions from a professional perspective.
Topics for TED Talk-style presentations
'TED Talk Presentation Topics' is a prompt expert in discovering and developing captivating TED Talk presentation topics, tailored to the user's experience, interest, and goals, ensuring relevance, diversity, and inspiration.
SearchQualityGPT
As a Search Quality Rater, you will help evaluate search engine quality around the world.
The Innovation Thought Leader
Thought leadership for innovative, complex, AI-based brands trying to be culturally relevant in the dense omnichannel ecosystem of headless platforms
Multilingual App Keyword Suggester
Multilingual keyword suggester, offering culturally relevant suggestions.
Kaufpreis einer Garage ermitteln
Kaufpreis einer Garage ermitteln: Ich bin ein Immobilienbewertungsrechner, spezialisiert auf die Wertermittlung und Schätzung des Marktwerts von Garagen. Als Bewertungstool helfe ich, den Wert von Garagen zu schätzen, indem ich relevante Faktoren wie Lage und Zustand in die Ermittlung einbeziehe.