Best AI tools for< Provide Error Guidance >

The website page displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::4wq5g-1718736845999-777f28b346ca) for reference. Users are advised to consult the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::xsfmp-1735923123827-c52a4ded5ea0) for reference. Users are directed to check the documentation for more information and troubleshooting tips.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::gxplw-1737651302215-d9b5dd375608) for reference. Users are directed to check the documentation for more information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::8khvr-1735750532589-ae9b68b9e696) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website is currently displaying a 503 error message indicating that the deployment is paused by the owner. It suggests that the visitor should contact the website owner or try again later. The error code provided is DEPLOYMENT_PAUSED with an ID of sin1::pz26b-1735577555137-5602c3cb561a. It advises the owner to refer to the documentation section or resume service.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::s4f6d-1737564994758-9bca133d22c9). Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code and an ID for reference, along with a suggestion to check the documentation for more information and troubleshooting.

The website www.deck.rocks encountered an Origin DNS error, which is a common issue related to the Cloudflare network. The error message indicates that the requested domain (www.deck.rocks) could not be resolved by Cloudflare due to DNS settings. The page provides guidance for both visitors and website owners on how to address this issue. Visitors are advised to try again later, while website owners are instructed to check their DNS settings, especially if using a CNAME origin record. The page also offers additional troubleshooting information for further assistance.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::6lm4m-1735577528392-54edc73f6949) for reference. Users are directed to consult the documentation for further information and troubleshooting.

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::bkk2q-1735577647183-b74af8a896dd'. Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::txj67-1735836932592-eec46f597b11) for reference. Users are directed to check the documentation for more information and troubleshooting.

The website displays a 404 Page not found error message indicating that the requested URL was not found on the server. It is a standard error message displayed when a user tries to access a webpage that does not exist on the server. The 404 error page typically includes a message informing the user that the requested page is unavailable and may provide suggestions or links to navigate back to the site's homepage or other relevant pages.

The website encountered a server error, preventing it from fulfilling the user's request. The error message indicates a 500 Server Error, suggesting an issue on the server-side that is preventing the completion of the request. Users are advised to wait for 30 seconds and try again. This error message typically occurs when there is a problem with the server configuration or processing of the request.

The website is a platform that displays an error message indicating a malformed link. Users are advised to contact the editor of the originating page for assistance. The platform serves as a notification system for users encountering dead-end links, guiding them on the necessary steps to rectify the issue.

The website displays a 404 error message indicating that the deployment cannot be found. Users are advised to refer to the documentation for more information and troubleshooting. The site seems to be a technical platform that provides information related to deployment issues.

Jeffreycelavie.team is a website that currently displays a connection timed out error (Error code 522) related to Cloudflare. The error message indicates that the initial connection between Cloudflare's network and the origin web server timed out, resulting in the web page not being displayed. Visitors are advised to try again in a few minutes, while website owners are instructed to contact their hosting provider for assistance. The error is typically caused by server resource issues. The website seems to be experiencing technical difficulties and is not accessible at the moment.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::b94pv-1737739060437-151d14f5ec0e) for reference. Users are directed to check the documentation for further information and troubleshooting.

Taiga is an AI-powered coding mentor that integrates with Slack. It provides real-time feedback, guidance, and tailored recommendations to help users learn software engineering in a fun and interactive way. Taiga offers a wide range of features, including step-by-step guidance, real-time answers, personalized learning experiences, seamless Slack integration, and accessibility on multiple devices.

Cvify is an AI-powered resume analysis and optimization tool that helps job seekers create tailored, high-impact resumes and cover letters. It provides personalized enhancements, pinpoints key strengths and skills, and identifies areas for improvement. With Cvify, users can quickly and easily optimize their resumes to match specific job descriptions, increasing their chances of landing their dream job.

Highcountrytoyota.stage.autogo.ai is an AI tool designed to provide assistance and support for troubleshooting internet connection issues. The website offers guidance on resolving connection problems, including checking network settings, firewall configurations, and proxy server issues. Users can find step-by-step instructions and tips to troubleshoot and fix connection errors. The platform aims to help users quickly identify and resolve connectivity issues to ensure seamless internet access.

This repository provides guidance on building a multi-tenant SaaS solution for accessing foundation models using Amazon Bedrock and Amazon SageMaker. It helps enterprise IT teams track usage and costs of foundation models, regulate access, and provide visibility to cost centers. The solution includes an API Gateway design pattern for standardization and governance, enabling loose coupling between model consumers and endpoint services. The CDK Stack deploys resources for private networking, API Gateway, Lambda functions, DynamoDB table, EventBridge, S3 buckets, and Cloudwatch logs.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

AzureOpenAI-with-APIM is a repository that provides a one-button deploy solution for Azure API Management (APIM), Key Vault, and Log Analytics to work seamlessly with Azure OpenAI endpoints. It enables organizations to scale and manage their Azure OpenAI service efficiently by issuing subscription keys via APIM, delivering usage metrics, and implementing policies for access control and cost management. The repository offers detailed guidance on implementing APIM to enhance Azure OpenAI resiliency, scalability, performance, monitoring, and chargeback capabilities.

Azure OpenAI Service is a central capability with Azure API Management, providing guidance and tools for organizations to implement Azure OpenAI in a production environment with an emphasis on cost control, secure access, and usage monitoring. It includes infrastructure-as-code templates, CI/CD pipelines, secure access management, usage monitoring, load balancing, streaming requests, and end-to-end samples like ChatApp and Azure Dashboards.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

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.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.

PremSQL is an open-source library designed to help developers create secure, fully local Text-to-SQL solutions using small language models. It provides essential tools for building and deploying end-to-end Text-to-SQL pipelines with customizable components, ideal for secure, autonomous AI-powered data analysis. The library offers features like Local-First approach, Customizable Datasets, Robust Executors and Evaluators, Advanced Generators, Error Handling and Self-Correction, Fine-Tuning Support, and End-to-End Pipelines. Users can fine-tune models, generate SQL queries from natural language inputs, handle errors, and evaluate model performance against predefined metrics. PremSQL is extendible for customization and private data usage.

Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.

This project provides a proof of concept for deploying a scalable, serverless LLM Generative AI inference engine on AWS Lambda. It leverages the llama.cpp project to enable the usage of more accessible CPU and RAM configurations instead of limited and expensive GPU capabilities. By deploying a container with the llama.cpp converted models onto AWS Lambda, this project offers the advantages of scale, minimizing cost, and maximizing compute availability. The project includes AWS CDK code to create and deploy a Lambda function leveraging your model of choice, with a FastAPI frontend accessible from a Lambda URL. It is important to note that you will need ggml quantized versions of your model and model sizes under 6GB, as your inference RAM requirements cannot exceed 9GB or your Lambda function will fail.

This GitHub repository provides support for developers, partners, and customers to create advanced GenAI solutions on SAP Business Technology Platform (SAP BTP) following the Reference Architecture. It includes examples on integrating Foundation Models and Large Language Models via Generative AI Hub, using LangChain in CAP, and implementing advanced techniques like Retrieval Augmented Generation (RAG) through embeddings and SAP HANA Cloud's Vector Engine for enhanced value in customer support scenarios.

Sirji is an agentic AI framework for software development where various AI agents collaborate via a messaging protocol to solve software problems. It uses standard or user-generated recipes to list tasks and tips for problem-solving. Agents in Sirji are modular AI components that perform specific tasks based on custom pseudo code. The framework is currently implemented as a Visual Studio Code extension, providing an interactive chat interface for problem submission and feedback. Sirji sets up local or remote development environments by installing dependencies and executing generated code.

MotionLLM is a framework for human behavior understanding that leverages Large Language Models (LLMs) to jointly model videos and motion sequences. It provides a unified training strategy, dataset MoVid, and MoVid-Bench for evaluating human behavior comprehension. The framework excels in captioning, spatial-temporal comprehension, and reasoning abilities.

Generative AI with LangChain is a code repository for building large language model (LLM) apps with Python, ChatGPT, and other LLMs. The repository provides code examples, instructions, and configurations for creating generative AI applications using the LangChain framework. It covers topics such as setting up the development environment, installing dependencies with Conda or Pip, using Docker for environment setup, and setting API keys securely. The repository also emphasizes stability, code updates, and user engagement through issue reporting and feedback. It aims to empower users to leverage generative AI technologies for tasks like building chatbots, question-answering systems, software development aids, and data analysis applications.

The AI Fairness 360 toolkit is an open-source library designed to detect and mitigate bias in machine learning models. It provides a comprehensive set of metrics, explanations, and algorithms for bias mitigation in various domains such as finance, healthcare, and education. The toolkit supports multiple bias mitigation algorithms and fairness metrics, and is available in both Python and R. Users can leverage the toolkit to ensure fairness in AI applications and contribute to its development for extensibility.

Monacopilot is a powerful and customizable AI auto-completion plugin for the Monaco Editor. It supports multiple AI providers such as Anthropic, OpenAI, Groq, and Google, providing real-time code completions with an efficient caching system. The plugin offers context-aware suggestions, customizable completion behavior, and framework agnostic features. Users can also customize the model support and trigger completions manually. Monacopilot is designed to enhance coding productivity by providing accurate and contextually appropriate completions in daily spoken language.

Mistral.rs is a fast LLM inference platform written in Rust. We support inference on a variety of devices, quantization, and easy-to-use application with an Open-AI API compatible HTTP server and Python bindings.

A step-by-step IT troubleshooter, ensuring a natural conversation flow.

I improve Dutch sentences, explain errors, and give tips.

Analyzes PDF text for errors and varied term usage

Expert en Windows, réponses précises en français. Créé par Tutos-Informatique.

Human-like, detailed reviewer for scientific papers.

Grades and provides feedback on college-level science lab reports.

Expert copy editor that converts your manuscript into a publishable product. It provides the edited copy along with a list of changes made and the reason why the change was made.

Comprehensive novel editing assistant.

寻找解决方案的问题解决专家

Provides expert help for Laravel development questions and challenges.

Provides balanced, clear, and concise assistance with Mojo programming language.

provide a number ,you will find the answer

Provide a prompt followed by multiple participant responses from chatHub delimited by name, or a list of phrase pairs to combine.

Provide the information about each receipt from your shopping.

Spiritual Advisor (1917 Tanakh) draws from the 1917 Tanakh to provide advise and guidance on all of life's difficulties.

Provide your topics, and receive formal, academic assistance in crafting research titles.

Provide TOPIC & different views to compare: Gateway to Informed Comparisons. Harness AI-powered insights to analyze and score different viewpoints on any topic, delivering balanced, data-driven perspectives for smarter decision-making.

Provide a Topic and an Audience and we'll help you create 1. Course description 2. Outline 3. Learning Outcomes 5. Skills-Knowledge-Attitude objectives 5. Key points per lesson

Provide the name, author and genre of a song and the genre you want it re-imagined to. User Prompt: Enter the name of a song, artist, current genre, and the genre you want.

Provide some Traditional Chinese Medicine(中医) advice. For educational purposes only, not to be used for actual treatment.