Best AI tools for< Generate Query Embeddings >

SQLPilot is an AI-first SQL editor that leverages artificial intelligence to help users quickly generate complex SQL queries. The tool supports multiple GPT models, offers SQL autocomplete, ensures privacy and security by not storing user data, and allows users to download query results in CSV format. With SQLPilot, users can write prompts in natural language, mention required tables, and let the AI model generate the query with all the necessary context. Testimonials from users highlight the tool's efficiency, accuracy, and time-saving capabilities in database management.

SoraPrompt is an AI model that can create realistic and imaginative scenes from text instructions. It is the latest text-to-video technology from the OpenAI development team. Users can compile text prompts to generate video query summaries for efficient content analysis. SoraPrompt also allows users to share their interests and ideas with others.

AI Query is a powerful tool that allows users to generate SQL queries in seconds using simple English. With AI Query, anyone can create efficient SQL queries, without even knowing a thing about it. AI Query is easy to use and affordable, making it a great choice for businesses of all sizes.

Mikie.AI is an AI-powered tool that allows users to generate SQL queries in seconds using natural language. It simplifies the process of creating efficient SQL queries by leveraging AI technology. Users can define database schemas easily, translate SQL to English, and benefit from simple pricing plans. Mikie.AI aims to make SQL query generation error-free and accessible to all types of users, even those with limited SQL knowledge.

Raw Query is a revolutionary tool that allows you to interact with your database using natural language, just like you would chat with a colleague. It's designed to save you time and effort, and make it easier than ever to access and manage your data. With Raw Query, you can query your data, add new data, and update your data, all through a simple chat interface. It's the perfect tool for anyone who wants to get more out of their data, without having to learn complex SQL queries or spend hours building custom tools.

Query Kitty is a Chrome extension that allows users to access ChatGPT from anywhere on the web. It provides a variety of features to help users get the most out of ChatGPT, including pre-written prompts, the ability to use web pages as context for prompts, and unlimited translations. Query Kitty is available in three plans: Starter, Basic, and Pro. The Starter plan is free and includes 60,000 words per month, the Basic plan costs $6 per month and includes 75,000 words per month, and the Pro plan costs $24 per month and includes 300,000 words per month. All plans come with a 3-day free trial.

AIContentfy is an AI-powered content generation tool that helps you create high-quality, engaging content for your website, blog, or social media. With AIContentfy, you can generate blog posts, articles, product descriptions, website copy, and more. Our AI is trained on a massive dataset of high-quality content, so you can be sure that your content will be well-written, informative, and engaging.

GPT Excel is an AI-powered tool that helps users generate spreadsheet formulas, SQL queries, Apps Script and VBA scripts easily. It supports over 50 languages and offers a free tier with limited requests per day. The pro plan includes additional features such as unlimited requests, priority customer support, and access to additional AI tools like a regex generator and an Excel template generator.

SQL Builder is an AI-powered SQL query generator that allows users to easily generate complex SQL queries without writing any code. It offers a range of features such as a no-code SQL builder, SQL syntax explainer, SQL optimizer, SQL formatter, NoSQL query builder, and SQL syntax validator. SQL Builder supports various databases including MySQL, MariaDB, SQLite, PostgreSQL, Oracle, Microsoft SQL Server, MongoDB, BigQuery, Snowflake, and Amazon Redshift.

Legalyze.ai is an AI-powered platform designed to assist lawyers in streamlining their document review process. It uses AI to summarize and extract key points from case documents, providing rapid insights, summaries, and answers to specific questions. The platform allows users to create document summaries in seconds, supports various file formats, and is externally security audited. Legalyze.ai aims to save time for legal professionals by automating tasks like fact-finding and document creation.

Text2SQL.AI is an AI-powered SQL query builder that helps users generate optimized SQL queries effortlessly. It supports various AI-powered services, including SQL query building from textual instructions, SQL query explanation to plain English, SQL query error fixation, adding custom database schemas, SQL dialects for various database types, Microsoft Excel and Google Sheets formula generation and explanation, and Regex expression generation and explanation. The tool is designed to improve SQL skills, save time, and assist beginners, data analysts, data scientists, data engineers, and software developers in their work.

DB Sensei is an AI-powered SQL tool that helps developers generate, fix, explain, and format SQL queries with ease. It features a user-friendly interface, AI-driven query generation, query fixing, query explaining, and query formatting. DB Sensei is designed for developers, database administrators, and students who want to get faster results and improve their database skills.

Refraction is an AI-powered code generation tool designed to help developers learn, improve, and generate code effortlessly. It offers a wide range of features such as bug detection, code conversion, function creation, CSP generation, CSS style conversion, debug statement addition, diagram generation, documentation creation, code explanation, code improvement, concept learning, CI/CD pipeline creation, SQL query generation, code refactoring, regex generation, style checking, type addition, and unit test generation. With support for 56 programming languages, Refraction is a versatile tool trusted by innovative companies worldwide to streamline software development processes using the magic of AI.

AutoQuery GPT is a tool that allows users to ask questions to ChatGPT and get answers automatically. It provides users with time-saving and performance benefits. Users can use this site by using their own API key to ask questions to ChatGPT and save the answers as a file, using the Query Block and Query Excel features.

ChartFast is an AI Data Analyzer tool that automates data visualization and analysis tasks, powered by GPT-4 technology. It allows users to generate precise and sleek graphs in seconds, process vast amounts of data, and provide interactive data queries and quick exports. With features like specialized internal libraries for complex graph generation, customizable visualization code, and instant data export, ChartFast aims to streamline data work and enhance data analysis efficiency.

Code99 is an AI-powered platform designed to speed up the development process by generating instant boilerplate code. It allows users to customize their tech stack, streamline development, and launch projects faster. Ideal for startups, developers, and IT agencies looking to accelerate project timelines and improve productivity.

BixGPT is an AI-powered tool designed to supercharge product documentation by leveraging the power of private AI models. It offers features like AI-assisted release notes generation, data encryption, autodiscovery of Jira data, multi-format support, client notifications, and more. With BixGPT, users can create and manage release notes effortlessly while ensuring data privacy and security through the use of private AI models. The tool provides a seamless experience for generating release web pages with custom styling and analytics.

AnyAPI is an AI tool that allows users to easily add AI features to their products in minutes. With the ability to craft the perfect GPT-3 prompt using A/B testing, users can quickly generate a live API endpoint to power their next AI feature. The platform offers a range of use cases, including turning emails into tasks, suggesting replies, and accessing plain text JSON. AnyAPI is designed to streamline the integration of AI capabilities into various products and services, making it a valuable tool for developers and businesses seeking to enhance their offerings with AI technology.

SQLyze is an AI SQL generator that revolutionizes the way users interact with SQL queries. By leveraging artificial intelligence, SQLyze simplifies the process of crafting complex SQL queries into a user-friendly three-step approach. Users can effortlessly describe their data needs, add database schema details, and receive custom AI-generated SQL queries tailored to their specific requirements. With SQLyze, users can streamline their SQL querying process and enhance query accuracy, ultimately saving time and improving productivity.

LINQ Me Up is an AI-powered tool designed to boost .Net productivity by generating and converting LINQ queries efficiently. It offers fast and reliable conversion of SQL queries to LINQ code, transformation of LINQ code into SQL queries, and tailored LINQ queries for various datasets. The tool supports C# and Visual Basic code, Method and Query syntax, and utilizes AI-powered analysis for optimized results. LINQ Me Up is more versatile and powerful than rule-based or syntax conversions, enabling users to effortlessly migrate, build, and focus on essential code parts.

STaRK is a large-scale semi-structure retrieval benchmark on Textual and Relational Knowledge Bases. It provides natural-sounding and practical queries crafted to incorporate rich relational information and complex textual properties, closely mirroring real-life scenarios. The benchmark aims to assess how effectively large language models can handle the interplay between textual and relational requirements in queries, using three diverse knowledge bases constructed from public sources.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

The official Node.js client for Pinecone, written in TypeScript. This client library provides a high-level interface for interacting with the Pinecone vector database service. With this client, you can create and manage indexes, upsert and query vector data, and perform other operations related to vector search and retrieval. The client is designed to be easy to use and provides a consistent and idiomatic experience for Node.js developers. It supports all the features and functionality of the Pinecone API, making it a comprehensive solution for building vector-powered applications in Node.js.

pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

This repository contains the code and instructions needed to build a sophisticated answer engine that leverages the capabilities of Groq, Mistral AI's Mixtral, Langchain.JS, Brave Search, Serper API, and OpenAI. Designed to efficiently return sources, answers, images, videos, and follow-up questions based on user queries, this project is an ideal starting point for developers interested in natural language processing and search technologies.

LlamaIndex.TS is a data framework for your LLM application. Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in Typescript and Javascript.

gemini-cli is a versatile command-line interface for Google's Gemini LLMs, written in Go. It includes tools for chatting with models, generating/comparing embeddings, and storing data in SQLite for analysis. Users can interact with Gemini models through various subcommands like prompt, chat, counttok, embed content, embed db, and embed similar.

RAG with txtai is a Retrieval Augmented Generation (RAG) Streamlit application that helps generate factually correct content by limiting the context in which a Large Language Model (LLM) can generate answers. It supports two categories of RAG: Vector RAG, where context is supplied via a vector search query, and Graph RAG, where context is supplied via a graph path traversal query. The application allows users to run queries, add data to the index, and configure various parameters to control its behavior.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

The discourse-chatbot is an original AI chatbot for Discourse forums that allows users to converse with the bot in posts or chat channels. Users can customize the character of the bot, enable RAG mode for expert answers, search Wikipedia, news, and Google, provide market data, perform accurate math calculations, and experiment with vision support. The bot uses cutting-edge Open AI API and supports Azure and proxy server connections. It includes a quota system for access management and can be used in RAG mode or basic bot mode. The setup involves creating embeddings to make the bot aware of forum content and setting up bot access permissions based on trust levels. Users must obtain an API token from Open AI and configure group quotas to interact with the bot. The plugin is extensible to support other cloud bots and content search beyond the provided set.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

Lantern is an open-source PostgreSQL database extension designed to store vector data, generate embeddings, and handle vector search operations efficiently. It introduces a new index type called 'lantern_hnsw' for vector columns, which speeds up 'ORDER BY ... LIMIT' queries. Lantern utilizes the state-of-the-art HNSW implementation called usearch. Users can easily install Lantern using Docker, Homebrew, or precompiled binaries. The tool supports various distance functions, index construction parameters, and operator classes for efficient querying. Lantern offers features like embedding generation, interoperability with pgvector, parallel index creation, and external index graph generation. It aims to provide superior performance metrics compared to other similar tools and has a roadmap for future enhancements such as cloud-hosted version, hardware-accelerated distance metrics, industry-specific application templates, and support for version control and A/B testing of embeddings.

Gemini is an open-source model designed to handle multiple modalities such as text, audio, images, and videos. It utilizes a transformer architecture with special decoders for text and image generation. The model processes input sequences by transforming them into tokens and then decoding them to generate image outputs. Gemini differs from other models by directly feeding image embeddings into the transformer instead of using a visual transformer encoder. The model also includes a component called Codi for conditional generation. Gemini aims to effectively integrate image, audio, and video embeddings to enhance its performance.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

yt-fts is a command line program that uses yt-dlp to scrape all of a YouTube channels subtitles and load them into a sqlite database for full text search. It allows users to query a channel for specific keywords or phrases and generates time stamped YouTube URLs to the videos containing the keyword. Additionally, it supports semantic search via the OpenAI embeddings API using chromadb.

Yet Another Chatbot is a sophisticated multimodal chat interface powered by advanced AI models and equipped with a variety of tools. This chatbot can search and browse the web in real-time, query Wikipedia for information, perform news and map searches, execute Python code, compose long-form articles mixing text and images, generate, search, and compare images, analyze documents and images, search and download arXiv papers, save conversations as text and audio files, manage checklists, and track personal improvements. It offers tools for web interaction, Wikipedia search, Python scripting, content management, image handling, arXiv integration, conversation generation, file management, personal improvement, and checklist management.

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.

Pass in the attributes of Pojo entity class objects, generate corresponding addition, deletion, modification, and pagination query functions, including generating database connection configuration files yaml and database script files, as well as XML dynamic SQL concatenation statements.

Supabase expert also supports query generation and Flutter code generation

Welcome to AIHelp.bot, your versatile assistant for any query. Whether it's a general knowledge question, a technical issue, or something more obscure, I'm here to help. Please type your question below, and I'll use my resources to find the best possible answer.

Specializes in web searches for chat.openai.com using specific query format.

Crafts prompts and provides answers using GPT-4, DALL-E 3, code interpreter, or Bing. Begin your query with "I need a prompt for" and then describe what you're looking for. If needed, request further refinement, and then simply paste the final prompt into the chat for tailored, high-quality outputs.

Generate SQL Queries Using Your Database, Tailored for Every Skill Level!

Connect and chat with your databases without writing SQL code - Supports MySQL, PostgreSQL, MongoDB, SQL Server. by AskYourDatabase.

Expert in generating and debugging Neo4j code, with explanations on graph database principles.

Creates complete queries for BRC20 data. Queries are GeniiData friendly

An Interactive Technical Companion for tech queries and guidance.

Expert in SQL queries, and Tutoring.

Your SQL crafting companion.

根据用户要求生成指定SQL语句

Generates Angular components based on requirements, with a focus on code-first responses.

Transforms lines into detailed prompts for visual storytelling.

Discover how your writing can shine with a unique and human style. This prompt guides you to create rich and varied texts, surprising with original twists and maintaining coherence and originality. Transform your writing and challenge AI detection tools!

Generate captions for your image and choose the vibe you like.

I generate top 10 PLG strategies in a table format

I generate viral GPT ideas based on your inputs.

Generate your eslint rule