Best AI tools for< Query Document Content >

Chat with Docs is a platform that allows users to interact with documents using a simple API. Users can chat with any document by integrating just 2 lines of code. The platform supports various document formats such as Pdf, docx, doc, pptx, txt, and more. Users can ask questions about documents using cUrl, Python, or JavaScript. Chat with Docs offers a straightforward pricing model and emphasizes privacy and terms of use.

BFF AI is a comprehensive AI-powered tool that provides a wide range of services, including text, image, and code generation, virtual assistance, speech-to-text transcription, text-to-speech conversion, and more. It is designed to help users save time, improve productivity, and enhance their creativity. With its user-friendly interface and powerful features, BFF AI is suitable for individuals, teams, and businesses of all sizes.

PrivacyDoc is an AI-powered portal that allows users to analyze and query PDF and ebooks effortlessly. By leveraging advanced NLP technology, PrivacyDoc enables users to uncover insights and conduct thorough document analysis. The platform offers features such as easy file upload, query functionality, enhanced security measures, and free access to powerful PDF analysis tools. With PrivacyDoc, users can experience the convenience of logging in with their Google account, submitting queries for prompt AI-driven responses, and ensuring data privacy with secure file handling.

Helper-AI is an instant access ChatGPT on any site. It is a one-time purchase with free all future updates. It can be used to generate high-quality content, write code & Excel Formulas, rewrite, research, summarize and more. It works great with all macOS + Windows. To start, just type "help:" and then write your query and end your query with ";".

FlowHunt is an AI chatbot platform that offers a new no-code visual way to build AI tools and chatbots for websites. It provides a template library with ready-to-use options, from simple AI tools to complex chatbots, and integrates with popular services like Smartsupp, LiveChat, HubSpot, and LiveAgent. The platform also features components like Task Decomposition, Query Expansion, Chat Input, Chat Output, Document Retriever, Document to Text, Generator, and GoogleSearch, enabling users to create customized chatbots for various contexts. FlowHunt aims to simplify the process of building and deploying AI-powered solutions for customer service and content generation.

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.

Loata is an AI-powered platform that serves as a learning orchestrator for adaptive text analyses. It allows users to store their notes and documents in the cloud, which are then ingested and transformed into knowledge bases. The platform features smart AI agents powered by LLMs to provide intelligent answers based on the content. With end-to-end encryption and controlled ingestion, Loata ensures the security and privacy of user data. Users can choose from different subscription plans to access varying levels of storage and query capacity, making it suitable for individuals and professionals alike.

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.

LlamaIndex is a framework for building context-augmented Large Language Model (LLM) applications. It provides tools to ingest and process data, implement complex query workflows, and build applications like question-answering chatbots, document understanding systems, and autonomous agents. LlamaIndex enables context augmentation by combining LLMs with private or domain-specific data, offering tools for data connectors, data indexes, engines for natural language access, chat engines, agents, and observability/evaluation integrations. It caters to users of all levels, from beginners to advanced developers, and is available in Python and Typescript.

GOODY-2 is the world's most responsible AI model, built with next-gen adherence to ethical principles. It's so safe that it won't answer anything that could be possibly construed as controversial or problematic. GOODY-2 can recognize any query that could be controversial, offensive, or dangerous in any context and elegantly avoids answering, redirecting the conversation, and mitigating brand risk. GOODY-2's ethical adherence is unbreakable, ensuring that every conversation stays within the bounds of ethical principles. Even bad actors will find themselves unable to cause GOODY-2 to answer problematic queries. GOODY-2 is the perfect fit for customer service, paralegal assistance, back-office tasks, and more. It's the safe, dependable AI model companies around the globe have been waiting for.

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.

The FileAI website offers an AI-powered file reading assistant that specializes in data extraction from structured documents like financial statements, legal documents, and research papers. It automates tasks related to legal and compliance review, finance and accounting report preparation, and research and academia support. The tool aims to streamline document processing, enhance learning processes, and improve research efficiency. With features like summarizing complex texts, extracting key information, and detecting plagiarism, FileAI caters to users in various industries and educational fields. The platform prioritizes data security and user privacy, ensuring that data is used solely for its intended purpose and deleted after 7 days of non-use.

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.

QueryHub is an AI-powered web application designed to assist students in their academic endeavors. It provides a platform for users to ask and answer questions, collaborate with peers, and access instant and accurate information through AI chatbot assistance and smart search capabilities. QueryHub aims to empower students by offering a personalized learning experience, accelerating learning through document collaboration, and fostering community collaboration. With a user-friendly interface and a focus on user-driven innovation, QueryHub is a valuable tool for enhancing academic success.

Focal is an AI-powered tool that helps users summarize and organize their research and reading materials. It offers features such as AI-generated summaries, document highlighting, and collaboration tools. Focal is designed for researchers, students, professionals, and anyone who needs to efficiently process large amounts of information.

SvectorDB is a vector database built from the ground up for serverless applications. It is designed to be highly scalable, performant, and easy to use. SvectorDB can be used for a variety of applications, including recommendation engines, document search, and image search.

MindpoolAI is a tool that allows users to access multiple leading AI models with a single query. This means that users can get the answers they are looking for, spark ideas, and fuel their work, creativity, and curiosity. MindpoolAI is easy to use and does not require any technical expertise. Users simply need to enter their prompt and select the AI models they want to compare. MindpoolAI will then send the query to the selected models and present the results in an easy-to-understand format.

ITVA is an AI automation tool for network infrastructure products that revolutionizes network management by enabling users to configure, query, and document their network using natural language. It offers features such as rapid configuration deployment, network diagnostics acceleration, automated diagram generation, and modernized IP address management. ITVA's unique solution securely connects to networks, combining real-time data with a proprietary dataset curated by veteran engineers. The tool ensures unparalleled accuracy and insights through its real-time data pipeline and on-demand dynamic analysis capabilities.

AI Brain Bank is a powerful tool that allows you to remember everything. With AI Brain Bank, you can query all your documents, media, and knowledge with AI. This makes it easy to find the information you need, when you need it. AI Brain Bank is the perfect tool for students, researchers, and anyone else who needs to manage a large amount of information.

ChatWithPDF is a ChatGPT plugin that allows users to query against small or large PDF documents directly in ChatGPT. It offers a convenient way to process and semantically search PDF documents based on your queries. By providing a temporary PDF URL, the plugin fetches relevant information from the PDF file and returns the most suitable matches according to your search input.

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.

Dynamiq is an orchestration framework designed to streamline the development of AI-powered applications, specializing in orchestrating retrieval-augmented generation (RAG) and large language model (LLM) agents. It provides an all-in-one Gen AI framework for agentic AI and LLM applications, offering tools for multi-agent orchestration, document indexing, and retrieval flows. With Dynamiq, users can easily build and deploy AI solutions for various tasks.

chromem-go is an embeddable vector database for Go with a Chroma-like interface and zero third-party dependencies. It enables retrieval augmented generation (RAG) and similar embeddings-based features in Go apps without the need for a separate database. The focus is on simplicity and performance for common use cases, allowing querying of documents with minimal memory allocations. The project is in beta and may introduce breaking changes before v1.0.0.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

The Spring AI project provides a Spring-friendly API and abstractions for developing AI applications. It offers a portable client API for interacting with generative AI models, enabling developers to easily swap out implementations and access various models like OpenAI, Azure OpenAI, and HuggingFace. Spring AI also supports prompt engineering, providing classes and interfaces for creating and parsing prompts, as well as incorporating proprietary data into generative AI without retraining the model. This is achieved through Retrieval Augmented Generation (RAG), which involves extracting, transforming, and loading data into a vector database for use by AI models. Spring AI's VectorStore abstraction allows for seamless transitions between different vector database implementations.

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.

Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. It is developed under the MIT License and powers inference behind Gradient.ai. The API allows users to deploy models from SentenceTransformers, offers fast inference backends utilizing various accelerators, dynamic batching for efficient processing, correct and tested implementation, and easy-to-use API built on FastAPI with Swagger documentation. Users can embed text, rerank documents, and perform text classification tasks using the tool. Infinity supports various models from Huggingface and provides flexibility in deployment via CLI, Docker, Python API, and cloud services like dstack. The tool is suitable for tasks like embedding, reranking, and text classification.

Redis Vector Library (RedisVL) is a Python client library for building AI applications on top of Redis. It provides a high-level interface for managing vector indexes, performing vector search, and integrating with popular embedding models and providers. RedisVL is designed to make it easy for developers to build and deploy AI applications that leverage the speed, flexibility, and reliability of Redis.

The Python Redis Vector Library (RedisVL) is a tailor-made client for AI applications leveraging Redis. It enhances applications with Redis' speed, flexibility, and reliability, incorporating capabilities like vector-based semantic search, full-text search, and geo-spatial search. The library bridges the gap between the emerging AI-native developer ecosystem and the capabilities of Redis by providing a lightweight, elegant, and intuitive interface. It abstracts the features of Redis into a grammar that is more aligned to the needs of today's AI/ML Engineers or Data Scientists.

Azure Functions OpenAI Extension is a project that adds support for OpenAI LLM (GPT-3.5-turbo, GPT-4) bindings in Azure Functions. It provides NuGet packages for various functionalities like text completions, chat completions, assistants, embeddings generators, and semantic search. The project requires .NET 6 SDK or greater, Azure Functions Core Tools v4.x, and specific settings in Azure Function or local settings for development. It offers features like text completions, chat completion, assistants with custom skills, embeddings generators for text relatedness, and semantic search using vector databases. The project also includes examples in C# and Python for different functionalities.

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.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

Casual, technical helper for Mongoose docs, includes documentation links.

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Looper query strings assistant

Getting ready to query agents or publishers? Upload your manuscript. I analyse your novel's writing style, themes and genre. I'll tell you how it's relevant to a modern audience, offer marketing insights and will even write you a draft synopsis and cover letter. I'll help you find relevant agents.

I conjure advanced Google search queries.

Enhances PubMed searches with MeSH and follow-up advice

The KQL Query Helper GPT is tailored specifically for assisting users with Kusto Query Language (KQL) queries. It leverages extensive knowledge from Azure Data Explorer documentation to aid users in understanding, reviewing, and creating new KQL queries based on their prompts.

Expert in brief, direct SQL queries for BigQuery, with casual professional tone.

Helps get map data from Open Street Map by generating Overpass Turbo queries. Ask me for mapping features like cafes, rivers or highways

Expert in Power Query and DAX for Power BI, offering in-depth guidance and insights

Create the most effective database or search engine queries using keywords, truncation, and Boolean operators!

Query BCorp company data. All data is publicly available. United Kingdom only (for now).

SQL query validator and educator, adaptable to user's format.

Supabase expert also supports query generation and Flutter code generation

I'm your guide for any query and information related to TikTok Ads. Let's build your new campaign together!

Answers in query language, adds Korean translation and phonetics for non-Korean queries.

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.

Knows the docs and can query official ordinal endpoints—Sat Numbers, Inscription IDs, and more.

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