Best AI tools for< Fetch And Embed Data >

Smarter Sales is a sales call data management and automation tool that helps businesses streamline their sales processes, improve performance metrics, and save time. It integrates with popular video conferencing platforms like Zoom, Teams, and Meets to automatically pull call recordings for analysis. The tool also automates CRM data entry, providing instant, personalized feedback post-call. Managers can access detailed performance dashboards and summarized email reports to make data-driven coaching decisions. Smarter Sales is fully customizable, allowing businesses to set their own CRM data preferences and extract specific data from each call. The tool also offers personalized AI learning materials and stunning chart creation capabilities to help businesses better understand their sales data and improve their sales strategies.

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.

Alter is an AI tool designed for Apple power users to enhance productivity by leveraging AI capabilities that understand tasks and fetch context from various applications. It offers immediate AI-driven actions to streamline tasks such as writing, coding, managing emails, creating pitch decks, handling social media, translating documents, fixing grammar, and generating YouTube summaries. Alter works seamlessly across Finder, Apple Mail, Keynote, browsers, and other macOS apps, providing mnemonic shortcuts and task-based suggestions. Users can customize their AI actions and access specialized AI experts for guidance in Marketing, Technology, and Business.

RoleplayWithVideo is a platform that allows users to engage in role-playing activities using video content. Users can create and participate in various scenarios, enhancing their creativity and communication skills. The platform provides a unique way to interact with others and explore different roles and perspectives through video-based interactions. With RoleplayWithVideo, users can immerse themselves in virtual scenarios and enhance their storytelling abilities.

Fetch AI is an open platform that allows users to build, deploy, and monetize AI applications and services. It provides a new AI economy by connecting multiple integrations to create new services and offers a range of features to transform legacy systems to be AI ready without changing existing APIs. The platform enables users to make their services discoverable on the Fetch.ai Platform with the first open network for AI Agents.

StudyFetch is a revolutionary new platform that allows you to upload your course materials and create interactive study sets. You can study with an AI tutor, create flashcards, generate notes, take practice tests, and more. StudyFetch's AI, Spark.e, utilizes advanced machine learning algorithms to offer a tailored, interactive tutoring experience. Once you upload your study materials, Spark.e scans and indexes them, making the content searchable and accessible for real-time queries.

Fetch.ai Innovation Lab is a leading platform advancing artificial intelligence and driving innovation to create value at scale. The lab unites academic institutes, research teams, and businesses to develop and expand advanced AI solutions. It fosters a collaborative environment that supports impactful projects and pushes the boundaries of what's possible with AI. The lab offers resources, support, and networking opportunities to drive groundbreaking ideas and growth in the AI ecosystem.

Sku Fetch is a powerful tool that helps you fetch, prepare, and list product information from hundreds of suppliers. It provides multiple free templates, helps you find keywords, and can even add UPCs to your products. With Sku Fetch, you can also analyze your competition, add reviews to your listings, and process multiple products with preset settings. Plus, it supports multiple listers, such as Wise Lister, Crazy Lister, eBay Selling Manager, Ink Frog, Shopify, and others.

Collie is a one-click application that fetches every asset from your website to create an impressive knowledge hub for your users. It is powered by Mixpeek and offers amazing search experiences by extracting content, media, and files from URLs provided. Collie supports various types of content like PDFs, Images, Videos, Audio, HTML, and Text, making it a versatile tool for website owners. The application is free for up to 1000 pages or files and offers a private embedded file search for select users in beta.

DataBanc is an AI-powered platform that serves as a data bank, allowing users to retrieve, store, and utilize their personal data for personalized experiences. It empowers individuals to take control of their data, enabling them to access insights and recommendations tailored to their preferences. DataBanc aims to revolutionize the way people interact with their data, offering a secure and user-friendly solution for managing personal information in the digital age.

Keymate.AI is an AI application that allows users to build GPTs with advanced search, browse, and long-term memory capabilities. It offers a personalized long-term memory on ChatGPT, parallel search functionality, and privacy features using Google API. Keymate.AI aims to elevate research, projects, and daily tasks by providing efficient AI memory management and real-time data retrieval from the web.

Recordme-Client is a web application designed to provide automated services for accounting processes. Users can access their accounts, fetch data, and manage their credentials securely. The application offers a seamless experience for users to streamline their accounting tasks efficiently.

Unfetch is an online IDE that enables users to generate, deploy, and run AI agents to automate various tasks. It combines coding capabilities with an online deployment platform, making it easy to create AI agents. Unfetch agents are designed specifically for AI tasks and are compatible with tools like Open AI GPT Store and Langchain. Users can build and deploy AI agents to solve a wide range of tasks efficiently.

AIJ is an AI tool designed to streamline the job application process by automating tasks such as job search, application submission, and answering frequently asked questions. Users can save time and energy by letting AIJ handle these tasks efficiently. The tool also allows users to correct AI mistakes and save common questions for AI to answer. With pricing plans available, AIJ aims to simplify the job application process for users.

JiraGPT is an AI-powered Jira Assistant that simplifies Jira tasks directly from Slack. It allows users to search Jira issues using natural language, eliminating the need for complex JQL queries. By seamlessly integrating with Slack and Jira, JiraGPT provides quick project updates, team member oversight, and efficient bug tracking. The tool ensures data safety by following best practices and encrypting all interactions. With a user-friendly interface and free plan option, JiraGPT transforms the way users interact with Jira.

TED SMRZR is a web application that converts TEDx Talks into short summaries. It uses AI models to fetch the transcript from the TEDx video, punctuate the transcribed data, and then summarize it. The summarized talks are then translated into different languages and compared to similar TEDx Talks for deep insights. TED SMRZR provides nicely punctuated TED Talks to read and short summaries for all the available TED Talks. Users can also select multiple Talks and compare their summaries.

Fletch is the world's first cyber threat AI application that helps users stay ahead of cyber threats by automating busywork with AI agents. It continuously trends the threat landscape, forecasts impact, prioritizes alerts, generates tailored advice, and provides daily proactive insights to guide users in defending against threats. Fletch filters and prioritizes alerts, uncovers weaknesses in SaaS supply chains, and offers timely tactical advice to act fast in critical moments. The application also assists in articulating threat messages and provides instant answers through AskFletch chat. Fletch integrates with existing tools, simplifying users' lives and offering hands-on guidance for businesses of all sizes.

RAFT (Retrieval-Augmented Fine-Tuning) is a method for creating conversational agents that realistically emulate specific human targets. It involves a dual-phase process of fine-tuning and retrieval-based augmentation to generate nuanced and personalized dialogue. The tool is designed to combine interview transcripts with memories from past writings to enhance language model responses. RAFT has the potential to advance the field of personalized, context-sensitive conversational agents.

LLMClient is a JavaScript/TypeScript library that simplifies working with large language models (LLMs) by providing an easy-to-use interface for building and composing efficient prompts using prompt signatures. These signatures enable the automatic generation of typed prompts, allowing developers to leverage advanced capabilities like reasoning, function calling, RAG, ReAcT, and Chain of Thought. The library supports various LLMs and vector databases, making it a versatile tool for a wide range of applications.

Ax is a Typescript library that allows users to build intelligent agents inspired by agentic workflows and the Stanford DSP paper. It seamlessly integrates with multiple Large Language Models (LLMs) and VectorDBs to create RAG pipelines or collaborative agents capable of solving complex problems. The library offers advanced features such as streaming validation, multi-modal DSP, and automatic prompt tuning using optimizers. Users can easily convert documents of any format to text, perform smart chunking, embedding, and querying, and ensure output validation while streaming. Ax is production-ready, written in Typescript, and has zero dependencies.

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.

WebWhiz is an open-source tool that allows users to train ChatGPT on website data to build AI chatbots for customer queries. It offers easy integration, data-specific responses, regular data updates, no-code builder, chatbot customization, fine-tuning, and offline messaging. Users can create and train chatbots in a few simple steps by entering their website URL, automatically fetching and preparing training data, training ChatGPT, and embedding the chatbot on their website. WebWhiz can crawl websites monthly, collect text data and metadata, and process text data using tokens. Users can train custom data, but bringing custom open AI keys is not yet supported. The tool has no limitations on context size but may limit the number of pages based on the chosen plan. WebWhiz SDK is available on NPM, CDNs, and GitHub, and users can self-host it using Docker or manual setup involving MongoDB, Redis, Node, Python, and environment variables setup. For any issues, users can contact [email protected].

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.

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 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

This NVIDIA AI Workbench project is designed for developing a Retrieval Augmented Generation application with a customizable Gradio Chat app. It allows users to embed documents into a locally running vector database and run inference locally on a Hugging Face TGI server, in the cloud using NVIDIA inference endpoints, or using microservices via NVIDIA Inference Microservices (NIMs). The project supports various models with different quantization options and provides tutorials for using different inference modes. Users can troubleshoot issues, customize the Gradio app, and access advanced tutorials for specific tasks.

The serverless-rag-demo repository showcases a solution for building a Retrieval Augmented Generation (RAG) system using Amazon Opensearch Serverless Vector DB, Amazon Bedrock, Llama2 LLM, and Falcon LLM. The solution leverages generative AI powered by large language models to generate domain-specific text outputs by incorporating external data sources. Users can augment prompts with relevant context from documents within a knowledge library, enabling the creation of AI applications without managing vector database infrastructure. The repository provides detailed instructions on deploying the RAG-based solution, including prerequisites, architecture, and step-by-step deployment process using AWS Cloudshell.

RAGGENIE is a low-code RAG builder tool designed to simplify the creation of conversational AI applications. It offers out-of-the-box plugins for connecting to various data sources and building conversational AI on top of them, including integration with pre-built agents for actions. The tool is open-source under the MIT license, with a current focus on making it easy to build RAG applications and future plans for maintenance, monitoring, and transitioning applications from pilots to production.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

Lumos is a Chrome extension powered by a local LLM co-pilot for browsing the web. It allows users to summarize long threads, news articles, and technical documentation. Users can ask questions about reviews and product pages. The tool requires a local Ollama server for LLM inference and embedding database. Lumos supports multimodal models and file attachments for processing text and image content. It also provides options to customize models, hosts, and content parsers. The extension can be easily accessed through keyboard shortcuts and offers tools for automatic invocation based on prompts.

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.

Langchain.rb is a Ruby library that makes it easy to build LLM-powered applications. It provides a unified interface to a variety of LLMs, vector search databases, and other tools, making it easy to build and deploy RAG (Retrieval Augmented Generation) systems and assistants. Langchain.rb is open source and available under the MIT License.

ALLCHAT is a Node.js backend and React MUI frontend for an application that interacts with the Gemini Pro 1.5 (and others), with history, image generating/recognition, PDF/Word/Excel upload, code run, model function calls and markdown support. It is a comprehensive tool that allows users to connect models to the world with Web Tools, run locally, deploy using Docker, configure Nginx, and monitor the application using a dockerized monitoring solution (Loki+Grafana).

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