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DocTextExtractor: A Flutter Package to Extract Text from Word, PDF, Google Docs, and Markdown

DocTextExtractor is a Dart package created to extract text from various formats like .doc, .docx, .pdf, Google Docs URLs, and .md files.
The tool was developed to support NotteChat, an app facilitating conversational interaction with documents using AI.
Challenges in supporting multiple document formats led to the creation of DocTextExtractor for seamless text extraction.
Key features include unified API, clean filename extraction, minimal dependencies, and cross-platform support.
Various technologies like http, syncfusion_flutter_pdf, archive + xml, and markdown were used to build DocTextExtractor.
The Dart package offers a TextExtractor class with features like unified return types, smart format detection, and offline support.
Format-specific logic was applied for .doc, .docx, .md, PDF, and Google Docs for efficient text extraction.
DocTextExtractor is crucial for NotteChat's AI-powered document chat, enabling AI chat, offline use, smart UX, and versatile support.
Steps to integrate DocTextExtractor into Flutter apps involve adding dependencies, importing, initializing, and extracting text from URLs or local files.
Integration with AI APIs like OpenAI, Gemini, or Sonar can enhance app functionality using extracted text.

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Dev

300

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Deploying Storage Solution for Testing and Training.

A technical specification for a storage infrastructure has been outlined for the IT department's testing and training environments with a focus on scalability, high availability, and performance.
To set up the project resources, a resource group needs to be created in the Azure portal with a specified name and region for consistent use.
For facilitating testing and training, a storage account must be set up in the Azure portal with basic settings like Locally-redundant storage (LRS) and Secure transfer enabled.
To ensure security and efficiency, configurations like Minimum TLS version 1.2, Disable storage account key access, and enabling public network access from all networks need to be implemented.

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Johndcook

378

Multiplying by quaternions on the left and right

The map that takes a quaternion x to the quaternion qx is linear, represented as multiplication by a matrix.
The matrix representation for multiplying on the left by q is different from the matrix representation for multiplying on the right by q.
One can prove both matrix representations are correct by demonstrating their accuracy when q = 1, i, j, and k.
The post discusses how to represent rotations with quaternions and provides an equation for the equivalent rotation matrix for a rotation described by a quaternion.

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Dev

104

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ApostropheCMS 4.17.0: Live widget preview now default and image cropping shortcut

ApostropheCMS 4.17.0 update includes a more intuitive image widget editing experience with a streamlined workflow for adjusting image cropping and focal point.
The live widget preview feature is now enabled by default, providing immediate visual feedback as users type or select options in the widget modal.
Developers can extend any widget's capabilities using the new widgetOperations cascade config property, allowing for the addition of custom operations to the menu interface.
Enhanced documentation is on the way to help developers create better editorial interfaces, covering topics like configuring the admin bar, adding support desk help, tooltips, and more to elevate the quality of editorial experiences.

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6 Likes

Medium

133

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Designing Reliable Distributed Systems: Transactional Outbox- Inbox Pattern

The Outbox-Inbox pattern ensures end-to-end delivery guarantees between services in an event-driven architecture.
The pattern consists of two sides - Outbox and Inbox, where the Inbox acts as a local, persistent ledger of received and handled messages.
This pattern does not replace other messaging patterns but instead works in conjunction to create a resilient messaging layer.
Consider including the outbox event ID as the message key when sending across Kafka to ensure uniqueness and reliable message delivery.

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Dev

341

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The Rise of AI Agents in 2025

In 2025, AI agents have become transformative tools for business automation, with their capabilities expanding rapidly.
Approximately 25% of companies using AI plan to launch agentic AI pilots in 2025, increasing to 50% by 2027.
AI agents have evolved from rule-based chatbots to autonomous multi-agent systems, capable of observing, reasoning, planning, and executing tasks.
Technological advancements enabling modern AI agents include foundation models, agent memory systems, planning frameworks, and tool integration.
Types of AI agents dominating in 2025 include multi-agent systems, purpose-built industry-specific agents, and consumer-facing personal assistant agents.
Business impact and use cases of AI agents include process automation, customer service enhancements, decision support, and business intelligence.
Challenges in AI agent implementation involve integration with existing systems, security and privacy considerations, and training and adoption hurdles.
Future outlooks for AI agents beyond 2025 include increased autonomy, enhanced collaboration, specialized verticals, and democratized development.
Industry standards are emerging around agent interoperability, security protocols, testing methodologies, and ethical guidelines for AI agents.
AI agents represent a significant shift in how organizations approach automation and decision support, offering measurable business value and new opportunities for efficiency.

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Dev

369

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The “Pizza Shop Principle” for React Developers 🍕

React developers can benefit from the 'Pizza Shop Principle' where every React project is likened to a pizza shop with different components representing various elements of a restaurant.
The focus is on delivering value to users rather than perfecting technical aspects like the 'dough' or 'oven.'
Validation of product ideas, building a minimum viable product (MVP) quickly, pricing software based on value, and targeting local businesses are key strategies suggested.
Using React's component model to iterate quickly, deploy efficiently, and charge appropriately for the value provided is emphasized.
The article encourages React developers to think like a 'digital chef' or a 'product creator' and offers practical steps to improve product development and pricing strategies.
Key takeaways include validating early, building fast, shipping quickly, pricing according to value, and embracing iteration.
By following the 'Pizza Shop Rules for Devs,' developers are advised to focus on serving customers, delivering on time, and seeking feedback rather than striving for perfection.
The article concludes by urging React developers to view their work as a culinary endeavor, aiming to satisfy the digital hunger of users and generate revenue from their creations.
Ultimately, the analogy of a pizza shop serves as a reminder to prioritize user satisfaction and business value in React development projects.

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Dev

218

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Learning Python by Teaching Your Computer to Be Petty and Petty Good at It

Learn Python by creating a program that tracks and shames you for overusing certain apps like Slack, YouTube, Steam, etc.
The program involves file handling, scheduling tasks, conditional logic, and notifications, providing practical Python script-building experience.
Using the psutil library, the script monitors the activity of specific programs and updates a count in a JSON file.
It includes a feature to issue humorous notifications when app usage crosses a certain threshold.
The script can be scheduled to run automatically using the 'schedule' module in Python.
The project highlights tracking app usage, creating persistent counters, and using humor to aid learning.
The article suggests exploring more Python projects, setting usage limits, building dashboards, and integrating with APIs like Twitter.
Learning through practical, humorous projects can help solidify Python skills and solve real-world problems in creative ways.
The article also mentions resources for Python developers and encourages building projects that align with personal interests.
The final message is to keep learning, coding, and exploring unique Python projects that combine humor and productivity.
The author shares insights on using Python to build tools that encourage productivity in a playful manner.

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Dev

159

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Dev ADHD: Why You Can Build Anything But Launch Nothing

Dev ADHD refers to the struggle of developers to launch projects despite being able to build them quickly.
The issue stems from solving boredom rather than real problems, leading to unfinished projects.
To succeed, developers must focus on addressing clear, annoying, and expensive problems that people are willing to pay for.
Rather than chasing big ideas, developers should aim to create painkillers that solve real pain points for users.
A 7-day launch shortcut is suggested, involving finding a niche, writing a simple offer, sharing it, building the easiest version, and delivering with feedback.
It is emphasized that developers can make money without writing a single line of code by selling results, tutorials, or using automation tools.
Looking for tasks people are willing to pay for, selling before building, and focusing on launching quickly are key strategies to overcome Dev ADHD.
Developers are advised to pair their ability to build with the courage to launch faster and solve real pain points to achieve success.
The article encourages developers to shift their focus from frameworks and numerous ideas to delivering one impactful solution that addresses a real need.
In conclusion, the key takeaway is to stop building unnecessary apps, identify tasks that people will pay to avoid, sell before building, and use tools for faster launches.

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Dev

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🕵️‍♂️ The Sherlock Holmes Method for AI Startups

The article presents the 'Sherlock Holmes Method' for AI startups, emphasizing the importance of addressing real-world problems and market needs.
It highlights the significance of finding urgent, specific problems and using AI to automate tasks in niche industries that face high-friction workflows.
The framework suggests starting with a minimal viable landing page before diving into backend development to validate ideas quickly and effectively.
Advice includes conducting thorough market research, collecting leads, documenting progress, and focusing on providing tangible relief to customers rather than flashy demos.
By following these principles, developers can build AI solutions that cater to overlooked niches, solve critical pains, and ultimately, monetize effectively.
The 'Sherlock Holmes Method' encourages developers to adopt investigative approaches, leverage local SEO, and engage with potential customers in a strategic and transparent manner.
The article suggests that successful AI startups focus on delivering solutions that address real needs, rather than just showcasing technical capabilities.
Implementing the strategies outlined in the article can help AI startups gain traction, solve market needs efficiently, and build sustainable businesses in overlooked niches.
The framework underscores the importance of building trust, validating ideas through customer interaction, and consistently refining solutions based on feedback.
Ultimately, the key takeaway is that AI startups should prioritize solving real problems, engaging with the target market effectively, and delivering tangible value to customers in order to thrive in the competitive landscape.
By following the 'Sherlock Holmes Method,' developers can elevate their AI startups by focusing on investigative problem-solving, market validation, and customer-centric product development.

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2 Likes

Dev

354

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🔥 How AI Tools Like Copilot & Tabnine Are Transforming Dev Workflows in 2025

In 2025, AI coding assistants like GitHub Copilot, Tabnine, and Amazon CodeWhisperer are revolutionizing how developers code, debug, and deploy.
Modern AI tools go beyond autocompletion, offering context-aware code suggestions, real-time error detection, automated test generation, and in-line documentation support.
These AI tools are enhancing developer productivity by saving time in writing boilerplate code, debugging errors, writing tests, and researching syntax.
Popular AI coding tools in 2025 include GitHub Copilot, Tabnine, Amazon CodeWhisperer, and Cody by Sourcegraph, each catering to specific developer needs and enhancing overall efficiency.

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Dev

236

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Imperative vs Declarative Deployment Approach in Kubernetes

Kubernetes offers imperative and declarative approaches for deployment.
Imperative approach involves manual execution of commands, while the declarative approach defines a desired state in a YAML file.
The declarative approach simplifies management, reduces errors, and allows for easy sharing of configurations.
Using the declarative approach in Kubernetes offers a reliable, scalable, and maintainable way to manage applications with consistency and automation.

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Dev

127

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How to Show Details on Hover in HTML with CSS?

Hover effects in web development are useful for displaying additional information without cluttering the user interface.
CSS hover effects involve changing styles when a user hovers over an element, allowing for the display of extra details.
In an Angular application, extra details can be shown when hovering over a table cell containing an item's name using simple HTML and CSS techniques.
To achieve this, the tooltip is styled with CSS to appear below the hovered element and reveal the details, enhancing user experience.

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7 Likes

Pymnts

369

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Expedia Adds APIs to B2B Platform to Help Build Travel Packages

Expedia Group enhanced its B2B platform, Private Label Solutions, by adding APIs to help partners build travel packages.
The new APIs include offerings for rental cars, bookable experiences, trip protection insurance, and air travel integration to facilitate all-in-one booking.
Expedia Group also introduced a Reservation Management API for hoteliers to manage bookings and traveler experience more effectively.
The company unveiled Expedia Trip Matching on Instagram and tools by Expedia Group Advertising to help travel advertisers create shoppable content and target high-intent audiences.

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Medium

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Google’s Gemini 2.5 Pro Introduces Unprecedented 1 Million Token Context Window

Google’s Gemini 2.5 Pro introduces an unprecedented 1 million token context window for analyzing vast datasets.
The model can process entire novels, extensive codebases, or feature-length films in a single session without fragmenting data.
Gemini 2.5 Pro offers seamless multimodal analysis, handling text, images, audio, and video for various tasks like interpreting tutorial videos and generating text based on visual inputs.
The model employs step-by-step reasoning for enhanced accuracy in complex tasks such as coding and mathematical problem-solving.

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