Nocode AI Reasoning Agent for Building Apps

Today’s top AI Highlights:

1. Comprehensive Python toolkit for retrieval, re-ranking & RAG

2. First AI reasoning agent for building full-stack no-code applications

3. Hugging Face’s free course on building and using AI agents

4. Give Cursor AI agent an AI team with web search, larger context window, and browser automation

5. Second multimodal AI cursor for your desktop - open source and free

& so much more!

Read time: 3 mins

AI Tutorials

For businesses looking to stay competitive, understanding the competition is crucial. But manually gathering and analyzing competitor data is time-consuming and often yields incomplete insights. What if we could automate this process using AI agents that work together to deliver comprehensive competitive intelligence?

In this tutorial, we'll build a multi-agent competitor analysis team that automatically discovers competitors, extracts structured data from their websites, and generates actionable insights. You'll create a team of specialized AI agents that work together to deliver detailed competitor analysis reports with market opportunities and strategic recommendations.

This system combines web crawling, data extraction, and AI analysis to transform raw competitor website data into structured insights. Using a team of coordinated AI agents, each specializing in different aspects of competitive analysis

We share hands-on tutorials like this 2-3 times a week, designed to help you stay ahead in the world of AI. If you're serious about leveling up your AI skills and staying ahead of the curve, subscribe now and be the first to access our latest tutorials.

Don’t forget to share this newsletter on your social channels and tag Unwind AI (X, LinkedIn, Threads, Facebook) to support us!

Latest Developments

One Python Package for Retrieval and Re-ranking Workflows 🔎📋

Rankify is an open source Python toolkit that combines retrieval, re-ranking, and RAG capabilities into a unified framework, making it easier for developers to build robust search and question-answering systems. The toolkit integrates 40 pre-retrieved benchmark datasets and supports 7 retrieval techniques along with 24 state-of-the-art re-ranking models, saving you from building custom data processing pipelines.

It's designed to be modular and extensible, letting you experiment with different retrieval pipelines while maintaining consistent benchmarking. With ready-to-use document processing tools and built-in evaluation through Ragas integration, you can focus on building your applications rather than wrestling with infrastructure setup.

Key Highlights:

1. Ready-to-Use Retrieval - Rankify supports seven retrieval techniques out-of-the-box, including BM25, DPR, ANCE, BPR, ColBERT, BGE, and Contriever. It also provides pre-built indices for Wikipedia and MS MARCO, saving you the time and resources needed for indexing. This means you can jump directly into retrieval tasks without extensive setup.

2. Comprehensive Re-ranking - The toolkit includes 24 state-of-the-art re-ranking models with 41 sub-methods, offering pointwise, pairwise, and listwise approaches. This extensive range allows developers to experiment with various strategies and fine-tune their ranking performance for specific applications.

3. Document Processing - Built-in PDF to Markdown conversion pipeline that handles multiple formats through optional Pandoc integration. The toolkit automatically manages semantic chunking using binary integer programming and includes a query adapter that optimizes based on usage patterns, reducing the time you spend fine-tuning retrieval performance.

4. Production-Ready Architecture - Designed for seamless scaling from local development to production deployment. The lightweight architecture eliminates dependencies on heavy frameworks like PyTorch or LangChain, resulting in faster performance and reduced complexity in your applications.

Nocode AI Reasoning Agent that can Plan and Build Software 🧠💻

Databutton lets you build full-stack AI applications using natural language, acting as your AI-powered development partner. The system employs an AI agent that generates Python FastAPI endpoints and React components based on natural language descriptions.

The agent not only writes code but also manages infrastructure tasks like API key storage, package management, and deployment. The platform streamlines the entire development workflow from ideation to production, letting you focus on refining your app's logic rather than wrestling with boilerplate code.

Key Highlights:

1. Start with natural language description - Define your app's capabilities in plain language, such as "analyze insurance claim images" or "categorize user feedback." The agent breaks this down into actionable tasks, suggests relevant APIs, and confirms the implementation plan with you before proceeding.

2. Backend Development Flow - The agent translates requirements into FastAPI endpoints, handling API modeling and integrations. Share your API keys once, and the agent manages secure storage and implementation. Monitor progress through detailed server logs and get real-time debugging support.

3. Long Term Memory - It maintains context throughout the development process, allowing you to iteratively refine your apps through natural conversation. The system provides immediate feedback through a live preview environment, making it easy to test and adjust functionality on the fly.

4. Frontend Implementation - Use natural language or upload design screenshots to describe your UI needs. The agent creates React components and integrates with backend capabilities through a simple tagging system. Refine the interface iteratively by requesting specific changes or adding custom components.

5. Deploy and Iterate - Once satisfied with the implementation, deploy directly to AWS or Google Cloud with a click. The platform handles infrastructure setup while giving you access to logs and configurations. Continue enhancing your app by describing new features or directly editing the generated code.

Quick Bites

Anthropic has launched the Economic Index to track AI's evolving impact on jobs and the economy using real-world usage data instead of surveys or forecasts. Analyzing millions of anonymized Claude conversations, the initial report reveals that while 36% of occupations use AI for at least a quarter of their tasks, usage is currently concentrated in software development and technical writing, with a slight tilt toward augmentation (57%) over automation.

Anthropic is open-sourcing this dataset to help researchers and policymakers better understand and prepare for AI's transformation of the labor market.

Zyphra has released Zonos-v0.1 beta, an open-source text-to-speech suite featuring two 1.6B parameter models (transformer and hybrid SSM) under Apache 2.0 license. The models support high-fidelity voice cloning, real-time generation, and emotional control, outperforming other SOTA TTS models. Access available through both an API ($0.02/minute) and model weights on Hugging Face.

Hugging Face has launched a free AI Agents course covering theory, implementation, and practical applications using libraries like smolagents, LangChain, and LlamaIndex. The comprehensive curriculum spans from agent fundamentals to hands-on assignments, with certification options available until May 2025. Live Q&A sessions and Discord support for course material and collaboration.

Tools of the Trade

1. Cursor Tools: CLI tool to enhance Cursor IDE's AI agent with additional tools by integrating Perplexity for web research, Gemini 2.0 for large context window, and Stagehand for browser automation. When installed in a Cursor project, it automatically configures the IDE's AI agent to use these tools through simple commands like "ask Perplexity" or "ask Gemini."

2. Gemini Cursor: Open source desktop application that creates a second AI-powered cursor which can see your screen, hear your voice, and provide real-time visual and verbal guidance while you navigate your computer. It is built using Google’s Multimodal Live API.

3. AI Agent Workflow by Simple-ai.dev: Pre-built AI agent workflows and React Flow components that can be copied directly via the shadcn CLI. It has four main workflow patterns (Chain, Routing, Parallelization, and Orchestrator-Workers) based on Anthropic's agent architecture principles, implemented using Vercel AI SDK and xyflow for visual node-based development.

4. Awesome LLM Apps: Build awesome LLM apps with RAG, AI agents, and more to interact with data sources like GitHub, Gmail, PDFs, and YouTube videos, and automate complex work.

Hot Takes

1. A world-changing idea for the European Union:
   Find a way to stop the "allow cookies" nonsense on every website, and the entire world will forever be grateful to you.
   You ruined the Internet. ~
   Santiago

   
   

2. No entrepreneur is worried about an AI taking their job. ~
   Naval Ravikant

That’s all for today! See you tomorrow with more such AI-filled content.

Don’t forget to share this newsletter on your social channels and tag Unwind AI to support us!

Unwind AI - X | LinkedIn | Threads | Facebook

Awesome LLM Apps | Sponsor Us

PS: We curate this AI newsletter every day for FREE, your support is what keeps us going. If you find value in what you read, share it with at least one, two (or 20) of your friends 😉