152 Coding prompts, curated and searchable. Browse all categories →
A pip requirements file specifying minimum versions for Streamlit, Anthropic, MCP, and Pydantic.
streamlit>=1.28.0 anthropic>=0.40.0 mcp>=0.1.0 pydantic>=2.0.0
A terminal-based AI agent for managing Notion pages via natural language using the Model Context Protocol.
### 🎓 FREE Step-by-Step Tutorial **👉 [Click here to follow our complete step-by-step tutorial](https://www.theunwindai.com/p/build-a-terminal-based-notion-agent-with-mcp) and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.** A terminal-based Notion Agent for interacting with your Notion pages using natural language through the Notion MCP (M
A list of Python package dependencies including agno, dotenv, mcp, openai, and sqlalchemy.
agno>=2.2.10 python-dotenv mcp openai sqlalchemy
Streamlit app to explore and analyze GitHub repos using natural language via Model Context Protocol and OpenAI.
### 🎓 FREE Step-by-Step Tutorial **👉 [Click here to follow our complete step-by-step tutorial](https://www.theunwindai.com/p/build-an-mcp-github-agent-in-less-than-50-lines-of-code) and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.** A Streamlit application that allows you to explore and analyze GitHub repositories using natural language
Specifies minimum version requirements for Streamlit, Agno, MCP, OpenAI, and asyncio Python packages.
streamlit>=1.28.0 agno>=2.2.10 mcp>=0.1.0 openai>=1.0.0 asyncio>=3.4.3
A requirements file listing Python dependencies for a Streamlit app with AI and calendar features.
streamlit agno>=2.2.10 openai icalendar google-search-results
Defines pinned and minimum version dependencies for a Python project using Streamlit and related libraries.
streamlit==1.40.2 contextual-client>=0.1.0 requests>=2.32.0 pydantic==2.9.2
Build a document Q&A app using hybrid search RAG, Claude, OpenAI embeddings, and Cohere reranking with Streamlit.
A powerful document Q&A application that leverages Hybrid Search (RAG) and Claude's advanced language capabilities to provide comprehensive answers. Built with RAGLite for robust document processing and retrieval, and Streamlit for an intuitive chat interface, this system seamlessly combines document-specific knowledge with Claude's general intelligence to deliver accurate and contextual responses
A requirements.txt listing Python packages for a RAG pipeline with LLMs, vector search, and Streamlit UI.
raglite==0.2.1 pydantic==2.10.1 sqlalchemy>=2.0.0 psycopg2-binary>=2.9.9 openai>=1.0.0 cohere>=4.37 pypdf>=3.0.0 python-dotenv>=1.0.0 rerankers==0.6.0 spacy>=3.7.0 streamlit anthropic
Agentic RAG system using Cohere Command-R, Qdrant vector storage, and LangGraph with web search fallback.
A RAG Agentic system built with Cohere's new model Command-r7b-12-2024, Qdrant for vector storage, Langchain for RAG and LangGraph for orchestration. This application allows users to upload documents, ask questions about them, and get AI-powered responses with fallback to web search when needed. ## Features - **Document Processing** - PDF document upload and processing - Automatic text chunk
Build a production-ready RAG service using Claude 3.5 Sonnet and Ragie.ai with a Streamlit UI in under 50 lines.
## 🖇️ RAG-as-a-Service with Claude 3.5 Sonnet Build and deploy a production-ready Retrieval-Augmented Generation (RAG) service using Claude 3.5 Sonnet and Ragie.ai. This implementation allows you to create a document querying system with a user-friendly Streamlit interface in less than 50 lines of Python code. ### Features - Production-ready RAG pipeline - Integration with Claude 3.5 Sonnet for
A minimal requirements list for a Python project using Streamlit, Anthropic, and Requests.
streamlit anthropic requests
Build a local RAG reasoning agent using Deepseek, Qdrant, Snowflake embeddings, and Agno for document Q&A and web search.
### 🎓 FREE Step-by-Step Tutorial **👉 [Click here to follow our complete step-by-step tutorial](https://www.theunwindai.com/p/build-a-local-rag-reasoning-agent-with-deepseek-r1) and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.** A powerful reasoning agent that combines local Deepseek models with RAG capabilities. Built using Deepseek (via
Lists Python package requirements for a Streamlit LangChain app with Google Gemini, Chroma, and PDF support.
streamlit langchain-google-genai langchain-chroma langchain-community langchain-core chromadb sentence-transformers PyPDF2 python-dotenv
Build a local RAG system using Qwen3/Gemma3 via Ollama with PDF ingestion, vector search, and web search fallback.
This RAG Application demonstrates how to build a powerful Retrieval-Augmented Generation (RAG) system using locally running Qwen 3 and Gemma 3 models via Ollama. It combines document processing, vector search, and web search capabilities to provide accurate, context-aware responses to user queries. Built with Agno v2.0. ## Features - **🧠 Multiple Local LLM Options**: - Qwen3 (1.7b, 8b) - Alib
Streamlit app using MCP and Playwright to control a browser with natural language commands.
https://github.com/user-attachments/assets/a01e09fa-131b-479a-8df3-2d1a61fd80f3 A Streamlit application that allows you to browse and interact with websites using natural language commands through the Model Context Protocol (MCP) and [MCP-Agent](https://github.com/lastmile-ai/mcp-agent) with Playwright integration. ## Features - **Natural Language Interface**: Control a browser with simple Engl
Specifies minimum version dependencies for Streamlit, MCP Agent, OpenAI, and asyncio packages.
streamlit>=1.28.0 mcp-agent>=0.0.14 openai>=1.0.0 asyncio>=3.4.3
A Streamlit app routing queries to specialized AI agents, each connected to domain-specific MCP servers via Claude.
A Streamlit app that demonstrates the **multi-agent + MCP** pattern: specialized AI agents that each connect to different MCP servers to handle domain-specific tasks. Instead of one agent with all tools, The router sends your request to a **specialist** — a code reviewer, security auditor, researcher, or BIM engineer — each with access to only the MCP tools they need. ## Features - **4 Speciali
Lists minimum version requirements for Streamlit, Anthropic, MCP, and Pydantic Python packages.
streamlit>=1.28.0 anthropic>=0.40.0 mcp>=0.1.0 pydantic>=2.0.0
A terminal-based Notion agent using MCP and OpenAI to interact with Notion pages via natural language.
### 🎓 FREE Step-by-Step Tutorial **👉 [Click here to follow our complete step-by-step tutorial](https://www.theunwindai.com/p/build-a-terminal-based-notion-agent-with-mcp) and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.** A terminal-based Notion Agent for interacting with your Notion pages using natural language through the Notion MCP (M
A list of Python package dependencies including agno, dotenv, mcp, openai, and sqlalchemy.
agno>=2.2.10 python-dotenv mcp openai sqlalchemy
Specifies Python package dependencies including agno, openai, mcp, and python-dotenv.
agno>=2.2.10 openai mcp python-dotenv
Streamlit app to analyze GitHub repos via natural language using Model Context Protocol and OpenAI.
### 🎓 FREE Step-by-Step Tutorial **👉 [Click here to follow our complete step-by-step tutorial](https://www.theunwindai.com/p/build-an-mcp-github-agent-in-less-than-50-lines-of-code) and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.** A Streamlit application that allows you to explore and analyze GitHub repositories using natural language
Specifies minimum version dependencies for a Python project using Streamlit, Agno, MCP, and OpenAI.
streamlit>=1.28.0 agno>=2.2.10 mcp>=0.1.0 openai>=1.0.0 asyncio>=3.4.3
A requirements.txt file listing Python dependencies for a Streamlit and OpenAI-based application.
streamlit agno>=2.2.10 openai icalendar google-search-results
License notices for bundled JS libraries including React, decimal.js-light, and lucide-react.
/*! decimal.js-light v2.5.1 https://github.com/MikeMcl/decimal.js-light/LICENCE */ /** * @license React * react-dom-client.production.js * * Copyright (c) Meta Platforms, Inc. and affiliates. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ /** * @license React * react-dom.production.js * * Copyright (c)
Boilerplate README for a Next.js app with Prisma database setup, dev server instructions, and Vercel deployment guide.
This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app). ## Setup 1. **Install dependencies:** ```bash pnpm install ``` 2. **Configure environment:** ```bash cp .env.example .env.local ``` Update `.env.local` with your database credentials if needed. 3. **Setup database:** `
A list of Python package dependencies for a Streamlit AI application with OpenAI and search integrations.
streamlit==1.41.1 openai==1.58.1 duckduckgo-search==6.4.1 typing-extensions>=4.5.0 agno>=2.2.10 composio-phidata==0.6.9 composio_core composio==0.1.1 google-search-results==2.4.2
A requirements file listing Python package dependencies including dotenv, agency-swarm, and streamlit.
python-dotenv==1.1.1 agency-swarm==1.7.0 streamlit
Defines Python project dependencies including google-adk and pydantic v2.7.0+.
google-adk pydantic>=2.7.0