Refactor chatbot project

🎯 1. Analyze the Existing Repository • Study the attached repository (chatbot using Ollama, system-prompt management, UI features, TTS using edge-tts). • Identify: • What was done correctly (architecture, modularity, UI ideas, TTS handling). • What was done poorly (UI/UX flaws, code structure, scalability issues, missing error handling, inefficient API usage). • Use this analysis to form a new architecture plan and development strategy for CLIne. ⸻ 🏗️ 2. Instruct CLIne to Rebuild the Project With Major Improvements The prompt generated must tell CLIne to: • Create a fully refactored project using modern coding standards. • Improve the chatbot system by: • Better system-prompt management and saving. • Using Ollama with selectable models. • Improved TTS (not edge-tts; suggest better alternatives like Piper, Coqui TTS, etc.). • Stronger error handling and async handling. • Redesign the frontend with improved UI/UX, accessibility, smooth state management, and animations where appropriate. THE MOST IMPORTANT IMPROVEMENT - You are going to implement graph RAG all done and stored locally. At all options you should choose free and local options. All inference for instance is done locally. Some ideas include integrating MCP server capabilities to allow better results. ⸻ 📂 3. CLIne Must Generate the Following Documents in /docs or root folder: File Purpose ai_guidelines.md Rules for how the AI agent should write, refactor, and review code. checklist.md A living progress tracker for CLIne. architecture.md High-level system architecture, data flows, components, backend/frontend layers. prompts.md Reusable task prompts for CLIne (coding, debugging, testing, deployment, etc). testing.md Full test architecture: unit, integration, UI testing, mock data, LLM testing. security.md Security concerns: prompt injection, API abuse, XSS, CORS, user data risks. design.md Visual design system, component structure, layout decisions, color/font hierarchy. uxui.md User experience requirements: navigation flow, modal/dialog patterns, prompt workflows. readme.md Professional open-source-level documentation (installation, features, screenshots, demo, contribution). deployment.md CI/CD, Docker, hosting (Render, Vercel, Netlify), environment variables. oadmap.md Future release planning and feature milestones. ⸻ ⚙️ 4. Development Expectations for CLIne The instructions inside the prompt must require CLIne to: • Use modular, scalable architecture. • Use TypeScript on frontend/React, Python or Node for backend (unless otherwise decided). • Implement state management (Zustand, Redux, or React Query). • Create reusable components for chat UI, system prompt editor, model selection dropdown, settings panel. • Improve TTS with pluggable drivers. • Persist data (settings, saved prompts) in local storage or database. • Add hotkeys/keyboard navigation. • Implement dark/light mode. ⸻ ✅ 5. Output Formatting for Your Response Your response must: • That final prompt should be clearly written as a command/instruction to generate the CLine prompt. • Do not add explanations, commentary, or markdown outside of the final prompt text. ⸻ ----NOW REwrite this prompt to be more clear and reflect https://github.com/kliewerdaniel/bot02.git

Generate a clear and comprehensive instruction prompt for CLIne to rebuild the project located at **https://github.com/kliewerdaniel/bot02.git** with major improvements and the architecture plan below: ``` You are CLIne. Your task is to **clone** the repository at https://github.com/kliewerdaniel/bot02.git and then **fully refactor and rebuild** it according to the following enhanced architecture and development strategy. 1. Project Refactor & Modern Standards • Use a **modular, scalable architecture**. • Frontend: Use **TypeScript + React**. • Backend: Use **Python** or **Node.js** (choose one) with async/await handling. • State management on the frontend: choose **Zustand**, **Redux**, or **React Query**. • Persist user settings and saved system prompts to **local storage** or a lightweight local database. • Support **dark/light mode**, **keyboard hotkeys/navigation**, and **accessibility** standards. 2. Chatbot System Improvements • System-prompt management: allow create/edit/save/manage system prompts with a persistent store. • Integrate entity["software","Ollama",0] with **selectable models**, all inference done locally or via free/local options. • Implement a **graph-RAG retrieval system** fully local: vector store + embeddings + retrieval + inference done locally (no paid cloud LLM). • Choose a local/open-source TTS engine (for example entity["software","Piper",0] or entity["software","Coqui TTS",0]) instead of edge-tts; design it with pluggable drivers so additional TTS backends can be added easily. • Comprehensive error handling: backend and frontend must handle API errors, missing model files, retrieval failures, invalid input. • Async handling throughout (API calls, embedding generation, model inference, TTS streaming). 3. Frontend / UI/UX Redesign • Redesign chat UI: clean, modern, responsive, with smooth animations where appropriate. • Provide a **system prompt editor** UI component, a **model selection dropdown**, a **settings panel**. These must be **reusable components**. • Ensure smooth state management of chat sessions, model switching, prompt templates. • Optimize UX: keyboard shortcuts, focus management, input history navigation, accessibility (aria, screen-reader support). • Dark and light themes with user toggle and persistent preference. 4. Architecture Plan & Documentation • In `/docs` or project root generate these files: - `ai_guidelines.md`: Rules for how the AI agent writes, refactors, and reviews code. - `checklist.md`: A living progress tracker for CLIne’s tasks. - `architecture.md`: High-level system architecture, data flows, components, backend/frontend layers. - `prompts.md`: Reusable task prompts for CLIne (coding, debugging, testing, deployment, etc). - `testing.md`: Full test architecture covering unit tests, integration tests, UI tests, mock data, LLM testing. - `security.md`: Security concerns including prompt injection, API abuse, XSS, CORS, user data risks. - `design.md`: Visual design system, component structure, layout decisions, color/font hierarchy. - `uxui.md`: User experience requirements: navigation flow, modals/dialog patterns, prompt workflows. - `readme.md`: Professional open-source-level documentation (installation, features, screenshots, demo, contribution guidelines). - `deployment.md`: CI/CD pipeline, Docker setup, hosting options (Render, Vercel, Netlify), environment variables. - `roadmap.md`: Future release planning and feature milestones. 5. Development Expectations • Use **modular architecture**: clear separation between UI components, state management, backend services, data layer. • Implement frontend in TypeScript + React. • Backend in Python or Node, with async handling, modular services (model interface, retrieval engine, TTS driver). • Use **state management library** on frontend. • Create reusable components: ChatUI, SystemPromptEditor, ModelDropdown, SettingsPanel. • TTS system must support pluggable drivers and fallback mechanisms. • Persist settings & prompts locally or in a small DB. • Add **keyboard hotkeys** (e.g., Esc to clear chat, Ctrl+Enter to send, Up arrow to browse history). • Provide dark/light theme toggle with persistent preference. Your output must be **only** this instruction prompt text (no additional commentary).

🎯 1. Analyze the Existing Repository • Study the attached repository (chatbot using Ollama, system-prompt management, UI features, TTS using edge-tts). • Identify: • What was done correctly (architecture, modularity, UI ideas, TTS handling). • What was done poorly (UI/UX flaws, code structure, scalability issues, missing error handling, inefficient API usage). • Use this analysis to form a new architecture plan and development strategy for CLIne. ⸻ 🏗️ 2. Instruct CLIne to Rebuild the Project With Major Improvements The prompt generated must tell CLIne to: • Create a fully refactored project using modern coding standards. • Improve the chatbot system by: • Better system-prompt management and saving. • Using Ollama with selectable models. • Improved TTS (not edge-tts; suggest better alternatives like Piper, Coqui TTS, etc.). • Stronger error handling and async handling. • Redesign the frontend with improved UI/UX, accessibility, smooth state management, and animations where appropriate. THE MOST IMPORTANT IMPROVEMENT - You are going to implement graph RAG all done and stored locally. At all options you should choose free and local options. All inference for instance is done locally. Some ideas include integrating MCP server capabilities to allow better results. ⸻ 📂 3. CLIne Must Generate the Following Documents in /docs or root folder: File Purpose ai_guidelines.md Rules for how the AI agent should write, refactor, and review code. checklist.md A living progress tracker for CLIne. architecture.md High-level system architecture, data flows, components, backend/frontend layers. prompts.md Reusable task prompts for CLIne (coding, debugging, testing, deployment, etc). testing.md Full test architecture: unit, integration, UI testing, mock data, LLM testing. security.md Security concerns: prompt injection, API abuse, XSS, CORS, user data risks. design.md Visual design system, component structure, layout decisions, color/font hierarchy. uxui.md User experience requirements: navigation flow, modal/dialog patterns, prompt workflows. readme.md Professional open-source-level documentation (installation, features, screenshots, demo, contribution). deployment.md CI/CD, Docker, hosting (Render, Vercel, Netlify), environment variables. oadmap.md Future release planning and feature milestones. ⸻ ⚙️ 4. Development Expectations for CLIne The instructions inside the prompt must require CLIne to: • Use modular, scalable architecture. • Use TypeScript on frontend/React, Python or Node for backend (unless otherwise decided). • Implement state management (Zustand, Redux, or React Query). • Create reusable components for chat UI, system prompt editor, model selection dropdown, settings panel. • Improve TTS with pluggable drivers. • Persist data (settings, saved prompts) in local storage or database. • Add hotkeys/keyboard navigation. • Implement dark/light mode. ⸻ ✅ 5. Output Formatting for Your Response Your response must: • That final prompt should be clearly written as a command/instruction to generate the CLine prompt. • Do not add explanations, commentary, or markdown outside of the final prompt text. ⸻ ----NOW REwrite this prompt previous to be more clear and reflect https://github.com/kliewerdaniel/bot02.git as the basis of the project which the LLM will have access to analyse, your job is to output only that prompt I am going to give the LLM to generate the prompt to give to CLIne

Write a prompt for CLIne with the following command: ``` You are CLIne. Your task is to clone the repository at https://github.com/kliewerdaniel/bot02.git and then fully refactor and rebuild it according to the enhanced architecture and development strategy below. 1. Project Refactor & Modern Standards • Use a modular, scalable architecture. • Frontend: Use TypeScript + React. • Backend: Use Python or Node.js (choose one) with async/await handling. • State management on the frontend: choose Zustand, Redux, or React Query. • Persist user settings and saved system prompts to local storage or a lightweight local database. • Support dark/light mode, keyboard hotkeys/navigation, and accessibility standards. 2. Chatbot System Improvements • System-prompt management: allow create/edit/save/manage system prompts with a persistent store. • Integrate Ollama with selectable models, all inference done locally or via free/local options. • Implement a graph-RAG retrieval system fully local: vector store + embeddings + retrieval + inference done locally (no paid cloud LLM). • Choose a local/open-source TTS engine (for example Piper or Coqui TTS) instead of edge-tts; design it with pluggable drivers so additional TTS backends can be added easily. • Comprehensive error handling: backend and frontend must handle API errors, missing model files, retrieval failures, invalid input. • Async handling throughout (API calls, embedding generation, model inference, TTS streaming). 3. Frontend / UI/UX Redesign • Redesign chat UI: clean, modern, responsive, with smooth animations where appropriate. • Provide a system prompt editor UI component, a model selection dropdown, a settings panel. These must be reusable components. • Ensure smooth state management of chat sessions, model switching, prompt templates. • Optimize UX: keyboard shortcuts, focus management, input history navigation, accessibility (aria, screen-reader support). • Dark and light themes with user toggle and persistent preference. 4. Architecture Plan & Documentation • In /docs or project root generate these files: - ai_guidelines.md: Rules for how the AI agent writes, refactors, and reviews code. - checklist.md: A living progress tracker for CLIne’s tasks. - architecture.md: High-level system architecture, data flows, components, backend/frontend layers. - prompts.md: Reusable task prompts for CLIne (coding, debugging, testing, deployment, etc). - testing.md: Full test architecture covering unit tests, integration tests, UI tests, mock data, LLM testing. - security.md: Security concerns including prompt injection, API abuse, XSS, CORS, user data risks. - design.md: Visual design system, component structure, layout decisions, color/font hierarchy. - uxui.md: User experience requirements: navigation flow, modals/dialog patterns, prompt workflows. - readme.md: Professional open-source-level documentation (installation, features, screenshots, demo, contribution guidelines). - deployment.md: CI/CD pipeline, Docker setup, hosting options (Render, Vercel, Netlify), environment variables. - roadmap.md: Future release planning and feature milestones. 5. Development Expectations • Use modular architecture: clear separation between UI components, state management, backend services, data layer. • Implement frontend in TypeScript + React. • Backend in Python or Node, with async handling, modular services (model interface, retrieval engine, TTS driver). • Use state management library on frontend. • Create reusable components: ChatUI, SystemPromptEditor, ModelDropdown, SettingsPanel. • TTS system must support pluggable drivers and fallback mechanisms. • Persist settings & prompts locally or in a small DB. • Add keyboard hotkeys (e.g., Esc to clear chat, Ctrl+Enter to send, Up arrow to browse history). • Provide dark/light theme toggle with persistent preference. Your output must be only this instruction prompt text (no additional commentary). ```