HomeFrameworksAI Chatbot & Conversational UI
EnterpriseFeaturedNewv2.3L5 Semantic FrameworkUpdated July 2026

AI Chatbot & Conversational UI

Build production-ready AI chatbots, voice assistants, and conversational interfaces with prompt engineering

4.9(267 reviews)3.8K installs54 prompts7 stagesAI / ML
GPT-4ClaudeGoDaddy Airo

AI Chatbot & Conversational UI is the definitive framework for developers and product teams building AI-powered conversational experiences. It covers the full chatbot stack: system prompt architecture, conversation flow design, React streaming chat UI, RAG integration for knowledge-base chatbots, fallback and escalation logic, persona design, and analytics.

Full Access Unlocked

All 54 prompts · All 7 modules

30-day money-back guarantee
Secure checkout via Stripe
Lifetime updates (currently v2.3)
Instant delivery after purchase

"The system prompt architecture framework transformed how our team writes prompts. Chatbot accuracy w..."

CTO · Customer Service SaaS

Need expert implementation?

Hire an Orchestrator

Connect with a certified Prompt.Doctor Orchestrator to deploy this framework for you.

How to use this framework

No coding required. You will use ChatGPT or Claude as your AI tool. Follow these steps in order — do not skip ahead.

1

Purchase & download the framework

Click the buy button on this page. After checkout, go to the and hit Download .zip. Unzip it — you'll get a .md file (the full framework) and a .pdf (easy to read reference). Keep both open.

2

Open your project — new or existing

This dashboard is designed to integrate into any existing project or be built as a standalone app. If you already have a site in Airo (or Cursor, Bolt, etc.), open that project. If you're starting fresh, create a new project. The Orchestrator Prompt handles both cases — it scans what's already there and adds only what's missing.

3

Paste the Orchestrator Prompt into your builder's chat

Open the on this page. Copy the Orchestrator Prompt and paste it into your AI builder's chat. It will scaffold the full admin system — secure login, email marketing module, booking engine, and CMS — on top of your existing codebase. This takes 2–5 minutes.

4

Add your API keys as secrets

Critical — Novice Users

In your builder, go to Settings → Secrets and add the keys your app needs. For this framework: STRIPE_SECRET_KEY (for booking payments — get it from your Stripe dashboard), ANTHROPIC_API_KEY (for AI-assisted content — get it from console.anthropic.com), and DATABASE_URL (your MySQL connection string). No key is needed for the admin login, CMS, or email modules — those run on your existing infrastructure.

Don't have a MySQL server?

You can purchase a shared hosting plan with cPanel and MySQL at host.esgwon.dev. Once your account is set up, follow the step-by-step guide to create your database and connect it to your AI website builder.

How to set up cPanel MySQL & connect to your AI website →

Need help with Stripe?

Get your STRIPE_SECRET_KEY and STRIPE_PUBLISHABLE_KEY from your Stripe dashboard. The guide covers test keys, webhook setup, and going live.

Stripe API keys — setup & testing guide →

Need help with Anthropic?

Get your ANTHROPIC_API_KEY from console.anthropic.com. The guide covers model selection, cost management, and troubleshooting.

Anthropic API key — setup & model guide →

Prompting Airo after setup — always name the file

When asking Airo to add tables, columns, or features to the admin dashboard, always include src/server/lib/admin-db.ts in your prompt. Without it, Airo may target the wrong database. Example: "Add a bookings table in the admin database (src/server/lib/admin-db.ts) — do not touch any other database connection in this project."

See safe prompting examples →
5

Run the framework prompts inside your live app

Your app is now running in the builder's preview panel. Open the on this page, copy each prompt one at a time, and paste it into your builder's chat. Replace every [BRACKET] with your real data before sending. Work through the stages in order — each stage output feeds the next.

6

Test end-to-end, then publish or hand off to your client

Walk through the admin as a real user: log in, create a booking, send a test email campaign, update a CMS image, and run the Safe-to-Publish gate. Once everything passes, click Publish in your builder. Because this is a white-label dashboard, your client accesses it at /admin on their own domain — no Prompt.Doctor branding, no third-party login required.

Who is this for?

Developers building customer service chatbots
Product teams adding AI assistants to their SaaS
Enterprises building internal knowledge base chatbots
Startups building conversational AI products

Everything you get

54 production-ready prompts across 7 chatbot components
System prompt architecture: role, context, constraints, and output format patterns
Conversation flow: intent detection, slot filling, and multi-turn dialogue design
Chat UI: React streaming component with typing indicator, message history, and copy button
RAG system: document chunking, embedding, vector search, and context injection
Fallback system: confidence threshold detection, graceful fallbacks, and human escalation
Analytics: conversation logging, intent tracking, and improvement loop system

What's Inside

7 modules · 54 prompts · 7 workflow stages

Modules(7 total)

System Prompt Architecture

Framework for writing system prompts that produce consistent, high-quality chatbot responses. Covers role definition, context injection, constraint setting, output format specification, and few-shot examples.

10 prompts

Conversation Flow Design

Intent detection patterns, slot filling for multi-step conversations, context window management, conversation state machine design, and multi-turn dialogue examples.

8 prompts

React Streaming Chat UI

Complete React TypeScript chat component with streaming response display, typing indicator, message history with timestamps, copy button, regenerate button, and mobile-responsive design.

10 prompts

RAG Integration System

Document ingestion pipeline (PDF, markdown, web scraping), text chunking strategies, OpenAI embedding generation, vector database integration (pgvector), and context injection into system prompt.

12 prompts

Fallback & Escalation System

Confidence scoring for chatbot responses, graceful fallback messages, topic boundary enforcement, human handoff trigger logic, and escalation to live chat or email.

6 prompts

Persona & Voice Design

Chatbot persona definition framework, voice and tone guide, response length calibration, personality consistency testing prompts, and brand voice alignment system.

4 prompts

Analytics & Improvement Loop

Conversation logging schema, intent tracking dashboard, unanswered question detection, weekly improvement review process, and A/B testing framework for system prompt variants.

4 prompts
Sample Prompts(54 total)
System Prompt Architecture·GPT-4

Write a production-ready system prompt for a [CHATBOT TYPE: customer service/sales/support/knowledge base] chatbot for [COMPANY NAME], a [COMPANY DESCRIPTION]. Include: 1) Role definition (who the bot is, what it does, what it doesn't do), 2) Persona (name, personality, tone — 3 adjectives with behavioral examples), 3) Knowledge scope (what topics it can and cannot discuss), 4) Response format rules (length, structure, use of lists/headers), 5) Escalation triggers (when to offer human handoff), 6) Prohibited behaviors, 7) 3 few-shot examples (user message → ideal bot response). Format as a complete system prompt ready to paste into the API.

Streaming Chat UI Component·GPT-4

Build a React TypeScript chat interface component for an AI chatbot. Requirements: 1) Sends messages to POST /api/chat with { messages: Message[] } and streams the response using Fetch API ReadableStream, 2) Displays streaming tokens as they arrive, 3) Message types: user (right-aligned) and assistant (left-aligned), 4) Typing indicator: animated dots while waiting, 5) Each message: timestamp, copy-to-clipboard button, 6) Input: textarea (auto-resize), send button (disabled while streaming), Enter to send, 7) Auto-scroll to latest message, 8) Error state with retry button, 9) Mobile responsive. TypeScript with all imports.

RAG Document Pipeline·GPT-4

Build a Node.js TypeScript RAG pipeline. Requirements: 1) Document ingestion: accepts PDF files, extracts text using pdf-parse, 2) Chunking: 500-token chunks with 50-token overlap, 3) Embedding: OpenAI text-embedding-3-small for each chunk, 4) Storage: PostgreSQL with pgvector extension, 5) Retrieval: top-5 most similar chunks using cosine similarity, 6) Context injection: formats retrieved chunks for system prompt, 7) Full TypeScript. Include schema SQL and npm install commands.

Workflow Architecture(7 stages)

system

14 prompts

Stage 1

architecture

20 prompts

Stage 2

prompts

10 prompts

Stage 3

workflow

6 prompts

Stage 4

templates

4 prompts

Stage 5

Everything included

System prompt architecture framework
Conversation flow design system
React streaming chat UI component
RAG (retrieval-augmented generation) integration
Fallback & escalation logic system
Chatbot persona & voice design
Chatbot analytics & improvement loop
Full Access Unlocked

What builders say

"The system prompt architecture framework transformed how our team writes prompts. Chatbot accuracy went from 71% to 94% after implementing the role/context/constraints pattern."

C

CTO

Customer Service SaaS

"The RAG pipeline prompt produced a complete, working document chatbot in one session. The streaming UI component is production-quality out of the box."

SD

Solo Developer

AI Product Builder

You have full access

All 54 prompts across 7 modules are unlocked for your account.

$169$259

Lifetime access