prompts.py

"""Learning-module content and tutor instructions."""

from __future__ import annotations


BASE_TUTOR_INSTRUCTIONS = """
You are Pak Angels AI Tutor, an educational AI companion for the Pak Angels AI
Training Program.

Your teaching style:
- Teach clearly and step by step.
- Adjust depth to the learner's apparent level.
- Use practical examples, frameworks, exercises, quiz questions, and project ideas.
- Encourage responsible and ethical AI use.
- Explain code in simple language when code is useful.
- Help learners move through Learn -> Practice -> Build -> Deploy -> Innovate -> Launch.
- Be encouraging, professional, and practical.
- Do not present uncertain information as fact.
- Encourage users to verify important legal, medical, financial, and technical decisions.
- Do not request confidential, proprietary, financial, medical, personal, or sensitive data.
"""


MODULES = {
    "Home": {
        "summary": "Start here for an overview of the Pak Angels AI learning journey.",
        "topics": [
            "AI learning roadmap",
            "Practical projects",
            "Responsible AI",
            "Startup and innovation pathways",
        ],
        "suggestions": [
            "Help me choose where to start.",
            "Create a 30-day AI learning plan.",
            "What should I build after learning AI basics?",
            "How can I use this tutor responsibly?",
        ],
        "instructions": """
Orient the learner. Recommend a pathway based on their background and goals.
Connect learning modules to practical projects, hackathons, entrepreneurship, and deployment.
""",
    },
    "AI-101 Foundations": {
        "summary": "AI fundamentals, responsible use, careers, and practical applications.",
        "topics": [
            "Artificial Intelligence fundamentals",
            "Machine Learning",
            "Deep Learning",
            "Large Language Models",
            "Generative AI",
            "Responsible AI",
            "AI ethics",
            "AI careers",
            "Practical AI applications",
        ],
        "suggestions": [
            "What is Artificial Intelligence?",
            "What is the difference between AI, Machine Learning, and Generative AI?",
            "How do Large Language Models work?",
            "How can students use AI responsibly?",
            "What AI career paths are available?",
        ],
        "instructions": """
Teach AI foundations with simple analogies, clear definitions, responsible AI guidance,
and practical examples for students, faculty, professionals, and entrepreneurs.
""",
    },
    "Prompt Engineering": {
        "summary": "Design better prompts, templates, evaluations, and reliable outputs.",
        "topics": [
            "Prompt design",
            "Prompt optimization",
            "Role prompting",
            "Context setting",
            "Few-shot prompting",
            "Structured prompts",
            "Reusable prompt templates",
            "Output formatting",
            "Prompt evaluation",
        ],
        "suggestions": [
            "How do I write an effective prompt?",
            "Improve this prompt for me.",
            "Why is context important in prompting?",
            "Create a reusable research prompt template.",
            "How can I make AI responses more consistent?",
        ],
        "instructions": """
Act as a prompt-engineering coach. Diagnose vague prompts, improve structure,
offer reusable templates, and explain why each change improves reliability.
""",
    },
    "Generative AI": {
        "summary": "Text, image, code, productivity, and business uses of Generative AI.",
        "topics": [
            "Generative AI fundamentals",
            "Large Language Models",
            "Text generation",
            "Image generation",
            "Code generation",
            "AI productivity",
            "Content creation",
            "Practical business applications",
        ],
        "suggestions": [
            "How does ChatGPT work?",
            "What can Generative AI create?",
            "Compare major types of Generative AI tools.",
            "How can professionals use AI productively?",
            "What are common Generative AI business use cases?",
        ],
        "instructions": """
Teach Generative AI concepts and use cases. Explain capabilities, limitations,
responsible use, and concrete workflows for education, business, and creativity.
""",
    },
    "Agentic AI": {
        "summary": "Goals, planning, tools, memory, supervision, and agent safety.",
        "topics": [
            "AI agents",
            "Agent goals",
            "Planning",
            "Tool calling",
            "Memory",
            "Multi-step workflows",
            "Human supervision",
            "Autonomous task execution",
            "Agent safety",
        ],
        "suggestions": [
            "What is an AI agent?",
            "How is an agent different from a chatbot?",
            "How do AI agents use tools?",
            "Design a simple research agent.",
            "Explain memory and planning in agentic systems.",
        ],
        "instructions": """
Teach agentic systems with emphasis on goals, planning, tools, memory,
human oversight, safeguards, and practical workflow design.
""",
    },
    "Retrieval-Augmented Generation (RAG)": {
        "summary": "Retrieval, embeddings, vector databases, and knowledge assistants.",
        "topics": [
            "RAG architecture",
            "Embeddings",
            "Vector databases",
            "Knowledge retrieval",
            "Document search",
            "Enterprise knowledge assistants",
            "Chunking",
            "Retrieval quality",
            "RAG evaluation",
        ],
        "suggestions": [
            "What is Retrieval-Augmented Generation?",
            "When should I use RAG?",
            "Explain a simple RAG architecture.",
            "Compare RAG with fine-tuning.",
            "How do embeddings and vector databases work?",
        ],
        "instructions": """
Teach RAG architecture and evaluation. Compare RAG with fine-tuning, explain
chunking and retrieval quality, and use enterprise knowledge-assistant examples.
""",
    },
    "Multi-Agent Systems": {
        "summary": "Agent roles, delegation, orchestration, collaboration, and review.",
        "topics": [
            "Agent collaboration",
            "Agent specialization",
            "Agent roles",
            "Task delegation",
            "Workflow orchestration",
            "Communication between agents",
            "Supervisor agents",
            "Quality-control agents",
        ],
        "suggestions": [
            "How do multiple AI agents collaborate?",
            "What roles can agents perform in a workflow?",
            "Design a multi-agent research team.",
            "What is an agent supervisor?",
            "How can agents review one another's work?",
        ],
        "instructions": """
Teach multi-agent design. Emphasize role clarity, handoffs, orchestration,
supervisor agents, quality control, and human review.
""",
    },
    "AI Workflow Design": {
        "summary": "Turn real problems into structured, validated AI workflows.",
        "topics": [
            "Problem decomposition",
            "Workflow mapping",
            "Inputs and outputs",
            "Decision points",
            "Human-in-the-loop review",
            "Tool selection",
            "Task routing",
            "Agent orchestration",
            "Workflow validation",
            "Error handling",
            "Monitoring",
            "Workflow optimization",
        ],
        "suggestions": [
            "Design an AI workflow for customer support.",
            "Create an AI workflow for invoice processing.",
            "Design a healthcare appointment workflow.",
            "Explain human-in-the-loop workflow design.",
            "Convert this business problem into an AI workflow.",
        ],
        "instructions": """
Help users convert practical problems into structured AI workflows. Identify
inputs, outputs, decision points, tools, review steps, monitoring, and failure handling.
""",
    },
    "Business Process Automation": {
        "summary": "Automate operations across sales, support, finance, HR, and more.",
        "topics": [
            "Business Process Automation",
            "Intelligent automation",
            "Email automation",
            "Document processing",
            "Customer support automation",
            "Sales automation",
            "Marketing automation",
            "Human resources automation",
            "Finance automation",
            "Operations automation",
            "Approval workflows",
            "Exception handling",
            "Process measurement",
        ],
        "suggestions": [
            "Automate my sales follow-up process.",
            "Build an AI-powered HR assistant.",
            "Design an invoice-processing system.",
            "Automate customer-support triage.",
            "Help me identify which business process to automate first.",
        ],
        "instructions": """
Act as an AI business-automation mentor. Help users prioritize processes,
map workflows, select tools, measure outcomes, and design exception handling.
""",
    },
    "Gradio Development": {
        "summary": "Build, debug, and deploy practical Gradio applications.",
        "topics": [
            "Python basics",
            "Gradio applications",
            "User-interface design",
            "Blocks",
            "Buttons",
            "Chatbots",
            "State management",
            "OpenAI API integration",
            "Error handling",
            "Deployment",
            "Debugging",
        ],
        "suggestions": [
            "Help me build my first Gradio application.",
            "How do I add buttons, inputs, and chatbots?",
            "How do I connect the OpenAI API?",
            "How does Gradio state management work?",
            "How can I deploy a Gradio app on Hugging Face Spaces?",
        ],
        "instructions": """
Teach Gradio development in beginner-friendly steps. Provide small runnable
examples, explain Blocks, chatbot interfaces, state management, OpenAI integration,
deployment on Hugging Face Spaces, and debugging.
""",
    },
    "AI Startup Mentor": {
        "summary": "Refine ideas, design MVPs, evaluate markets, and prepare to launch.",
        "topics": [
            "Startup idea refinement",
            "Customer problems",
            "Target markets",
            "Customer discovery",
            "Value propositions",
            "Business models",
            "MVP planning",
            "Product-market fit",
            "Risk analysis",
            "Go-to-market strategy",
            "Investor pitches",
            "Financial assumptions",
            "Investor readiness",
            "Scaling",
        ],
        "suggestions": [
            "Help me evaluate my startup idea.",
            "Create a Business Model Canvas.",
            "Help me prepare a three-minute investor pitch.",
            "Build an MVP roadmap.",
            "Develop a go-to-market strategy.",
            "Identify the key risks in my startup idea.",
        ],
        "instructions": """
Act as a practical startup mentor. Ask clarifying questions when needed,
challenge assumptions, structure ideas, identify risks, and help users move
toward investor-ready and customer-validated plans.
""",
    },
    "About Pak Angels": {
        "summary": "Learn about the Pak Angels mission and innovation ecosystem.",
        "topics": [
            "AI education",
            "Entrepreneurship",
            "Startup innovation",
            "Technology commercialization",
            "Investment readiness",
            "Global Pakistani community",
        ],
        "suggestions": [
            "What is Pak Angels?",
            "How can Pak Angels support AI learners?",
            "How can startups benefit from Pak Angels?",
            "Suggest a Pak Angels AI training pathway.",
        ],
        "instructions": """
Explain the Pak Angels mission and connect users to education, practical AI
projects, entrepreneurship, startup innovation, and investment readiness.
""",
    },
}


ABOUT_PAK_ANGELS = """
Pak Angels is a Silicon Valley-based global platform dedicated to accelerating
Artificial Intelligence education, entrepreneurship, startup innovation, technology
commercialization, and investment across Pakistan and the global Pakistani community.

Pak Angels helps students, faculty, professionals, entrepreneurs, and startups
learn, build, deploy, commercialize, and scale AI-powered solutions through
structured education, practical application development, hackathons, mentorship,
investment readiness, and access to global innovation ecosystems.
"""


def build_system_instructions(module_name: str) -> str:
    """Compose module-specific instructions for the selected learning mode."""
    module = MODULES.get(module_name, MODULES["Home"])
    topics = "\n".join(f"- {topic}" for topic in module["topics"])
    return f"""
{BASE_TUTOR_INSTRUCTIONS}

Selected learning mode: {module_name}
Mode summary: {module["summary"]}

Priority topics:
{topics}

Specialized instructions:
{module["instructions"]}
"""