Monétiser son expertise grâce à un avatar IA

# AI consulting system with expert context
import openai
from datetime import datetime

SYSTEM_PROMPT = """You are the AI avatar of [Your Name], an expert in [field]
with [X] years of experience.

METHODOLOGY:
- Always start by understanding the client’s context
- Use the [your proprietary framework]
- Provide actionable recommendations with priorities
- Cite concrete examples from similar cases

LIMITATIONS:
- Never give definitive legal/tax advice
- Redirect complex cases to human consultation
- Mention that recommendations are AI-generated

KNOWLEDGE BASE:
{knowledge_base}
"""

def consultation(user_query, user_context, knowledge_base):
    """Handles an AI consulting session."""
    response = openai.chat.completions.create(
        model="claude-sonnet-4-20250514",  # via OpenRouter
        messages=[
            {"role": "system", "content": SYSTEM_PROMPT.format(
                knowledge_base=knowledge_base
            )},
            {"role": "user", "content": f"Client context: {user_context}\n"
                                        f"Question: {user_query}"}
        ],
        max_tokens=2000,
        temperature=0.3  # Precise, consistent responses
    )
    return response.choices[0].message.content

# AI-powered training system
COURSE_MODULES = {
    "module_1": {
        "title": "SEO Fundamentals",
        "objectives": [
            "Understand how Google works",
            "Identify relevant keywords"
        ],
        "exercises": [
            {
                "type": "analysis",
                "prompt": "Analyze the site {student_url} and identify "
                         "3 major SEO issues",
                "evaluation_criteria": [
                    "Identified missing title tags",
                    "Spotted speed issues",
                    "Noted internal linking errors"
                ]
            }
        ],
        "quiz": [
            {
                "q": "What is Google’s #1 ranking factor in 2025?",
                "options": ["Backlinks", "Content",
                           "User experience", "Speed"],
                "correct": 2,
                "explanation": "User experience (Core Web Vitals + "
                              "satisfaction) has become the dominant factor."
            }
        ]
    }
}

def evaluate_exercise(student_response, exercise, avatar_context):
    """The avatar evaluates the student’s work."""
    evaluation_prompt = f"""
    As an expert trainer, evaluate this response:

    Exercise: {exercise['prompt']}
    Student’s answer: {student_response}
    Evaluation criteria: {exercise['evaluation_criteria']}

    Provide:
    1. A score out of 10
    2. Strengths
    3. Areas for improvement
    4. Personalized advice for progress
    """
    return call_avatar(evaluation_prompt, avatar_context)

# Vertical SaaS avatar architecture
stack:
  frontend: Next.js / React
  backend: FastAPI / Node.js
  avatar_engine:
    llm: Claude via OpenRouter  # Best quality/price ratio
    knowledge: Vector database (Pinecone / Qdrant)
    prompts: Versioned prompt system
  auth: Clerk / Auth0 / NextAuth
  payments: Stripe / LemonSqueezy
  hosting: Dedicated VPS  # Hostinger offers great value
  monitoring: PostHog + Sentry
  database: PostgreSQL + Redis (cache)

# Stripe integration for subscriptions
import stripe
from fastapi import FastAPI, HTTPException

app = FastAPI()
stripe.api_key = "sk_live_..."

PLANS = {
    "starter": {"price_id": "price_xxx", "queries_limit": 100},
    "pro": {"price_id": "price_yyy", "queries_limit": 1000},
    "enterprise": {"price_id": "price_zzz", "queries_limit": -1},
}

@app.post("/api/subscribe")
async def create_subscription(user_id: str, plan: str):
    """Creates a Stripe subscription."""
    if plan not in PLANS:
        raise HTTPException(400, "Invalid plan")

    checkout = stripe.checkout.Session.create(
        customer=get_or_create_customer(user_id),
        line_items=[{"price": PLANS[plan]["price_id"], "quantity": 1}],
        mode="subscription",
        success_url="https://your-app.com/dashboard?success=true",
        cancel_url="https://your-app.com/pricing",
        metadata={"user_id": user_id, "plan": plan}
    )
    return {"checkout_url": checkout.url}

@app.post("/api/webhook/stripe")
async def stripe_webhook(request):
    """Handles Stripe events (activation, cancellation, etc.)."""
    event = stripe.Webhook.construct_event(
        await request.body(),
        request.headers["stripe-signature"],
        "whsec_..."
    )
    if event.type == "checkout.session.completed":
        session = event.data.object
        activate_subscription(
            session.metadata["user_id"],
            session.metadata["plan"]
        )