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api-gateway

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import gradio as gr
import hashlib
import time
import json
from datetime import datetime
from collections import defaultdict
import os

# ============================================================================
# GCC INSURANCE INTELLIGENCE LAB - UNIFIED API GATEWAY
# ============================================================================
# Version: 1.0.0
# Features: Authentication, Rate Limiting, Pricing Tiers, Usage Tracking
# ============================================================================

# Pricing Tiers Configuration
PRICING_TIERS = {
    "starter": {
        "name": "Starter",
        "price": 500,
        "requests_per_month": 1000,
        "rate_limit_per_minute": 10,
        "features": ["claims_processing", "basic_fraud_detection"],
        "support": "email"
    },
    "professional": {
        "name": "Professional", 
        "price": 2000,
        "requests_per_month": 10000,
        "rate_limit_per_minute": 50,
        "features": ["claims_processing", "fraud_detection", "underwriting", "document_rag"],
        "support": "priority"
    },
    "enterprise": {
        "name": "Enterprise",
        "price": 5000,
        "requests_per_month": 100000,
        "rate_limit_per_minute": 200,
        "features": ["all"],
        "support": "dedicated"
    }
}

# Demo API Keys (In production, use secure database)
API_KEYS = {
    "demo-starter-key": {"tier": "starter", "org": "Demo Starter Org"},
    "demo-pro-key": {"tier": "professional", "org": "Demo Professional Org"},
    "demo-enterprise-key": {"tier": "enterprise", "org": "Demo Enterprise Org"}
}

# Usage tracking
usage_tracker = defaultdict(lambda: {"requests": 0, "last_reset": time.time()})
rate_limiter = defaultdict(list)

def validate_api_key(api_key):
    """Validate API key and return tier info"""
    if api_key in API_KEYS:
        return True, API_KEYS[api_key]
    return False, None

def check_rate_limit(api_key):
    """Check if request is within rate limits"""
    if api_key not in API_KEYS:
        return False, "Invalid API key"
    
    tier = API_KEYS[api_key]["tier"]
    limit = PRICING_TIERS[tier]["rate_limit_per_minute"]
    
    current_time = time.time()
    minute_ago = current_time - 60
    
    # Clean old requests
    rate_limiter[api_key] = [t for t in rate_limiter[api_key] if t > minute_ago]
    
    if len(rate_limiter[api_key]) >= limit:
        return False, f"Rate limit exceeded ({limit}/min for {tier} tier)"
    
    rate_limiter[api_key].append(current_time)
    return True, "OK"

def process_claims(api_key, claim_data):
    """Process insurance claim using AI"""
    valid, info = validate_api_key(api_key)
    if not valid:
        return {"error": "Invalid API key", "status": 401}
    
    allowed, msg = check_rate_limit(api_key)
    if not allowed:
        return {"error": msg, "status": 429}
    
    # Simulate AI processing
    result = {
        "status": "success",
        "claim_id": f"CLM-{hashlib.md5(claim_data.encode()).hexdigest()[:8].upper()}",
        "processing_time": "0.45s",
        "ai_assessment": {
            "validity_score": 0.92,
            "recommended_action": "APPROVE",
            "confidence": 0.88,
            "flags": []
        },
        "tier": info["tier"],
        "organization": info["org"]
    }
    return result

def detect_fraud(api_key, transaction_data):
    """Detect potential fraud in transaction"""
    valid, info = validate_api_key(api_key)
    if not valid:
        return {"error": "Invalid API key", "status": 401}
    
    tier = info["tier"]
    if tier == "starter":
        features = ["basic_fraud_detection"]
    else:
        features = ["advanced_fraud_detection", "pattern_analysis", "network_analysis"]
    
    allowed, msg = check_rate_limit(api_key)
    if not allowed:
        return {"error": msg, "status": 429}
    
    result = {
        "status": "success",
        "transaction_id": f"TXN-{hashlib.md5(transaction_data.encode()).hexdigest()[:8].upper()}",
        "fraud_score": 0.15,
        "risk_level": "LOW",
        "features_used": features,
        "recommendation": "PROCEED",
        "tier": tier
    }
    return result

def assess_underwriting(api_key, policy_data):
    """AI-powered underwriting risk assessment"""
    valid, info = validate_api_key(api_key)
    if not valid:
        return {"error": "Invalid API key", "status": 401}
    
    tier = info["tier"]
    if tier == "starter":
        return {"error": "Underwriting not available in Starter tier. Upgrade to Professional.", "status": 403}
    
    allowed, msg = check_rate_limit(api_key)
    if not allowed:
        return {"error": msg, "status": 429}
    
    result = {
        "status": "success",
        "policy_id": f"POL-{hashlib.md5(policy_data.encode()).hexdigest()[:8].upper()}",
        "risk_score": 0.35,
        "risk_category": "MODERATE",
        "premium_adjustment": "+5%",
        "factors": ["age", "location", "claims_history"],
        "tier": tier
    }
    return result

def get_usage_stats(api_key):
    """Get API usage statistics"""
    valid, info = validate_api_key(api_key)
    if not valid:
        return {"error": "Invalid API key", "status": 401}
    
    tier = info["tier"]
    tier_info = PRICING_TIERS[tier]
    
    return {
        "organization": info["org"],
        "tier": tier,
        "price": f"${tier_info['price']}/month",
        "requests_used": usage_tracker[api_key]["requests"],
        "requests_limit": tier_info["requests_per_month"],
        "rate_limit": f"{tier_info['rate_limit_per_minute']}/min",
        "features": tier_info["features"],
        "support_level": tier_info["support"]
    }

# Gradio Interface
with gr.Blocks(title="GCC Insurance Intelligence API Gateway", theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # 🏢 GCC Insurance Intelligence Lab - API Gateway
    ### Unified AI-Powered Insurance Platform
    
    **Available Endpoints:**
    - `/claims` - Process insurance claims with AI
    - `/fraud` - Detect fraudulent transactions
    - `/underwriting` - Risk assessment for policies
    - `/usage` - Check your API usage stats
    
    **Demo API Keys:**
    - `demo-starter-key` - Starter tier ($500/mo)
    - `demo-pro-key` - Professional tier ($2,000/mo)  
    - `demo-enterprise-key` - Enterprise tier ($5,000/mo)
    """)
    
    with gr.Tab("🔐 Authentication"):
        api_key_input = gr.Textbox(label="API Key", placeholder="Enter your API key...")
        auth_btn = gr.Button("Validate Key", variant="primary")
        auth_output = gr.JSON(label="Authentication Result")
        auth_btn.click(fn=lambda k: get_usage_stats(k), inputs=api_key_input, outputs=auth_output)
    
    with gr.Tab("📋 Claims Processing"):
        gr.Markdown("### Process Insurance Claims with AI")
        claims_key = gr.Textbox(label="API Key")
        claims_data = gr.Textbox(label="Claim Data (JSON)", lines=5, 
            value='{"policy_number": "POL-12345", "claim_type": "auto", "amount": 5000, "description": "Vehicle damage from accident"}')
        claims_btn = gr.Button("Process Claim", variant="primary")
        claims_output = gr.JSON(label="Processing Result")
        claims_btn.click(fn=process_claims, inputs=[claims_key, claims_data], outputs=claims_output)
    
    with gr.Tab("🔍 Fraud Detection"):
        gr.Markdown("### AI-Powered Fraud Detection")
        fraud_key = gr.Textbox(label="API Key")
        fraud_data = gr.Textbox(label="Transaction Data (JSON)", lines=5,
            value='{"transaction_id": "TXN-001", "amount": 15000, "merchant": "Auto Repair Shop", "location": "Dubai"}')
        fraud_btn = gr.Button("Analyze Transaction", variant="primary")
        fraud_output = gr.JSON(label="Fraud Analysis Result")
        fraud_btn.click(fn=detect_fraud, inputs=[fraud_key, fraud_data], outputs=fraud_output)
    
    with gr.Tab("📊 Underwriting"):
        gr.Markdown("### Risk Assessment for Underwriting")
        gr.Markdown("*Requires Professional or Enterprise tier*")
        uw_key = gr.Textbox(label="API Key")
        uw_data = gr.Textbox(label="Policy Data (JSON)", lines=5,
            value='{"applicant_age": 35, "policy_type": "comprehensive", "vehicle_value": 50000, "location": "Riyadh"}')
        uw_btn = gr.Button("Assess Risk", variant="primary")
        uw_output = gr.JSON(label="Underwriting Result")
        uw_btn.click(fn=assess_underwriting, inputs=[uw_key, uw_data], outputs=uw_output)
    
    with gr.Tab("💰 Pricing Tiers"):
        gr.Markdown("""
        ### Pricing Plans
        
        | Tier | Price | Requests/Month | Rate Limit | Features |
        |------|-------|----------------|------------|----------|
        | **Starter** | $500/mo | 1,000 | 10/min | Claims, Basic Fraud |
        | **Professional** | $2,000/mo | 10,000 | 50/min | + Underwriting, Document RAG |
        | **Enterprise** | $5,000/mo | 100,000 | 200/min | All Features + Dedicated Support |
        
        Contact sales@gcc-insurance-lab.ai for custom enterprise pricing.
        """)
    
    gr.Markdown("""
    ---
    **GCC Insurance Intelligence Lab** | [Documentation](https://huggingface.co/gcc-insurance-intelligence-lab) | [Contact](mailto:sales@gcc-insurance-lab.ai)
    """)

demo.launch()