🤖 COMPLETE: Learning-Enhanced AI with HTTP Compatibility

LEARNING INTEGRATION:
- Enhanced AI analysis service feeds historical data into OpenAI prompts
- Symbol/timeframe specific learning optimization
- Pattern recognition from past trade outcomes
- Confidence adjustment based on success rates

 HTTP COMPATIBILITY SYSTEM:
- HttpUtil with automatic curl/no-curl detection
- Node.js fallback for Docker environments without curl
- Updated all automation systems to use HttpUtil
- Production-ready error handling

 AUTONOMOUS RISK MANAGEMENT:
- Enhanced risk manager with learning integration
- Simplified learners using existing AILearningData schema
- Real-time position monitoring every 30 seconds
- Smart stop-loss decisions with AI learning

 INFRASTRUCTURE:
- Database utility for shared Prisma connections
- Beach mode status display system
- Complete error handling and recovery
- Docker container compatibility tested

Historical performance flows into OpenAI prompts before every trade.

lib/stop-loss-decision-learner.js

@@ -7,11 +7,10 @@
  * It records every decision, tracks outcomes, and continuously improves decision-making.
  */
 
-const { PrismaClient } = require('@prisma/client');
+const { getDB } = require('./db');
 
 class StopLossDecisionLearner {
   constructor() {
-    this.prisma = new PrismaClient();
     this.decisionHistory = [];
     this.learningThresholds = {
       emergencyDistance: 1.0,
@@ -20,6 +19,10 @@ class StopLossDecisionLearner {
     };
   }
 
+  async getPrisma() {
+    return await getDB();
+  }
+
   async log(message) {
     const timestamp = new Date().toISOString();
     console.log(`[${timestamp}] 🧠 SL Learner: ${message}`);
@@ -52,7 +55,8 @@ class StopLossDecisionLearner {
       };
 
       // Store in database
-      await this.prisma.sLDecision.create({
+      const prisma = await this.getPrisma();
+      await prisma.sLDecision.create({
         data: {
           id: decision.id,
           tradeId: decision.tradeId,
@@ -92,7 +96,8 @@ class StopLossDecisionLearner {
       const learningScore = this.calculateLearningScore(wasCorrect, pnlImpact, timeToOutcome);
 
       // Update decision record
-      await this.prisma.sLDecision.update({
+      const prisma = await this.getPrisma();
+      await prisma.sLDecision.update({
         where: { id: decisionId },
         data: {
           outcome: actualOutcome,
@@ -135,7 +140,8 @@ class StopLossDecisionLearner {
    */
   async analyzeDecisionPatterns() {
     try {
-      const decisions = await this.prisma.sLDecision.findMany({
+      const prisma = await this.getPrisma();
+      const decisions = await prisma.sLDecision.findMany({
         where: { status: 'ASSESSED' },
         orderBy: { decisionTimestamp: 'desc' },
         take: 100 // Analyze last 100 decisions
@@ -438,7 +444,8 @@ class StopLossDecisionLearner {
     const { distanceFromSL, marketConditions } = currentSituation;
     const tolerance = 0.5; // 0.5% tolerance for distance matching
 
-    const decisions = await this.prisma.sLDecision.findMany({
+    const prisma = await this.getPrisma();
+    const decisions = await prisma.sLDecision.findMany({
       where: {
         status: 'ASSESSED',
         distanceFromSL: {