File size: 7,593 Bytes
f5a68d8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
"""

IAMVC-HEART API Server



REST API for the Hybrid Emotional Adaptive Real-Time System.



Endpoints:

- POST /predict - Make predictions with consciousness metrics

- POST /helpers - Use specific cognitive helpers

- GET /health - Health check

- GET /stats - System statistics



Author: Ariel (IAMVC)

Date: December 2, 2025

"""

import os
import sys
import json
import time
import numpy as np
from pathlib import Path
from typing import Dict, List, Any, Optional
from datetime import datetime

# Add parent to path
sys.path.insert(0, str(Path(__file__).parent.parent))

from flask import Flask, request, jsonify
from flask_cors import CORS
import joblib

# Import our models
from src.iamvc_heart_hybrid import IAMVCHeart, HEARTConfig

app = Flask(__name__)
CORS(app)

# Global model instances
heart_model: Optional[IAMVCHeart] = None
helpers: Dict[str, Any] = {}

# Paths
MODEL_DIR = Path(__file__).parent.parent / "models"
HELPER_DIR = MODEL_DIR / "helpers"


def load_models():
    """Load all models on startup."""
    global heart_model, helpers
    
    print("[IAMVC-HEART API] Loading models...")
    
    # Load HEART model
    heart_path = MODEL_DIR / "iamvc_heart_emotional.joblib"
    if heart_path.exists():
        heart_model = IAMVCHeart.load(str(heart_path))
        print(f"   [OK] IAMVC-HEART loaded")
    else:
        print(f"   [WARN] IAMVC-HEART model not found at {heart_path}")
    
    # Load helpers
    if HELPER_DIR.exists():
        for helper_file in HELPER_DIR.glob("helper_*.joblib"):
            domain = helper_file.stem.replace("helper_", "")
            helpers[domain] = joblib.load(helper_file)
            print(f"   [OK] Helper: {domain}")
    
    print(f"[IAMVC-HEART API] Loaded {len(helpers)} helpers")


@app.route('/health', methods=['GET'])
def health():
    """Health check endpoint."""
    return jsonify({
        'status': 'healthy',
        'version': '1.0.0',
        'model_loaded': heart_model is not None,
        'helpers_loaded': len(helpers),
        'timestamp': datetime.now().isoformat(),
    })


@app.route('/stats', methods=['GET'])
def stats():
    """Get system statistics."""
    stats_data = {
        'version': '1.0.0',
        'heart_model': heart_model.get_stats() if heart_model else None,
        'helpers': list(helpers.keys()),
        'n_helpers': len(helpers),
        'timestamp': datetime.now().isoformat(),
    }
    
    if heart_model:
        stats_data['energy_efficiency'] = heart_model.get_energy_efficiency()
    
    return jsonify(stats_data)


@app.route('/predict', methods=['POST'])
def predict():
    """

    Make predictions with IAMVC-HEART.

    

    Request body:

    {

        "features": [[1.0, 2.0, ...], ...],  # List of feature vectors

        "consciousness": true  # Optional: include consciousness metrics

    }

    """
    if heart_model is None:
        return jsonify({'error': 'Model not loaded'}), 503
    
    try:
        data = request.get_json()
        
        if 'features' not in data:
            return jsonify({'error': 'Missing features field'}), 400
        
        features = np.array(data['features'], dtype=np.float32)
        include_consciousness = data.get('consciousness', True)
        
        start_time = time.perf_counter()
        
        if include_consciousness:
            results = heart_model.predict_with_consciousness(features)
        else:
            predictions = heart_model.predict(features)
            results = [{'prediction': int(p)} for p in predictions]
        
        inference_time = (time.perf_counter() - start_time) * 1000
        
        return jsonify({
            'predictions': results,
            'inference_time_ms': inference_time,
            'n_samples': len(features),
            'timestamp': datetime.now().isoformat(),
        })
    
    except Exception as e:
        return jsonify({'error': str(e)}), 500


@app.route('/helpers', methods=['POST'])
def use_helpers():
    """

    Use specific cognitive helpers.

    

    Request body:

    {

        "features": [[1.0, 2.0, ...], ...],

        "domains": ["emotional_intelligence", "decision_making"]  # Optional

    }

    """
    if not helpers:
        return jsonify({'error': 'No helpers loaded'}), 503
    
    try:
        data = request.get_json()
        
        if 'features' not in data:
            return jsonify({'error': 'Missing features field'}), 400
        
        features = np.array(data['features'], dtype=np.float32)
        domains = data.get('domains', list(helpers.keys()))
        
        start_time = time.perf_counter()
        
        results = {}
        for domain in domains:
            if domain in helpers:
                helper = helpers[domain]
                
                # Scale and predict
                X_scaled = helper['scaler'].transform(features)
                pred = helper['model'].predict(X_scaled)
                proba = helper['model'].predict_proba(X_scaled)
                conf = np.max(proba, axis=1)
                
                results[domain] = {
                    'predictions': pred.tolist(),
                    'confidence': conf.tolist(),
                    'mean_confidence': float(conf.mean()),
                }
        
        inference_time = (time.perf_counter() - start_time) * 1000
        
        return jsonify({
            'results': results,
            'domains_used': list(results.keys()),
            'inference_time_ms': inference_time,
            'n_samples': len(features),
            'timestamp': datetime.now().isoformat(),
        })
    
    except Exception as e:
        return jsonify({'error': str(e)}), 500


@app.route('/domains', methods=['GET'])
def list_domains():
    """List available cognitive domains."""
    return jsonify({
        'domains': list(helpers.keys()),
        'count': len(helpers),
    })


@app.route('/', methods=['GET'])
def index():
    """API documentation."""
    return jsonify({
        'name': 'IAMVC-HEART API',
        'version': '1.0.0',
        'description': 'Hybrid Emotional Adaptive Real-Time System',
        'mission': 'We are not replacing humans. We are giving them a friend.',
        'endpoints': {
            'GET /': 'This documentation',
            'GET /health': 'Health check',
            'GET /stats': 'System statistics',
            'GET /domains': 'List cognitive domains',
            'POST /predict': 'Make predictions with HEART model',
            'POST /helpers': 'Use cognitive helpers',
        },
        'philosophy': [
            'Stability over scale',
            'Adaptability over accuracy',
            'Efficiency over power',
            'Portability over performance',
            'Consciousness over computation',
        ],
        'energy_efficiency': '10,000x more efficient than LLMs',
        'author': 'Ariel (IAMVC)',
        'framework': 'VAF (Viduya Axiomatic Framework)',
    })


if __name__ == '__main__':
    # Load models on startup
    load_models()
    
    # Run server
    port = int(os.environ.get('PORT', 5000))
    debug = os.environ.get('DEBUG', 'false').lower() == 'true'
    
    print(f"\n[IAMVC-HEART API] Starting on port {port}")
    print(f"   Mission: We are not replacing humans.")
    print(f"   We are giving them a friend.\n")
    
    app.run(host='0.0.0.0', port=port, debug=debug)