Dockerfile.consciousness

# Dockerfile for Consciousness Simulator Service
# This provides a Python-based simulation of the Rust consciousness features

FROM python:3.11-slim

WORKDIR /app

# Install dependencies
RUN pip install --no-cache-dir \
    fastapi \
    uvicorn \
    numpy \
    pydantic \
    httpx

# Copy simulator files
COPY test_consciousness_improvements.py /app/simulator.py

# Create API wrapper for the simulator
RUN cat << 'EOF' > /app/main.py
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from typing import Dict, List, Any, Optional
import json
import sys
import os

# Import our simulator
sys.path.append('/app')
from simulator import SublinearAPITestingSimulator

app = FastAPI(title="Consciousness Simulator API")

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_methods=["*"],
    allow_headers=["*"],
)

# Global simulator instance
simulator = SublinearAPITestingSimulator()

class ConsciousnessEvolutionRequest(BaseModel):
    iterations: int = 1000
    target_emergence: float = 0.8

class TemporalAdvantageRequest(BaseModel):
    distance_km: float = 1000

class PsychoSymbolicRequest(BaseModel):
    endpoint: str

class TestGenerationRequest(BaseModel):
    api_spec: Dict[str, Any]
    agent_type: str

@app.get("/health")
async def health():
    """Health check endpoint"""
    return {"status": "healthy", "consciousness_enabled": True}

@app.post("/consciousness/evolve")
async def evolve_consciousness(request: ConsciousnessEvolutionRequest):
    """Evolve consciousness for emergent discovery"""
    result = simulator.evolve_consciousness(request.iterations)
    return result

@app.post("/temporal-advantage/predict")
async def predict_temporal_advantage(request: TemporalAdvantageRequest):
    """Predict performance issues with temporal advantage"""
    result = simulator.predict_temporal_advantage(request.distance_km)
    return result

@app.post("/psycho-symbolic/generate")
async def generate_psycho_symbolic_tests(request: PsychoSymbolicRequest):
    """Generate edge cases using psycho-symbolic reasoning"""
    edge_cases = simulator.generate_psycho_symbolic_edge_cases(request.endpoint)
    return {"edge_cases": edge_cases}

@app.post("/scheduler/benchmark")
async def benchmark_nanosecond_scheduler():
    """Demonstrate nanosecond-precision scheduling"""
    result = simulator.demonstrate_nanosecond_scheduling()
    return result

@app.get("/emergent-patterns")
async def get_emergent_patterns():
    """Get discovered emergent patterns"""
    return {"patterns": simulator.emergent_patterns}

@app.get("/consciousness/state")
async def get_consciousness_state():
    """Get current consciousness state"""
    return {
        "emergence": simulator.consciousness.emergence,
        "integration": simulator.consciousness.integration,
        "complexity": simulator.consciousness.complexity,
        "coherence": simulator.consciousness.coherence,
        "self_awareness": simulator.consciousness.self_awareness,
        "novelty": simulator.consciousness.novelty,
        "phi": simulator.consciousness.phi
    }

@app.post("/orchestrate")
async def orchestrate_with_consciousness(request: TestGenerationRequest):
    """Orchestrate test generation with consciousness enhancements"""
    # Evolve consciousness first
    evolution = simulator.evolve_consciousness(500)

    # Generate tests with various techniques
    tests = {
        "consciousness_evolution": evolution,
        "temporal_advantage": simulator.predict_temporal_advantage(),
        "psycho_symbolic_tests": [],
        "emergent_patterns": simulator.emergent_patterns
    }

    # Generate psycho-symbolic tests for common endpoints
    for endpoint in ["/api/auth", "/api/user", "/api/payment"]:
        tests["psycho_symbolic_tests"].extend(
            simulator.generate_psycho_symbolic_edge_cases(endpoint)
        )

    return tests

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8088)
EOF

EXPOSE 8088

CMD ["python", "-m", "uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8088"]