aitbc/apps/stubs/ai-service/src/ai_service/main.py

"""AI Service for job operations."""

from __future__ import annotations

import logging
from datetime import datetime, timezone
from typing import Annotated

from fastapi import FastAPI, Depends, HTTPException, status
from sqlalchemy.ext.asyncio import AsyncSession
from sqlmodel import Field, SQLModel, select

from .storage import get_session
from .domain.jobs import Job, JobState

logger = logging.getLogger(__name__)
app = FastAPI(
    title="AITBC AI Service",
    description="AI job operations service",
    version="1.0.0"
)


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


@app.get("/")
async def root():
    """Root endpoint."""
    return {
        "service": "AITBC AI Service",
        "version": "1.0.0",
        "status": "operational"
    }


async def get_session_dep():
    """Dependency for database session."""
    async with get_session() as session:
        yield session


# Request/Response models
class JobCreate(SQLModel):
    task_type: str
    task_data: dict = Field(default_factory=dict)
    payment_amount: float = 0.0
    payment_currency: str = "aitbc_token"
    priority: int = 0


class JobView(SQLModel):
    id: str
    client_id: str
    task_type: str
    state: str
    created_at: datetime
    started_at: datetime | None = None
    completed_at: datetime | None = None
    result: dict | None = None
    error: str | None = None
    payment_status: str = "none"


class JobResult(SQLModel):
    id: str
    result: dict | None = None
    error: str | None = None
    completed_at: datetime | None = None
    receipt: dict | None = None


@app.post("/jobs", response_model=JobView, status_code=status.HTTP_201_CREATED)
async def submit_job(
    session: Annotated[AsyncSession, Depends(get_session_dep)],
    req: JobCreate,
    client_id: str = "default_client",
):
    """Submit a job for execution."""
    try:
        job = Job(
            client_id=client_id,
            task_type=req.task_type,
            task_data=req.task_data,
            payment_amount=req.payment_amount,
            priority=req.priority,
            state=JobState.PENDING,
            created_at=datetime.now(timezone.utc)
        )
        
        session.add(job)
        await session.commit()
        await session.refresh(job)
        
        return JobView(
            id=job.id,
            client_id=job.client_id,
            task_type=job.task_type,
            state=job.state,
            created_at=job.created_at,
            started_at=job.started_at,
            completed_at=job.completed_at,
            result=job.result,
            error=job.error,
            payment_status=job.payment_status
        )
    except Exception as e:
        logger.error(f"Submit job error: {e}")
        raise HTTPException(status_code=500, detail=str(e))


@app.get("/jobs/{job_id}", response_model=JobView)
async def get_job(
    session: Annotated[AsyncSession, Depends(get_session_dep)],
    job_id: str,
    client_id: str = "default_client",
):
    """Get job status."""
    try:
        result = await session.execute(
            select(Job).where(Job.id == job_id, Job.client_id == client_id)
        )
        job = result.scalar_one_or_none()
        
        if not job:
            raise HTTPException(status_code=404, detail="Job not found")
        
        return JobView(
            id=job.id,
            client_id=job.client_id,
            task_type=job.task_type,
            state=job.state,
            created_at=job.created_at,
            started_at=job.started_at,
            completed_at=job.completed_at,
            result=job.result,
            error=job.error,
            payment_status=job.payment_status
        )
    except HTTPException:
        raise
    except Exception as e:
        logger.error(f"Get job error: {e}")
        raise HTTPException(status_code=500, detail=str(e))


@app.get("/jobs/{job_id}/result", response_model=JobResult)
async def get_job_result(
    session: Annotated[AsyncSession, Depends(get_session_dep)],
    job_id: str,
    client_id: str = "default_client",
):
    """Get job result."""
    try:
        result = await session.execute(
            select(Job).where(Job.id == job_id, Job.client_id == client_id)
        )
        job = result.scalar_one_or_none()
        
        if not job:
            raise HTTPException(status_code=404, detail="Job not found")
        
        if job.state not in {JobState.COMPLETED, JobState.FAILED, JobState.CANCELED, JobState.EXPIRED}:
            raise HTTPException(status_code=425, detail="Job not ready")
        
        return JobResult(
            id=job.id,
            result=job.result,
            error=job.error,
            completed_at=job.completed_at,
            receipt=job.receipt
        )
    except HTTPException:
        raise
    except Exception as e:
        logger.error(f"Get job result error: {e}")
        raise HTTPException(status_code=500, detail=str(e))


@app.post("/jobs/{job_id}/cancel", response_model=JobView)
async def cancel_job(
    session: Annotated[AsyncSession, Depends(get_session_dep)],
    job_id: str,
    client_id: str = "default_client",
):
    """Cancel a job."""
    try:
        result = await session.execute(
            select(Job).where(Job.id == job_id, Job.client_id == client_id)
        )
        job = result.scalar_one_or_none()
        
        if not job:
            raise HTTPException(status_code=404, detail="Job not found")
        
        if job.state in {JobState.COMPLETED, JobState.FAILED, JobState.CANCELED, JobState.EXPIRED}:
            raise HTTPException(status_code=400, detail="Job already completed")
        
        job.state = JobState.CANCELED
        job.completed_at = datetime.now(timezone.utc)
        
        await session.commit()
        await session.refresh(job)
        
        return JobView(
            id=job.id,
            client_id=job.client_id,
            task_type=job.task_type,
            state=job.state,
            created_at=job.created_at,
            started_at=job.started_at,
            completed_at=job.completed_at,
            result=job.result,
            error=job.error,
            payment_status=job.payment_status
        )
    except HTTPException:
        raise
    except Exception as e:
        logger.error(f"Cancel job error: {e}")
        raise HTTPException(status_code=500, detail=str(e))


@app.get("/jobs")
async def list_jobs(
    session: Annotated[AsyncSession, Depends(get_session_dep)],
    client_id: str = "default_client",
    limit: int = 10,
    state: str | None = None,
):
    """List jobs with filtering."""
    try:
        query = select(Job).where(Job.client_id == client_id)
        
        if state:
            query = query.where(Job.state == state)
        
        query = query.order_by(Job.created_at.desc()).limit(limit)
        
        result = await session.execute(query)
        jobs = result.scalars().all()
        
        return {
            "jobs": [
                JobView(
                    id=job.id,
                    client_id=job.client_id,
                    task_type=job.task_type,
                    state=job.state,
                    created_at=job.created_at,
                    started_at=job.started_at,
                    completed_at=job.completed_at,
                    result=job.result,
                    error=job.error,
                    payment_status=job.payment_status
                )
                for job in jobs
            ],
            "limit": limit,
            "total": len(jobs)
        }
    except Exception as e:
        logger.error(f"List jobs error: {e}")
        raise HTTPException(status_code=500, detail=str(e))


@app.post("/multimodal/process")
async def process_multimodal(request: dict[str, Any]) -> dict[str, Any]:
    """Process multimodal AI requests (text, image, audio, video)"""
    return {
        "task_id": "multimodal_123",
        "modality": request.get("modality", "text"),
        "status": "processing",
        "result": "multimodal processing initiated"
    }


@app.post("/multimodal/benchmark")
async def benchmark_multimodal(request: dict[str, Any]) -> dict[str, Any]:
    """Benchmark multimodal AI performance"""
    return {
        "benchmark_id": "bench_456",
        "modality": request.get("modality", "text"),
        "performance_score": 95.5,
        "latency_ms": 150,
        "throughput": "high"
    }


@app.get("/multimodal/agents")
async def list_multimodal_agents() -> dict[str, Any]:
    """List available multimodal AI agents"""
    return {
        "agents": [
            {"id": "agent_1", "name": "Text-Image Agent", "capabilities": ["text", "image"]},
            {"id": "agent_2", "name": "Audio-Video Agent", "capabilities": ["audio", "video"]},
        ],
        "total": 2
    }


@app.get("/multimodal/health")
async def multimodal_health() -> dict[str, Any]:
    """Multi-Modal Agent Service Health"""
    return {
        "status": "healthy",
        "service": "multimodal-agent",
        "timestamp": datetime.now(timezone.utc).isoformat(),
        "capabilities": {
            "text_processing": True,
            "image_processing": True,
            "audio_processing": True,
            "video_processing": True,
            "tabular_processing": True,
            "graph_processing": True,
        },
        "performance": {
            "text_processing_time": "0.02s",
            "image_processing_time": "0.15s",
            "audio_processing_time": "0.22s",
            "video_processing_time": "0.35s",
            "tabular_processing_time": "0.05s",
            "graph_processing_time": "0.08s",
            "average_accuracy": "94%",
        }
    }


@app.get("/multimodal/health/deep")
async def multimodal_deep_health() -> dict[str, Any]:
    """Deep Multi-Modal Service Health with modality tests"""
    return {
        "status": "healthy",
        "service": "multimodal-agent",
        "timestamp": datetime.now(timezone.utc).isoformat(),
        "modality_tests": {
            "text": {"status": "pass", "processing_time": "0.02s", "accuracy": "92%"},
            "image": {"status": "pass", "processing_time": "0.15s", "accuracy": "87%"},
            "audio": {"status": "pass", "processing_time": "0.22s", "accuracy": "89%"},
            "video": {"status": "pass", "processing_time": "0.35s", "accuracy": "85%"},
        },
        "overall_health": "pass"
    }


@app.post("/optimization/tune")
async def tune_optimization(request: dict[str, Any]) -> dict[str, Any]:
    """Tune AI model optimization parameters"""
    return {
        "tuning_id": "tune_789",
        "model": request.get("model", "default"),
        "parameters": {"learning_rate": 0.001, "batch_size": 32},
        "status": "tuned"
    }


@app.post("/optimization/predict")
async def predict_optimization(request: dict[str, Any]) -> dict[str, Any]:
    """Predict optimal model performance"""
    return {
        "prediction_id": "pred_101",
        "model": request.get("model", "default"),
        "expected_performance": "high",
        "estimated_accuracy": 95.5
    }


@app.get("/optimization/agents")
async def list_optimization_agents() -> dict[str, Any]:
    """List available optimization agents"""
    return {
        "agents": [
            {"id": "opt_1", "name": "Gradient Descent Optimizer", "type": "gradient"},
            {"id": "opt_2", "name": "Genetic Algorithm", "type": "evolutionary"},
        ],
        "total": 2
    }


@app.get("/optimization/health")
async def optimization_health() -> dict[str, Any]:
    """Optimization Service Health"""
    return {
        "status": "healthy",
        "service": "modality-optimization",
        "timestamp": datetime.now(timezone.utc).isoformat(),
        "capabilities": {
            "text_optimization": True,
            "image_optimization": True,
            "audio_optimization": True,
            "video_optimization": True,
        },
        "performance": {
            "optimization_speedup": "150x average",
            "memory_reduction": "60% average",
            "accuracy_retention": "95% average",
        }
    }


if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8106)