Files
AI-Trader/api/main.py
Bill fb9583b374 feat: transform to REST API service with SQLite persistence (v0.3.0)
Major architecture transformation from batch-only to API service with
database persistence for Windmill integration.

## REST API Implementation
- POST /simulate/trigger - Start simulation jobs
- GET /simulate/status/{job_id} - Monitor job progress
- GET /results - Query results with filters (job_id, date, model)
- GET /health - Service health checks

## Database Layer
- SQLite persistence with 6 tables (jobs, job_details, positions,
  holdings, reasoning_logs, tool_usage)
- Foreign key constraints with cascade deletes
- Replaces JSONL file storage

## Backend Components
- JobManager: Job lifecycle management with concurrency control
- RuntimeConfigManager: Thread-safe isolated runtime configs
- ModelDayExecutor: Single model-day execution engine
- SimulationWorker: Date-sequential, model-parallel orchestration

## Testing
- 102 unit and integration tests (85% coverage)
- Database: 98% coverage
- Job manager: 98% coverage
- API endpoints: 81% coverage
- Pydantic models: 100% coverage
- TDD approach throughout

## Docker Deployment
- Dual-mode: API server (persistent) + batch (one-time)
- Health checks with 30s interval
- Volume persistence for database and logs
- Separate entrypoints for each mode

## Validation Tools
- scripts/validate_docker_build.sh - Build validation
- scripts/test_api_endpoints.sh - Complete API testing
- scripts/test_batch_mode.sh - Batch mode validation
- DOCKER_API.md - Deployment guide
- TESTING_GUIDE.md - Testing procedures

## Configuration
- API_PORT environment variable (default: 8080)
- Backwards compatible with existing configs
- FastAPI, uvicorn, pydantic>=2.0 dependencies

Co-Authored-By: AI Assistant <noreply@example.com>
2025-10-31 11:47:10 -04:00

367 lines
11 KiB
Python

"""
FastAPI REST API for AI-Trader simulation service.
Provides endpoints for:
- Triggering simulation jobs
- Checking job status
- Querying results
- Health checks
"""
import logging
from typing import Optional, List, Dict, Any
from datetime import datetime
from pathlib import Path
from fastapi import FastAPI, HTTPException, Query
from fastapi.responses import JSONResponse
from pydantic import BaseModel, Field, field_validator
from api.job_manager import JobManager
from api.simulation_worker import SimulationWorker
from api.database import get_db_connection
import threading
import time
logger = logging.getLogger(__name__)
# Pydantic models for request/response validation
class SimulateTriggerRequest(BaseModel):
"""Request body for POST /simulate/trigger."""
config_path: str = Field(..., description="Path to configuration file")
date_range: List[str] = Field(..., min_length=1, description="List of trading dates (YYYY-MM-DD)")
models: List[str] = Field(..., min_length=1, description="List of model signatures to simulate")
@field_validator("date_range")
@classmethod
def validate_date_range(cls, v):
"""Validate date format."""
for date in v:
try:
datetime.strptime(date, "%Y-%m-%d")
except ValueError:
raise ValueError(f"Invalid date format: {date}. Expected YYYY-MM-DD")
return v
class SimulateTriggerResponse(BaseModel):
"""Response body for POST /simulate/trigger."""
job_id: str
status: str
total_model_days: int
message: str
class JobProgress(BaseModel):
"""Job progress information."""
total_model_days: int
completed: int
failed: int
pending: int
class JobStatusResponse(BaseModel):
"""Response body for GET /simulate/status/{job_id}."""
job_id: str
status: str
progress: JobProgress
date_range: List[str]
models: List[str]
created_at: str
started_at: Optional[str] = None
completed_at: Optional[str] = None
total_duration_seconds: Optional[float] = None
error: Optional[str] = None
details: List[Dict[str, Any]]
class HealthResponse(BaseModel):
"""Response body for GET /health."""
status: str
database: str
timestamp: str
def create_app(db_path: str = "data/jobs.db") -> FastAPI:
"""
Create FastAPI application instance.
Args:
db_path: Path to SQLite database
Returns:
Configured FastAPI app
"""
app = FastAPI(
title="AI-Trader Simulation API",
description="REST API for triggering and monitoring AI trading simulations",
version="1.0.0"
)
# Store db_path in app state
app.state.db_path = db_path
@app.post("/simulate/trigger", response_model=SimulateTriggerResponse, status_code=200)
async def trigger_simulation(request: SimulateTriggerRequest):
"""
Trigger a new simulation job.
Creates a job with specified config, dates, and models.
Job runs asynchronously in background thread.
Raises:
HTTPException 400: If another job is already running or config invalid
HTTPException 422: If request validation fails
"""
try:
# Validate config path exists
if not Path(request.config_path).exists():
raise HTTPException(
status_code=400,
detail=f"Config path does not exist: {request.config_path}"
)
job_manager = JobManager(db_path=app.state.db_path)
# Check if can start new job
if not job_manager.can_start_new_job():
raise HTTPException(
status_code=400,
detail="Another simulation job is already running or pending. Please wait for it to complete."
)
# Create job
job_id = job_manager.create_job(
config_path=request.config_path,
date_range=request.date_range,
models=request.models
)
# Start worker in background thread (only if not in test mode)
if not getattr(app.state, "test_mode", False):
def run_worker():
worker = SimulationWorker(job_id=job_id, db_path=app.state.db_path)
worker.run()
thread = threading.Thread(target=run_worker, daemon=True)
thread.start()
logger.info(f"Triggered simulation job {job_id}")
return SimulateTriggerResponse(
job_id=job_id,
status="pending",
total_model_days=len(request.date_range) * len(request.models),
message=f"Simulation job {job_id} created and started"
)
except HTTPException:
raise
except ValueError as e:
logger.error(f"Validation error: {e}")
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error(f"Failed to trigger simulation: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@app.get("/simulate/status/{job_id}", response_model=JobStatusResponse)
async def get_job_status(job_id: str):
"""
Get status and progress of a simulation job.
Args:
job_id: Job UUID
Returns:
Job status, progress, and model-day details
Raises:
HTTPException 404: If job not found
"""
try:
job_manager = JobManager(db_path=app.state.db_path)
# Get job info
job = job_manager.get_job(job_id)
if not job:
raise HTTPException(status_code=404, detail=f"Job {job_id} not found")
# Get progress
progress = job_manager.get_job_progress(job_id)
# Get model-day details
details = job_manager.get_job_details(job_id)
# Calculate pending (total - completed - failed)
pending = progress["total_model_days"] - progress["completed"] - progress["failed"]
return JobStatusResponse(
job_id=job["job_id"],
status=job["status"],
progress=JobProgress(
total_model_days=progress["total_model_days"],
completed=progress["completed"],
failed=progress["failed"],
pending=pending
),
date_range=job["date_range"],
models=job["models"],
created_at=job["created_at"],
started_at=job.get("started_at"),
completed_at=job.get("completed_at"),
total_duration_seconds=job.get("total_duration_seconds"),
error=job.get("error"),
details=details
)
except HTTPException:
raise
except Exception as e:
logger.error(f"Failed to get job status: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@app.get("/results")
async def get_results(
job_id: Optional[str] = Query(None, description="Filter by job ID"),
date: Optional[str] = Query(None, description="Filter by date (YYYY-MM-DD)"),
model: Optional[str] = Query(None, description="Filter by model signature")
):
"""
Query simulation results.
Supports filtering by job_id, date, and/or model.
Returns position data with holdings.
Args:
job_id: Optional job UUID filter
date: Optional date filter (YYYY-MM-DD)
model: Optional model signature filter
Returns:
List of position records with holdings
"""
try:
conn = get_db_connection(app.state.db_path)
cursor = conn.cursor()
# Build query with filters
query = """
SELECT
p.id,
p.job_id,
p.date,
p.model,
p.action_id,
p.action_type,
p.symbol,
p.amount,
p.price,
p.cash,
p.portfolio_value,
p.daily_profit,
p.daily_return_pct,
p.created_at
FROM positions p
WHERE 1=1
"""
params = []
if job_id:
query += " AND p.job_id = ?"
params.append(job_id)
if date:
query += " AND p.date = ?"
params.append(date)
if model:
query += " AND p.model = ?"
params.append(model)
query += " ORDER BY p.date, p.model, p.action_id"
cursor.execute(query, params)
rows = cursor.fetchall()
results = []
for row in rows:
position_id = row[0]
# Get holdings for this position
cursor.execute("""
SELECT symbol, quantity
FROM holdings
WHERE position_id = ?
ORDER BY symbol
""", (position_id,))
holdings = [{"symbol": h[0], "quantity": h[1]} for h in cursor.fetchall()]
results.append({
"id": row[0],
"job_id": row[1],
"date": row[2],
"model": row[3],
"action_id": row[4],
"action_type": row[5],
"symbol": row[6],
"amount": row[7],
"price": row[8],
"cash": row[9],
"portfolio_value": row[10],
"daily_profit": row[11],
"daily_return_pct": row[12],
"created_at": row[13],
"holdings": holdings
})
conn.close()
return {"results": results, "count": len(results)}
except Exception as e:
logger.error(f"Failed to query results: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@app.get("/health", response_model=HealthResponse)
async def health_check():
"""
Health check endpoint.
Verifies database connectivity and service status.
Returns:
Health status and timestamp
"""
try:
# Test database connection
conn = get_db_connection(app.state.db_path)
cursor = conn.cursor()
cursor.execute("SELECT 1")
cursor.fetchone()
conn.close()
database_status = "connected"
except Exception as e:
logger.error(f"Database health check failed: {e}")
database_status = "disconnected"
return HealthResponse(
status="healthy" if database_status == "connected" else "unhealthy",
database=database_status,
timestamp=datetime.utcnow().isoformat() + "Z"
)
return app
# Create default app instance
app = create_app()
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8080)