mirror of
https://github.com/velocitatem/PHANTOM.git
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114 lines
3.9 KiB
Python
114 lines
3.9 KiB
Python
from fastapi import FastAPI, HTTPException, Query
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from typing import Literal, Optional
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import uvicorn, os, sys
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from supabase import create_client, Client
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from dotenv import load_dotenv
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import numpy as np
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import pandas as pd
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load_dotenv()
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# Local imports of registry and pricing function
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sys.path.append(os.path.dirname(os.path.abspath(__file__))+ "/../../experiments/")
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from procesing.providers import SupabaseProvider, BackendAPIProvider
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from procesing.pricers import (
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StaticPricer,
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RandomPricer,
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ElasticityBasedPricer
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)
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from procesing.steps import (
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PredictPricesStep
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)
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from procesing import PipelineContext
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sys.path.append(os.path.dirname(os.path.abspath(__file__))+ "/../../lib/")
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print(os.path.dirname(os.path.abspath(__file__))+ "/../../lib/")
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from lib.model_registry import ModelRegistry
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# Config
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app = FastAPI(title="PHANTOM Pricing Provider")
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app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
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supabase: Client = create_client(os.getenv("NEXT_PUBLIC_SUPABASE_URL"), os.getenv("NEXT_PUBLIC_SUPABASE_ANON_KEY"))
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registry = ModelRegistry()
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class PriceResponse(BaseModel):
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productId: str
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price: float
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base_price: float
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markup: float
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elasticity: Optional[float] = None
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model_version: str = 'latest'
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@app.get("/health")
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def health() -> dict:
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return {"status": "healthy", "redis": registry.health_check()}
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@app.get("/api/{mode}/price/{productId}", response_model=PriceResponse)
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def get_price(mode: Literal['hotel', 'airline'], productId: str, sessionId: Optional[str] = Query(None), experimentId: Optional[str] = Query(None)):
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product = supabase.table(f'{mode}_products').select("metadata").eq('id', productId).execute().data[0]
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if not product: raise HTTPException(404, f"Product {productId} not found")
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metadata = product['metadata']
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base_price = metadata.get('base_price', 100.0)
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# fetch pre-computed prices from registry
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prices_df = registry.get_prices('latest')
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elasticity_df = registry.get_elasticity('latest')
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if prices_df is None:
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# fallback: no pre-computed prices available
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return PriceResponse(
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productId=productId,
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price=base_price,
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base_price=base_price,
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markup=1.0,
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elasticity=None
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)
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# lookup pre-computed price for this product
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product_price_row = prices_df[prices_df['productId'] == productId]
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if product_price_row.empty:
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# product not in pre-computed prices, fallback to base
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return PriceResponse(
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productId=productId,
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price=base_price,
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base_price=base_price,
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markup=1.0,
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elasticity=None
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)
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optimal_price = float(product_price_row['predicted_price'].iloc[0])
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# get elasticity if available
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product_elasticity = None
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if elasticity_df is not None:
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product_elasticity_row = elasticity_df[elasticity_df['productId'] == productId]
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if not product_elasticity_row.empty:
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product_elasticity = float(product_elasticity_row['elasticity'].iloc[0])
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return PriceResponse(
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productId=productId,
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price=optimal_price,
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base_price=base_price,
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markup=optimal_price/base_price,
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elasticity=product_elasticity
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)
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@app.get("/models")
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def list_models(): return registry.list_models()
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@app.post("/models/reload")
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def reload_models():
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elasticity, pricing_model = registry.get_elasticity('latest'), registry.get_pricing_model('latest')
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return {
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"elasticity_loaded": bool(elasticity),
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"n_products": len(elasticity) if elasticity is not None else 0,
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"pricing_model_loaded": bool(pricing_model),
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"model_class": pricing_model.__class__.__name__ if pricing_model else None
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}
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=int(os.getenv("PROVIDER_PORT", "5001")))
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