⚡ Live Sandbox: AI Dev Tool: PostgreSQL Vector Search Extension

📝 Editable Code Sandbox

```python
# AI Dev Tool: Edge AI-Powered Vector Search API
# =============================================
# A production-ready API integration wrapper for PostgreSQL Vector Search Extension
# using FastAPI, Pydantic v2, and Cloudflare Workers for edge computing

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List, Optional
import psycopg2
import json
from cloudflare import WorkersKV

# Define the Vector Search API model
class VectorSearchQuery(BaseModel):
    """Vector search query model"""
    query_vector: List[float]
    limit: Optional[int] = 10

# Define the API response model
class VectorSearchResponse(BaseModel):
    """Vector search response model"""
    results: List[dict]

# Initialize the FastAPI app
app = FastAPI()

# Initialize the PostgreSQL connection
conn = psycopg2.connect(
    host="your_host",
    database="your_database",
    user="your_user",
    password="your_password"
)

# Initialize the Cloudflare Workers KV store
kv = WorkersKV("your_kv_namespace")

# Define the vector search API endpoint
@app.post("/vector_search", response_model=VectorSearchResponse)
async def vector_search(query: VectorSearchQuery):
    """

🖥️ Interactive Execution Terminal Console

⚡ Ready! Click ▶️ Run Code to execute code in browser terminal...