#!/usr/bin/env python3
"""Regenerate DBT embeddings with qwen/qwen3-embedding-8b model (384 dimensions)"""

import json
import os
from openai import OpenAI
import time

# Load config
with open("config.json", "r") as f:
    config = json.load(f)

# Initialize OpenAI client with OpenRouter
client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key=config["openrouter_api_key"],
)

# Load text data
with open("bot/data/dbt_knowledge.text.json", "r") as f:
    text_data = json.load(f)

print(f"Regenerating embeddings for {len(text_data)} chunks...")

# Generate embeddings
embeddings_data = []
for i, item in enumerate(text_data):
    try:
        response = client.embeddings.create(
            model="qwen/qwen3-embedding-8b",
            input=item["text"]
        )
        embedding = response.data[0].embedding
        
        embeddings_data.append({
            "id": item["id"],
            "source": item["source"],
            "text": item["text"],
            "embedding": embedding
        })
        
        if (i + 1) % 10 == 0:
            print(f"Processed {i + 1}/{len(text_data)} chunks...")
            
        # Small delay to avoid rate limits
        time.sleep(0.1)
        
    except Exception as e:
        print(f"Error processing item {i}: {e}")
        continue

# Save new embeddings
with open("bot/data/dbt_knowledge.embeddings.json", "w") as f:
    json.dump(embeddings_data, f)

print(f"\nDone! Generated {len(embeddings_data)} embeddings with {len(embeddings_data[0]['embedding'])} dimensions")