merge: chore/cleanup-remove-bloat-and-secrets into main
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scripts/migrate_redis_to_pgvector_v2.py
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258
scripts/migrate_redis_to_pgvector_v2.py
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#!/usr/bin/env python3
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"""
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Resilient Redis → Supabase pgvector migration v2.
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Fixes: smaller batches, retry on timeout, HNSW index dropped for speed.
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"""
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import asyncio
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import json
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import logging
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import os
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import time
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import httpx
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import redis.asyncio as aioredis
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from dotenv import load_dotenv
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load_dotenv("/app/.env", override=True)
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logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
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logger = logging.getLogger(__name__)
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TARGET_DIM = 640
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BATCH_SIZE = 50 # Smaller batches to avoid Supabase statement timeout
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MAX_RETRIES = 3
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COLLECTIONS = [
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"wallet_profiles", # ~50K already migrated
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"token_analysis",
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"known_scams",
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"scam_patterns",
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"forensic_reports",
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"market_intel",
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"contract_audits",
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"news_articles",
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"transaction_patterns",
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"general",
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]
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def _get_url():
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return os.environ.get("SUPABASE_URL", "")
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def _get_key():
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return os.environ.get("SUPABASE_SERVICE_KEY", "") or os.environ.get("SUPABASE_SERVICE_ROLE_KEY", "")
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def _get_headers():
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key = _get_key()
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return {
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"apikey": key,
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"Authorization": f"Bearer {key}",
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"Content-Type": "application/json",
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"Prefer": "resolution=merge-duplicates",
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}
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def pad_vector(vec: list, target_dim: int) -> list:
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if len(vec) == target_dim:
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return vec
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if len(vec) > target_dim:
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return vec[:target_dim]
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return vec + [0.0] * (target_dim - len(vec))
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async def get_existing_ids(client: httpx.AsyncClient) -> set:
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"""Fetch existing doc IDs from rag_vectors for idempotency."""
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existing = set()
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offset = 0
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limit = 1000
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while True:
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url = f"{_get_url()}/rest/v1/rag_vectors"
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params = {"select": "id", "limit": str(limit), "offset": str(offset), "order": "id"}
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try:
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resp = await client.get(url, params=params, headers=_get_headers(), timeout=30)
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if resp.status_code != 200:
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logger.warning(f"Could not fetch existing IDs: {resp.status_code}")
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break
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rows = resp.json() if resp.text else []
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if not rows:
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break
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for row in rows:
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existing.add(row["id"])
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if len(rows) < limit:
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break
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offset += limit
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except Exception as e:
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logger.warning(f"Error fetching existing IDs: {e}")
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break
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logger.info(f"Found {len(existing)} existing docs in rag_vectors")
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return existing
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async def insert_with_retry(client: httpx.AsyncClient, rows: list, batch_num: int) -> int:
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"""Insert a batch with retry logic."""
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url = f"{_get_url()}/rest/v1/rag_vectors"
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params = {"on_conflict": "id"}
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for attempt in range(MAX_RETRIES):
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try:
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resp = await client.post(url, json=rows, params=params, headers=_get_headers(), timeout=60)
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if resp.status_code in (200, 201):
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return len(rows)
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elif resp.status_code == 500 and "timeout" in (resp.text or "").lower():
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# Statement timeout — split into smaller batches
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logger.warning(f"Batch {batch_num}: statement timeout (attempt {attempt + 1}), splitting")
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if len(rows) > 10:
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# Split into two halves
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mid = len(rows) // 2
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count = 0
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for half in [rows[:mid], rows[mid:]]:
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r2 = await client.post(url, json=half, params=params, headers=_get_headers(), timeout=90)
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if r2.status_code in (200, 201):
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count += len(half)
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else:
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# Last resort: insert one by one
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for row in half:
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try:
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r3 = await client.post(
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url,
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json=[row],
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params=params,
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headers=_get_headers(),
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timeout=30,
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)
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if r3.status_code in (200, 201):
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count += 1
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await asyncio.sleep(0.02)
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except Exception:
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pass
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return count
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else:
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logger.error(f"Batch {batch_num} insert failed: {resp.status_code} {resp.text[:300]}")
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return 0
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except httpx.ReadTimeout:
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logger.warning(f"Batch {batch_num}: timeout (attempt {attempt + 1})")
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await asyncio.sleep(2**attempt)
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except Exception as e:
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logger.error(f"Batch {batch_num} exception: {e}")
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await asyncio.sleep(1)
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return 0
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async def migrate_collection(r: aioredis.Redis, client: httpx.AsyncClient, collection: str, existing_ids: set) -> int:
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"""Migrate all docs from one Redis collection to Supabase."""
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idx_key = f"rag:idx:{collection}"
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doc_ids = await r.smembers(idx_key)
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if not doc_ids:
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logger.info(f"Collection {collection}: empty, skipping")
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return 0
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total_docs = len(doc_ids)
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to_migrate = [did for did in doc_ids if did not in existing_ids]
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skipped = total_docs - len(to_migrate)
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if skipped > 0:
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logger.info(
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f"Collection {collection}: {total_docs} total, skipping {skipped} already-migrated, {len(to_migrate)} to go"
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)
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migrated = 0
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errors = 0
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batch_rows = []
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batch_count = 0
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for _i, doc_id in enumerate(to_migrate):
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doc_key = f"rag:{collection}:{doc_id}"
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try:
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data = await r.get(doc_key)
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if not data:
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continue
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doc = json.loads(data)
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vector = doc.get("vector", [])
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content = doc.get("content", "") or ""
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metadata = doc.get("metadata", {}) or {}
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source = metadata.get("source", "") or doc.get("source", "") or ""
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severity = metadata.get("severity", "") or doc.get("severity", "") or "medium"
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chain = metadata.get("chain", "") or doc.get("chain", "") or ""
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padded = pad_vector(vector, TARGET_DIM) if vector else [0.0] * TARGET_DIM
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row = {
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"id": str(doc_id),
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"collection": collection,
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"content": content[:10000],
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"embedding": padded,
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"metadata": json.dumps(metadata) if isinstance(metadata, dict) else str(metadata),
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"source": source[:200] if source else "",
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"severity": severity[:50] if severity else "medium",
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"chain": chain[:50] if chain else "",
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}
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batch_rows.append(row)
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if len(batch_rows) >= BATCH_SIZE:
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count = await insert_with_retry(client, batch_rows, batch_count)
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migrated += count
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batch_count += 1
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if batch_count % 10 == 0:
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logger.info(f" Progress: {migrated}/{len(to_migrate)} migrated ({batch_count} batches)")
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batch_rows = []
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await asyncio.sleep(0.1)
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except json.JSONDecodeError:
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errors += 1
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except Exception as e:
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errors += 1
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if errors <= 5:
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logger.warning(f" Doc {doc_id}: {e}")
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# Flush remaining
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if batch_rows:
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count = await insert_with_retry(client, batch_rows, batch_count)
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migrated += count
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logger.info(f"Collection {collection}: DONE {migrated}/{len(to_migrate)} ({errors} errors)")
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return migrated
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async def main():
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logger.info(f"Starting migration v2 (batch_size={BATCH_SIZE})")
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logger.info(f"Supabase: {_get_url()[:30]}...")
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logger.info(f"Target dim: {TARGET_DIM}")
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r = aioredis.Redis(
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host=os.environ.get("REDIS_HOST", "rmi-redis"),
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port=int(os.environ.get("REDIS_PORT", "6379")),
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password=os.environ.get("REDIS_PASSWORD", ""),
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decode_responses=True,
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)
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await r.ping()
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logger.info("Redis connected")
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async with httpx.AsyncClient(timeout=120) as client:
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existing_ids = await get_existing_ids(client)
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total = 0
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start = time.time()
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for coll in COLLECTIONS:
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try:
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n = await migrate_collection(r, client, coll, existing_ids)
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total += n
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except Exception as e:
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logger.error(f"Collection {coll} FAILED: {e}")
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elapsed = time.time() - start
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logger.info("=" * 60)
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logger.info(f"Migration v2 complete: {total} docs in {elapsed:.1f}s")
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logger.info(
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"Now rebuild HNSW index: CREATE INDEX idx_rag_vectors_hnsw ON rag_vectors USING hnsw (embedding vector_cosine_ops) WITH (m = 16, ef_construction = 64);"
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)
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await r.aclose()
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if __name__ == "__main__":
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asyncio.run(main())
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