Merge pull request #2335 from danielaskdd/llm-cache-cleanup
Feat: Add LLM Query Cache Cleanup Tool
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lightrag/tools/README_CLEAN_LLM_QUERY_CACHE.md
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lightrag/tools/README_CLEAN_LLM_QUERY_CACHE.md
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# LLM Query Cache Cleanup Tool - User Guide
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## Overview
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This tool cleans up LightRAG's LLM query cache from KV storage implementations. It specifically targets query caches generated during RAG query operations (modes: `mix`, `hybrid`, `local`, `global`), including both query and keywords caches.
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## Supported Storage Types
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1. **JsonKVStorage** - File-based JSON storage
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2. **RedisKVStorage** - Redis database storage
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3. **PGKVStorage** - PostgreSQL database storage
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4. **MongoKVStorage** - MongoDB database storage
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## Cache Types
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The tool cleans up the following query cache types:
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### Query Cache Modes (4 types)
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- `mix:*` - Mixed mode query caches
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- `hybrid:*` - Hybrid mode query caches
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- `local:*` - Local mode query caches
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- `global:*` - Global mode query caches
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### Cache Content Types (2 types)
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- `*:query:*` - Query result caches
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- `*:keywords:*` - Keywords extraction caches
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### Cache Key Format
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```
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<mode>:<cache_type>:<hash>
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```
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Examples:
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- `mix:query:5ce04d25e957c290216cee5bfe6344fa`
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- `mix:keywords:fee77b98244a0b047ce95e21060de60e`
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- `global:query:abc123def456...`
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- `local:keywords:789xyz...`
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**Important Note**: This tool does NOT clean extraction caches (`default:extract:*` and `default:summary:*`). Use the migration tool or manual deletion for those caches.
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## Prerequisites
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- The tool reads storage configuration from environment variables or `config.ini`
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- Ensure the target storage is properly configured and accessible
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- Backup important data before running cleanup operations
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## Usage
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### Basic Usage
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Run from the LightRAG project root directory:
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```bash
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python -m lightrag.tools.clean_llm_query_cache
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# or
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python lightrag/tools/clean_llm_query_cache.py
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```
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### Interactive Workflow
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The tool guides you through the following steps:
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#### 1. Select Storage Type
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```
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============================================================
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LLM Query Cache Cleanup Tool - LightRAG
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============================================================
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=== Storage Setup ===
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Supported KV Storage Types:
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[1] JsonKVStorage
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[2] RedisKVStorage
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[3] PGKVStorage
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[4] MongoKVStorage
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Select storage type (1-4) (Press Enter to exit): 1
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```
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**Note**: You can press Enter or type `0` at any prompt to exit gracefully.
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#### 2. Storage Validation
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The tool will:
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- Check required environment variables
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- Auto-detect workspace configuration
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- Initialize and connect to storage
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- Verify connection status
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```
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Checking configuration...
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✓ All required environment variables are set
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Initializing storage...
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- Storage Type: JsonKVStorage
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- Workspace: space1
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- Connection Status: ✓ Success
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```
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#### 3. View Cache Statistics
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The tool displays a detailed breakdown of query caches by mode and type:
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```
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Counting query cache records...
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📊 Query Cache Statistics (Before Cleanup):
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┌────────────┬────────────┬────────────┬────────────┐
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│ Mode │ Query │ Keywords │ Total │
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├────────────┼────────────┼────────────┼────────────┤
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│ mix │ 1,234 │ 567 │ 1,801 │
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│ hybrid │ 890 │ 423 │ 1,313 │
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│ local │ 2,345 │ 1,123 │ 3,468 │
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│ global │ 678 │ 345 │ 1,023 │
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├────────────┼────────────┼────────────┼────────────┤
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│ Total │ 5,147 │ 2,458 │ 7,605 │
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└────────────┴────────────┴────────────┴────────────┘
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```
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#### 4. Select Cleanup Scope
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Choose what type of caches to delete:
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```
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=== Cleanup Options ===
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[1] Delete all query caches (both query and keywords)
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[2] Delete query caches only (keep keywords)
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[3] Delete keywords caches only (keep query)
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[0] Cancel
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Select cleanup option (0-3): 1
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```
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**Cleanup Types:**
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- **Option 1 (all)**: Deletes both query and keywords caches across all modes
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- **Option 2 (query)**: Deletes only query caches, preserves keywords caches
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- **Option 3 (keywords)**: Deletes only keywords caches, preserves query caches
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#### 5. Confirm Deletion
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Review the cleanup plan and confirm:
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```
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============================================================
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Cleanup Confirmation
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============================================================
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Storage: JsonKVStorage (workspace: space1)
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Cleanup Type: all
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Records to Delete: 7,605 / 7,605
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⚠️ WARNING: This will delete ALL query caches across all modes!
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Continue with deletion? (y/n): y
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```
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#### 6. Execute Cleanup
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The tool performs batch deletion with real-time progress:
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**JsonKVStorage Example:**
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```
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=== Starting Cleanup ===
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💡 Processing 1,000 records at a time from JsonKVStorage
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Batch 1/8: ████░░░░░░░░░░░░░░░░ 1,000/7,605 (13.1%) ✓
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Batch 2/8: ████████░░░░░░░░░░░░ 2,000/7,605 (26.3%) ✓
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...
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Batch 8/8: ████████████████████ 7,605/7,605 (100.0%) ✓
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Persisting changes to storage...
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✓ Changes persisted successfully
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```
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**RedisKVStorage Example:**
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```
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=== Starting Cleanup ===
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💡 Processing Redis keys in batches of 1,000
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Batch 1: Deleted 1,000 keys (Total: 1,000) ✓
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Batch 2: Deleted 1,000 keys (Total: 2,000) ✓
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...
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```
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**PostgreSQL Example:**
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```
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=== Starting Cleanup ===
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💡 Executing PostgreSQL DELETE query
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✓ Deleted 7,605 records in 0.45s
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```
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**MongoDB Example:**
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```
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=== Starting Cleanup ===
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💡 Executing MongoDB deleteMany operations
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Pattern 1/8: Deleted 1,234 records ✓
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Pattern 2/8: Deleted 567 records ✓
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...
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Total deleted: 7,605 records
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```
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#### 7. Review Cleanup Report
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The tool provides a comprehensive final report:
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**Successful Cleanup:**
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```
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============================================================
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Cleanup Complete - Final Report
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============================================================
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📊 Statistics:
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Total records to delete: 7,605
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Total batches: 8
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Successful batches: 8
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Failed batches: 0
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Successfully deleted: 7,605
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Failed to delete: 0
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Success rate: 100.00%
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📈 Before/After Comparison:
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Total caches before: 7,605
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Total caches after: 0
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Net reduction: 7,605
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============================================================
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✓ SUCCESS: All records cleaned up successfully!
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============================================================
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📊 Query Cache Statistics (After Cleanup):
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┌────────────┬────────────┬────────────┬────────────┐
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│ Mode │ Query │ Keywords │ Total │
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├────────────┼────────────┼────────────┼────────────┤
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│ mix │ 0 │ 0 │ 0 │
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│ hybrid │ 0 │ 0 │ 0 │
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│ local │ 0 │ 0 │ 0 │
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│ global │ 0 │ 0 │ 0 │
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├────────────┼────────────┼────────────┼────────────┤
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│ Total │ 0 │ 0 │ 0 │
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└────────────┴────────────┴────────────┴────────────┘
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```
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**Cleanup with Errors:**
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```
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============================================================
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Cleanup Complete - Final Report
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============================================================
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📊 Statistics:
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Total records to delete: 7,605
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Total batches: 8
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Successful batches: 7
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Failed batches: 1
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Successfully deleted: 6,605
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Failed to delete: 1,000
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Success rate: 86.85%
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📈 Before/After Comparison:
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Total caches before: 7,605
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Total caches after: 1,000
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Net reduction: 6,605
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⚠️ Errors encountered: 1
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Error Details:
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------------------------------------------------------------
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Error Summary:
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- ConnectionError: 1 occurrence(s)
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First 5 errors:
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1. Batch 3
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Type: ConnectionError
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Message: Connection timeout after 30s
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Records lost: 1,000
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============================================================
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⚠️ WARNING: Cleanup completed with errors!
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Please review the error details above.
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============================================================
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```
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## Technical Details
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### Workspace Handling
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The tool retrieves workspace in the following priority order:
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1. **Storage-specific workspace environment variables**
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- PGKVStorage: `POSTGRES_WORKSPACE`
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- MongoKVStorage: `MONGODB_WORKSPACE`
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- RedisKVStorage: `REDIS_WORKSPACE`
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2. **Generic workspace environment variable**
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- `WORKSPACE`
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3. **Default value**
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- Empty string (uses storage's default workspace)
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### Batch Deletion
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- Default batch size: 1000 records/batch
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- Prevents memory overflow and connection timeouts
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- Each batch is processed independently
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- Failed batches are logged but don't stop cleanup
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### Storage-Specific Deletion Strategies
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#### JsonKVStorage
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- Collects all matching keys first (snapshot approach)
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- Deletes in batches with lock protection
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- Fast in-memory operations
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#### RedisKVStorage
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- Uses SCAN with pattern matching
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- Pipeline DELETE for batch operations
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- Cursor-based iteration for large datasets
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#### PostgreSQL
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- Single DELETE query with OR conditions
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- Efficient server-side bulk deletion
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- Uses LIKE patterns for mode/type matching
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#### MongoDB
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- Multiple deleteMany operations (one per pattern)
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- Regex-based document matching
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- Returns exact deletion counts
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### Pattern Matching Implementation
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**JsonKVStorage:**
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```python
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# Direct key prefix matching
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if key.startswith("mix:query:") or key.startswith("mix:keywords:")
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```
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**RedisKVStorage:**
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```python
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# SCAN with namespace-prefixed patterns
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pattern = f"{namespace}:mix:query:*"
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cursor, keys = await redis.scan(cursor, match=pattern)
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```
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**PostgreSQL:**
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```python
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# SQL LIKE conditions
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WHERE id LIKE 'mix:query:%' OR id LIKE 'mix:keywords:%'
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```
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**MongoDB:**
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```python
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# Regex queries on _id field
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{"_id": {"$regex": "^mix:query:"}}
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```
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## Error Handling & Resilience
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The tool implements comprehensive error tracking:
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### Batch-Level Error Tracking
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- Each batch is independently error-checked
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- Failed batches are logged with full details
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- Successful batches commit even if later batches fail
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- Real-time progress shows ✓ (success) or ✗ (failed)
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### Error Reporting
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After cleanup completes, a detailed report includes:
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- **Statistics**: Total records, success/failure counts, success rate
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- **Before/After Comparison**: Net reduction in cache count
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- **Error Summary**: Grouped by error type with occurrence counts
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- **Error Details**: Batch number, error type, message, and records lost
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- **Recommendations**: Clear indication of success or need for review
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### Verification
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- Post-cleanup count verification
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- Before/after statistics comparison
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- Identifies partial cleanup scenarios
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## Important Notes
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1. **Irreversible Operation**
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- Deleted caches cannot be recovered
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- Always backup important data before cleanup
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- Test on non-production data first
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2. **Performance Impact**
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- Query performance may degrade temporarily after cleanup
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- Caches will rebuild on subsequent queries
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- Consider cleanup during off-peak hours
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3. **Selective Cleanup**
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- Choose cleanup scope carefully
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- Keywords caches may be valuable for future queries
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- Query caches rebuild faster than keywords caches
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4. **Workspace Isolation**
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- Cleanup only affects the selected workspace
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- Other workspaces remain untouched
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- Verify workspace before confirming cleanup
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5. **Interrupt and Resume**
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- Cleanup can be interrupted at any time (Ctrl+C)
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- Already deleted records cannot be recovered
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- No automatic resume - must run tool again
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## Storage Configuration
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The tool supports multiple configuration methods with the following priority:
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1. **Environment variables** (highest priority)
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2. **config.ini file** (medium priority)
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3. **Default values** (lowest priority)
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### Environment Variable Configuration
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Configure storage settings in your `.env` file:
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#### Workspace Configuration (Optional)
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```bash
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# Generic workspace (shared by all storages)
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WORKSPACE=space1
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# Or configure independent workspace for specific storage
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POSTGRES_WORKSPACE=pg_space
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MONGODB_WORKSPACE=mongo_space
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REDIS_WORKSPACE=redis_space
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```
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**Workspace Priority**: Storage-specific > Generic WORKSPACE > Empty string
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#### JsonKVStorage
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```bash
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WORKING_DIR=./rag_storage
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```
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#### RedisKVStorage
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```bash
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REDIS_URI=redis://localhost:6379
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```
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#### PGKVStorage
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```bash
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POSTGRES_HOST=localhost
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POSTGRES_PORT=5432
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POSTGRES_USER=your_username
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POSTGRES_PASSWORD=your_password
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POSTGRES_DATABASE=your_database
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```
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#### MongoKVStorage
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```bash
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MONGO_URI=mongodb://root:root@localhost:27017/
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MONGO_DATABASE=LightRAG
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```
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### config.ini Configuration
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Alternatively, create a `config.ini` file in the project root:
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```ini
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[redis]
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uri = redis://localhost:6379
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[postgres]
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host = localhost
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port = 5432
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user = postgres
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password = yourpassword
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database = lightrag
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[mongodb]
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uri = mongodb://root:root@localhost:27017/
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database = LightRAG
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```
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**Note**: Environment variables take precedence over config.ini settings.
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## Troubleshooting
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### Missing Environment Variables
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```
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⚠️ Warning: Missing environment variables: POSTGRES_USER, POSTGRES_PASSWORD
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```
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**Solution**: Add missing variables to your `.env` file or configure in `config.ini`
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### Connection Failed
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```
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✗ Initialization failed: Connection refused
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```
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**Solutions**:
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- Check if database service is running
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- Verify connection parameters (host, port, credentials)
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- Check firewall settings
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- Ensure network connectivity for remote databases
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### No Caches Found
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```
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⚠️ No query caches found in storage
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```
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**Possible Reasons**:
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||||
- No queries have been run yet
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- Caches were already cleaned
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||||
- Wrong workspace selected
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||||
- Different storage type was used for queries
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||||
|
||||
### Partial Cleanup
|
||||
```
|
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⚠️ WARNING: Cleanup completed with errors!
|
||||
```
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**Solutions**:
|
||||
- Check error details in the report
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||||
- Verify storage connection stability
|
||||
- Re-run tool to clean remaining caches
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- Check storage capacity and permissions
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||||
|
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## Use Cases
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### Use Case 1: Clean All Query Caches
|
||||
|
||||
**Scenario**: Free up storage space by removing all query caches
|
||||
|
||||
```bash
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# Run tool
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||||
python -m lightrag.tools.clean_llm_query_cache
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||||
|
||||
# Select: Storage type -> Option 1 (all) -> Confirm (y)
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||||
```
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||||
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||||
**Result**: All query and keywords caches deleted, maximum storage freed
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||||
|
||||
### Use Case 2: Refresh Query Caches Only
|
||||
|
||||
**Scenario**: Force query cache rebuild while keeping keywords
|
||||
|
||||
```bash
|
||||
# Run tool
|
||||
python -m lightrag.tools.clean_llm_query_cache
|
||||
|
||||
# Select: Storage type -> Option 2 (query only) -> Confirm (y)
|
||||
```
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||||
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||||
**Result**: Query caches deleted, keywords preserved for faster rebuild
|
||||
|
||||
### Use Case 3: Clean Stale Keywords
|
||||
|
||||
**Scenario**: Remove outdated keywords while keeping recent query results
|
||||
|
||||
```bash
|
||||
# Run tool
|
||||
python -m lightrag.tools.clean_llm_query_cache
|
||||
|
||||
# Select: Storage type -> Option 3 (keywords only) -> Confirm (y)
|
||||
```
|
||||
|
||||
**Result**: Keywords deleted, query caches preserved
|
||||
|
||||
### Use Case 4: Workspace-Specific Cleanup
|
||||
|
||||
**Scenario**: Clean caches for a specific workspace
|
||||
|
||||
```bash
|
||||
# Configure workspace
|
||||
export WORKSPACE=development
|
||||
|
||||
# Run tool
|
||||
python -m lightrag.tools.clean_llm_query_cache
|
||||
|
||||
# Select: Storage type -> Cleanup option -> Confirm (y)
|
||||
```
|
||||
|
||||
**Result**: Only development workspace caches cleaned
|
||||
|
||||
## Best Practices
|
||||
|
||||
1. **Backup Before Cleanup**
|
||||
- Always backup your storage before major cleanup
|
||||
- Test cleanup on non-production data first
|
||||
- Document cleanup decisions
|
||||
|
||||
2. **Monitor Performance**
|
||||
- Watch storage metrics during cleanup
|
||||
- Monitor query performance after cleanup
|
||||
- Allow time for cache rebuild
|
||||
|
||||
3. **Scheduled Cleanup**
|
||||
- Clean caches periodically (weekly/monthly)
|
||||
- Automate cleanup for development environments
|
||||
- Keep production cleanup manual for safety
|
||||
|
||||
4. **Selective Deletion**
|
||||
- Consider cleanup scope based on needs
|
||||
- Keywords caches are harder to rebuild
|
||||
- Query caches rebuild automatically
|
||||
|
||||
5. **Storage Capacity**
|
||||
- Monitor storage usage trends
|
||||
- Clean caches before reaching capacity limits
|
||||
- Archive old data if needed
|
||||
|
||||
## Comparison with Migration Tool
|
||||
|
||||
| Feature | Cleanup Tool | Migration Tool |
|
||||
|---------|-------------|----------------|
|
||||
| **Purpose** | Delete query caches | Migrate extraction caches |
|
||||
| **Cache Types** | mix/hybrid/local/global | default:extract/summary |
|
||||
| **Modes** | query, keywords | extract, summary |
|
||||
| **Operation** | Deletion | Copy between storages |
|
||||
| **Reversible** | No | Yes (source unchanged) |
|
||||
| **Use Case** | Free storage, refresh caches | Change storage backend |
|
||||
|
||||
## Limitations
|
||||
|
||||
1. **Single Storage Operation**
|
||||
- Can only clean one storage type at a time
|
||||
- To clean multiple storages, run tool multiple times
|
||||
|
||||
2. **No Dry Run Mode**
|
||||
- Deletion is immediate after confirmation
|
||||
- No preview-only mode available
|
||||
- Test on non-production first
|
||||
|
||||
3. **No Selective Mode Cleanup**
|
||||
- Cannot clean only specific modes (e.g., only `mix`)
|
||||
- Cleanup applies to all modes for selected cache type
|
||||
- All-or-nothing per cache type
|
||||
|
||||
4. **No Scheduled Cleanup**
|
||||
- Manual execution required
|
||||
- No built-in scheduling
|
||||
- Use cron/scheduler if automation needed
|
||||
|
||||
5. **Verification Limitations**
|
||||
- Post-cleanup verification may fail in error scenarios
|
||||
- Manual verification recommended for critical operations
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
Potential improvements for future versions:
|
||||
|
||||
- Selective mode cleanup (e.g., clean only `mix` mode)
|
||||
- Age-based cleanup (delete caches older than X days)
|
||||
- Size-based cleanup (delete largest caches first)
|
||||
- Dry run mode for safe preview
|
||||
- Automated scheduling support
|
||||
- Cache statistics export
|
||||
- Incremental cleanup with pause/resume
|
||||
|
||||
## Support
|
||||
|
||||
For issues, questions, or feature requests:
|
||||
- Check the error details in the cleanup report
|
||||
- Review storage configuration
|
||||
- Verify workspace settings
|
||||
- Test with a small dataset first
|
||||
- Report bugs through project issue tracker
|
||||
1112
lightrag/tools/clean_llm_query_cache.py
Normal file
1112
lightrag/tools/clean_llm_query_cache.py
Normal file
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Reference in a new issue