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+###########################################################################################
+### LightRAG Configuration - Optimized for Books, Articles, and Podcast Transcripts
+###
+### FILL IN THE FOLLOWING PLACEHOLDERS:
+### - YOUR_OPENAI_API_KEY_HERE (for GPT-5-mini)
+### - YOUR_VOYAGE_API_KEY_HERE (for voyage-3-large embeddings)
+### - YOUR_JINA_API_KEY_HERE (for Jina reranker)
+### - Neo4j connection details (URI, username, password, database)
+### - Postgres connection details (host, port, user, password, database)
+###########################################################################################
+
+###########################
+### Server Configuration
+###########################
+HOST=0.0.0.0
+PORT=9621
+WEBUI_TITLE='My Graph KB'
+WEBUI_DESCRIPTION="Knowledge Graph for Books, Articles & Podcasts"
+
+### Worker Configuration
+### Optimized for Dell T140 (6-core Xeon E-2226G, 32GB RAM)
+WORKERS=3
+TIMEOUT=180
+
+### Directory Configuration
+### Uncomment and set if you want custom paths (otherwise defaults to ./inputs and ./rag_storage)
+# INPUT_DIR=/path/to/your/inputs
+# WORKING_DIR=/path/to/your/working_dir
+
+### Logging
+LOG_LEVEL=INFO
+# LOG_DIR=/path/to/logs
+
+#####################################
+### Authentication (Optional)
+#####################################
+### Uncomment if you want to secure your API
+# LIGHTRAG_API_KEY=your-secure-api-key-here
+# AUTH_ACCOUNTS='admin:admin123'
+# TOKEN_SECRET=Your-Secret-Key-For-JWT
+# TOKEN_EXPIRE_HOURS=48
+
+######################################################################################
+### Query Configuration
+### Optimized for long-form content (books, articles, transcripts)
+######################################################################################
+ENABLE_LLM_CACHE=true
+
+### Increase these for better context with long documents
+TOP_K=50
+CHUNK_TOP_K=25
+MAX_ENTITY_TOKENS=8000
+MAX_RELATION_TOKENS=10000
+MAX_TOTAL_TOKENS=40000
+
+### Use VECTOR method for better semantic matching
+KG_CHUNK_PICK_METHOD=VECTOR
+
+#########################################################
+### Reranking Configuration - JINA AI
+#########################################################
+RERANK_BINDING=jina
+RERANK_BY_DEFAULT=true
+RERANK_MODEL=jina-reranker-v2-base-multilingual
+RERANK_BINDING_HOST=https://api.jina.ai/v1/rerank
+RERANK_BINDING_API_KEY=YOUR_JINA_API_KEY_HERE
+
+### Keep all chunks for reranking (let Jina do the filtering)
+MIN_RERANK_SCORE=0.0
+
+########################################
+### Document Processing Configuration
+########################################
+ENABLE_LLM_CACHE_FOR_EXTRACT=true
+SUMMARY_LANGUAGE=English
+
+### Chunk size optimized for long-form content
+CHUNK_SIZE=1200
+CHUNK_OVERLAP_SIZE=100
+
+### Entity types optimized for mixed content (books, articles, podcasts)
+ENTITY_TYPES='["Person", "Organization", "Location", "Event", "Concept", "Method", "Theory", "Technology", "Product", "Research", "Topic"]'
+
+### Summary configuration
+FORCE_LLM_SUMMARY_ON_MERGE=8
+SUMMARY_MAX_TOKENS=1500
+SUMMARY_LENGTH_RECOMMENDED_=800
+SUMMARY_CONTEXT_SIZE=15000
+
+### Related chunks per entity/relation
+RELATED_CHUNK_NUMBER=5
+
+###############################
+### Concurrency Configuration
+### Optimized for Dell T140 (6-core Xeon E-2226G, 32GB RAM)
+###############################
+MAX_ASYNC=6
+MAX_PARALLEL_INSERT=2
+EMBEDDING_FUNC_MAX_ASYNC=12
+EMBEDDING_BATCH_NUM=10
+
+###########################################################################
+### LLM Configuration - OpenAI GPT-5-mini
+###########################################################################
+LLM_BINDING=openai
+LLM_MODEL=gpt-5-mini
+LLM_BINDING_HOST=https://api.openai.com/v1
+LLM_BINDING_API_KEY=YOUR_OPENAI_API_KEY_HERE
+LLM_TIMEOUT=180
+
+### GPT-5 configuration
+OPENAI_LLM_MAX_COMPLETION_TOKENS=9000
+OPENAI_LLM_TEMPERATURE=0.7
+
+#######################################################################################
+### Embedding Configuration - Voyage AI (voyage-3-large)
+### ⚠️ IMPORTANT: Do NOT change after processing your first file!
+#######################################################################################
+EMBEDDING_BINDING=openai
+EMBEDDING_MODEL=voyage-3-large
+EMBEDDING_DIM=2048
+EMBEDDING_SEND_DIM=false
+EMBEDDING_TOKEN_LIMIT=32000
+EMBEDDING_BINDING_HOST=https://api.voyageai.com/v1
+EMBEDDING_BINDING_API_KEY=YOUR_VOYAGE_API_KEY_HERE
+EMBEDDING_TIMEOUT=60
+
+####################################################################
+### Workspace Configuration (Optional)
+### Uncomment to isolate data between different LightRAG instances
+####################################################################
+# WORKSPACE=my_knowledge_base
+
+############################
+### Storage Configuration
+############################
+### Using Neo4j for graph + Postgres for everything else
+
+### Graph Storage
+LIGHTRAG_GRAPH_STORAGE=Neo4JStorage
+
+### Vector, KV, and Doc Status Storage (All in Postgres)
+LIGHTRAG_VECTOR_STORAGE=PGVectorStorage
+LIGHTRAG_KV_STORAGE=PGKVStorage
+LIGHTRAG_DOC_STATUS_STORAGE=PGDocStatusStorage
+
+###########################
+### PostgreSQL Configuration
+### FILL IN YOUR DETAILS:
+###   - POSTGRES_HOST: Docker container name (e.g., 'postgres') or IP address
+###   - POSTGRES_PORT: Usually 5432
+###   - POSTGRES_USER: Your postgres username
+###   - POSTGRES_PASSWORD: Your postgres password
+###   - POSTGRES_DATABASE: Database name (e.g., 'lightrag')
+###########################
+POSTGRES_HOST=YOUR_POSTGRES_HOST_HERE
+POSTGRES_PORT=5432
+POSTGRES_USER=YOUR_POSTGRES_USER_HERE
+POSTGRES_PASSWORD='YOUR_POSTGRES_PASSWORD_HERE'
+POSTGRES_DATABASE=YOUR_POSTGRES_DATABASE_HERE
+POSTGRES_MAX_CONNECTIONS=20
+
+### PostgreSQL Vector Storage - HNSW index (best for quality)
+POSTGRES_VECTOR_INDEX_TYPE=HNSW
+POSTGRES_HNSW_M=16
+POSTGRES_HNSW_EF=200
+
+### Connection retry configuration (good for Docker networking)
+POSTGRES_CONNECTION_RETRIES=3
+POSTGRES_CONNECTION_RETRY_BACKOFF=0.5
+POSTGRES_CONNECTION_RETRY_BACKOFF_MAX=5.0
+POSTGRES_POOL_CLOSE_TIMEOUT=5.0
+
+###########################
+### Neo4j Configuration
+### FILL IN YOUR DETAILS:
+###   - NEO4J_URI: Connection string
+###     Examples:
+###       bolt://neo4j:7687 (Docker, no SSL)
+###       neo4j://neo4j:7687 (Docker, no SSL)
+###       neo4j+s://your-instance.databases.neo4j.io (Cloud with SSL)
+###   - NEO4J_USERNAME: Usually 'neo4j'
+###   - NEO4J_PASSWORD: Your neo4j password
+###   - NEO4J_DATABASE: Database name (usually 'neo4j')
+###########################
+NEO4J_URI=YOUR_NEO4J_URI_HERE
+NEO4J_USERNAME=neo4j
+NEO4J_PASSWORD='YOUR_NEO4J_PASSWORD_HERE'
+NEO4J_DATABASE=neo4j
+
+### Neo4j connection pool settings (optimized for your Dell T140)
+NEO4J_MAX_CONNECTION_POOL_SIZE=75
+NEO4J_CONNECTION_TIMEOUT=30
+NEO4J_CONNECTION_ACQUISITION_TIMEOUT=30
+NEO4J_MAX_TRANSACTION_RETRY_TIME=30
+NEO4J_MAX_CONNECTION_LIFETIME=300
+NEO4J_LIVENESS_CHECK_TIMEOUT=30
+NEO4J_KEEP_ALIVE=true
+
+###########################################################################################
+### WORKER CONFIGURATION - OPTIMIZED FOR YOUR DELL T140
+###########################################################################################
+### Current settings optimized for:
+###   - CPU: Intel Xeon E-2226G (6 cores @ 3.40GHz)
+###   - RAM: 32GB (currently 65% utilized, ~11GB free)
+###   - Current load: 10-15% CPU usage
+###
+### Settings:
+###   WORKERS=3              - 3 Gunicorn server processes (good for 6-core CPU)
+###   MAX_ASYNC=6            - 6 concurrent LLM API requests (balanced for API limits)
+###   MAX_PARALLEL_INSERT=2  - 2 documents processed in parallel (prevents API overload)
+###   EMBEDDING_FUNC_MAX_ASYNC=12 - 12 concurrent embedding requests (embeddings are lighter)
+###
+### These settings utilize ~40-50% of your CPU during heavy processing, leaving plenty
+### of headroom for your other Unraid services. API rate limits are the bottleneck, not
+### your server hardware.
+###
+### If you experience OpenAI rate limit errors, reduce MAX_ASYNC to 4.
+### If your server load stays very low (<20%), you can increase MAX_ASYNC to 8.
+###########################################################################################
+
+###########################################################################################
+### QUICK START CHECKLIST
+###########################################################################################
+### 1. Fill in API keys:
+###    - YOUR_OPENAI_API_KEY_HERE (for GPT-5-mini)
+###    - YOUR_VOYAGE_API_KEY_HERE (for voyage-3-large embeddings)
+###    - YOUR_JINA_API_KEY_HERE (for reranking)
+###
+### 2. Fill in Postgres details:
+###    - POSTGRES_HOST (e.g., 'postgres' if Docker container name)
+###    - POSTGRES_USER
+###    - POSTGRES_PASSWORD
+###    - POSTGRES_DATABASE (create a database named 'lightrag' or similar)
+###
+### 3. Fill in Neo4j details:
+###    - NEO4J_URI (e.g., bolt://neo4j:7687 or neo4j://neo4j:7687)
+###    - NEO4J_PASSWORD
+###    - NEO4J_DATABASE (usually 'neo4j')
+###
+### 4. Verify your Postgres has pgvector extension enabled:
+###    Run in psql: CREATE EXTENSION IF NOT EXISTS vector;
+###
+### 5. Start LightRAG and verify it connects to both databases
+###
+### 6. (Optional) Adjust WORKERS/MAX_ASYNC based on your server specs (see guide above)
+###
+### 7. (Optional) Enable authentication by uncommenting LIGHTRAG_API_KEY
+###########################################################################################