rag-module 0.6.7

Enterprise RAG module with chat context storage, vector search, session management, and model downloading. Rust implementation with Node.js compatibility.
embeddingModel: embaas/sentence-transformers-e5-large-v2
embeddingDimensions: 1024
vectorStore:
  backend: qdrant-embedded
  connection:
    url: http://localhost:6333
    api_key: null
    timeout_secs: 30
  storagePath: ./qdrant-data
  serverSyncUrl: http://dev-qdrant-nlb-e8c337edc3ee861b.elb.ap-south-1.amazonaws.com:6334
  enableServerSync: true
chunkSize: 1024
searchTopK: 10
privacyLevel: minimal-aws
backendMapping: false
encryption:
  algorithm: AES-256-GCM
  enable_content_encryption: false
  enable_embedding_encryption: false
  enable_metadata_encryption: false
  key_rotation_days: 90
embedding:
  model: embaas/sentence-transformers-e5-large-v2
  dimensions: 1024
  service_url: null
  api_key: null
  batch_size: 32
privacy:
  level: minimal-aws
  enable_data_filtering: true
  confidential_fields:
  - resource_id
  - arn
  - vpc_id
  - security_groups
  - iam_roles
  non_confidential_fields:
  - account_id
  - region
  - service
  - instance_type
  - environment
iam:
  enable_iam_analysis: true
  supported_services:
  - ec2
  - rds
  - s3
  - lambda
  risk_assessment: true
s3Config:
  enabled: false
  bucket: ''
  region: us-east-1
  encryptionEnabled: true
  endpointUrl: null
azureBlobConfig:
  enabled: false
  containerName: ''
  encryptionEnabled: true
gcsConfig:
  enabled: false
  bucketName: ''
  encryptionEnabled: true