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LightRAG/docs/action_plan/02-implementation-plan.md
Raphael MANSUY fe9b8ec02a
tests: stabilize integration tests + skip external services; fix multi-tenant API behavior and idempotency (#4) 
* feat: Implement multi-tenant architecture with tenant and knowledge base models

- Added data models for tenants, knowledge bases, and related configurations.
- Introduced role and permission management for users in the multi-tenant system.
- Created a service layer for managing tenants and knowledge bases, including CRUD operations.
- Developed a tenant-aware instance manager for LightRAG with caching and isolation features.
- Added a migration script to transition existing workspace-based deployments to the new multi-tenant architecture.

* chore: ignore lightrag/api/webui/assets/ directory

* chore: stop tracking lightrag/api/webui/assets (ignore in .gitignore)

* feat: Initialize LightRAG Multi-Tenant Stack with PostgreSQL

- Added README.md for project overview, setup instructions, and architecture details.
- Created docker-compose.yml to define services: PostgreSQL, Redis, LightRAG API, and Web UI.
- Introduced env.example for environment variable configuration.
- Implemented init-postgres.sql for PostgreSQL schema initialization with multi-tenant support.
- Added reproduce_issue.py for testing default tenant access via API.

* feat: Enhance TenantSelector and update related components for improved multi-tenant support

* feat: Enhance testing capabilities and update documentation

- Updated Makefile to include new test commands for various modes (compatibility, isolation, multi-tenant, security, coverage, and dry-run).
- Modified API health check endpoint in Makefile to reflect new port configuration.
- Updated QUICK_START.md and README.md to reflect changes in service URLs and ports.
- Added environment variables for testing modes in env.example.
- Introduced run_all_tests.sh script to automate testing across different modes.
- Created conftest.py for pytest configuration, including database fixtures and mock services.
- Implemented database helper functions for streamlined database operations in tests.
- Added test collection hooks to skip tests based on the current MULTITENANT_MODE.

* feat: Implement multi-tenant support with demo mode enabled by default

- Added multi-tenant configuration to the environment and Docker setup.
- Created pre-configured demo tenants (acme-corp and techstart) for testing.
- Updated API endpoints to support tenant-specific data access.
- Enhanced Makefile commands for better service management and database operations.
- Introduced user-tenant membership system with role-based access control.
- Added comprehensive documentation for multi-tenant setup and usage.
- Fixed issues with document visibility in multi-tenant environments.
- Implemented necessary database migrations for user memberships and legacy support.

* feat(audit): Add final audit report for multi-tenant implementation

- Documented overall assessment, architecture overview, test results, security findings, and recommendations.
- Included detailed findings on critical security issues and architectural concerns.

fix(security): Implement security fixes based on audit findings

- Removed global RAG fallback and enforced strict tenant context.
- Configured super-admin access and required user authentication for tenant access.
- Cleared localStorage on logout and improved error handling in WebUI.

chore(logs): Create task logs for audit and security fixes implementation

- Documented actions, decisions, and next steps for both audit and security fixes.
- Summarized test results and remaining recommendations.

chore(scripts): Enhance development stack management scripts

- Added scripts for cleaning, starting, and stopping the development stack.
- Improved output messages and ensured graceful shutdown of services.

feat(starter): Initialize PostgreSQL with AGE extension support

- Created initialization scripts for PostgreSQL extensions including uuid-ossp, vector, and AGE.
- Ensured successful installation and verification of extensions.

* feat: Implement auto-select for first tenant and KB on initial load in WebUI

- Removed WEBUI_INITIAL_STATE_FIX.md as the issue is resolved.
- Added useTenantInitialization hook to automatically select the first available tenant and KB on app load.
- Integrated the new hook into the Root component of the WebUI.
- Updated RetrievalTesting component to ensure a KB is selected before allowing user interaction.
- Created end-to-end tests for multi-tenant isolation and real service interactions.
- Added scripts for starting, stopping, and cleaning the development stack.
- Enhanced API and tenant routes to support tenant-specific pipeline status initialization.
- Updated constants for backend URL to reflect the correct port.
- Improved error handling and logging in various components.

* feat: Add multi-tenant support with enhanced E2E testing scripts and client functionality

* update client

* Add integration and unit tests for multi-tenant API, models, security, and storage

- Implement integration tests for tenant and knowledge base management endpoints in `test_tenant_api_routes.py`.
- Create unit tests for tenant isolation, model validation, and role permissions in `test_tenant_models.py`.
- Add security tests to enforce role-based permissions and context validation in `test_tenant_security.py`.
- Develop tests for tenant-aware storage operations and context isolation in `test_tenant_storage_phase3.py`.

* feat(e2e): Implement OpenAI model support and database reset functionality

* Add comprehensive test suite for gpt-5-nano compatibility

- Introduced tests for parameter normalization, embeddings, and entity extraction.
- Implemented direct API testing for gpt-5-nano.
- Validated .env configuration loading and OpenAI API connectivity.
- Analyzed reasoning token overhead with various token limits.
- Documented test procedures and expected outcomes in README files.
- Ensured all tests pass for production readiness.

* kg(postgres_impl): ensure AGE extension is loaded in session and configure graph initialization

* dev: add hybrid dev helper scripts, Makefile, docker-compose.dev-db and local development docs

* feat(dev): add dev helper scripts and local development documentation for hybrid setup

* feat(multi-tenant): add detailed specifications and logs for multi-tenant improvements, including UX, backend handling, and ingestion pipeline

* feat(migration): add generated tenant/kb columns, indexes, triggers; drop unused tables; update schema and docs

* test(backward-compat): adapt tests to new StorageNameSpace/TenantService APIs (use concrete dummy storages)

* chore: multi-tenant and UX updates — docs, webui, storage, tenant service adjustments

* tests: stabilize integration tests + skip external services; fix multi-tenant API behavior and idempotency

- gpt5_nano_compatibility: add pytest-asyncio markers, skip when OPENAI key missing, prevent module-level asyncio.run collection, add conftest
- Ollama tests: add server availability check and skip markers; avoid pytest collection warnings by renaming helper classes
- Graph storage tests: rename interactive test functions to avoid pytest collection
- Document & Tenant routes: support external_ids for idempotency; ensure HTTPExceptions are re-raised
- LightRAG core: support external_ids in apipeline_enqueue_documents and idempotent logic
- Tests updated to match API changes (tenant routes & document routes)
- Add logs and scripts for inspection and audit
2025-12-04 16:04:21 +08:00

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Multi-Tenancy Implementation Plan

Goal: Upgrade LightRAG to a battle-tested, production-grade multi-tenant architecture.

Phase 1: Tenant Identification & Middleware

  • Step 1.1: Create lightrag/api/middleware/tenant.py.
    • Implement TenantMiddleware to extract tenant from subdomain (optional) and JWT.
    • Use Redis to cache subdomain -> tenant_id resolution.
    • Set request.state.tenant_id.
  • Step 1.2: Update lightrag/api/dependencies.py.
    • Update get_tenant_context to read from request.state.
    • Remove reliance on X-Tenant-ID header when subdomain/JWT is present (enforce source of truth).

Phase 2: PostgreSQL Row-Level Security (RLS)

  • Step 2.1: Update lightrag/kg/postgres_tenant_support.py.
    • Add SQL to enable RLS on tables: ALTER TABLE ... ENABLE ROW LEVEL SECURITY.
    • Add SQL to create policies: CREATE POLICY ... USING (tenant_id = current_setting('app.tenant_id')).
  • Step 2.2: Update Database Connection Logic.
    • In lightrag/kg/postgres_impl.py (or equivalent), ensure app.tenant_id is set for each session/connection.
    • Use SET LOCAL app.tenant_id = ... at the start of transactions.

Phase 3: MongoDB Strict Scoping

  • Step 3.1: Create lightrag/kg/mongo_repo.py.
    • Implement MongoTenantRepo class.
    • It should take tenant_id in __init__.
    • Override find, find_one, insert_one, etc., to automatically inject tenant_id.
  • Step 3.2: Refactor lightrag/kg/mongo_impl.py.
    • Use MongoTenantRepo instead of raw motor collection.

Phase 4: Graph Database Session Wrapper (Neo4j, Memgraph)

  • Step 4.1: Create lightrag/kg/graph_session.py.
    • Implement GraphTenantSession abstract base class.
    • Implement Neo4jTenantSession and MemgraphTenantSession.
    • Wrap run method to inject tenant_id parameter and append WHERE n.tenant_id = $tenant_id if missing (or rely on strict parameterized queries).
  • Step 4.2: Refactor lightrag/kg/neo4j_impl.py and memgraph_impl.py.
    • Use GraphTenantSession.

Phase 5: Vector Database Strict Scoping

  • Step 5.1: Create lightrag/kg/vector_repo.py.
    • Implement VectorTenantRepo abstract base class.
    • Implement specific repositories for Qdrant, Milvus, FAISS, Nano.
    • Qdrant: Automatically add must filter for tenant_id and kb_id to all searches.
    • Milvus: Automatically append tenant_id == "..." to expressions.
    • FAISS: Manage tenant-specific indices (e.g., index_tenant_kb) to avoid scanning all vectors.
    • Nano: Enforce metadata filtering.
  • Step 5.2: Refactor Vector Implementations.
    • Update qdrant_impl.py, milvus_impl.py, faiss_impl.py, nano_vector_db_impl.py to use the new repositories.

Phase 6: Redis Strict Prefixing

  • Step 6.1: Enforce RedisTenantNamespace.
    • Ensure all Redis interactions in lightrag/kg/redis_impl.py use the namespace wrapper.

Phase 7: Verification

  • Step 7.1: Create tests in tests/test_multi_tenant_security.py.
    • Test RLS: Try to access another tenant's data via raw SQL.
    • Test Middleware: Verify subdomain resolution.
    • Test Isolation: Verify data separation across all backends (SQL, NoSQL, Graph, Vector).