- Fix final_namespace error in get_namespace_data()
- Fix get_workspace_from_request return type
- Add workspace param to pipeline status calls
(cherry picked from commit 52c812b9a0)
Fixes two compatibility issues in workspace isolation:
1. Problem: lightrag_server.py calls initialize_pipeline_status()
without workspace parameter, causing pipeline to initialize in
global namespace instead of rag's workspace.
Solution: Add set_default_workspace() mechanism in shared_storage.
LightRAG.initialize_storages() now sets default workspace, which
initialize_pipeline_status() uses when called without parameters.
2. Problem: /health endpoint hardcoded to use "pipeline_status",
cannot return workspace-specific status or support frontend
workspace selection.
Solution: Add LIGHTRAG-WORKSPACE header support. Endpoint now
extracts workspace from header or falls back to server default,
returning correct workspace-specific pipeline status.
Changes:
- lightrag/kg/shared_storage.py: Add set/get_default_workspace()
- lightrag/lightrag.py: Call set_default_workspace() in initialize_storages()
- lightrag/api/lightrag_server.py: Add get_workspace_from_request() helper,
update /health endpoint to support LIGHTRAG-WORKSPACE header
Testing:
- Backward compatibility: Old code works without modification
- Multi-instance safety: Explicit workspace passing preserved
- /health endpoint: Supports both default and header-specified workspaces
Related: #2353
(cherry picked from commit 18a4870229)
Problem:
In multi-tenant scenarios, different workspaces share a single global
pipeline_status namespace, causing pipelines from different tenants to
block each other, severely impacting concurrent processing performance.
Solution:
- Extended get_namespace_data() to recognize workspace-specific pipeline
namespaces with pattern "{workspace}:pipeline" (following GraphDB pattern)
- Added workspace parameter to initialize_pipeline_status() for per-tenant
isolated pipeline namespaces
- Updated all 7 call sites to use workspace-aware locks:
* lightrag.py: process_document_queue(), aremove_document()
* document_routes.py: background_delete_documents(), clear_documents(),
cancel_pipeline(), get_pipeline_status(), delete_documents()
Impact:
- Different workspaces can process documents concurrently without blocking
- Backward compatible: empty workspace defaults to "pipeline_status"
- Maintains fail-fast: uninitialized pipeline raises clear error
- Expected N× performance improvement for N concurrent tenants
Bug fixes:
- Fixed AttributeError by using self.workspace instead of self.global_config
- Fixed pipeline status endpoint to show workspace-specific status
- Fixed delete endpoint to check workspace-specific busy flag
Code changes: 4 files, 141 insertions(+), 28 deletions(-)
Testing: All syntax checks passed, comprehensive workspace isolation tests completed
(cherry picked from commit eb52ec94d7)
- Add --docling CLI flag for easier setup
- Add numpy version constraints
- Exclude docling on macOS (fork-safety)
(cherry picked from commit c246eff725)
- Add --docling CLI flag for easier setup
- Add numpy version constraints
- Exclude docling on macOS (fork-safety)
(cherry picked from commit a24d8181c2)
Add 5 markdown documents that users can index to reproduce evaluation results.
Changes:
- Add sample_documents/ folder with 5 markdown files covering LightRAG features
- Update sample_dataset.json with 3 improved, specific test questions
- Shorten and correct evaluation README (removed outdated info about mock responses)
- Add sample_documents reference with expected ~95% RAGAS score
Test Results with sample documents:
- Average RAGAS Score: 95.28%
- Faithfulness: 100%, Answer Relevance: 96.67%
- Context Recall: 88.89%, Context Precision: 95.56%
(cherry picked from commit a172cf893d)
**Lint Fixes (ruff)**:
- Sort imports alphabetically (I001)
- Add blank line after import traceback (E302)
- Add trailing comma to dict literals (COM812)
- Reformat writer.writerow for readability (E501)
**Rename test_dataset.json → sample_dataset.json**:
- Avoids .gitignore pattern conflict (test_* is ignored)
- More descriptive name - it's a sample/template, not actual test data
- Updated all references in eval_rag_quality.py and README.md
Resolves lint-and-format CI check failure.
Addresses reviewer feedback about test dataset naming.
(cherry picked from commit 5cdb4b0ef2)
This contribution adds optional Langfuse support for LLM observability and tracing.
Langfuse provides a drop-in replacement for the OpenAI client that automatically
tracks all LLM interactions without requiring code changes.
Features:
- Optional Langfuse integration with graceful fallback
- Automatic LLM request/response tracing
- Token usage tracking
- Latency metrics
- Error tracking
- Zero code changes required for existing functionality
Implementation:
- Modified lightrag/llm/openai.py to conditionally use Langfuse's AsyncOpenAI
- Falls back to standard OpenAI client if Langfuse is not installed
- Logs observability status on import
Configuration:
To enable Langfuse tracing, install the observability extras and set environment variables:
```bash
pip install lightrag-hku[observability]
export LANGFUSE_PUBLIC_KEY="your_public_key"
export LANGFUSE_SECRET_KEY="your_secret_key"
export LANGFUSE_HOST="https://cloud.langfuse.com" # or your self-hosted instance
```
If Langfuse is not installed or environment variables are not set, LightRAG
will use the standard OpenAI client without any functionality changes.
Changes:
- Modified lightrag/llm/openai.py (added optional Langfuse import)
- Updated pyproject.toml with optional 'observability' dependencies
Dependencies (optional):
- langfuse>=3.8.1
(cherry picked from commit 626b42bc40)
Previously, configure_vchordrq would fail silently when probes was empty
(the default), preventing epsilon from being configured. Now each parameter
is handled independently with conditional execution, and configuration
errors fail-fast instead of being swallowed.
This fixes the documented epsilon setting being impossible to use in the
default configuration.
(cherry picked from commit 3096f844fb)
* Unify empty workspace behavior by changing workspace from "_" to ""
* Fixed incorrect empty workspace detection in get_all_update_flags_status()
(cherry picked from commit d54d0d55d9)
- Add _default_workspace to global vars
- Set _default_workspace to None on cleanup
- Ensure complete resource cleanup
- Fix missing workspace finalization
(cherry picked from commit 6d6716e9f8)
• Add workspace param to get_namespace_data
• Update docstring with proper usage example
• Simplify demo to show correct workflow
• Remove confusing before/after comparison
• Clarify tool should run after init
(cherry picked from commit 393f880311)
- Fast path for clean data (no sanitization)
- Slow path sanitizes during encoding
- Reload shared memory after sanitization
- Custom encoder avoids deep copies
- Comprehensive test coverage
(cherry picked from commit 777c987371)
- Snapshot JSON data before yielding batches
- Release lock during batch processing
- Exclude source type from target selection
- Add detailed docstring for lock behavior
- Filter available storage types properly
(cherry picked from commit 5be04263b2)
• Add MongoDB env requirements
• Support config.ini fallback
• Warn on missing env vars
• Check available storage count
• Show config source info
(cherry picked from commit 1a91bcdb5f)
• Move rag_semaphore to wrap full function
• Increase RAG concurrency to 2x eval limit
• Prevent memory buildup from slow evals
• Keep eval_semaphore for RAGAS control
(cherry picked from commit e5abe9dd3d)
• Split RAG gen and eval stages
• Add rag_semaphore for stage 1
• Add eval_semaphore for stage 2
• Improve concurrency control
• Update connection pool limits
(cherry picked from commit 83715a3ac1)
