fix: resolve n8n package workspace dependency issue (v0.4.1)#64
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saschabuehrle merged 5 commits intomainfrom Nov 7, 2025
Merged
fix: resolve n8n package workspace dependency issue (v0.4.1)#64saschabuehrle merged 5 commits intomainfrom
saschabuehrle merged 5 commits intomainfrom
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Add comprehensive documentation and examples for running draft and verifier models on separate Ollama or vLLM instances. This enables optimal GPU utilization in multi-GPU systems and distributed deployments. Changes: - Update .env.example with multi-instance configuration sections - OLLAMA_DRAFT_URL and OLLAMA_VERIFIER_URL - VLLM_DRAFT_URL and VLLM_VERIFIER_URL - References to TypeScript, Python, and Docker examples - Add TypeScript examples - multi-instance-ollama.ts: Three configuration scenarios with health checks - multi-instance-vllm.ts: vLLM-specific features and API key support - Add Python examples - multi_instance_ollama.py: Async implementation with health checks - multi_instance_vllm.py: Includes PagedAttention and batching notes - Add Docker Compose setup for multi-GPU deployment - GPU device assignment (draft on GPU 0, verifier on GPU 1) - Separate ports (11434 and 11435) - Health checks and volume isolation - Comprehensive README with troubleshooting Note: Multi-instance support already exists via ModelConfig.baseUrl. This commit adds documentation and examples for the existing feature.
- Add Multi-Instance Ollama and vLLM to advanced examples tables in main README - Python advanced examples section (lines 402-403) - TypeScript advanced examples section (lines 439-440) - Update examples/README.md with comprehensive documentation - Add examples to 'Find by Feature' quick reference - Update table of contents (3 examples instead of 1) - Add detailed sections for both multi-instance examples - Include Docker Compose guide references - Document use cases, hardware requirements, and performance benefits All documentation now consistently references the new multi-instance examples.
- Remove invalid quality_threshold parameter from CascadeAgent - Add quality_threshold to ModelConfig (0.7 for draft, 0.95 for verifier) - Remove non-existent usage attribute access - Match cascade setup from basic_usage.py
BREAKING BUG FIX: VLLMProvider and other providers now respect ModelConfig.base_url for multi-instance deployments. Problem: - Providers were instantiated once per provider type, ignoring ModelConfig.base_url and api_key parameters - Multi-instance setups (draft on GPU 0, verifier on GPU 1) failed because both models tried to use the same provider instance - Examples: multi_instance_vllm.py and multi_instance_ollama.py couldn't connect to separate instance URLs Solution: - CascadeAgent._init_providers() now creates separate provider instances for each model with model-specific base_url/api_key - Added model_providers dict mapping model.name → provider instance - WholeResponseCascade and CascadeAgent use _get_provider() helper to look up model-specific providers (with backwards compat fallback) - Maintains full backwards compatibility for single-instance setups Backwards Compatibility: ✅ Tested with basic_usage.py (OpenAI standard setup) ✅ All existing functionality preserved ✅ Only activates when ModelConfig.base_url is set ✅ Falls back to provider-type lookup for existing code Files Changed: - cascadeflow/agent.py: _init_providers(), _get_provider(), all direct routing methods (_execute_direct_with_timing, etc.) - cascadeflow/core/cascade.py: __init__(), _get_provider(), _call_drafter(), _call_verifier() Tested: - ✅ multi_instance_vllm.py with DeepSeek-R1-7B and R1-32B on separate instances (192.168.0.199:8000 and :8001) - ✅ basic_usage.py with OpenAI (standard single-instance) - ✅ Cascade routing works correctly - ✅ Direct routing works correctly - ✅ Health checks pass for both instances
- Update n8n package version from 0.4.0 to 0.4.1 - Fix GitHub workflow to use pnpm publish for n8n package - pnpm automatically converts workspace:* to actual version during publish - Resolves npm EUNSUPPORTEDPROTOCOL error when installing the package Fixes the issue where npm couldn't install @cascadeflow/n8n-nodes-cascadeflow because it contained workspace:* protocol in dependencies.
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Summary
This PR fixes the
EUNSUPPORTEDPROTOCOLerror that prevented users from installing@cascadeflow/n8n-nodes-cascadeflowfrom npm.Changes
npm publishtopnpm publishfor n8n packageworkspace:*dependencies to actual versions during publishProblem
The n8n package had
"@cascadeflow/core": "workspace:*"in its dependencies. When published withnpm publish, this workspace protocol was included in the published package, causing npm to fail when users tried to install it:Solution
Using
pnpm publishinstead ofnpm publishautomatically converts workspace dependencies to their actual versions (e.g.,workspace:*→^0.4.0) during the publish process.Verification
The package has been published to npm and verified:
@cascadeflow/core: ^0.4.0(notworkspace:*)Impact
workspace:*)