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version](https://img.shields.io/npm/v/@cascadeflow/n8n-nodes-cascadeflow?color=red&label=npm)](https://www.npmjs.com/package/@cascadeflow/n8n-nodes-cascadeflow)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](../../../LICENSE)\n[![n8n](https://img.shields.io/badge/n8n-1.0+-orange.svg)](https://n8n.io/)\n\n**<img src=\"../../../.github/assets/CF_n8n_color.svg\" width=\"22\" height=\"22\" alt=\"n8n\" style=\"vertical-align: middle;\"/> n8n community node for cascadeflow**\n\n</div>\n\n**Intelligent AI model cascading for n8n workflows with domain understanding.**\n\n![cascadeflow Domain Routing](../../../.github/assets/n8n-CF-domains.jpg)\n\nThis package provides **two nodes** for n8n workflows:\n\n| Node | Type | Use case |\n|------|------|----------|\n| **CascadeFlow (Model)** | Language Model sub-node | Drop-in replacement for any AI Chat Model. Wire into Basic LLM Chain, Chain, or any node that accepts a Language Model. |\n| **CascadeFlow Agent** | Standalone agent node | Full agent with tool calling, memory, and multi-step reasoning. Wire directly into workflows like Chat Trigger → Agent → response. |\n\nBoth nodes share the same cascade engine: try a cheap drafter first, validate quality, escalate to a verifier only when needed. **40-85% cost savings.**\n\n[n8n](https://n8n.io/) is a fair-code licensed workflow automation platform.\n\n## Installation\n\nFollow the [installation guide](https://docs.n8n.io/integrations/community-nodes/installation/) in the n8n community nodes documentation.\n\n### Community Nodes (Recommended)\n\n1. Go to **Settings** > **Community Nodes**\n2. Select **Install**\n3. Enter `@cascadeflow/n8n-nodes-cascadeflow` in **Enter npm package name**\n4. Agree to the risks and install\n\n### Manual installation\n\n```bash\nnpm install @cascadeflow/n8n-nodes-cascadeflow\n```\n\nFor Docker-based deployments add the following line before the font installation command in your [n8n Dockerfile](https://github.com/n8n-io/n8n/blob/master/docker/images/n8n/Dockerfile):\n\n```dockerfile\nRUN cd /usr/local/lib/node_modules/n8n && npm install @cascadeflow/n8n-nodes-cascadeflow\n```\n\n---\n\n## Node 1: CascadeFlow (Model)\n\nA **Language Model sub-node** (`ai_languageModel` output) that acts as a drop-in cascading wrapper around two models.\n\n### When to use\n\n- You want to plug cascadeflow into an existing chain or LLM node\n- No tool calling or memory needed\n- Works with: Basic LLM Chain, Chain, Question and Answer Chain, Summarization Chain, and any node that accepts a Language Model input\n\n### Architecture\n\n```\n┌─────────────┐\n│  Drafter    │ (e.g., Claude Haiku, GPT-4o-mini)\n└──────┬──────┘\n       │\n       ├──────► ┌──────────────┐\n       │        │  CascadeFlow │\n       │        │  (Model)     │ ────► ┌──────────────┐\n       │        └──────────────┘       │ Basic Chain  │\n       │        Quality checks         │ Chain        │\n       │        Cascades if needed     │ & more       │\n       │                                └──────────────┘\n┌──────┴──────┐\n│  Verifier   │ (e.g., Claude Sonnet, GPT-4o)\n└─────────────┘\n```\n\n### Inputs\n\n| Port | Type | Required | Description |\n|------|------|----------|-------------|\n| Verifier | `ai_languageModel` | Yes | Powerful model used when drafter quality is too low |\n| Drafter | `ai_languageModel` | Yes | Cheap/fast model tried first |\n| Domain models | `ai_languageModel` | No | Appear when domain cascading is enabled |\n\n### Output\n\n| Port | Type | Description |\n|------|------|-------------|\n| Model | `ai_languageModel` | Language Model connection for downstream chain/LLM nodes |\n\n### Parameters\n\n| Parameter | Default | Description |\n|-----------|---------|-------------|\n| Quality Threshold | 0.4 | Minimum quality score (0-1) to accept drafter response |\n| Use Complexity Thresholds | true | Per-complexity confidence thresholds (trivial→expert) |\n| Enable Alignment Scoring | true | Score query-response alignment for better validation |\n| Enable Complexity Routing | true | Route complex queries directly to verifier |\n| Enable Domain Cascading | false | Detect query domain and route to specialized models |\n\n### Quick Start\n\n```\n┌──────────────────┐\n│ When chat        │\n│ message received │\n└────────┬─────────┘\n         │\n         v\n┌──────────────────┐       ┌──────────────────┐\n│  OpenAI Model    │──────►│                  │\n│  gpt-4o-mini     │       │  CascadeFlow     │       ┌──────────────────┐\n└──────────────────┘       │  (Model)         │──────►│ Basic LLM Chain  │\n                           │                  │       │                  │\n┌──────────────────┐       │  Threshold: 0.4  │       └──────────────────┘\n│  OpenAI Model    │──────►│                  │\n│  gpt-4o          │       └──────────────────┘\n└──────────────────┘\n```\n\n---\n\n## Node 2: CascadeFlow Agent\n\nA **standalone agent node** (`main` in/out) with its own agent loop, tool calling, memory, and per-tool cascade/verifier routing.\n\n### When to use\n\n- You need tool calling with cascade-aware routing\n- You want memory (conversation history) built in\n- You want to wire directly into a workflow (Chat Trigger → Agent → response)\n- You need per-tool routing rules (force verifier after specific tools)\n- You need tool call validation (drafter tool calls verified before execution)\n\n### Architecture\n\n```\n┌──────────────────┐\n│ Chat Trigger     │\n│ or any node      │\n└────────┬─────────┘\n         │ (main)\n         v\n┌──────────────────────────────────────────┐\n│            CascadeFlow Agent             │\n│                                          │\n│  ┌─────────┐  ┌─────────┐  ┌──────────┐│\n│  │ Verifier│  │ Drafter │  │ Memory   ││\n│  └────┬────┘  └────┬────┘  └────┬─────┘│\n│       │            │            │       │\n│  ┌────┴────────────┴────┐       │       │\n│  │  Cascade Engine      │◄──────┘       │\n│  │  + Agent Loop        │               │\n│  └──────────┬───────────┘               │\n│             │                           │\n│  ┌──────────┴───────────┐               │\n│  │  Tools               │               │\n│  └──────────────────────┘               │\n└──────────────────┬───────────────────────┘\n                   │ (main)\n                   v\n┌──────────────────┐\n│ Next node        │\n│ (response, etc.) │\n└──────────────────┘\n```\n\n### Inputs\n\n| Port | Type | Required | Description |\n|------|------|----------|-------------|\n| (main) | `main` | Yes | Workflow items from upstream node (e.g., Chat Trigger) |\n| Verifier | `ai_languageModel` | Yes | Powerful model for verification and escalation |\n| Drafter | `ai_languageModel` | Yes | Cheap/fast model tried first |\n| Memory | `ai_memory` | No | Chat memory (e.g., Window Buffer Memory) for conversation history |\n| Tools | `ai_tool` | No | Up to 99 tools for the agent to call |\n| Domain models | `ai_languageModel` | No | Appear when domain cascading is enabled |\n\n### Output\n\n| Port | Type | Description |\n|------|------|-------------|\n| Output | `main` | Workflow items with `output`, cascade metadata, and `trace` |\n\nThe output JSON for each item contains:\n\n```json\n{\n  \"output\": \"The agent's final response text\",\n  \"model_used\": \"gpt-4o-mini\",\n  \"domain\": \"code\",\n  \"confidence\": 0.85,\n  \"trace\": [\n    { \"model_used\": \"gpt-4o-mini\", \"tool_calls\": [\"search\"] },\n    { \"model_used\": \"gpt-4o\", \"tool_calls\": [] }\n  ]\n}\n```\n\n### Parameters\n\n| Parameter | Default | Description |\n|-----------|---------|-------------|\n| System Message | (empty) | System prompt for the agent |\n| Text | `{{ $json.chatInput }}` | User input message. Auto-wires with Chat Trigger. |\n| Quality Threshold | 0.4 | Minimum quality score to accept drafter response |\n| Use Complexity Thresholds | true | Per-complexity confidence thresholds |\n| Enable Tool Call Validation | true | Validate drafter tool calls before execution; re-generate with verifier on failure |\n| Max Tool Iterations | 3 | Maximum tool-call loop iterations |\n| Tool Routing Rules | (none) | Per-tool routing overrides (cascade or force verifier) |\n| Enable Domain Cascading | false | Domain-specific model routing |\n\n### Quick Start\n\n```\n┌──────────────────┐\n│ Chat Trigger     │\n└────────┬─────────┘\n         │\n         v\n┌──────────────────────────────────────────┐\n│            CascadeFlow Agent             │\n│                                          │\n│  Claude Haiku ──► Drafter                │\n│  Claude Sonnet ─► Verifier               │       ┌──────────────────┐\n│  Window Buffer ─► Memory                 │──────►│  Respond to      │\n│  HTTP Request ──► Tool                   │       │  Webhook         │\n│  Calculator ────► Tool                   │       └──────────────────┘\n└──────────────────────────────────────────┘\n```\n\n### Tool Routing Rules\n\nOverride cascade behavior for specific tools:\n\n| Routing | Behavior |\n|---------|----------|\n| **Cascade** (default) | Drafter generates tool calls, cascade validates |\n| **Verifier** | After this tool executes, the verifier generates the final response |\n\nUse verifier routing for high-stakes tools (e.g., database writes, payment APIs) where you want the powerful model to interpret results.\n\n### Tool Call Validation\n\nWhen enabled (default), the agent validates drafter-generated tool calls before executing them:\n- JSON syntax check\n- Schema validation\n- Safety checks\n\nIf validation fails, tool calls are re-generated by the verifier model, preventing malformed or unsafe tool invocations.\n\n---\n\n## Shared Features\n\nBoth nodes share these capabilities:\n\n### Cascade Flow\n\n1. Query goes to cheap drafter model first\n2. cascadeflow validates the response quality\n3. If quality passes → return drafter response (fast + cheap)\n4. If quality fails → escalate to verifier model (slower but accurate)\n\n**Result:** 70-80% of queries accept the drafter, saving 40-85% on costs.\n\n### Multi-Domain Cascading (Optional)\n\nBoth nodes support domain-specific cascading. Enable it in the node settings to automatically detect query domains and route to specialized models.\n\n**Supported domains:**\n\n| Domain | Description | Example Queries |\n|--------|-------------|-----------------|\n| **Code** | Programming, debugging, code generation | \"Write a Python function...\", \"Debug this code...\" |\n| **Math** | Mathematical reasoning, calculations, proofs | \"Solve this equation...\", \"Prove that...\" |\n| **Data** | Data analysis, statistics, pandas/SQL | \"Analyze this dataset...\", \"Write a SQL query...\" |\n| **Creative** | Creative writing, stories, poetry | \"Write a short story...\", \"Compose a poem...\" |\n| **Legal** | Legal documents, contracts, regulations | \"Draft a contract...\", \"Explain this law...\" |\n| **Medical** | Healthcare, medical knowledge, clinical | \"What are the symptoms of...\", \"Explain this diagnosis...\" |\n| **Financial** | Finance, accounting, investment analysis | \"Analyze this stock...\", \"Calculate ROI...\" |\n| **Science** | Scientific knowledge, research, experiments | \"Explain quantum...\", \"How does photosynthesis...\" |\n| **Structured** | JSON, XML, structured output | \"Generate a JSON schema...\" |\n| **RAG** | Retrieval-augmented generation | \"Based on the document...\" |\n| **Conversation** | General chat, small talk | \"How are you?\", \"Tell me about...\" |\n| **Tool** | Tool-oriented queries | \"Search for...\", \"Calculate...\" |\n| **Summary** | Summarization tasks | \"Summarize this article...\" |\n| **Translation** | Language translation | \"Translate to French...\" |\n| **Multimodal** | Image/audio/video queries | \"Describe this image...\" |\n| **General** | Catch-all domain | Everything else |\n\n**Setup:**\n1. Enable Domain Cascading in node settings\n2. Toggle individual domains\n3. Connect domain-specific models to the new input ports\n4. Optionally enable domain verifiers to override the global verifier per domain\n\n### Complexity Thresholds\n\nWhen enabled (default), acceptance is driven by query complexity:\n\n| Complexity | Default Threshold |\n|------------|-------------------|\n| Trivial | 0.25 |\n| Simple | 0.40 |\n| Moderate | 0.55 |\n| Hard | 0.70 |\n| Expert | 0.80 |\n\n---\n\n## Flow Visualization\n\n### Viewing Cascade Decisions in Real-Time\n\ncascadeflow provides detailed logging of every cascade decision in n8n's UI:\n\n1. **Execute your workflow**\n2. **For CascadeFlow (Model):** Click the downstream Chain node → \"Logs\" tab\n3. **For CascadeFlow Agent:** Click the Agent node → \"Output\" tab (trace is in the output JSON)\n\nExample log output:\n\n```\nCascadeFlow: Trying drafter model...\n   Quality validation: confidence=0.85, method=heuristic\n   Alignment: 0.82\n\n   FLOW: DRAFTER ACCEPTED (FAST PATH)\n   Query -> Drafter -> Quality Check -> Response\n   Confidence: 0.85 (threshold: 0.70)\n   Cost savings: ~93.8% (used cheap model)\n```\n\n---\n\n## Recommended Model Configurations\n\n### Claude Haiku + GPT-4o (Recommended)\n\n```\nDrafter: claude-3-5-haiku-20241022\nVerifier: gpt-4o\nSavings: ~73% average\nBest for: General purpose, coding, reasoning\n```\n\n### Anthropic Only (High Quality)\n\n```\nDrafter: claude-3-5-haiku-20241022\nVerifier: claude-3-5-sonnet-20241022\nSavings: ~70% average\n```\n\n### OpenAI Only (Good Balance)\n\n```\nDrafter: gpt-4o-mini\nVerifier: gpt-4o\nSavings: ~85% average\n```\n\n### Ultra Fast with Ollama (Local)\n\n```\nDrafter: ollama/qwen2.5:3b (local)\nVerifier: gpt-4o (cloud)\nSavings: ~99% on drafter calls (no API cost)\nNote: Requires Ollama installed locally\n```\n\n---\n\n## Troubleshooting\n\n### \"Drafter model is required\"\n\nMake sure you've connected an AI Chat Model to the **Drafter** input port.\n\n### \"Verifier model is required\"\n\nMake sure you've connected an AI Chat Model to the **Verifier** input port.\n\n### Not seeing cascade logs\n\n- **CascadeFlow (Model):** Logs appear in the downstream Chain node's \"Logs\" tab, not the cascadeflow node itself.\n- **CascadeFlow Agent:** Cascade metadata and trace are in the output JSON of the Agent node.\n\n### Always escalating to verifier\n\n1. Try lowering the Quality Threshold (0.3-0.4)\n2. Verify your drafter model is actually a cheaper/faster model\n3. Check logs for the confidence scores being reported\n\n### \"This node cannot be connected\"\n\n- Use **CascadeFlow (Model)** with Chain/LLM nodes that accept Language Model inputs\n- Use **CascadeFlow Agent** for standalone agent workflows with tool calling and memory\n\n---\n\n## Compatibility\n\n- **n8n version**: 1.0+\n- **Works with any AI Chat Model node** in n8n:\n  - OpenAI Chat Model\n  - Anthropic Chat Model\n  - Ollama Chat Model\n  - Azure OpenAI Chat Model\n  - Google PaLM Chat Model\n  - And more...\n\n## Resources\n\n- [n8n community nodes documentation](https://docs.n8n.io/integrations/community-nodes/)\n- [cascadeflow GitHub](https://github.com/lemony-ai/cascadeflow)\n- [cascadeflow Documentation](https://github.com/lemony-ai/cascadeflow/blob/main/README.md)\n\n## License\n\n[MIT](https://github.com/lemony-ai/cascadeflow/blob/main/LICENSE)\n\n## Version History\n\n### v1.3.0 (Latest)\n\n- **PreRouter integration**: Complexity-based routing now uses `PreRouter` with structured `RoutingDecision` (strategy, confidence, metadata) instead of hardcoded branching\n- **Domain-aware routing context**: PreRouter receives detected domain and domain config for richer routing decisions\n- **Router metadata**: `direct_verifier` responses include `router: 'pre-router' | 'complexity'` in cascade metadata\n- **Moved `@langchain/core` to peerDependencies**: Avoids duplicate installs since n8n provides it at runtime\n\n### v1.0.0\n\n- **CascadeFlow Agent → standalone node**: Converted from `supplyData()` sub-node to `execute()` node with main in/out\n- **Memory support**: Added `ai_memory` input for conversation history (Window Buffer Memory, etc.)\n- **System message & text params**: Agent node now has its own system prompt and text input (defaults to `{{ $json.chatInput }}`)\n- **Direct workflow wiring**: Chat Trigger → CascadeFlow Agent → response, no intermediate Chain node needed\n\n### v0.7.x\n\n- **Domain cascading labels**: Shortened domain input labels, section dividers, tool call validation on by default\n- **Single getInputConnectionData call**: Correct model resolution and n8n highlighting\n\n### v0.6.x\n\n- **Multi-domain cascading**: 16-domain intelligent routing with individual toggles and dynamic input ports\n- **Removed semantic validation**: Disabled ML-based semantic validation to prevent OOM crashes\n- **Circuit breaker**: Added circuit breaker pattern for improved reliability\n\n### v0.5.0\n\n- **Flow visualization**: Detailed cascade flow logging in n8n Logs tab\n- **Quality validator integration**: Integrated QualityValidator from @cascadeflow/core\n- **Complexity-aware validation**: Replacing naive length-based checks\n\n### v0.4.x and earlier\n\n- Initial releases as LangChain sub-node\n- Support for any AI Chat Model in n8n\n- Lazy verifier loading\n- Quality threshold configuration\n","readmeFilename":"README.md"}