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Overview

Codika workflows use n8n’s LangChain integration nodes to run AI operations. The two main node types for LLM processing are:
NodeUse whenWhy
chainLlmStructured output (classification, extraction, JSON)Direct response, no reasoning noise
agentMulti-step reasoning, tool usagePlanning and iteration capability
Critical rule: Use chainLlm when you need structured JSON output. The agent node adds verbose reasoning before the final answer, which breaks structured output parsers.

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Architecture

Both node types follow the same wiring pattern: 
lmChatAnthropic (model + credentials) ──ai_languageModel──┐
                                                           ├──→ chainLlm or agent
outputParserStructured ────────────ai_outputParser─────────┘
Credentials go on the model node, not on the chain/agent node.

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Basic chainLlm example

This classifies an email as “newsletter”, “action_item”, or “spam”:

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LLM Model node

{
  "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
  "typeVersion": 1.3,
  "position": [600, 500],
  "id": "model-1",
  "name": "Claude Model",
  "parameters": {
    "model": {
      "__rl": true,
      "value": "claude-haiku-4-5-20251001",
      "mode": "list"
    },
    "options": {
      "maxTokensToSample": 1024,
      "temperature": 0.3
    }
  },
  "credentials": {
    "anthropicApi": {
      "id": "{{FLEXCRED_ANTHROPIC_ID_DERCXELF}}",
      "name": "{{FLEXCRED_ANTHROPIC_NAME_DERCXELF}}"
    }
  }
}

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Output Parser node

{
  "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
  "typeVersion": 1.3,
  "position": [600, 600],
  "id": "parser-1",
  "name": "Classification Parser",
  "parameters": {
    "jsonSchemaExample": "{\"category\": \"newsletter\", \"confidence\": \"high\", \"reason\": \"Contains subscription links\"}"
  }
}

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Chain LLM node

{
  "type": "@n8n/n8n-nodes-langchain.chainLlm",
  "typeVersion": 1.7,
  "position": [800, 400],
  "id": "chain-1",
  "name": "Classify Email",
  "parameters": {
    "promptType": "define",
    "text": "Classify the following email into one of these categories: newsletter, action_item, spam.\n\nEmail subject: {{ $json.subject }}\nEmail body: {{ $json.body }}\n\nRespond with the category, confidence (high/medium/low), and a brief reason.",
    "hasOutputParser": true
  }
}

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Connections

{
  "Claude Model": {
    "ai_languageModel": [[{ "node": "Classify Email", "type": "ai_languageModel", "index": 0 }]]
  },
  "Classification Parser": {
    "ai_outputParser": [[{ "node": "Classify Email", "type": "ai_outputParser", "index": 0 }]]
  }
}

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Accessing LLM output

After the chainLlm node executes, the parsed output is available at: 
// In a Code node after chainLlm
const result = $('Classify Email').first().json;
const category = result.output.category;
const confidence = result.output.confidence;
For outputParserStructured, the parsed JSON is in the output field of the chain’s result.

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Available Claude models

ModelIDBest for
Claude Haiku 4.5claude-haiku-4-5-20251001Fast classification, simple extraction
Claude Sonnet 4.6claude-sonnet-4-6-20250514Complex analysis, generation
Claude Opus 4.6claude-opus-4-6-20250527Most capable, multi-step reasoning
Use FLEXCRED placeholders for AI provider credentials — they automatically handle org-owned vs. Codika-provided API keys.

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Multi-step processing pattern

For workflows that need to process multiple items (e.g., classify each email in a batch): 
Fetch Items → Loop Over Items → chainLlm (classify each) → Aggregate → Submit Result
Use n8n’s SplitInBatches or Loop Over Items node to iterate, with the chainLlm inside the loop.

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Temperature guidelines

TaskTemperatureWhy
Classification0.0 - 0.3Deterministic, consistent results
Extraction0.0 - 0.2Accurate data extraction
Summarization0.3 - 0.5Some creative flexibility
Generation0.5 - 0.8Creative, varied output

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Common mistakes

  1. Credentials on chainLlm instead of lmChatAnthropic — credentials must be on the model node
  2. Using agent for JSON output — agent adds reasoning text that breaks structured parsers
  3. Missing hasOutputParser: true on chainLlm — required when using outputParserStructured
  4. Accessing output incorrectly — use $('Node Name').first().json.output, not .json directly