{ "name": "Bulletproof AI JSON: clean, validate against a schema and auto-repair LLM output", "nodes": [ { "parameters": {}, "id": "6adcc21c-6adb-55b7-922c-a71acc48eb70", "name": "Run Once: Create Log Table", "type": "n8n-nodes-base.manualTrigger", "typeVersion": 1, "position": [ -1900, -420 ] }, { "parameters": { "resource": "table", "operation": "create", "tableName": "ai_json_guard_log", "columns": { "column": [ { "name": "record_id", "type": "string" }, { "name": "source", "type": "string" }, { "name": "status", "type": "string" }, { "name": "attempts", "type": "number" }, { "name": "fixes", "type": "string" }, { "name": "errors", "type": "string" }, { "name": "data_json", "type": "string" }, { "name": "raw_output", "type": "string" } ] }, "options": { "createIfNotExists": true } }, "id": "58a6e8b3-13cf-502d-bc70-fd3f25451baa", "name": "Create Log Data Table", "type": "n8n-nodes-base.dataTable", "typeVersion": 1.1, "position": [ -1680, -420 ] }, { "parameters": {}, "id": "88b0c4f1-7c43-56c1-a715-e06e769cb294", "name": "Try It: Run Demo", "type": "n8n-nodes-base.manualTrigger", "typeVersion": 1, "position": [ -1900, 0 ] }, { "parameters": { "jsCode": "// Three example tickets. Replace this node with your own data (form, webhook, sheet, email...).\nreturn [\n { json: { record_id: 'T-1001', ticket: 'Hi, I was charged twice for my October invoice. Please refund one of them asap.' } },\n { json: { record_id: 'T-1002', ticket: 'The export button crashes the app on Android 14 every time. Can you fix it?' } },\n { json: { record_id: 'T-1003', ticket: 'Would love a dark mode. Not urgent, just an idea!' } },\n];\n" }, "id": "3b257194-3bff-5b06-8ede-31e8f01df895", "name": "Sample Support Tickets", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -1680, 0 ] }, { "parameters": { "assignments": { "assignments": [ { "id": "68e6111a-4b06-5730-85ae-cfb13bb47ee0", "name": "json_schema", "value": "{\n \"type\": \"object\",\n \"additionalProperties\": false,\n \"required\": [\n \"category\",\n \"priority\",\n \"summary\",\n \"needs_human\",\n \"tags\"\n ],\n \"properties\": {\n \"category\": {\n \"type\": \"string\",\n \"enum\": [\n \"billing\",\n \"bug\",\n \"feature_request\",\n \"account\",\n \"other\"\n ]\n },\n \"priority\": {\n \"type\": \"integer\",\n \"minimum\": 1,\n \"maximum\": 5\n },\n \"summary\": {\n \"type\": \"string\",\n \"minLength\": 5,\n \"maxLength\": 200\n },\n \"needs_human\": {\n \"type\": \"boolean\"\n },\n \"tags\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"string\"\n },\n \"maxItems\": 5\n }\n }\n}", "type": "string" }, { "id": "db46474d-9e65-5ad3-9087-9c7c2cbdb4ec", "name": "max_retries", "value": 2, "type": "number" }, { "id": "a672b3f1-f9dc-515c-b23f-0128f4657700", "name": "coerce_types", "value": true, "type": "boolean" } ] }, "includeOtherFields": true, "options": {} }, "id": "67d67275-f409-51d6-8af4-7d045de79442", "name": "Demo Settings (edit me)", "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ -1460, 0 ] }, { "parameters": { "promptType": "define", "text": "={{ $json.ticket }}", "hasOutputParser": false, "messages": { "messageValues": [ { "message": "=You turn customer support tickets into data.\nReply with one JSON object only, matching this JSON Schema:\n{{ $json.json_schema }}" } ] }, "batching": {} }, "id": "391b3a94-60a0-5acb-90f4-7dc17dfdcbd6", "name": "AI: Extract Ticket Fields", "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.9, "position": [ -1240, 0 ], "onError": "continueRegularOutput" }, { "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4.1-mini" }, "options": { "temperature": 0.2 } }, "id": "95aa151a-f11f-576c-aa9a-5be1c78ba090", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "typeVersion": 1.3, "position": [ -1240, 220 ] }, { "parameters": { "jsCode": "// The AI node returns one item per ticket, in order: {text} on success, {error} if the call failed\n// (its On Error setting is \"Continue\"). Matched to the settings by position, because LLM chain\n// outputs don't carry item links.\nconst settings = $('Demo Settings (edit me)').all();\nreturn $input.all().map((item, i) => {\n const s = settings[i].json, j = item.json;\n return { json: {\n order: i, record_id: s.record_id, source: 'demo', task: s.ticket, schema: s.json_schema,\n max_retries: s.max_retries, coerce_types: s.coerce_types, attempt: 1,\n raw_output: j.text ?? j.output ?? '', llm_error: j.error ? (j.error.message || String(j.error)) : '',\n } };\n});\n" }, "id": "34f6f0b1-ebd9-5eae-a630-662d82356299", "name": "Package For Guard", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -1000, 0 ] }, { "parameters": { "inputSource": "passthrough" }, "id": "ed85eb47-6bfd-5006-bee1-8726a5fd31b4", "name": "When Called By Another Workflow", "type": "n8n-nodes-base.executeWorkflowTrigger", "typeVersion": 1.1, "position": [ -1460, 420 ] }, { "parameters": { "mode": "runOnceForEachItem", "jsCode": "// Accepts raw_output (or text / output) plus schema (object or JSON string). Everything else is optional.\nconst j = $json;\nconst err = j.llm_error || j.error;\nreturn { json: {\n order: $itemIndex, record_id: String(j.record_id ?? $itemIndex), source: j.source || 'caller', task: j.task || '',\n schema: j.schema ?? j.json_schema ?? null, max_retries: Number(j.max_retries ?? 2), coerce_types: j.coerce_types !== false,\n attempt: 1, raw_output: j.raw_output ?? j.text ?? j.output ?? '',\n llm_error: err ? (err.message || String(err)) : '',\n} };\n" }, "id": "efe1d61f-40c8-57ca-8935-96d15133f603", "name": "Normalize Caller Input", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -1240, 420 ] }, { "parameters": { "jsCode": "// Turns whatever the model returned into a parsed JSON value, without another AI call.\n// Handles: ```json fences, / blocks, \"Thought/Action/Final Answer\" agent steps,\n// prose before or after the JSON, Responses-API content blocks, {\"output\": ...} wrappers,\n// trailing commas, // comments, smart quotes, Python True/False/None and single-quoted keys.\nfunction toText(raw, fixes) {\n if (raw === null || raw === undefined) return '';\n if (typeof raw === 'string') return raw;\n if (Array.isArray(raw) && raw.length && raw.every(b => b && typeof b === 'object' && ('text' in b || 'type' in b))) {\n fixes.push('joined content blocks'); // Responses API / Anthropic style: [{type:'output_text', text:'...'}]\n return raw.map(b => typeof b.text === 'string' ? b.text : (b.text && b.text.value) || '').join('\\n');\n }\n if (typeof raw === 'object') {\n for (const k of ['text', 'output_text', 'content']) if (typeof raw[k] === 'string') { fixes.push('read .' + k); return raw[k]; }\n return { __object: raw };\n }\n return String(raw);\n}\nfunction candidates(s) { // every balanced {...} or [...] that respects strings\n const out = [];\n for (let i = 0; i < s.length; i++) {\n const open = s[i]; if (open !== '{' && open !== '[') continue;\n const stack = []; let inStr = null, esc = false;\n for (let j = i; j < s.length; j++) {\n const c = s[j];\n if (inStr) { if (esc) esc = false; else if (c === '\\\\') esc = true; else if (c === inStr) inStr = null; continue; }\n if (c === '\"' || c === \"'\") { inStr = c; continue; }\n if (c === '{' || c === '[') stack.push(c);\n else if (c === '}' || c === ']') { stack.pop(); if (!stack.length) { out.push(s.slice(i, j + 1)); i = j; break; } }\n }\n if (out.length >= 20) break;\n }\n return out;\n}\nfunction lightRepair(t) {\n return t\n .replace(/[\\u201C\\u201D]/g, '\"').replace(/[\\u2018\\u2019]/g, \"'\")\n .replace(/^\\s*\\/\\/.*$/gm, '')\n .replace(/,\\s*([}\\]])/g, '$1')\n .replace(/([{,]\\s*)'([^'\"\\n]+?)'\\s*:/g, '$1\"$2\":')\n .replace(/:\\s*'([^'\"\\n]*)'(\\s*[,}\\]])/g, ': \"$1\"$2')\n .replace(/([:\\[,]\\s*)True(\\s*[,}\\]])/g, '$1true$2').replace(/([:\\[,]\\s*)False(\\s*[,}\\]])/g, '$1false$2').replace(/([:\\[,]\\s*)None(\\s*[,}\\]])/g, '$1null$2');\n}\nconst out = [];\nfor (const item of $input.all()) {\n const j = item.json; const fixes = [];\n let parsed, parseError = '', text = toText(j.raw_output, fixes);\n if (j.llm_error) parseError = 'AI step failed: ' + String(j.llm_error).slice(0, 300);\n else if (text && typeof text === 'object' && text.__object) { parsed = text.__object; text = JSON.stringify(parsed); }\n else {\n let s = String(text);\n if (/<(think|thinking|reasoning)>/i.test(s)) { s = s.replace(/<(think|thinking|reasoning)>[\\s\\S]*?<\\/\\1>/gi, ''); fixes.push('removed block'); }\n const fa = s.lastIndexOf('Final Answer:');\n if (fa >= 0) { s = s.slice(fa + 13); fixes.push('kept only the text after Final Answer:'); }\n const fence = s.match(/```(?:json|JSON)?\\s*([\\s\\S]*?)```/);\n if (fence) { s = fence[1]; fixes.push('stripped ``` code fence'); }\n s = s.trim();\n try { parsed = JSON.parse(s); }\n catch (e) {\n parseError = e.message;\n const cands = candidates(s).sort((a, b) => b.length - a.length);\n for (const c of cands) {\n try { parsed = JSON.parse(c); fixes.push('removed text around the JSON'); parseError = ''; break; } catch (e2) {}\n try { parsed = JSON.parse(lightRepair(c)); fixes.push('repaired JSON syntax (commas/quotes/True/None)'); parseError = ''; break; } catch (e3) { parseError = e3.message; }\n }\n if (parsed === undefined && !cands.length) parseError = !s ? 'Model output was empty' : /[\\[{]/.test(s) ? 'JSON is incomplete (the output looks cut off; raise Maximum Number of Tokens)' : 'No JSON object or array found in the model output';\n }\n // A JSON string that itself contains JSON (double-encoded)\n if (typeof parsed === 'string' && /^\\s*[\\[{]/.test(parsed)) { try { parsed = JSON.parse(parsed); fixes.push('decoded double-encoded JSON'); } catch (e) {} }\n }\n out.push({ json: { ...j, raw_text: typeof text === 'string' ? text : JSON.stringify(text), parsed: parsed === undefined ? null : parsed,\n parse_ok: parsed !== undefined && !j.llm_error, parse_error: parseError, fixes: [...(j.fixes || []), ...fixes] }, pairedItem: item.pairedItem });\n}\nreturn out;\n" }, "id": "7d075a4b-3878-554c-9c44-28e1fc86928f", "name": "Clean + Extract JSON", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -760, 200 ] }, { "parameters": { "jsCode": "// Validates the parsed JSON against your JSON Schema (a practical subset: type, required, properties,\n// additionalProperties, enum, items, min/max, minLength/maxLength, minItems/maxItems, pattern).\n// With coerce_types on, safe fixes are applied and listed: \"3\" -> 3, \"true\" -> true, 7 -> \"7\",\n// \"Billing\" -> \"billing\" (enum case), a single value -> [value], extra keys removed.\nfunction typeOf(v) { return v === null ? 'null' : Array.isArray(v) ? 'array' : Number.isInteger(v) ? 'integer' : typeof v; }\nfunction okType(v, t) { const a = typeOf(v); return t === a || (t === 'number' && a === 'integer'); }\nfunction check(v, s, path, errs, fixes, coerce) {\n if (!s || typeof s !== 'object') return v;\n const types = s.type ? [].concat(s.type) : null;\n if (types && !types.some(t => okType(v, t))) {\n let fixed, did = false;\n if (coerce) for (const t of types) {\n if ((t === 'number' || t === 'integer') && typeof v === 'string' && v.trim() !== '' && !isNaN(Number(v)) && (t === 'number' || Number.isInteger(Number(v)))) { fixed = Number(v); did = true; break; }\n if (t === 'integer' && typeof v === 'number' && Math.abs(v - Math.round(v)) < 1e-9) { fixed = Math.round(v); did = true; break; }\n if (t === 'boolean' && typeof v === 'string' && /^(true|false|yes|no)$/i.test(v.trim())) { fixed = /^(true|yes)$/i.test(v.trim()); did = true; break; }\n if (t === 'string' && (typeof v === 'number' || typeof v === 'boolean')) { fixed = String(v); did = true; break; }\n if (t === 'array' && v !== null && v !== undefined && !Array.isArray(v)) { fixed = [v]; did = true; break; }\n if (t === 'null' && (v === '' || v === 'null')) { fixed = null; did = true; break; }\n }\n if (did) { fixes.push(`coerced ${path || 'value'} ${JSON.stringify(v)} -> ${JSON.stringify(fixed)}`); v = fixed; }\n else { errs.push(`${path || 'value'} must be ${types.join(' or ')}, got ${typeOf(v)} ${JSON.stringify(v).slice(0, 60)}`); return v; }\n }\n if (s.enum) {\n if (!s.enum.includes(v)) {\n const m = coerce && typeof v === 'string' ? s.enum.find(e => typeof e === 'string' && e.toLowerCase() === v.trim().toLowerCase()) : undefined;\n if (m !== undefined) { fixes.push(`coerced ${path} ${JSON.stringify(v)} -> ${JSON.stringify(m)}`); v = m; }\n else errs.push(`${path || 'value'} must be one of ${JSON.stringify(s.enum)}, got ${JSON.stringify(v)}`);\n }\n }\n if (typeof v === 'number') {\n if (s.minimum !== undefined && v < s.minimum) errs.push(`${path} must be >= ${s.minimum}, got ${v}`);\n if (s.maximum !== undefined && v > s.maximum) errs.push(`${path} must be <= ${s.maximum}, got ${v}`);\n }\n if (typeof v === 'string') {\n if (s.minLength !== undefined && v.length < s.minLength) errs.push(`${path} must have at least ${s.minLength} characters`);\n if (s.maxLength !== undefined && v.length > s.maxLength) errs.push(`${path} must have at most ${s.maxLength} characters`);\n if (s.pattern && !(new RegExp(s.pattern)).test(v)) errs.push(`${path} must match ${s.pattern}`);\n }\n if (Array.isArray(v)) {\n if (s.minItems !== undefined && v.length < s.minItems) errs.push(`${path} needs at least ${s.minItems} items`);\n if (s.maxItems !== undefined && v.length > s.maxItems) errs.push(`${path} allows at most ${s.maxItems} items`);\n if (s.items) v = v.map((x, i) => check(x, s.items, `${path}[${i}]`, errs, fixes, coerce));\n }\n if (typeOf(v) === 'object') {\n const props = s.properties || {};\n for (const r of s.required || []) if (!(r in v) || v[r] === undefined) errs.push(`missing required field \"${path ? path + '.' : ''}${r}\"`);\n for (const k of Object.keys(v)) {\n if (props[k]) v[k] = check(v[k], props[k], path ? `${path}.${k}` : k, errs, fixes, coerce);\n else if (s.additionalProperties === false) {\n if (coerce) { fixes.push(`removed extra field \"${path ? path + '.' : ''}${k}\"`); delete v[k]; }\n else errs.push(`unexpected field \"${path ? path + '.' : ''}${k}\"`);\n }\n }\n }\n return v;\n}\nconst out = [];\nfor (const item of $input.all()) {\n const j = item.json; const errs = [], fixes = [...(j.fixes || [])];\n let schema = j.schema;\n if (typeof schema === 'string') { try { schema = JSON.parse(schema); } catch (e) { schema = null; errs.push('Your JSON Schema itself is not valid JSON: ' + e.message); } }\n let data = j.parsed;\n if (!j.parse_ok) errs.push(j.parse_error || 'Could not parse JSON');\n else if (schema) {\n data = JSON.parse(JSON.stringify(data));\n const wantObj = [].concat(schema.type || []).includes('object');\n // n8n's Structured Output Parser convention wraps results as {\"output\": {...}}; models copy it.\n if (wantObj && data && typeOf(data) === 'object' && Object.keys(data).length === 1 && 'output' in data && !(schema.properties || {}).output && typeOf(data.output) === 'object') { data = data.output; fixes.push('unwrapped {\"output\": ...}'); }\n if (wantObj && Array.isArray(data) && data.length === 1 && typeOf(data[0]) === 'object') { data = data[0]; fixes.push('unwrapped single-item array'); }\n data = check(data, schema, '', errs, fixes, j.coerce_types !== false);\n }\n const attempt = Number(j.attempt || 1), maxRetries = Number(j.max_retries ?? 2);\n const valid = errs.length === 0;\n const route = valid ? 'valid' : (attempt <= maxRetries ? 'retry' : 'give_up');\n out.push({ json: { ...j, schema, data: valid ? data : null, valid, errors: errs, fixes, route,\n history: [...(j.history || []), { attempt, errors: errs, fixes: fixes.slice((j.fixes || []).length) }] }, pairedItem: item.pairedItem });\n}\nreturn out;\n" }, "id": "5e287841-31ce-5569-aa08-bb8434c32a7f", "name": "Validate Against Schema", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -540, 200 ] }, { "parameters": { "rules": { "values": [ { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "id": "3258955f-6e9c-5b7a-af5f-915f9a47886b", "leftValue": "={{ $json.route }}", "rightValue": "valid", "operator": { "type": "string", "operation": "equals" } } ], "combinator": "and" }, "renameOutput": true, "outputKey": "Valid" }, { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "id": "c0380438-2acd-584f-8fe8-e69641cae1a7", "leftValue": "={{ $json.route }}", "rightValue": "retry", "operator": { "type": "string", "operation": "equals" } } ], "combinator": "and" }, "renameOutput": true, "outputKey": "Retry" }, { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "id": "a7549416-5368-5713-8df3-1561c13d0bd9", "leftValue": "={{ $json.route }}", "rightValue": "give_up", "operator": { "type": "string", "operation": "equals" } } ], "combinator": "and" }, "renameOutput": true, "outputKey": "Give Up" } ] }, "options": {} }, "id": "1ce897b3-f5fe-5a13-8806-611742a2f4e0", "name": "Valid, Retry Or Give Up?", "type": "n8n-nodes-base.switch", "typeVersion": 3.2, "position": [ -320, 200 ] }, { "parameters": { "mode": "runOnceForEachItem", "jsCode": "// Tells the model exactly what was wrong, so the retry is a targeted fix instead of a re-roll.\nconst j = $json;\nconst prev = String(j.llm_error ? '(the AI step errored: ' + j.llm_error + ')' : j.raw_text || '').slice(0, 4000);\nconst prompt = [\n 'Your previous answer could not be used.',\n 'Problems found:', ...j.errors.map(e => '- ' + e), '',\n 'Return ONLY one JSON value that matches this JSON Schema. No code fences, no explanation, no text before or after it.',\n JSON.stringify(j.schema), '',\n j.task ? 'Original task:\\n' + String(j.task).slice(0, 4000) + '\\n' : '',\n 'Previous answer:', prev,\n].join('\\n');\nreturn { json: { ...j, correction_prompt: prompt } };\n" }, "id": "46d5e981-13f3-5013-9e96-b9e608dda8c3", "name": "Build Correction Prompt", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -80, 300 ] }, { "parameters": { "promptType": "define", "text": "={{ $json.correction_prompt }}", "hasOutputParser": false, "messages": { "messageValues": [ { "message": "You repair JSON for a program. Output only valid JSON, nothing else." } ] }, "batching": {} }, "id": "2e65cac0-0b60-5ec9-ba46-4cae470a7dff", "name": "AI: Repair JSON", "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.9, "position": [ 140, 300 ], "onError": "continueRegularOutput" }, { "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4.1-mini" }, "options": { "temperature": 0 } }, "id": "bd5a5e2b-6513-58f5-87f2-6c8a2bdc0bcb", "name": "OpenAI Chat Model (Repair)", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "typeVersion": 1.3, "position": [ 140, 520 ] }, { "parameters": { "jsCode": "// Carries the context forward (matched by position, like Package For Guard), counts the attempt,\n// then loops back to Clean + Extract JSON.\nconst prompts = $('Build Correction Prompt').all();\nreturn $input.all().map((item, i) => {\n const { correction_prompt, parsed, data, valid, errors, route, raw_text, parse_ok, parse_error, ...ctx } = prompts[i].json;\n const j = item.json;\n return { json: { ...ctx, attempt: ctx.attempt + 1,\n raw_output: j.text ?? j.output ?? '', llm_error: j.error ? (j.error.message || String(j.error)) : '' } };\n});\n" }, "id": "f1eaa74d-f604-5ff2-be43-7f332a8a6ab4", "name": "Next Attempt", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 380, 300 ] }, { "parameters": { "mode": "runOnceForEachItem", "jsCode": "const j = $json;\nconst status = j.valid ? (j.attempt > 1 ? 'ok_after_retry' : 'ok') : 'failed';\nreturn { json: { ok: j.valid, status, data: j.data, errors: j.errors, fixes: j.fixes, attempts: j.attempt, order: j.order,\n record_id: j.record_id, source: j.source, raw_output: j.valid ? '' : String(j.raw_text || j.llm_error || '').slice(0, 2000) } };\n" }, "id": "addae9ed-755d-5028-8cb5-4b22f1d1c213", "name": "Build Final Result", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -80, 0 ] }, { "parameters": { "resource": "row", "operation": "insert", "dataTableId": { "__rl": true, "mode": "name", "value": "ai_json_guard_log" }, "columns": { "mappingMode": "defineBelow", "value": { "record_id": "={{ $json.record_id }}", "source": "={{ $json.source }}", "status": "={{ $json.status }}", "attempts": "={{ $json.attempts }}", "fixes": "={{ $json.fixes.join('; ') }}", "errors": "={{ $json.errors.join('; ') }}", "data_json": "={{ $json.ok ? JSON.stringify($json.data) : '' }}", "raw_output": "={{ $json.raw_output }}" }, "schema": [ { "id": "record_id", "displayName": "record_id", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "source", "displayName": "source", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "status", "displayName": "status", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "attempts", "displayName": "attempts", "required": false, "defaultMatch": false, "display": true, "type": "number", "canBeUsedToMatch": true }, { "id": "fixes", "displayName": "fixes", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "errors", "displayName": "errors", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "data_json", "displayName": "data_json", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "raw_output", "displayName": "raw_output", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true } ] }, "options": {} }, "id": "afbe3b26-c5ca-5bc9-a641-ed9c7bcb9ce4", "name": "Log Result (Failures = Dead Letter)", "type": "n8n-nodes-base.dataTable", "typeVersion": 1.1, "position": [ 140, 0 ] }, { "parameters": { "jsCode": "// This is what a calling workflow receives. Use data when ok is true; errors explain a failure.\n// Items finish in different passes of the repair loop, so this gathers every finished item so far,\n// in the original order. The last run (the one a calling workflow gets) has all of them.\nconst done = [];\nfor (let r = 0; r <= $runIndex; r++) done.push(...$('Build Final Result').all(0, r));\nreturn done.sort((a, b) => a.json.order - b.json.order).map(({ json: r }) => ({ json: {\n ok: r.ok, status: r.status, data: r.data, errors: r.errors, fixes: r.fixes, attempts: r.attempts, record_id: r.record_id } }));\n" }, "id": "1a126d3c-20a2-5248-88d3-83fefccb8705", "name": "Return Result", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 360, 0 ] }, { "parameters": {}, "id": "b7ee3e1e-ae16-5549-8c25-85422d4a5d7b", "name": "Check Success Rate", "type": "n8n-nodes-base.manualTrigger", "typeVersion": 1, "position": [ -1900, 860 ] }, { "parameters": { "resource": "row", "operation": "get", "dataTableId": { "__rl": true, "mode": "name", "value": "ai_json_guard_log" }, "matchType": "anyCondition", "filters": {}, "returnAll": true }, "id": "e4515f2d-0eea-549f-812e-e6456342d0f0", "name": "Read Log Table", "type": "n8n-nodes-base.dataTable", "typeVersion": 1.1, "position": [ -1680, 860 ] }, { "parameters": { "jsCode": "// How often does your prompt need help? A high retry rate means the prompt or schema needs work.\nconst rows = $input.all().map(i => i.json).filter(r => r.status);\nconst n = rows.length || 1, count = s => rows.filter(r => r.status === s).length;\nconst tally = {};\nfor (const r of rows) for (const e of String(r.errors || '').split('; ').filter(Boolean)) tally[e] = (tally[e] || 0) + 1;\nfor (const r of rows) for (const f of String(r.fixes || '').split('; ').filter(Boolean)) tally['fixed: ' + f.replace(/ \".*$/, '')] = (tally['fixed: ' + f.replace(/ \".*$/, '')] || 0) + 1;\nreturn [{ json: { total: rows.length,\n ok_first_try_pct: Math.round(100 * count('ok') / n), ok_after_retry_pct: Math.round(100 * count('ok_after_retry') / n),\n failed_pct: Math.round(100 * count('failed') / n),\n top_issues: Object.entries(tally).sort((a, b) => b[1] - a[1]).slice(0, 8).map(([k, v]) => `${v}x ${k}`) } }];\n" }, "id": "b5dfcb2e-c4fb-5357-9bda-0ba97fcc792b", "name": "Summarize Success Rate", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -1460, 860 ] }, { "parameters": { "content": "## Bulletproof AI JSON: clean, validate, repair\n\n### How it works\n1. The AI step returns **plain text** (no Structured Output Parser), so a bad answer can't stop the run with *\"Model output doesn't fit required format\"* or *\"Failed to parse agent steps\"*.\n2. **Clean + Extract JSON** fixes the usual mess without another AI call: ```json fences, `` blocks, \"Thought / Final Answer\" agent text, chatter before or after the JSON, content-block arrays, trailing commas, smart quotes and `True`/`None`.\n3. **Validate Against Schema** checks it against your JSON Schema. Safe type fixes (\"3\" → 3, \"yes\" → true, \"Billing\" → \"billing\") are applied and listed.\n4. If it still fails, the exact errors go back to the model in a **correction prompt**, up to **max_retries** times.\n5. Every result is logged to the **ai_json_guard_log** Data Table. Failures are kept as a dead-letter row with the raw output.\n\n### Setup\n1. Open **OpenAI Chat Model** and **OpenAI Chat Model (Repair)** and pick your OpenAI credential. Any chat model node works.\n2. Run the **Run Once: Create Log Table** branch.\n3. Run **Try It: Run Demo**, then edit **Demo Settings (edit me)**: paste your JSON Schema and set max_retries.\n\n### Use it from your own workflows\nAdd an **Execute Workflow** node that calls this workflow with `raw_output` (the model's text), `schema` (JSON Schema) and, optionally, `task`, `max_retries` and `record_id`. It returns `ok`, `data`, `errors`, `fixes` and `attempts`.\n\n### Customize\nAdd rules to the schema (enum, minimum, maxLength, pattern). Turn off `coerce_types` to make it strict. Read **Check Success Rate** to see how often your prompt needs a repair.", "width": 680, "height": 1560, "color": 1 }, "id": "da83f243-3e54-5aa0-9c9b-e2e13f138b34", "name": "Main Description", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -2700, -500 ] }, { "parameters": { "content": "## 0. One-time setup\nRun this branch once. It creates the **ai_json_guard_log** Data Table (or reuses it).", "width": 480, "height": 260, "color": 7 }, "id": "c4d95220-35a7-5585-a7ea-42f1b0944576", "name": "Section 0", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -1960, -520 ] }, { "parameters": { "content": "## 1. Demo: AI step with no parser\n**Require Specific Output Format** is off, so the model's text always reaches the guard. Its **On Error** setting is *Continue*, so a failed AI call (rate limit, timeout) reaches the guard as an error and gets retried instead of stopping the run.", "width": 1180, "height": 500, "color": 7 }, "id": "c6b80f1b-7ca9-5d4f-9315-c5930d93ad86", "name": "Section 1", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -1960, -160 ] }, { "parameters": { "content": "## 2. Call it from any workflow\n**Publish** this workflow once so other workflows can call it. Then send `raw_output` + `schema` with an **Execute Workflow** node. Optional: `task` (your original prompt, used in repairs), `max_retries`, `record_id`, `coerce_types`.", "width": 980, "height": 300, "color": 7 }, "id": "17dfa967-b4ae-51a1-8a09-7c2571894750", "name": "Section 2", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -1960, 360 ] }, { "parameters": { "content": "## 3. Clean, extract, validate\nNo AI calls here. Each fix is listed in `fixes`, and each schema problem in `errors`.", "width": 700, "height": 400, "color": 7 }, "id": "cc1a56ea-671f-5daa-bf8e-87811bcb5f6e", "name": "Section 3", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -820, 60 ] }, { "parameters": { "content": "## 4. Repair loop\nOnly items that still fail come here. The model gets the exact errors, the schema, the task and its previous answer. **Next Attempt** sends the reply back through the same checks.", "width": 680, "height": 500, "color": 7 }, "id": "c7968edc-f9c4-5287-a176-31c2733f57e9", "name": "Section 4", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -120, 200 ] }, { "parameters": { "content": "## 5. Log + return\nEvery item is logged. `failed` rows keep the raw output so you can see what the model said. **Return Result** is what callers receive.", "width": 680, "height": 400, "color": 7 }, "id": "2c46810c-4ca7-5638-8a12-3718ab4bf4af", "name": "Section 5", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -120, -220 ] }, { "parameters": { "content": "## 6. Success rate\nRun this to see first-try vs. after-retry vs. failed percentages and the most common issues.", "width": 700, "height": 340, "color": 7 }, "id": "91c54601-d653-566c-97b9-80ddc1ac4845", "name": "Section 6", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -1960, 720 ] } ], "connections": { "Run Once: Create Log Table": { "main": [ [ { "node": "Create Log Data Table", "type": "main", "index": 0 } ] ] }, "OpenAI Chat Model": { "ai_languageModel": [ [ { "node": "AI: Extract Ticket Fields", "type": "ai_languageModel", "index": 0 } ] ] }, "Try It: Run Demo": { "main": [ [ { "node": "Sample Support Tickets", "type": "main", "index": 0 } ] ] }, "Sample Support Tickets": { "main": [ [ { "node": "Demo Settings (edit me)", "type": "main", "index": 0 } ] ] }, "Demo Settings (edit me)": { "main": [ [ { "node": "AI: Extract Ticket Fields", "type": "main", "index": 0 } ] ] }, "AI: Extract Ticket Fields": { "main": [ [ { "node": "Package For Guard", "type": "main", "index": 0 } ] ] }, "When Called By Another Workflow": { "main": [ [ { "node": "Normalize Caller Input", "type": "main", "index": 0 } ] ] }, "Package For Guard": { "main": [ [ { "node": "Clean + Extract JSON", "type": "main", "index": 0 } ] ] }, "Normalize Caller Input": { "main": [ [ { "node": "Clean + Extract JSON", "type": "main", "index": 0 } ] ] }, "Clean + Extract JSON": { "main": [ [ { "node": "Validate Against Schema", "type": "main", "index": 0 } ] ] }, "Validate Against Schema": { "main": [ [ { "node": "Valid, Retry Or Give Up?", "type": "main", "index": 0 } ] ] }, "OpenAI Chat Model (Repair)": { "ai_languageModel": [ [ { "node": "AI: Repair JSON", "type": "ai_languageModel", "index": 0 } ] ] }, "Valid, Retry Or Give Up?": { "main": [ [ { "node": "Build Final Result", "type": "main", "index": 0 } ], [ { "node": "Build Correction Prompt", "type": "main", "index": 0 } ], [ { "node": "Build Final Result", "type": "main", "index": 0 } ] ] }, "Build Correction Prompt": { "main": [ [ { "node": "AI: Repair JSON", "type": "main", "index": 0 } ] ] }, "AI: Repair JSON": { "main": [ [ { "node": "Next Attempt", "type": "main", "index": 0 } ] ] }, "Next Attempt": { "main": [ [ { "node": "Clean + Extract JSON", "type": "main", "index": 0 } ] ] }, "Build Final Result": { "main": [ [ { "node": "Log Result (Failures = Dead Letter)", "type": "main", "index": 0 } ] ] }, "Log Result (Failures = Dead Letter)": { "main": [ [ { "node": "Return Result", "type": "main", "index": 0 } ] ] }, "Check Success Rate": { "main": [ [ { "node": "Read Log Table", "type": "main", "index": 0 } ] ] }, "Read Log Table": { "main": [ [ { "node": "Summarize Success Rate", "type": "main", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" }, "pinData": {}, "tags": [] }