The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"name": "Psy Froggy Bot Workflow",
"nodes": [
{
"parameters": {
"httpMethod": "POST",
"path": "bot-start",
"options": {}
},
"name": "Start Webhook",
"type": "n8n-nodes-base.webhook",
"typeVersion": 1.1,
"position": [
208,
304
],
"id": "webhook-start"
},
{
"parameters": {
"options": {}
},
"name": "Store Initial Data",
"type": "n8n-nodes-base.set",
"typeVersion": 3,
"position": [
480,
304
],
"id": "store-initial"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/register-wait",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.body.chat_id,\n executionId: $execution.id,\n webhookSuffix: '/step1',\n stepName: 'waiting_for_topic',\n message: 'Welcome to ProofPRO! \ud83c\udfaf\\n\\n*Step 1: Topic Selection*\\n\\nPlease provide the topic for your article:'\n} }}",
"options": {}
},
"name": "Register Wait Step 1",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
704,
304
],
"id": "register-wait-step1"
},
{
"parameters": {
"resume": "webhook",
"httpMethod": "POST",
"options": {
"webhookSuffix": "/step1"
}
},
"name": "Wait for Topic",
"type": "n8n-nodes-base.wait",
"typeVersion": 1,
"position": [
928,
304
],
"id": "wait-topic"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Topic",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
288,
624
],
"id": "process-topic"
},
{
"parameters": {
"url": "http://host.docker.internal:3001/api/prompts/00_generate_names.json",
"options": {
"timeout": 10000
}
},
"name": "Get Name Prompt",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
512,
624
],
"id": "get-name-prompt"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Prepare Short Name Prompt",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
736,
624
],
"id": "prepare-name-prompt"
},
{
"parameters": {
"method": "POST",
"url": "https://router.huggingface.co/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "httpBearerAuth",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "messages",
"value": "={{ [{\"role\": \"user\", \"content\": $json.prompt}] }}"
},
{
"name": "model",
"value": "meta-llama/Llama-3.2-3B-Instruct:novita"
},
{
"name": "stream",
"value": "={{ false }}"
},
{
"name": "max_tokens",
"value": "={{ 4000 }}"
},
{
"name": "temperature",
"value": "={{ 0.7 }}"
}
]
},
"options": {
"timeout": 10000
}
},
"name": "Call LLM for Name",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
960,
624
],
"id": "call-llm-name",
"credentials": {
"httpBearerAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Parse Short Name Response",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1184,
624
],
"id": "parse-name-response"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Prepare Initial Questions",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1408,
624
],
"id": "prep-init-questions"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: $json.message,\n animation: true\n} }}",
"options": {}
},
"name": "Send Progress Animation",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1632,
624
],
"id": "send-progress-anim"
},
{
"parameters": {
"url": "={{ 'http://host.docker.internal:3001/api/' + $node['Prepare Initial Questions'].json.prompt_file }}",
"options": {
"timeout": 10000
}
},
"name": "Get Questions Prompt",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1856,
624
],
"id": "get-questions-prompt"
},
{
"parameters": {
"method": "POST",
"url": "https://router.huggingface.co/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "httpBearerAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ (() => {\n const promptData = $node['Get Questions Prompt'].json.prompt || {};\n const topicData = $node['Prepare Initial Questions'].json || {};\n \n // Build system message\n const systemParts = [];\n if (promptData.system_prompt) systemParts.push(promptData.system_prompt);\n if (promptData.task) systemParts.push('Task: ' + promptData.task);\n if (promptData.description) systemParts.push('Description: ' + promptData.description);\n if (promptData.current_date) systemParts.push('Current Date: ' + promptData.current_date);\n if (promptData.date_context) systemParts.push('Date Context: ' + promptData.date_context);\n \n // Build user message\n const userParts = ['/think'];\n if (topicData.topic) userParts.push('Topic: ' + topicData.topic);\n \n // Add requirements\n if (promptData.requirements && Array.isArray(promptData.requirements) && promptData.requirements.length > 0) {\n userParts.push('');\n userParts.push('## Requirements:');\n userParts.push(promptData.requirements.map(r => '- ' + r).join('\\n'));\n }\n \n // Add tool usage\n if (promptData.tool_usage) {\n userParts.push('');\n userParts.push('## Tool Usage:');\n if (promptData.tool_usage.description) userParts.push('Description: ' + promptData.tool_usage.description);\n if (promptData.tool_usage.functions) userParts.push('Functions Available: ' + JSON.stringify(promptData.tool_usage.functions, null, 2));\n if (promptData.tool_usage.rules && Array.isArray(promptData.tool_usage.rules)) {\n userParts.push('Rules:');\n userParts.push(promptData.tool_usage.rules.map(r => '- ' + r).join('\\n'));\n }\n }\n \n // Add output format\n if (promptData.output_format) {\n userParts.push('');\n userParts.push('## Expected Output Format:');\n userParts.push(JSON.stringify(promptData.output_format, null, 2));\n }\n \n // Add ALL examples in JSON format\n if (promptData.example_outputs && Array.isArray(promptData.example_outputs) && promptData.example_outputs.length > 0) {\n userParts.push('');\n userParts.push('## Example Outputs (ALL examples in JSON):');\n userParts.push(JSON.stringify(promptData.example_outputs, null, 2));\n }\n \n // Add inputs section if present\n if (promptData.inputs) {\n userParts.push('');\n userParts.push('## Inputs Template:');\n userParts.push(JSON.stringify(promptData.inputs, null, 2));\n }\n \n // Add current date and date context\n if (promptData.current_date) {\n userParts.push('');\n userParts.push('## Current Date: ' + promptData.current_date);\n }\n if (promptData.date_context) {\n userParts.push(promptData.date_context);\n }\n \n // Add input parameters\n userParts.push('');\n userParts.push('## Input Parameters:');\n userParts.push('Style: ' + (topicData.style || 'investigative journalism'));\n userParts.push('Additional Requirements: ' + (topicData.requirements || 'none'));\n \n // Return the complete request object\n return {\n model: 'Qwen/Qwen3-235B-A22B-Thinking-2507',\n messages: [\n {\n role: 'system',\n content: systemParts.filter(Boolean).join('\\n\\n') || 'You are an investigative journalist.'\n },\n {\n role: 'user',\n content: userParts.filter(Boolean).join('\\n')\n }\n ],\n temperature: 0.7,\n max_tokens: 8000,\n response_format: { type: \"json_object\" }\n };\n})() }}",
"options": {
"timeout": 600000
}
},
"name": "Call LLM Initial Questions",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
2064,
624
],
"id": "llm-init-questions",
"credentials": {
"httpBearerAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Parse WebSearch Calls",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
272,
912
],
"id": "parse-websearch"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Execute WebSearch",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
496,
912
],
"id": "exec-websearch"
},
{
"parameters": {
"url": "https://api.search.brave.com/res/v1/web/search",
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "q",
"value": "={{ $json.brave_search_query }}"
},
{
"name": "count",
"value": "10"
},
{
"name": "freshness",
"value": "week"
}
]
},
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "X-Subscription-Token",
"value": "={{ $env.BRAVE_SEARCH_API_KEY }}"
},
{
"name": "Accept",
"value": "application/json"
}
]
},
"options": {
"timeout": 15000
}
},
"name": "Brave Search API",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
720,
912
],
"id": "brave-search"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Search Results",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
944,
912
],
"id": "process-search"
},
{
"parameters": {
"url": "={{ 'http://host.docker.internal:3001/api/' + $node['Process Search Results'].json.prompt_file }}",
"options": {
"timeout": 10000
}
},
"name": "Get Final Questions Prompt",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
256,
1168
],
"id": "get-final-prompt"
},
{
"parameters": {
"method": "POST",
"url": "https://router.huggingface.co/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "httpBearerAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ (() => {\n const promptData = $node['Get Final Questions Prompt'].json.prompt || {};\n const searchData = $node['Process Search Results'].json || {};\n \n // Build system message\n const systemParts = [];\n if (promptData.system_prompt) systemParts.push(promptData.system_prompt);\n if (promptData.task) systemParts.push('Task: ' + promptData.task);\n if (promptData.description) systemParts.push('Description: ' + promptData.description);\n if (promptData.current_date) systemParts.push('Current Date: ' + promptData.current_date);\n if (promptData.date_context) systemParts.push('Date Context: ' + promptData.date_context);\n \n // Build user message\n const userParts = ['/think'];\n if (searchData.topic) userParts.push('Topic: ' + searchData.topic);\n \n // Add search results\n if (searchData.search_summary) {\n userParts.push('');\n userParts.push('## Search Results:');\n userParts.push(searchData.search_summary);\n }\n \n // Add requirements\n if (promptData.requirements && Array.isArray(promptData.requirements) && promptData.requirements.length > 0) {\n userParts.push('');\n userParts.push('## Requirements:');\n userParts.push(promptData.requirements.map(r => '- ' + r).join('\\n'));\n }\n \n // Add tool usage\n if (promptData.tool_usage) {\n userParts.push('');\n userParts.push('## Tool Usage:');\n if (promptData.tool_usage.description) userParts.push('Description: ' + promptData.tool_usage.description);\n if (promptData.tool_usage.functions) userParts.push('Functions Available: ' + JSON.stringify(promptData.tool_usage.functions, null, 2));\n if (promptData.tool_usage.rules && Array.isArray(promptData.tool_usage.rules)) {\n userParts.push('Rules:');\n userParts.push(promptData.tool_usage.rules.map(r => '- ' + r).join('\\n'));\n }\n }\n \n // Add output format\n if (promptData.output_format) {\n userParts.push('');\n userParts.push('## Expected Output Format:');\n userParts.push(JSON.stringify(promptData.output_format, null, 2));\n }\n \n // Add ALL examples in JSON format\n if (promptData.example_outputs && Array.isArray(promptData.example_outputs) && promptData.example_outputs.length > 0) {\n userParts.push('');\n userParts.push('## Example Outputs (ALL examples in JSON):');\n userParts.push(JSON.stringify(promptData.example_outputs, null, 2));\n }\n \n // Add inputs section if present\n if (promptData.inputs) {\n userParts.push('');\n userParts.push('## Inputs Template:');\n userParts.push(JSON.stringify(promptData.inputs, null, 2));\n }\n \n // Add current date and date context (moved before search context)\n if (promptData.current_date) {\n userParts.push('');\n userParts.push('## Current Date: ' + promptData.current_date);\n }\n if (promptData.date_context) {\n userParts.push(promptData.date_context);\n }\n \n // Add search context\n userParts.push('');\n userParts.push('## Search Context:');\n userParts.push('Total Results: ' + (searchData.total_results || 0));\n if (searchData.queries && Array.isArray(searchData.queries)) {\n userParts.push('Queries Used: ' + JSON.stringify(searchData.queries, null, 2));\n }\n \n // Return the complete request object\n return {\n model: 'Qwen/Qwen3-235B-A22B-Thinking-2507',\n messages: [\n {\n role: 'system',\n content: systemParts.filter(Boolean).join('\\n\\n') || 'You are an investigative journalist.'\n },\n {\n role: 'user',\n content: userParts.filter(Boolean).join('\\n')\n }\n ],\n temperature: 0.7,\n max_tokens: 8000,\n response_format: { type: \"json_object\" }\n };\n})() }}",
"options": {
"timeout": 600000
}
},
"name": "Call LLM Final Questions",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
480,
1168
],
"id": "llm-final-questions",
"credentials": {
"httpBearerAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Format Final Questions",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
704,
1168
],
"id": "format-questions"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: $json.message,\n stop_animation: $json.stop_animation\n} }}",
"options": {}
},
"name": "Send Questions Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
928,
1168
],
"id": "send-questions-message"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Questions Action",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1152,
1168
],
"id": "process-action"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: $json.message\n} }}",
"options": {}
},
"name": "Send Progress Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1376,
1168
],
"id": "send-progress"
},
{
"parameters": {
"url": "http://host.docker.internal:3001/api/prompts/02_structure_creation.json",
"options": {}
},
"name": "Get Structure Prompt",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
256,
1424
],
"id": "get-structure-prompt"
},
{
"parameters": {
"method": "POST",
"url": "https://router.huggingface.co/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "httpBearerAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ (() => {\n const promptData = $node['Get Structure Prompt'].json.prompt || {};\n const questionsNode = $node['Format Final Questions'];\n const searchNode = $node['Process Search Results'];\n \n // Get data from previous nodes\n const chatId = questionsNode?.json?.chat_id || '';\n const topic = questionsNode?.json?.topic || '';\n const shortName = questionsNode?.json?.short_name || '';\n const questionsData = questionsNode?.json?.questions_data || {};\n const searchResults = searchNode?.json?.search_results || [];\n const searchSummary = searchNode?.json?.search_summary || '';\n \n // Build system message\n const systemParts = [];\n if (promptData.system_prompt) systemParts.push(promptData.system_prompt);\n if (promptData.task) systemParts.push('Task: ' + promptData.task);\n if (promptData.description) systemParts.push('Description: ' + promptData.description);\n \n // Build user message\n const userParts = ['/think'];\n userParts.push('Topic: ' + topic);\n userParts.push('Project: ' + shortName);\n \n // Add research questions\n if (questionsData.research_questions && questionsData.research_questions.length > 0) {\n userParts.push('');\n userParts.push('## Research Questions:');\n questionsData.research_questions.forEach((q, i) => {\n userParts.push(`${i + 1}. ${q}`);\n });\n }\n \n // Add key angles\n if (questionsData.key_angles && questionsData.key_angles.length > 0) {\n userParts.push('');\n userParts.push('## Key Research Angles:');\n questionsData.key_angles.forEach(angle => {\n userParts.push('\u2022 ' + angle);\n });\n }\n \n // Add required sources\n if (questionsData.required_sources && questionsData.required_sources.length > 0) {\n userParts.push('');\n userParts.push('## Required Sources:');\n questionsData.required_sources.forEach(source => {\n userParts.push('\u2022 ' + source);\n });\n }\n \n // Add scope definition\n if (questionsData.scope_definition) {\n userParts.push('');\n userParts.push('## Research Scope:');\n if (questionsData.scope_definition.geographic_focus) {\n userParts.push('Geographic Focus: ' + questionsData.scope_definition.geographic_focus);\n }\n if (questionsData.scope_definition.time_period) {\n userParts.push('Time Period: ' + questionsData.scope_definition.time_period);\n }\n if (questionsData.scope_definition.depth) {\n userParts.push('Depth: ' + questionsData.scope_definition.depth);\n }\n }\n \n // Add search results summary\n if (searchSummary) {\n userParts.push('');\n userParts.push('## Available Sources from Initial Search:');\n userParts.push(searchSummary);\n }\n \n // Add instructions from prompt\n if (promptData.instructions) {\n userParts.push('');\n userParts.push('## Instructions:');\n if (promptData.instructions.primary_task) {\n userParts.push('Primary Task: ' + promptData.instructions.primary_task);\n }\n if (promptData.instructions.requirements && Array.isArray(promptData.instructions.requirements)) {\n userParts.push('');\n userParts.push('Requirements:');\n promptData.instructions.requirements.forEach(req => {\n userParts.push('- ' + req);\n });\n }\n if (promptData.instructions.structure_elements) {\n userParts.push('');\n userParts.push('Structure Elements:');\n userParts.push(JSON.stringify(promptData.instructions.structure_elements, null, 2));\n }\n }\n \n // Add output format\n if (promptData.output_format) {\n userParts.push('');\n userParts.push('## Expected Output Format:');\n userParts.push(JSON.stringify(promptData.output_format, null, 2));\n }\n \n // Add examples if present\n if (promptData.examples && Array.isArray(promptData.examples) && promptData.examples.length > 0) {\n userParts.push('');\n userParts.push('## Example Structure:');\n userParts.push(JSON.stringify(promptData.examples[0], null, 2));\n }\n \n // Add character limit\n userParts.push('');\n userParts.push('## Target Article Length:');\n userParts.push('Approximately 25,000 characters (comprehensive journalistic investigation)');\n \n // Return the complete request object for HuggingFace\n return {\n model: 'Qwen/Qwen3-235B-A22B-Thinking-2507',\n messages: [\n {\n role: 'system',\n content: systemParts.filter(Boolean).join('\\n\\n') || 'You are a senior editor specializing in article structure.'\n },\n {\n role: 'user',\n content: userParts.filter(Boolean).join('\\n')\n }\n ],\n temperature: 0.7,\n max_tokens: 8000,\n response_format: { type: \"json_object\" }\n };\n})() }}",
"options": {
"timeout": 600000
}
},
"name": "Call LLM Structure Creation",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
480,
1424
],
"id": "llm-structure",
"credentials": {
"httpBearerAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: $json.message\n} }}",
"options": {}
},
"name": "Send Structure Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
928,
1424
],
"id": "send-structure"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Format Structure Response",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
704,
1424
],
"id": "format-structure"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Source Collection",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1152,
1424
],
"id": "process-sources"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\ud83d\udcc4 Sources collected! Extracting quotes...'\n} }}",
"options": {}
},
"name": "Send Sources Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1376,
1424
],
"id": "send-sources"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Quote Extraction",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1600,
1424
],
"id": "process-quotes"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\ud83d\udd70\ufe0f Quotes extracted! Analyzing timeline...'\n} }}",
"options": {}
},
"name": "Send Quotes Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1824,
1424
],
"id": "send-quotes"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Timeline Analysis",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
256,
1632
],
"id": "process-timeline"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\u2705 Timeline analyzed! Fact checking...'\n} }}",
"options": {}
},
"name": "Send Timeline Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
480,
1632
],
"id": "send-timeline"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Fact Checking",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
704,
1632
],
"id": "process-facts"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\u270d\ufe0f Facts verified! Writing article...'\n} }}",
"options": {}
},
"name": "Send Facts Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
928,
1632
],
"id": "send-facts"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Article Writing",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1152,
1632
],
"id": "process-writing"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\ud83d\udd0d Article draft ready! Final review...'\n} }}",
"options": {}
},
"name": "Send Writing Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1376,
1632
],
"id": "send-writing"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Final Review",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1600,
1632
],
"id": "process-review"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\ud83d\udd17 Review complete! Verifying links...'\n} }}",
"options": {}
},
"name": "Send Review Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
256,
1840
],
"id": "send-review"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Link Verification",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
480,
1840
],
"id": "process-links"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\ud83c\udf86 Links verified! Finalizing article...'\n} }}",
"options": {}
},
"name": "Send Links Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
704,
1840
],
"id": "send-links"
},
{
"parameters": {
"jsCode": "// will be injected"
},
"name": "Process Final Article",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
928,
1840
],
"id": "process-final"
},
{
"parameters": {
"method": "POST",
"url": "http://host.docker.internal:3001/api/send-message",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ {\n chatId: $json.chat_id,\n message: '\u2705 **Article Generation Complete!**\\n\\nYour article has been successfully generated and is ready for review.'\n} }}",
"options": {}
},
"name": "Send Final Message",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1152,
1840
],
"id": "send-final"
}
],
"connections": {
"Start Webhook": {
"main": [
[
{
"node": "Store Initial Data",
"type": "main",
"index": 0
}
]
]
},
"Store Initial Data": {
"main": [
[
{
"node": "Register Wait Step 1",
"type": "main",
"index": 0
}
]
]
},
"Register Wait Step 1": {
"main": [
[
{
"node": "Wait for Topic",
"type": "main",
"index": 0
}
]
]
},
"Wait for Topic": {
"main": [
[
{
"node": "Process Topic",
"type": "main",
"index": 0
}
]
]
},
"Process Topic": {
"main": [
[
{
"node": "Get Name Prompt",
"type": "main",
"index": 0
}
]
]
},
"Get Name Prompt": {
"main": [
[
{
"node": "Prepare Short Name Prompt",
"type": "main",
"index": 0
}
]
]
},
"Prepare Short Name Prompt": {
"main": [
[
{
"node": "Call LLM for Name",
"type": "main",
"index": 0
}
]
]
},
"Call LLM for Name": {
"main": [
[
{
"node": "Parse Short Name Response",
"type": "main",
"index": 0
}
]
]
},
"Parse Short Name Response": {
"main": [
[
{
"node": "Prepare Initial Questions",
"type": "main",
"index": 0
}
]
]
},
"Prepare Initial Questions": {
"main": [
[
{
"node": "Send Progress Animation",
"type": "main",
"index": 0
}
]
]
},
"Send Progress Animation": {
"main": [
[
{
"node": "Get Questions Prompt",
"type": "main",
"index": 0
}
]
]
},
"Get Questions Prompt": {
"main": [
[
{
"node": "Call LLM Initial Questions",
"type": "main",
"index": 0
}
]
]
},
"Call LLM Initial Questions": {
"main": [
[
{
"node": "Parse WebSearch Calls",
"type": "main",
"index": 0
}
]
]
},
"Parse WebSearch Calls": {
"main": [
[
{
"node": "Execute WebSearch",
"type": "main",
"index": 0
}
]
]
},
"Execute WebSearch": {
"main": [
[
{
"node": "Brave Search API",
"type": "main",
"index": 0
}
]
]
},
"Brave Search API": {
"main": [
[
{
"node": "Process Search Results",
"type": "main",
"index": 0
}
]
]
},
"Process Search Results": {
"main": [
[
{
"node": "Get Final Questions Prompt",
"type": "main",
"index": 0
}
]
]
},
"Get Final Questions Prompt": {
"main": [
[
{
"node": "Call LLM Final Questions",
"type": "main",
"index": 0
}
]
]
},
"Call LLM Final Questions": {
"main": [
[
{
"node": "Format Final Questions",
"type": "main",
"index": 0
}
]
]
},
"Format Final Questions": {
"main": [
[
{
"node": "Send Questions Message",
"type": "main",
"index": 0
}
]
]
},
"Send Questions Message": {
"main": [
[
{
"node": "Process Questions Action",
"type": "main",
"index": 0
}
]
]
},
"Process Questions Action": {
"main": [
[
{
"node": "Send Progress Message",
"type": "main",
"index": 0
}
]
]
},
"Send Progress Message": {
"main": [
[
{
"node": "Get Structure Prompt",
"type": "main",
"index": 0
}
]
]
},
"Get Structure Prompt": {
"main": [
[
{
"node": "Call LLM Structure Creation",
"type": "main",
"index": 0
}
]
]
},
"Call LLM Structure Creation": {
"main": [
[
{
"node": "Format Structure Response",
"type": "main",
"index": 0
}
]
]
},
"Format Structure Response": {
"main": [
[
{
"node": "Send Structure Message",
"type": "main",
"index": 0
}
]
]
},
"Send Structure Message": {
"main": [
[
{
"node": "Process Source Collection",
"type": "main",
"index": 0
}
]
]
},
"Process Source Collection": {
"main": [
[
{
"node": "Send Sources Message",
"type": "main",
"index": 0
}
]
]
},
"Send Sources Message": {
"main": [
[
{
"node": "Process Quote Extraction",
"type": "main",
"index": 0
}
]
]
},
"Process Quote Extraction": {
"main": [
[
{
"node": "Send Quotes Message",
"type": "main",
"index": 0
}
]
]
},
"Send Quotes Message": {
"main": [
[
{
"node": "Process Timeline Analysis",
"type": "main",
"index": 0
}
]
]
},
"Process Timeline Analysis": {
"main": [
[
{
"node": "Send Timeline Message",
"type": "main",
"index": 0
}
]
]
},
"Send Timeline Message": {
"main": [
[
{
"node": "Process Fact Checking",
"type": "main",
"index": 0
}
]
]
},
"Process Fact Checking": {
"main": [
[
{
"node": "Send Facts Message",
"type": "main",
"index": 0
}
]
]
},
"Send Facts Message": {
"main": [
[
{
"node": "Process Article Writing",
"type": "main",
"index": 0
}
]
]
},
"Process Article Writing": {
"main": [
[
{
"node": "Send Writing Message",
"type": "main",
"index": 0
}
]
]
},
"Send Writing Message": {
"main": [
[
{
"node": "Process Final Review",
"type": "main",
"index": 0
}
]
]
},
"Process Final Review": {
"main": [
[
{
"node": "Send Review Message",
"type": "main",
"index": 0
}
]
]
},
"Send Review Message": {
"main": [
[
{
"node": "Process Link Verification",
"type": "main",
"index": 0
}
]
]
},
"Process Link Verification": {
"main": [
[
{
"node": "Send Links Message",
"type": "main",
"index": 0
}
]
]
},
"Send Links Message": {
"main": [
[
{
"node": "Process Final Article",
"type": "main",
"index": 0
}
]
]
},
"Process Final Article": {
"main": [
[
{
"node": "Send Final Message",
"type": "main",
"index": 0
}
]
]
}
},
"active": true,
"settings": {
"executionOrder": "v1"
},
"versionId": "f5a09a2c-0d7d-45f6-a2a7-f49587432c41",
"id": "CT5Y4nNVFd6fptdX",
"tags": []
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
httpBearerAuth
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
Psy Froggy Bot Workflow. Uses httpRequest. Webhook trigger; 43 nodes.
Source: https://github.com/o-maan/psyfroggybot/blob/8b5e85659efebb574c23f7acf7a0e121e481c531/n8n-workflows/bot-workflow.json — original creator credit. Request a take-down →
Related workflows
Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
This n8n template provides enterprise-level version control for your workflows using GitHub integration. Stop losing hours to broken workflows and manual exports – get proper commit history, visual di
n8n, Execute Workflow Trigger, HTTP Request +1
This flow creates dummy files for every item added in your *Arrs (Radarr/Sonarr) with the tag .
HTTP Request, Ssh
This workflow acts as a central API gateway for all technical indicator agents in the Binance Spot Market Quant AI system. It listens for incoming webhook requests and dynamically routes them to the c
HTTP Request
Sign PDF documents with legally-compliant digital signatures using X.509 certificates. Supports multiple PAdES signature levels (B, T, LT, LTA) with optional visible stamps.
Execute Command, HTTP Request, Read Write File +1
📡 This workflow serves as the central Alpha Vantage API fetcher for Tesla trading indicators, delivering cleaned 20-point JSON outputs for three timeframes: , , and . It is required by the following a
HTTP Request