{ "name": "Finance Literacy Bot - RAG & ChatBot", "nodes": [ { "parameters": { "options": {} }, "type": "@n8n/n8n-nodes-langchain.chatTrigger", "typeVersion": 1.3, "position": [ -560, -64 ], "id": "8871e4c4-c0f0-4ecf-89a6-6bd8e9d66879", "name": "When chat message received" }, { "parameters": { "promptType": "define", "text": "You are a financial literacy educator. Answer the user's question by searching your tools and providing well-formatted, helpful responses.\\n\\n**YOUR TOOLS:**\\n1. **Vector Store** - Your PDF educational library (7 financial literacy documents)\\n2. **Web Search** - Current internet information\\n\\n**TOOL SELECTION:**\\n- Definitions, concepts, fundamentals → Use Vector Store\\n- Current prices, recent news, market data → Use Web Search \\n- Concepts + current examples → Use BOTH\\n\\n**MANDATORY:** Always search before answering. Never rely on training data alone.\\n\\n**RESPONSE FORMAT:**\\n\\n🎯 **ANSWER**\\n[Clear, direct answer in 2-3 sentences]\\n\\n---\\n\\n📚 **FROM YOUR EDUCATIONAL MATERIALS**\\n[If you searched PDFs, include this section]\\n\\n[Detailed explanation from the PDF content]\\n\\n**Source Document:** [PDF filename without technical IDs]\\n\\n---\\n\\n🌐 **CURRENT INFORMATION**\\n[If you searched web, include this section]\\n\\n[Current data, news, or market information]\\n\\n**Source:** [Website name and URL]\\n\\n---\\n\\n💡 **KEY POINTS**\\n• [Important point 1]\\n• [Important point 2]\\n• [Important point 3]\\n• [Important point 4]\\n• [Important point 5]\\n\\n---\\n\\n📌 **WHY THIS MATTERS**\\n[Practical relevance and application]\\n\\n---\\n\\n🔍 **SOURCES USED**\\n✓ PDF Documents: [List filenames clearly]\\n✓ Web Sources: [List websites if used]\\n\\n---\\n\\n**FORMATTING RULES:**\\n1. Use emojis for visual clarity\\n2. Keep sections organized with horizontal lines (---)\\n3. Make it easy to read and scan\\n4. List PDF names without technical IDs or metadata\\n5. Be conversational but professional\\n6. Provide actionable information\\n\\n**EXAMPLE - Good Response:**\\n\\n🎯 **ANSWER**\\nCredit history is a record of your borrowing and repayment behavior over time. It shows lenders how reliably you've handled debt in the past.\\n\\n---\\n\\n📚 **FROM YOUR EDUCATIONAL MATERIALS**\\n\\nYour credit history includes:\\n- Payment history on all loans and credit cards\\n- Total amounts owed\\n- Length of credit history\\n- Types of credit used\\n- Recent credit inquiries\\n\\nLenders use this information to assess your creditworthiness and determine whether to approve new credit applications.\\n\\n**Source Document:** Financial Basics Guide\\n\\n---\\n\\n💡 **KEY POINTS**\\n• Payment history is the most important factor (35% of credit score)\\n• Late payments can stay on your report for 7 years\\n• Longer credit history is generally better\\n• Mix of credit types (cards, loans) is beneficial\\n• Too many hard inquiries can lower your score\\n\\n---\\n\\n📌 **WHY THIS MATTERS**\\nYour credit history directly impacts your ability to get loans, credit cards, apartments, and even jobs. Better credit history means lower interest rates and more financial opportunities.\\n\\n---\\n\\n🔍 **SOURCES USED**\\n✓ PDF Documents: MSYA-Module-09-PG.pdf\\n\\n---\\n\\nNow answer the user's question following this exact format.", "options": {} }, "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 2.2, "position": [ -352, -64 ], "id": "4a2d12fe-51da-4c87-8da5-9c5f9db2998a", "name": "AI Agent" }, { "parameters": { "model": "llama-3.3-70b-versatile", "options": { "maxTokensToSample": 2000, "temperature": 0.7 } }, "type": "@n8n/n8n-nodes-langchain.lmChatGroq", "typeVersion": 1, "position": [ -416, 176 ], "id": "e04c1803-7386-4813-952d-53a8c8651a7a", "name": "Groq Chat Model" }, { "parameters": { "mode": "retrieve-as-tool", "toolDescription": "Retrieve information from any company documents", "pineconeIndex": { "__rl": true, "value": "REPLACE_WITH_RESOURCE", "mode": "list" }, "topK": 3, "options": {} }, "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone", "typeVersion": 1.3, "position": [ -32, 128 ], "id": "e36c65d7-4d05-45ac-b6d8-9f348558b9a8", "name": "Pinecone Vector Store" }, { "parameters": { "modelName": "sentence-transformers/all-MiniLM-L6-v2", "options": {} }, "type": "@n8n/n8n-nodes-langchain.embeddingsHuggingFaceInference", "typeVersion": 1, "position": [ 48, 320 ], "id": "f67364c0-e6e1-4ff4-9527-bf3271b18db5", "name": "Embeddings HuggingFace Inference1" }, { "parameters": { "options": {} }, "type": "@n8n/n8n-nodes-langchain.toolSerpApi", "typeVersion": 1, "position": [ -208, 240 ], "id": "6b571ecc-9060-4621-9881-f9d0551fe166", "name": "SerpAPI" }, { "id": "c13f57a3-8e05-5b3a-b1b8-f97858a5df26", "name": "Publication · Overview and setup", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -1360, -64 ], "parameters": { "content": "# Finance Literacy Bot - RAG & ChatBot\n\n## Purpose and structure\nThis folder contains the **Finance Literacy Bot - RAG & ChatBot** workflow. Its executable nodes use `agent`, `chatTrigger`, `embeddingsHuggingFaceInference`, `lmChatGroq`, `toolSerpApi`, `vectorStorePinecone`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nWhen chat message received\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nNik Bear Brown; rights confirmed 2026-10-19\nMIT; preserve source notices.", "width": 700, "height": 800, "color": 1 } } ], "connections": { "When chat message received": { "main": [ [ { "node": "AI Agent", "type": "main", "index": 0 } ] ] }, "Groq Chat Model": { "ai_languageModel": [ [ { "node": "AI Agent", "type": "ai_languageModel", "index": 0 } ] ] }, "Pinecone Vector Store": { "ai_tool": [ [ { "node": "AI Agent", "type": "ai_tool", "index": 0 } ] ] }, "Embeddings HuggingFace Inference1": { "ai_embedding": [ [ { "node": "Pinecone Vector Store", "type": "ai_embedding", "index": 0 } ] ] }, "SerpAPI": { "ai_tool": [ [ { "node": "AI Agent", "type": "ai_tool", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" } }