Workflow: build automation using n8n for Manual Code Create Triggered
Integrations: code, googleDrive, manualTrigger, set, stickyNote

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In Pinecone, create an index with 1536 dimensions and select it in the two vector store nodes\n2. Populate Pinecone by clicking the 'test workflow' button below\n3. Click the 'chat' button below and enter the following:\n\n_Which email provider does the creator of Bitcoin use?_"}, "typeVersion": 1}, {"id": "c1543b8a-dbea-42a9-a35e-e22ed86f565b", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [-500, 640], "parameters": {"color": 7, "width": 1594, "height": 529, "content": "## 2. Chat with file, getting citations in reponse"}, "typeVersion": 1}, {"id": "5300d5dd-4186-4402-9442-88adab4e9a89", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [-480, -40], "parameters": {"color": 7, "width": 179.58883583572606, "height": 257.75985739596473, "content": "Will fetch the Bitcoin whitepaper, but you can change this"}, "typeVersion": 1}, {"id": "9f707f2b-6cb2-47b8-88fc-65cfd09b6cae", "name": "Pinecone Vector Store", "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone", "position": [80, 40], "parameters": {"mode": "insert", "options": {}, "pineconeIndex": {"__rl": true, "mode": "id", "value": "test-index"}}, "credentials": {"pineconeApi": {"id": "OHDlDbBkaPDgpnOY", "name": "PineconeApi account"}}, "typeVersion": 1}, {"id": "a32ac59e-efdc-4ff3-92dd-be794c2be7f7", "name": "When chat message received", "type": "@n8n/n8n-nodes-langchain.chatTrigger", "position": [-660, 760], "webhookId": "cd2703a7-f912-46fe-8787-3fb83ea116ab", "parameters": 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Important: In your response, also include the the indexes of the chunks you used to generate the answer."}, "schemaType": "manual", "inputSchema": "{\n  \"type\": \"object\",\n  \"required\": [\"answer\", \"citations\"],\n  \"properties\": {\n    \"answer\": {\n      \"type\": \"string\"\n    },\n    \"citations\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"number\"\n      }\n    }\n  }\n}"}, "typeVersion": 1}, {"id": "e43abc0c-cedf-4e73-a766-7fad57601cfe", "name": "Compose citations", "type": "n8n-nodes-base.set", "position": [700, 760], "parameters": {"options": {}, "assignments": {"assignments": [{"id": "ace6185e-8b3d-4f89-ae36-dfe0c391a0a9", "name": "citations", "type": "array", "value": "={{ $json.citations.map(i => '[' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata.file_name + ', lines ' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata['loc.lines.from'] + '-' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata['loc.lines.to'] + ']') }}"}]}}, "typeVersion": 3.4}, {"id": "f82df340-42fc-4e92-9e9d-d808f19e0407", "name": "Generate response", "type": "n8n-nodes-base.set", "position": [900, 760], "parameters": {"options": {}, "assignments": {"assignments": [{"id": "11396286-0378-4c3a-86e1-c9ef51afbfc7", "name": "text", "type": "string", "value": "={{ $json.answer }} {{ $if(!$json.citations.isEmpty(), \"\\n\" + $json.citations.join(\"\"), '') }}"}]}}, "typeVersion": 3.4}], "pinData": {}, "connections": {"Download file": {"main": [[{"node": "Pinecone Vector Store", "type": "main", "index": 0}]]}, "Prepare chunks": {"main": [[{"node": "Answer the query based on chunks", "type": "main", "index": 0}]]}, "Compose citations": {"main": [[{"node": "Generate response", "type": "main", "index": 0}]]}, "Embeddings OpenAI": {"ai_embedding": [[{"node": "Pinecone Vector Store", "type": "ai_embedding", "index": 0}]]}, "Embeddings OpenAI2": {"ai_embedding": [[{"node": "Get top chunks matching query", "type": "ai_embedding", "index": 0}]]}, "OpenAI Chat Model1": {"ai_languageModel": [[{"node": "Answer the query based on chunks", "type": "ai_languageModel", "index": 0}]]}, "Default Data Loader": {"ai_document": [[{"node": "Pinecone Vector Store", "type": "ai_document", "index": 0}]]}, "When chat message received": {"main": [[{"node": "Set max chunks to send to model", "type": "main", "index": 0}]]}, "Set file URL in Google Drive": {"main": [[{"node": "Download file", "type": "main", "index": 0}]]}, "Get top chunks matching query": {"main": [[{"node": "Prepare chunks", "type": "main", "index": 0}]]}, "Set max chunks to send to model": {"main": [[{"node": "Get top chunks matching query", "type": "main", "index": 0}]]}, "Answer the query based on chunks": {"main": [[{"node": "Compose citations", "type": "main", "index": 0}]]}, "When clicking \"Execute Workflow\"": {"main": [[{"node": "Set file URL in Google Drive", "type": "main", "index": 0}]]}, "Recursive Character Text Splitter": {"ai_textSplitter": [[{"node": "Default Data Loader", "type": "ai_textSplitter", "index": 0}]]}}}