{
  "workflow": {
    "id": 6620,
    "name": "Reddit comment sentiment analysis with Bright Data and Gemini AI to Google Sheets",
    "views": 439,
    "recentViews": 0,
    "totalViews": 439,
    "createdAt": "2025-07-29T09:06:15.224Z",
    "description": "\nThis workflow automatically analyzes Reddit comments to understand public sentiment and community reactions. It saves you hours of manual reading by using AI to classify comments as positive, negative, or neutral, providing instant insights into how people feel about any Reddit post.\n\n## Overview\nThis workflow scrapes Reddit post comments using Bright Data's web scraping capabilities, then uses Google Gemini AI to analyze the sentiment of each comment. The results are automatically saved to Google Sheets with the comment text, sentiment classification, and reasoning behind each classification.\n\n## Tools Used\n* **n8n**: The automation platform that orchestrates the workflow\n* **Bright Data**: For scraping Reddit comments without restrictions or rate limits\n* **Google Gemini**: AI model for intelligent sentiment analysis\n* **Google Sheets**: For storing and tracking sentiment analysis results\n\n## How to Install\n1. **Import the Workflow**: Download the .json file and import it into your n8n instance\n2. **Configure Bright Data**: Add your Bright Data credentials to the scraping nodes\n3. **Set Up Google Gemini**: Configure your Google Gemini API credentials\n4. **Configure Google Sheets**: Connect your Google Sheets account and copy the template spreadsheet\n5. **Customize**: Simply paste any Reddit post URL and run the workflow\n\n## Use Cases\n* **Brand Monitoring**: Track sentiment around your brand or products on Reddit\n* **Product Managers**: Understand user feedback and pain points from Reddit discussions\n* **Market Research**: Analyze community reactions to news, launches, or announcements\n* **Community Managers**: Monitor sentiment trends and identify issues early\n* **Content Creators**: Gauge audience reactions to topics before creating content\n\n## Connect with Me\n* **Website**: https://www.nofluff.online\n* **YouTube**: https://www.youtube.com/@YaronBeen/videos\n* **LinkedIn**: https://www.linkedin.com/in/yaronbeen/\n* **Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission)\n\n#n8n #automation #sentimentanalysis #reddit #brightdata #webscraping #marketresearch #n8nworkflow #workflow #nocode #brandmonitoring #communityanalysis #redditanalytics #customersentiment #sociallistening #aianalysis #publicsentiment #marketintelligence #userresearch #communityinsights #redditmonitoring #sentimenttracking #customervoice #brandreputation #socialmediaanalysis #consumerinsights #feedbackan",
    "workflow": {
      "meta": {
        "instanceId": "741fe657cb1cf25e93c97c159943779bc83f3af267584292298f2b35e660e8e8",
        "templateCredsSetupCompleted": true
      },
      "nodes": [
        {
          "id": "ee795e8e-16a9-4df6-8b86-95cf51c031d0",
          "name": "Google Gemini Chat Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
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          ],
          "parameters": {
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          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
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          "name": "Auto-fixing Output Parser",
          "type": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
          "position": [
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          ],
          "parameters": {
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          },
          "typeVersion": 1
        },
        {
          "id": "9dd364d6-9745-49fe-ba37-1d6696f6e8d7",
          "name": "Google Gemini Chat Model1",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
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          ],
          "parameters": {
            "options": {}
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "90aa8498-a254-431e-931c-55743b71fc5b",
          "name": "Structured Output Parser",
          "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
          "position": [
            1584,
            480
          ],
          "parameters": {
            "jsonSchemaExample": "{\n  \"comment\": \"My 14 pro feels a bit laggy after the update.\",\n  \"sentiment\": \"negative\",\n  \"reason\": \"The user expressed dissatisfaction with the phone’s performance after the update, using the word 'laggy', which is a negative experience.\"\n}\n"
          },
          "typeVersion": 1.3
        },
        {
          "id": "54500d82-6d1b-4f65-945e-210a36208bda",
          "name": "Trigger: Manual Start",
          "type": "n8n-nodes-base.manualTrigger",
          "position": [
            -160,
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          ],
          "parameters": {},
          "typeVersion": 1
        },
        {
          "id": "f241718c-7a61-4a3b-adb9-da0e621f7cbc",
          "name": "Set Reddit Post URL",
          "type": "n8n-nodes-base.set",
          "position": [
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            0
          ],
          "parameters": {
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            "assignments": {
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                {
                  "id": "c602fcde-572b-43c9-b9e3-bb1ae11d3b22",
                  "name": "post URL",
                  "type": "string",
                  "value": "https://www.reddit.com/r/iphone/comments/1kl0tb5/new_ios_185_update/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button"
                }
              ]
            }
          },
          "typeVersion": 3.4
        },
        {
          "id": "a1593058-3d9b-4b3b-8b06-9e7ab53b561e",
          "name": "Bright Data: Get comments",
          "type": "@brightdata/n8n-nodes-brightdata.brightData",
          "position": [
            336,
            0
          ],
          "parameters": {
            "urls": "=[{\"url\":\"{{ $json[\"post URL\"] }}\"}]",
            "resource": "webScrapper",
            "dataset_id": {
              "__rl": true,
              "mode": "list",
              "value": "gd_lvzdpsdlw09j6t702",
              "cachedResultName": "Reddit - Comments"
            },
            "requestOptions": {}
          },
          "credentials": {
            "brightdataApi": {
              "id": "credential-id",
              "name": "brightdataApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "c2069b85-63a9-4e81-914f-bca4016f128d",
          "name": "Wait for Snapshot Processing (5 min)",
          "type": "n8n-nodes-base.wait",
          "position": [
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          ],
          "webhookId": "de346d16-e51c-4add-b1c1-fdc9b9a1b6d4",
          "parameters": {
            "unit": "minutes"
          },
          "typeVersion": 1.1
        },
        {
          "id": "1be77fde-720e-4283-970b-5228e7d0ccb3",
          "name": "Bright Data: Download Comments Snapshot",
          "type": "@brightdata/n8n-nodes-brightdata.brightData",
          "position": [
            768,
            0
          ],
          "parameters": {
            "resource": "webScrapper",
            "operation": "downloadSnapshot",
            "snapshot_id": "={{ $json.snapshot_id }}",
            "requestOptions": {}
          },
          "credentials": {
            "brightdataApi": {
              "id": "credential-id",
              "name": "brightdataApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "403fe1e9-aaab-49c6-a531-601641b08119",
          "name": "Limit to 5 Comments",
          "type": "n8n-nodes-base.limit",
          "position": [
            960,
            0
          ],
          "parameters": {
            "maxItems": 5
          },
          "typeVersion": 1
        },
        {
          "id": "3c6c116e-b384-42ff-af10-cad357fdf44f",
          "name": "AI Sentiment Classifier",
          "type": "@n8n/n8n-nodes-langchain.agent",
          "position": [
            1264,
            0
          ],
          "parameters": {
            "text": "=Based on the Reddit post's comment below, decide whether the sentiment is positive, negative or neutral.\n\ncomment: {{ $json.comment }}\nNumber of upvotes: {{ $json.num_upvotes }}",
            "options": {},
            "promptType": "define",
            "hasOutputParser": true
          },
          "typeVersion": 2.1
        },
        {
          "id": "05188346-66f3-453c-8f57-dab11b11899c",
          "name": "Save Sentiment to Google Sheets",
          "type": "n8n-nodes-base.googleSheets",
          "position": [
            1616,
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          ],
          "parameters": {
            "columns": {
              "value": {
                "Reason": "={{ $json.output.reason }}",
                "Comment": "={{ $json.output.comment }}",
                "Sentiment": "={{ $json.output.sentiment }}"
              },
              "schema": [
                {
                  "id": "Comment",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Comment",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Sentiment",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Sentiment",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Reason",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Reason",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                }
              ],
              "mappingMode": "defineBelow",
              "matchingColumns": [],
              "attemptToConvertTypes": false,
              "convertFieldsToString": false
            },
            "options": {},
            "operation": "append",
            "sheetName": {
              "__rl": true,
              "mode": "list",
              "value": "gid=0",
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1WPOfGgyqbcu8RFdA_LyMvCRxqrwr-nUL5JT656ASwOA/edit#gid=0",
              "cachedResultName": "Sheet1"
            },
            "documentId": {
              "__rl": true,
              "mode": "list",
              "value": "1WPOfGgyqbcu8RFdA_LyMvCRxqrwr-nUL5JT656ASwOA",
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1WPOfGgyqbcu8RFdA_LyMvCRxqrwr-nUL5JT656ASwOA/edit?usp=drivesdk",
              "cachedResultName": "Reddit post's comment sentiment analysis"
            }
          },
          "credentials": {
            "googleSheetsOAuth2Api": {
              "id": "credential-id",
              "name": "googleSheetsOAuth2Api Credential"
            }
          },
          "typeVersion": 4.6
        },
        {
          "id": "9fac1e20-5b36-47c7-9fa3-74fbdeb49520",
          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -192,
            -608
          ],
          "parameters": {
            "color": 6,
            "width": 352,
            "height": 784,
            "content": "### 🔹 **Section 1: Trigger & Input Setup**\n\n📌 *(\"Trigger: Manual Start\" + \"Set Reddit Post URL\")*\n\n#### 🔘 `Trigger: Manual Start`\n\n▶️ **Icon:** 🖱️\nThis is a **manual trigger node**. You start the workflow by clicking a button in the n8n editor.\n\n> 💡 *Perfect for testing and running when you want full control.*\n\n#### 📝 `Set Reddit Post URL`\n\n▶️ **Icon:** 🔗\nThis **Set node** lets you **manually enter the Reddit post URL** that you want to analyze.\n\n> 🧠 *You can later automate this with an API or Google Sheets feed, but for now, it’s easy to paste a URL manually.*\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "23c69791-3aef-453e-91b7-c32c75066f96",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            288,
            -688
          ],
          "parameters": {
            "color": 4,
            "width": 352,
            "height": 880,
            "content": "### 🔹 **Section 2: Snapshot Creation & Waiting**\n\n📌 *(\"Bright Data: Extract Snapshot ID\" + \"Wait for Snapshot Processing\")*\n\n#### 🔍 `Bright Data: Extract Snapshot ID`\n\n▶️ **Icon:** 🧠🔄\nThis node uses **Bright Data’s Web Scraper API** to create a new **snapshot job** for the provided Reddit URL. That job will start capturing all the structured data, including comments.\n\n> ⚙️ *It sends the request to start the scrape and gives us a snapshot ID to check later.*\n\n#### ⏳ `Wait for Snapshot Processing`\n\n▶️ **Icon:** ⏱️\nThe workflow **pauses for 5 minutes** to give Bright Data time to collect all the data.\n\n> 🛑 *Waiting ensures we don’t request results before the scraping job is complete.*\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "1fe96203-40e6-446d-b6d5-d36d98cafd0d",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            736,
            -672
          ],
          "parameters": {
            "color": 5,
            "width": 352,
            "height": 864,
            "content": "### 🔹 **Section 3: Download & Limit Data**\n\n📌 *(\"Bright Data: Download Comments Snapshot\" + \"Limit to 5 Comments\")*\n\n#### 💾 `Bright Data: Download Comments Snapshot`\n\n▶️ **Icon:** 📥\nThis node downloads the **scraped data using the snapshot ID**. It includes all comments under the Reddit post.\n\n> 📘 *Each comment is structured data, ready to be processed.*\n\n#### 🔢 `Limit to 5 Comments`\n\n▶️ **Icon:** 🚦\nThis **limits the number of comments** passed to the next step to just **5** for testing or to avoid long processing times.\n\n> ⚡ *You can increase this number later as needed.*\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "9cffe2f5-f99c-495f-96f0-4b08a7dcab33",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1232,
            -1120
          ],
          "parameters": {
            "color": 3,
            "width": 512,
            "height": 1312,
            "content": "### 🔹 **Section 4: Sentiment Analysis & Storage**\n\n📌 *(\"AI Sentiment Classifier\" + Output Parsers + Gemini + Google Sheets)*\n\nCopy this spreadsheet:\nhttps://docs.google.com/spreadsheets/d/1ycEjFdFK9MXQif2O_jh0Fhjlw5R9zwFUZ4qZdx8Duss/edit?usp=sharing\n\n#### 🤖 `AI Sentiment Classifier`\n\n▶️ **Icon:** 🧠💬\nThis is the **AI Agent node** that takes each comment and asks the AI:\n\n> *“Is this comment Positive, Negative, or Neutral?”*\n\n#### 🌈 `Google Gemini Chat Model`\n\n▶️ **Icon:** 🔵🟥🟡\nThe primary **AI model (Gemini)** that understands the text and returns a **sentiment label** with context.\n\n#### 🛠️ `Auto-Correct Output Parser`\n\n▶️ **Icon:** 🔧✨\nThis node **fixes any response issues** (like malformed data) to ensure it can be processed correctly downstream.\n\n#### 📋 `Sentiment Output Formatter`\n\n▶️ **Icon:** 🧾💡\nThis node converts the AI’s response into a **structured format** (like JSON), with fields like:\n\n```json\n{\n  \"sentiment\": \"positive\",\n  \"comment\": \"I love this post! So insightful.\"\n}\n```\n\n#### 📊 `Save Sentiment to Google Sheets`\n\n▶️ **Icon:** 📈📝\nFinally, the structured results are **saved to a Google Sheet**, making it easy to:\n\n* Track sentiment trends\n* Analyze user feedback\n* Export for reports or dashboards\n\n> 📁 *Each row contains the original comment and the AI's sentiment analysis.*\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "3af53eb1-98d7-441a-bf70-8db0d468c891",
          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1824,
            -1120
          ],
          "parameters": {
            "color": 7,
            "width": 380,
            "height": 240,
            "content": "## I’ll receive a tiny commission if you join Bright Data through this link—thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25"
          },
          "typeVersion": 1
        },
        {
          "id": "5e9cc429-7b58-476c-9e85-9881f9d93285",
          "name": "Sticky Note9",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1824,
            -608
          ],
          "parameters": {
            "color": 4,
            "width": 1300,
            "height": 320,
            "content": "=======================================\n            WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
          },
          "typeVersion": 1
        },
        {
          "id": "82f3a17c-4317-4132-92e4-f5a3e00c38bb",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1824,
            -272
          ],
          "parameters": {
            "color": 4,
            "width": 1289,
            "height": 3106,
            "content": "## 🌐✨ Reddit Sentiment Analyzer – Workflow Breakdown\n\nThis n8n workflow helps **automatically analyze the sentiment of Reddit post comments** and **save the results to Google Sheets**. It’s divided into 4 easy-to-understand sections:\n\n---\n\n### 🔹 **Section 1: Trigger & Input Setup**\n\n📌 *(\"Trigger: Manual Start\" + \"Set Reddit Post URL\")*\n\n#### 🔘 `Trigger: Manual Start`\n\n▶️ **Icon:** 🖱️\nThis is a **manual trigger node**. You start the workflow by clicking a button in the n8n editor.\n\n> 💡 *Perfect for testing and running when you want full control.*\n\n#### 📝 `Set Reddit Post URL`\n\n▶️ **Icon:** 🔗\nThis **Set node** lets you **manually enter the Reddit post URL** that you want to analyze.\n\n> 🧠 *You can later automate this with an API or Google Sheets feed, but for now, it’s easy to paste a URL manually.*\n\n---\n\n### 🔹 **Section 2: Snapshot Creation & Waiting**\n\n📌 *(\"Bright Data: Extract Snapshot ID\" + \"Wait for Snapshot Processing\")*\n\n#### 🔍 `Bright Data: Extract Snapshot ID`\n\n▶️ **Icon:** 🧠🔄\nThis node uses **Bright Data’s Web Scraper API** to create a new **snapshot job** for the provided Reddit URL. That job will start capturing all the structured data, including comments.\n\n> ⚙️ *It sends the request to start the scrape and gives us a snapshot ID to check later.*\n\n#### ⏳ `Wait for Snapshot Processing`\n\n▶️ **Icon:** ⏱️\nThe workflow **pauses for 5 minutes** to give Bright Data time to collect all the data.\n\n> 🛑 *Waiting ensures we don’t request results before the scraping job is complete.*\n\n---\n\n### 🔹 **Section 3: Download & Limit Data**\n\n📌 *(\"Bright Data: Download Comments Snapshot\" + \"Limit to 5 Comments\")*\n\n#### 💾 `Bright Data: Download Comments Snapshot`\n\n▶️ **Icon:** 📥\nThis node downloads the **scraped data using the snapshot ID**. It includes all comments under the Reddit post.\n\n> 📘 *Each comment is structured data, ready to be processed.*\n\n#### 🔢 `Limit to 5 Comments`\n\n▶️ **Icon:** 🚦\nThis **limits the number of comments** passed to the next step to just **5** for testing or to avoid long processing times.\n\n> ⚡ *You can increase this number later as needed.*\n\n---\n\n### 🔹 **Section 4: Sentiment Analysis & Storage**\n\n📌 *(\"AI Sentiment Classifier\" + Output Parsers + Gemini + Google Sheets)*\n\n#### 🤖 `AI Sentiment Classifier`\n\n▶️ **Icon:** 🧠💬\nThis is the **AI Agent node** that takes each comment and asks the AI:\n\n> *“Is this comment Positive, Negative, or Neutral?”*\n\n#### 🌈 `Google Gemini Chat Model`\n\n▶️ **Icon:** 🔵🟥🟡\nThe primary **AI model (Gemini)** that understands the text and returns a **sentiment label** with context.\n\n#### 🛠️ `Auto-Correct Output Parser`\n\n▶️ **Icon:** 🔧✨\nThis node **fixes any response issues** (like malformed data) to ensure it can be processed correctly downstream.\n\n#### 📋 `Sentiment Output Formatter`\n\n▶️ **Icon:** 🧾💡\nThis node converts the AI’s response into a **structured format** (like JSON), with fields like:\n\n```json\n{\n  \"sentiment\": \"positive\",\n  \"comment\": \"I love this post! So insightful.\"\n}\n```\n\n#### 📊 `Save Sentiment to Google Sheets`\n\n▶️ **Icon:** 📈📝\nFinally, the structured results are **saved to a Google Sheet**, making it easy to:\n\n* Track sentiment trends\n* Analyze user feedback\n* Export for reports or dashboards\n\n> 📁 *Each row contains the original comment and the AI's sentiment analysis.*\n\n---\n\n## 🎯 Why This Workflow Is Powerful (Especially for Beginners)\n\n✅ **No coding needed** — It's all visual automation\n✅ **Plug-and-play** — Just change the Reddit URL and you're good to go\n✅ **Real AI power** — Understand public sentiment using Google Gemini\n✅ **Structured output** — Clean data goes straight into a spreadsheet\n✅ **Expandable** — Add more analysis, automate triggering, or integrate with Slack, Notion, or CRMs\n\n---\n\n## 🛠️ Ready to Scale?\n\nYou can add enhancements like:\n\n* 🔄 Scheduled runs (to process trending Reddit posts automatically)\n* 🧵 Looping through more than 5 comments\n* 🔔 Slack notifications for negative sentiment\n* 📬 Email reports weekly with summary charts\n\n---\n"
          },
          "typeVersion": 1
        }
      ],
      "pinData": {},
      "connections": {
        "Limit to 5 Comments": {
          "main": [
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              {
                "node": "AI Sentiment Classifier",
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          ]
        },
        "Set Reddit Post URL": {
          "main": [
            [
              {
                "node": "Bright Data: Get comments",
                "type": "main",
                "index": 0
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            ]
          ]
        },
        "Trigger: Manual Start": {
          "main": [
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              {
                "node": "Set Reddit Post URL",
                "type": "main",
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        "AI Sentiment Classifier": {
          "main": [
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                "node": "Save Sentiment to Google Sheets",
                "type": "main",
                "index": 0
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            ]
          ]
        },
        "Google Gemini Chat Model": {
          "ai_languageModel": [
            [
              {
                "node": "AI Sentiment Classifier",
                "type": "ai_languageModel",
                "index": 0
              }
            ]
          ]
        },
        "Structured Output Parser": {
          "ai_outputParser": [
            [
              {
                "node": "Auto-fixing Output Parser",
                "type": "ai_outputParser",
                "index": 0
              }
            ]
          ]
        },
        "Auto-fixing Output Parser": {
          "ai_outputParser": [
            [
              {
                "node": "AI Sentiment Classifier",
                "type": "ai_outputParser",
                "index": 0
              }
            ]
          ]
        },
        "Bright Data: Get comments": {
          "main": [
            [
              {
                "node": "Wait for Snapshot Processing (5 min)",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Google Gemini Chat Model1": {
          "ai_languageModel": [
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              {
                "node": "Auto-fixing Output Parser",
                "type": "ai_languageModel",
                "index": 0
              }
            ]
          ]
        },
        "Wait for Snapshot Processing (5 min)": {
          "main": [
            [
              {
                "node": "Bright Data: Download Comments Snapshot",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Bright Data: Download Comments Snapshot": {
          "main": [
            [
              {
                "node": "Limit to 5 Comments",
                "type": "main",
                "index": 0
              }
            ]
          ]
        }
      }
    },
    "lastUpdatedBy": 29,
    "workflowInfo": {
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