├── README.md
├── app.py
└── script.js


/README.md:
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  1 | # From Local LLMs to Google Sheets
  2 | 
  3 | Locally run LLMs like `llama2`, `mistral`, `llava`, etc. on your computer and then get outputs inside Google Sheets.
  4 | 
  5 | [Watch this YouTube video](https://www.youtube.com/watch?v=q6b9MIktSAc) for more information on this.
  6 | 
  7 | ## Requirements
  8 | 
  9 | - Python
 10 | - [ollama](https://ollama.com/)
 11 | - [ngrok](https://ngrok.com/)
 12 | - Gmail account for Google Sheets
 13 | 
 14 | ## Process
 15 | 
 16 | ### 1. Install the `ollama` app on your computer
 17 | 
 18 | And run the following command after installing:
 19 | 
 20 | ```
 21 | ollama run mistral
 22 | ```
 23 | 
 24 | If you want to use any other model, you can replace `mistral` with other models that [you can find here](https://ollama.com/library).
 25 | 
 26 | ### 2. Run the Python code
 27 | 
 28 | Open a folder in VS Code or in any other code editor, and create a app.py file, and copy-paste the following code in it:
 29 | 
 30 | ```python
 31 | from flask import Flask, request, jsonify
 32 | import ollama
 33 | 
 34 | app = Flask(__name__)
 35 | 
 36 | @app.route('/api/chat', methods=['POST'])
 37 | def chat():
 38 |     data = request.json
 39 |     response = ollama.chat(model='mistral', messages=[{'role': 'user', 'content': data['content']}])
 40 |     return jsonify(response['message']['content'])
 41 | 
 42 | if __name__ == '__main__':
 43 |     app.run(debug=True, port=5001)
 44 | ```
 45 | 
 46 | If you're using any other model than `mistral`, make sure to replace in the above code as well.
 47 | 
 48 | ### 3. Install and run `ngrok`
 49 | 
 50 | Install `ngrok` by following the instruction from the [official website](https://ngrok.com/). You will also have to sign up for a free account, and you'll get a auth token which you can run in the terminal as:
 51 | 
 52 | ```
 53 | ngrok config add-authtoken <AUTH TOKEN>
 54 | ```
 55 | 
 56 | After this, run the following command and it will start listening to the http://localhost:5001 PORT:
 57 | 
 58 | ```
 59 | ngrok http 5001
 60 | ```
 61 | 
 62 | Copy the `https` forwarding URL you get, it will be used in the next step.
 63 | 
 64 | ### 4. Prepare Google Sheets Apps Script
 65 | 
 66 | Now, you just need to copy-paste the following script inside Google Sheets Apps Script:
 67 | 
 68 | ```javascript
 69 | function onOpen() {
 70 |     var ui = SpreadsheetApp.getUi();
 71 |     ui.createMenu('🎉')
 72 |         .addItem("Fetch Ollama Data", "callOllamaAPI")
 73 |         .addToUi();
 74 |   }
 75 |   
 76 |   function callOllamaAPI() {
 77 |     var spreadsheet = SpreadsheetApp.getActiveSpreadsheet();
 78 |     var settingsSheet = spreadsheet.getSheetByName('Settings');
 79 |   
 80 |     // Fetch the settings from Settings Sheet
 81 |     var settingsRange = settingsSheet.getRange(2, 2, 5, 1);
 82 |     var settingsValues = settingsRange.getValues();
 83 |   
 84 |     var startRow = Number(settingsValues[0][0]);
 85 |     var endRow = Number(settingsValues[1][0]);
 86 |     var dataSheet = spreadsheet.getSheetByName(settingsValues[2][0]);
 87 |     var promptColumns = settingsValues[3][0].split(',').map(function(item) { return letterToNum(item.trim()); });
 88 |     var outputColumns = settingsValues[4][0].split(',').map(function(item) { return letterToNum(item.trim()); });
 89 |   
 90 |     for (var i = startRow - 1; i < endRow; i++) {
 91 |       for (var j = 0; j < promptColumns.length; j++) {
 92 |         var promptCell = dataSheet.getRange(i + 1, promptColumns[j]);
 93 |         var finalPrompt = promptCell.getValue();
 94 |   
 95 |         if (!finalPrompt.trim()) {
 96 |           continue;
 97 |         }
 98 |   
 99 |         var outputCell = dataSheet.getRange(i + 1, outputColumns[j]);
100 |         
101 |         if (outputCell.getValue() === '') {
102 |           var ollamaData = {
103 |             content: finalPrompt
104 |           },
105 |           ollamaOptions = {
106 |               method: 'post',
107 |               contentType: 'application/json',
108 |               payload: JSON.stringify(ollamaData)
109 |           };
110 |   
111 |           try {
112 |             var ollamaResponse = UrlFetchApp.fetch(`<TUNNEL>/api/chat`, ollamaOptions);
113 |             var ollamaTextResponse = ollamaResponse.getContentText();
114 |             // Remove the leading and trailing quotation marks from the JSON response and trim any leading/trailing whitespace
115 |             var ollamaOutput = ollamaTextResponse.slice(1, -1).trim();
116 |             // If there's a trailing quotation mark left, remove it
117 |             if (ollamaOutput.endsWith('"')) {
118 |                 ollamaOutput = ollamaOutput.substring(0, ollamaOutput.length - 1);
119 |             }
120 |             // Replace \n with actual new line characters and \" with "
121 |             var formattedOutput = ollamaOutput.replace(/\\n/g, '\n').replace(/\\"/g, '"');
122 |             outputCell.setValue(formattedOutput);
123 |           } catch(e) {
124 |             console.error('Error calling Ollama API: ' + e.toString());
125 |           }
126 |         }
127 |       }  
128 |     }
129 |   }
130 |   
131 | function letterToNum(letter) {
132 | letter = letter.toUpperCase();
133 | var column = 0, length = letter.length;
134 | for (var i = 0; i < length; i++) {
135 |     column += (letter.charCodeAt(i) - 64) * Math.pow(26, length - i - 1);
136 | }
137 | return column;
138 | }
139 | ```
140 | 
141 | Replace the `<TUNNEL>` placeholder with the copied `ngrok` URL.
142 | 
143 | Save the code and run the script, you may need to authenticate for the very first time.
144 | 
145 | And just like that, you should start seeing your Google Sheets getting outputs from local LLMs running on your computer.
146 | 
147 | However, if you need more information, [this blog post](https://untalkedseo.com/locally-running-llms-in-google-sheets/) talks about the subject in even more detail.
148 | 


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/app.py:
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 1 | from flask import Flask, request, jsonify
 2 | import ollama
 3 | 
 4 | app = Flask(__name__)
 5 | 
 6 | @app.route('/api/chat', methods=['POST'])
 7 | def chat():
 8 |     data = request.json
 9 |     response = ollama.chat(model='mistral', messages=[{'role': 'user', 'content': data['content']}])
10 |     return jsonify(response['message']['content'])
11 | 
12 | if __name__ == '__main__':
13 |     app.run(debug=True, port=5001)
14 | 


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/script.js:
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 1 | function onOpen() {
 2 |     var ui = SpreadsheetApp.getUi();
 3 |     ui.createMenu('🎉')
 4 |         .addItem("Fetch Ollama Data", "callOllamaAPI")
 5 |         .addToUi();
 6 |   }
 7 |   
 8 |   function callOllamaAPI() {
 9 |     var spreadsheet = SpreadsheetApp.getActiveSpreadsheet();
10 |     var settingsSheet = spreadsheet.getSheetByName('Settings');
11 |   
12 |     // Fetch the settings from Settings Sheet
13 |     var settingsRange = settingsSheet.getRange(2, 2, 5, 1);
14 |     var settingsValues = settingsRange.getValues();
15 |   
16 |     var startRow = Number(settingsValues[0][0]);
17 |     var endRow = Number(settingsValues[1][0]);
18 |     var dataSheet = spreadsheet.getSheetByName(settingsValues[2][0]);
19 |     var promptColumns = settingsValues[3][0].split(',').map(function(item) { return letterToNum(item.trim()); });
20 |     var outputColumns = settingsValues[4][0].split(',').map(function(item) { return letterToNum(item.trim()); });
21 |   
22 |     for (var i = startRow - 1; i < endRow; i++) {
23 |       for (var j = 0; j < promptColumns.length; j++) {
24 |         var promptCell = dataSheet.getRange(i + 1, promptColumns[j]);
25 |         var finalPrompt = promptCell.getValue();
26 |   
27 |         if (!finalPrompt.trim()) {
28 |           continue;
29 |         }
30 |   
31 |         var outputCell = dataSheet.getRange(i + 1, outputColumns[j]);
32 |         
33 |         if (outputCell.getValue() === '') {
34 |           var ollamaData = {
35 |             content: finalPrompt
36 |           },
37 |           ollamaOptions = {
38 |               method: 'post',
39 |               contentType: 'application/json',
40 |               payload: JSON.stringify(ollamaData)
41 |           };
42 |   
43 |           try {
44 |             var ollamaResponse = UrlFetchApp.fetch(`<TUNNEL>/api/chat`, ollamaOptions);
45 |             var ollamaTextResponse = ollamaResponse.getContentText();
46 |             // Remove the leading and trailing quotation marks from the JSON response and trim any leading/trailing whitespace
47 |             var ollamaOutput = ollamaTextResponse.slice(1, -1).trim();
48 |             // If there's a trailing quotation mark left, remove it
49 |             if (ollamaOutput.endsWith('"')) {
50 |                 ollamaOutput = ollamaOutput.substring(0, ollamaOutput.length - 1);
51 |             }
52 |             // Replace \n with actual new line characters and \" with "
53 |             var formattedOutput = ollamaOutput.replace(/\\n/g, '\n').replace(/\\"/g, '"');
54 |             outputCell.setValue(formattedOutput);
55 |           } catch(e) {
56 |             console.error('Error calling Ollama API: ' + e.toString());
57 |           }
58 |         }
59 |       }  
60 |     }
61 |   }
62 |   
63 |   function letterToNum(letter) {
64 |     letter = letter.toUpperCase();
65 |     var column = 0, length = letter.length;
66 |     for (var i = 0; i < length; i++) {
67 |       column += (letter.charCodeAt(i) - 64) * Math.pow(26, length - i - 1);
68 |     }
69 |     return column;
70 |   }
71 |   


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