Use AI in Excel formulas to run your prompt on thousands of rows of data in minutes.
Website | Documentation | Releases | ⭐ Star this repo to help others discover Cellm!
Cellm is an Excel extension that lets you use Large Language Models (LLMs) like ChatGPT in cell formulas. Cellm's =PROMPT() function outputs AI responses to a range of text, similar to how Excel's =SUM() function outputs the sum of a range of numbers.
For example, you can write =PROMPT("Extract all person names mentioned in the text.", A1) in a cell's formula and drag the cell to apply the prompt to many rows. Cellm is useful when you want to use AI for repetitive tasks that would normally require copy-pasting data in and out of a chat window many times.
“I love feeding data to ChatGPT, one copy-paste at a time” — no one who’s run the same prompt 5 times
Say you need to track your international competitors, but their websites are in different languages. Visiting each one, finding the latest update, and plugging it into a translation tool totally sucks. Instead, let Cellm do the manual work for you:
https://github.com/user-attachments/assets/8967f557-50b8-4e39-80e8-86a1246c5a42
This example uses news websites. We give Cellm a list of URLs and write a simple prompt that asks Cellm to grab the top headline from each one. Then, in the next columns, we ask the model to translate the headline, identify its original language, and even sort it into a category like "Politics" or "Business".
With a drag to autofill, Cellm visits every site, pulls your data and organizes it for you. What would have taken perhaps an hour of manual work is now done in seconds. Imagine what you could prepare every day before your daily 09:00 meeting.
Just remember that the models do make mistakes at times. They might misunderstand a headline or assign the wrong category. It is your responsibility to validate that the results are accurate enough for your use case.
Go to the Release page and download Cellm-AddIn-Release-x64.msi.
Run the installer.
Open Excel, choose a provider from the drop-down menu in the Cellm tab, and plug in your API key.
You can also use local models, e.g., via Ollama. Download and install Ollama and open Excel. Choose the Ollama provider from the drop-down menu in the Cellm tab and select a model. Cellm will prompt you to download it automatically. Alternatively, open Windows Terminal (open start menu, type Windows Terminal, and click OK), type ollama pull gemma4:e4b, and wait for the download to finish.
Select a cell and type =PROMPT("What model are you and who made you?"). For Gemma 4 E4B, it will tell you that it's called "Gemma 4" and made by Google DeepMind.
You can also use cell references. For example, copy a news article into cell A1 and type in cell B1: =PROMPT("Extract all person names mentioned in the text", A1). You can reference many cells using standard Excel notation, e.g. =PROMPT("Extract all person names in the cells", A1:F10) or reference multiple separate ranges, e.g. =PROMPT("Compare these datasets", A1:B10, D1:E10)
For more advanced usage, including function calling and configuration, see our documentation.
Cellm supports:
For detailed information about configuring different models, see our documentation on local models and hosted models.
Cellm is useful for repetitive tasks on both structured and unstructured data:
For more use cases and examples, see our Prompting Guide.
For build instructions with Visual Studio or command line, see our development guide.
A friend was writing a systematic review paper and had to compare 7,500 papers against inclusion/exclusion criteria to identify papers relevant to her research. We thought this was a great use case for LLMs but quickly realized that individually copying papers in and out of chat windows was a total pain. This sparked the idea to make an AI tool to automate repetitive tasks for people who would rather avoid programming.
A quick prototype enabled her to quickly import a CSV file into Excel and classify all 7,500 papers with a prompt like "If the paper studies diabetic neuropathy and stroke, return INCLUDE otherwise return EXCLUDE". So we decided to develop it further.
We think Cellm is really cool because it enables everyone to automate tasks with AI to a level that was previously available only to programmers.
To help us improve Cellm, we collect limited, anonymous telemetry data:
=PROMPT("Extract person names", A1:B2), we capture the text "Extract person names" and prompt options. The prompt options are things like the model you use and the temperature setting. We do not capture the data in cells A1:B2.We do not collect any data from your spreadsheet and we have no way of associating your prompts with you. You can see for yourself at src/Cellm/Models/Behaviors/SentryBehavior.cs.
You can disable telemetry at any time by adding the following contents to the appsettings.Local.json file in installation directory C:\Users\{username}\AppData\Roaming\Cellm:
{
"SentryConfiguration": {
"IsEnabled": false
}
}
Fair Core License, Version 1.0, Apache 2.0 Future License
3,482 followers · starred Jan 2025
323 followers · starred Jul 2026
197 followers · starred Jan 2026
158 followers · starred Jan 2025
Use AI in Excel formulas to run your prompt on thousands of rows of data in minutes.
Website | Documentation | Releases | ⭐ Star this repo to help others discover Cellm!
Cellm is an Excel extension that lets you use Large Language Models (LLMs) like ChatGPT in cell formulas. Cellm's =PROMPT() function outputs AI responses to a range of text, similar to how Excel's =SUM() function outputs the sum of a range of numbers.
For example, you can write =PROMPT("Extract all person names mentioned in the text.", A1) in a cell's formula and drag the cell to apply the prompt to many rows. Cellm is useful when you want to use AI for repetitive tasks that would normally require copy-pasting data in and out of a chat window many times.
“I love feeding data to ChatGPT, one copy-paste at a time” — no one who’s run the same prompt 5 times
Say you need to track your international competitors, but their websites are in different languages. Visiting each one, finding the latest update, and plugging it into a translation tool totally sucks. Instead, let Cellm do the manual work for you:
https://github.com/user-attachments/assets/8967f557-50b8-4e39-80e8-86a1246c5a42
This example uses news websites. We give Cellm a list of URLs and write a simple prompt that asks Cellm to grab the top headline from each one. Then, in the next columns, we ask the model to translate the headline, identify its original language, and even sort it into a category like "Politics" or "Business".
With a drag to autofill, Cellm visits every site, pulls your data and organizes it for you. What would have taken perhaps an hour of manual work is now done in seconds. Imagine what you could prepare every day before your daily 09:00 meeting.
Just remember that the models do make mistakes at times. They might misunderstand a headline or assign the wrong category. It is your responsibility to validate that the results are accurate enough for your use case.
Go to the Release page and download Cellm-AddIn-Release-x64.msi.
Run the installer.
Open Excel, choose a provider from the drop-down menu in the Cellm tab, and plug in your API key.
You can also use local models, e.g., via Ollama. Download and install Ollama and open Excel. Choose the Ollama provider from the drop-down menu in the Cellm tab and select a model. Cellm will prompt you to download it automatically. Alternatively, open Windows Terminal (open start menu, type Windows Terminal, and click OK), type ollama pull gemma4:e4b, and wait for the download to finish.
Select a cell and type =PROMPT("What model are you and who made you?"). For Gemma 4 E4B, it will tell you that it's called "Gemma 4" and made by Google DeepMind.
You can also use cell references. For example, copy a news article into cell A1 and type in cell B1: =PROMPT("Extract all person names mentioned in the text", A1). You can reference many cells using standard Excel notation, e.g. =PROMPT("Extract all person names in the cells", A1:F10) or reference multiple separate ranges, e.g. =PROMPT("Compare these datasets", A1:B10, D1:E10)
For more advanced usage, including function calling and configuration, see our documentation.
Cellm supports:
For detailed information about configuring different models, see our documentation on local models and hosted models.
Cellm is useful for repetitive tasks on both structured and unstructured data:
For more use cases and examples, see our Prompting Guide.
For build instructions with Visual Studio or command line, see our development guide.
A friend was writing a systematic review paper and had to compare 7,500 papers against inclusion/exclusion criteria to identify papers relevant to her research. We thought this was a great use case for LLMs but quickly realized that individually copying papers in and out of chat windows was a total pain. This sparked the idea to make an AI tool to automate repetitive tasks for people who would rather avoid programming.
A quick prototype enabled her to quickly import a CSV file into Excel and classify all 7,500 papers with a prompt like "If the paper studies diabetic neuropathy and stroke, return INCLUDE otherwise return EXCLUDE". So we decided to develop it further.
We think Cellm is really cool because it enables everyone to automate tasks with AI to a level that was previously available only to programmers.
To help us improve Cellm, we collect limited, anonymous telemetry data:
=PROMPT("Extract person names", A1:B2), we capture the text "Extract person names" and prompt options. The prompt options are things like the model you use and the temperature setting. We do not capture the data in cells A1:B2.We do not collect any data from your spreadsheet and we have no way of associating your prompts with you. You can see for yourself at src/Cellm/Models/Behaviors/SentryBehavior.cs.
You can disable telemetry at any time by adding the following contents to the appsettings.Local.json file in installation directory C:\Users\{username}\AppData\Roaming\Cellm:
{
"SentryConfiguration": {
"IsEnabled": false
}
}
Fair Core License, Version 1.0, Apache 2.0 Future License
3,482 followers · starred Jan 2025
323 followers · starred Jul 2026
197 followers · starred Jan 2026
158 followers · starred Jan 2025