getcellm/cellm

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[![CI](https://github.com/getcellm/cellm/actions/workflows/ci.yml/badge.svg)](https://github.com/getcellm/cellm/actions/workflows/ci.yml) # Cellm Use AI in Excel formulas to run your prompt on thousands of rows of data in minutes. [Website](https://www.getcellm.com) | [Documentation](https://docs.getcellm.com) | [Releases](https://github.com/getcellm/cellm/releases) | ⭐ **Star this repo** to help others discover Cellm! ## What is 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. ## Why use Cellm? - Make quick work of data cleaning, classification, and extraction tasks. - Enable marketing, finance, sales, operations and other teams to automate everyday tasks without depending on developers. - Immediately free yourself and your team from repetitive manual work with the spreadsheet they already master. - Bypass lengthy rollouts of specialized AI apps. Your team already have Excel on their computers. - Create your own web scraper via MCP servers. Monitor your competitor's blogs, prices, and social media everyday before your daily 09:00 meeting. > “I love feeding data to ChatGPT, one copy-paste at a time” > — no one who’s run the same prompt 5 times ## Example 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. ## Quick start ### Requirements - Windows 10 or higher - [.NET 9.0 Runtime](https://dotnet.microsoft.com/en-us/download/dotnet/9.0) - [Excel 2010 or higher (desktop app)](https://www.microsoft.com/en-us/microsoft-365/excel) ### Install 1. Go to the [Release page](https://github.com/getcellm/cellm/releases) and download `Cellm-AddIn-Release-x64.msi`. 2. Run the installer. 3. 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](https://ollama.com/). Download and install [Ollama](https://ollama.com/) 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. ## Pricing - **Free tier:** Use local models or your own API keys - **Paid tiers:** Available for teams needing managed infrastructure and EU data processing - [View pricing →](https://getcellm.com/pricing) ## Basic usage 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](https://docs.getcellm.com). ## Models Cellm supports: - Hosted models from Azure, AWS, Google, Anthropic, OpenAI, Mistral, and others - Local models via Ollama, Llamafiles, or vLLM For detailed information about configuring different models, see our documentation on [local models](https://docs.getcellm.com/models/local-models) and [hosted models](https://docs.getcellm.com/models/hosted-models). ## Use cases Cellm is useful for repetitive tasks on both structured and unstructured data: 1. **Competitive monitoring:** Track competitor pricing across 50 websites daily 2. **Multi-language support:** Analyze customer feedback in 10+ languages 3. **Text classification:** Categorize survey responses, support tickets, etc. 4. **Model comparison:** Compare results from different LLMs side by side 5. **Data cleaning:** Standardize names, fix formatting issues 6. **Content summarization:** Condense articles, papers, or reports 7. **Entity recognition:** Pull out names, locations, dates from text For more use cases and examples, see our [Prompting Guide](https://docs.getcellm.com/usage/prompting). ## Development For build instructions with Visual Studio or command line, see our [development guide](https://docs.getcellm.com/get-started/development). ## Why did we make Cellm? 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. ## Telemetry To help us improve Cellm, we collect limited, anonymous telemetry data: - **Crash reports:** To help us fix bugs. - **Prompts:** To help us understand usage patterns. For example, if you use `=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](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`: ```json { "SentryConfiguration": { "IsEnabled": false } } ``` ## License Fair Core License, Version 1.0, Apache 2.0 Future License

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软件开发工程师

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sentry-triage

软件开发工程师

Use when triaging production bugs from Sentry, debugging unresolved issues, or when asked to check Sentry for errors

原文语言：英语

2026-04-13

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