> ## Knowledge Base Index > Fetch the complete knowledge base index at: https://help.lido.app/sitemap.xml > Use this file to discover available pages before exploring further. > Pure-Markdown content can be obtained by appending a '.md' suffix to the content URLs listed in the sitemap (without the trailing slash). # AI columns and formulas # AI columns and formulas Lido lets you call large language models directly from spreadsheet formulas. Use this to enrich rows with AI output (summaries, classifications, translations, structured extraction) without leaving the sheet. This article covers every AI formula, when to use which, and how to set up credentials. --- ## Which AI formula should I use? | If you want to… | Use… | | --- | --- | | Send a text prompt to OpenAI and write the response to a cell | `GPT` | | Analyze an image or PDF with OpenAI | `GPTVISION` | | Send a text prompt (with optional file) to Anthropic | `CLAUDE` | | Send a text prompt (with optional file) to Google Gemini | `GEMINI` | | Send a text prompt (with optional file) to AWS Bedrock | `BEDROCK` | | Have GPT analyze a URL's content | `GPTURL` | | Extract structured rows from text into a table | `EXTRACTTOTABLE` | | Extract data from a file into a single row | `EXTRACTFROMFILETOROW` | For document extraction at scale, use the **Data Extractor** (UI, workflow node, or API) instead — it's tuned for that and reuses one configuration across surfaces. --- ## Before you start You need a credential for the AI provider you want to call: - **OpenAI** (`GPT`, `GPTVISION`, `GPTURL`) — get an OpenAI API key, add it as a credential in workspace settings. - **Anthropic** (`CLAUDE`) — get an Anthropic API key. - **Google** (`GEMINI`) — get a Google API key with Generative AI access. - **AWS Bedrock** (`BEDROCK`) — get AWS access keys for an account with Bedrock model access. `EXTRACTTOTABLE` and `EXTRACTFROMFILETOROW` accept any AI credential — pick one based on which provider you want to use. --- ## Calling a single model ### `GPT` — OpenAI text generation ``` =GPT(credential, prompts, output_ref) =GPT(credential, prompts, output_ref, model, max_tokens, response_format, temperature, usage_output, tools) ``` `prompts` can be a string or an array of messages. `output_ref` is the cell to write the response into. `model` defaults to a current GPT model; specify one like `"gpt-4o"` to pin it. ### `GPTVISION` — analyze images and PDFs ``` =GPTVISION(files, credential, prompt, output_ref) =GPTVISION(files, credential, prompt, output_ref, page_ranges, model, max_tokens, response_format, image_detail, usage_output) ``` `files` is one or more file URLs. Use `page_ranges` like `"1-3"` to limit which PDF pages get analyzed. ### `CLAUDE` — Anthropic ``` =CLAUDE(credential, prompt, output_ref) =CLAUDE(credential, prompt, output_ref, model, max_tokens, system_message, files, page_ranges, usage_output) ``` `CLAUDE` accepts files in the same call. Useful when you want a single model to read a document and reason about it. ### `GEMINI` — Google ``` =GEMINI(credential, files, prompt, output_ref) =GEMINI(credential, files, prompt, output_ref, page_ranges, model, max_tokens, response_format, response_schema, usage_output) ``` `response_schema` accepts a JSON schema for structured output — useful when you want the model to return JSON in a fixed shape. ### `BEDROCK` — AWS ``` =BEDROCK(credential, prompt, output_ref) =BEDROCK(credential, prompt, output_ref, model, max_tokens, system_message, files, page_ranges, usage_output) ``` Same shape as `CLAUDE`. Use when your security or compliance setup requires AI inference inside AWS. ### `GPTURL` — analyze a URL ``` =GPTURL(credential, url, prompt, output_ref) =GPTURL(credential, url, prompt, output_ref, model, max_tokens) ``` Fetches the URL's content and runs your prompt against it. Good for "summarize this article" workflows. --- ## Extraction formulas ### `EXTRACTTOTABLE` — text → structured table ``` =EXTRACTTOTABLE(credential, input_content, output_table_ref) =EXTRACTTOTABLE(credential, input_content, output_table_ref, prompt, model, max_tokens, usage_output) ``` Send unstructured text (an email body, an article, a transcript) and get back a structured table. Use the optional `prompt` to specify what columns to extract. ### `EXTRACTFROMFILETOROW` — file → one row ``` =EXTRACTFROMFILETOROW(credential, file_source, output_ref) =EXTRACTFROMFILETOROW(credential, file_source, output_ref, prompt, model, max_tokens, usage_output) ``` Send a file URL and get back a single row of structured data. Use the optional `prompt` to describe the fields. --- ## Patterns ### AI per row in a table Add a computed column to a table: ``` =GPT("openai-cred", "Summarize in one sentence: " & Articles[@Body], Articles[@Summary]) ``` Every row gets a one-sentence summary. Lido evaluates it once per row. ### Classify and route ``` =GPT("openai-cred", "Classify this support ticket as one of: Billing, Bug, Feature Request, Other. Return only the category. Ticket: " & Tickets[@Body], Tickets[@Category]) ``` Then use the `Category` column to filter, sort, or trigger different downstream actions per category. ### Structured JSON output For machine-readable output, set `response_format` to `"json"` and ask for a specific shape: ``` =GPT("openai-cred", "Return JSON with keys 'sentiment' and 'urgency' (each 1-5). Text: " & Reviews[@Text], Reviews[@Analysis], "gpt-4o", 200, "json") ``` --- ## Tips - **Pin the model** when you care about consistency. The default model can change as providers update. - **Use `usage_output`** to track token consumption and cost per row. - **Cache when you can.** AI calls cost money and time. If the prompt and inputs haven't changed, the result hasn't either — reuse it. - **For document extraction at scale, use the Data Extractor**, not these formulas. The Data Extractor is tuned for that job and lets you share one configuration across the spreadsheet UI, workflows, and the API. - **Add credentials before writing formulas.** The credential ID is required. --- ## Common mistakes - **No credential ID.** Every AI formula starts with the credential ID. Add the credential in your workspace settings first; copy the ID into the formula. - **Putting an AI formula in a column where it'll re-run on every refresh.** AI calls cost money. Either put the formula in a plain column where the user triggers it, or accept the cost. - **Asking for "JSON" without `response_format: "json"`.** The model may return prose with JSON inside. Set `response_format` to lock the output shape. - **Hitting rate limits with big tables.** Every AI provider enforces rate limits. For large tables, break the work into batches with `LIMIT` or use a workflow with the Prompt AI node and concurrency settings. - **Reaching for `GPT` or `CLAUDE` when you need extraction.** The Data Extractor handles file-to-rows extraction far better. See **Extract data from PDFs and documents**. --- ## Related articles - Tables: how columns work - Actions: how spreadsheet automation works - Extract data from PDFs and documents - Expressions and the formula bar - Build your first workflow (Prompt AI node)