> ## Documentation Index > Fetch the complete documentation index at: https://docs.anyformat.ai/llms.txt > Use this file to discover all available pages before exploring further. # Extract > Pulls the fields you define out of the parsed document, each with a value, a confidence and the evidence it came from. **Extract** reads what [Parse](/guides/nodes/parse) produced and fills in a schema: the fields you name, typed, with a confidence score and the source text for each. It is the node most workflows exist for. It lives in the **Intelligence** section of the Studio palette. The one thing an Extract node needs is its **schema**: the list of fields to pull out. Everything else is optional. The **tier** (`mode`) sets how much work to spend per page. ## The node ```json API theme={null} { "id": "extract_1", "type": "extract", "extraction_schema": { "fields": [ { "name": "invoice_number", "description": "The unique invoice identifier", "data_type": "string" }, { "name": "total_amount", "description": "Total invoice amount", "data_type": "float" }, { "name": "issue_date", "description": "Date when the invoice was issued", "data_type": "date" } ] } } ``` ```python Python theme={null} import os from anyformat.sdk import Client from anyformat.workflow import Schema client = Client(api_key=os.environ["ANYFORMAT_API_KEY"]) workflow = ( client.workflow("Invoice Processing") .parse() .extract([ Schema.string("invoice_number", "The unique invoice identifier"), Schema.float("total_amount", "Total invoice amount"), Schema.date("issue_date", "Date when the invoice was issued"), ]) .create() ) ``` ```typescript TypeScript theme={null} import { Anyformat, Schema } from "@anyformat/sdk"; const af = new Anyformat({ apiKey: process.env.ANYFORMAT_API_KEY! }); const workflow = await af .workflow("Invoice Processing") .parse() .extract([ Schema.string("invoice_number", "The unique invoice identifier"), Schema.float("total_amount", "Total invoice amount"), Schema.date("issue_date", "Date when the invoice was issued"), ]) .create(); ``` Each field has a name, a description the model reads, and a type. The types (`string`, `float`, `date`, `enum`, `object` and the rest) are on [Field types](/concepts/field-types). How to write a schema that extracts well is on [Schemas](/concepts/schemas). The same node on the agentic tier, with a [Smart lookup](/guides/nodes/smart-lookup) field that resolves the supplier name against a reference CSV: ```json API theme={null} { "id": "extract_1", "type": "extract", "mode": "agentic", "extraction_schema": { "fields": [ { "name": "supplier_name", "description": "Supplier name as printed", "data_type": "string" }, { "name": "supplier_code", "description": "Internal supplier code", "data_type": "string", "source": "smart_lookup" } ] }, "lookup_file_uploads": [{ "filename": "suppliers.csv", "content": "" }], "lookup_suggestion": "Match supplier names ignoring legal suffixes like GmbH or Ltd" } ``` ```python Python theme={null} client.workflow("Invoices with supplier codes").parse().extract( [ Schema.string("supplier_name", "Supplier name as printed"), Schema.string("supplier_code", "Internal supplier code", source="smart_lookup"), ], lookup_files=["suppliers.csv"], lookup_suggestion="Match supplier names ignoring legal suffixes like GmbH or Ltd", ) ``` ```typescript TypeScript theme={null} af.workflow("Invoices with supplier codes").parse().extract( [ Schema.string("supplier_name", "Supplier name as printed"), Schema.string("supplier_code", "Internal supplier code", { source: "smart_lookup" }), ], { mode: "agentic", lookupFiles: ["suppliers.csv"], lookupSuggestion: "Match supplier names ignoring legal suffixes like GmbH or Ltd", }, ) ``` The SDKs read each path in `lookup_files` from disk and send it as `lookup_file_uploads`. The API call sends the file content inline, base64-encoded. The Python SDK's `extract()` does not take `mode`, `use_images` or `lookup_reasoning_effort` yet. Set them in the API JSON, in Studio, or from the TypeScript SDK. A workflow can hold several Extract nodes. After a [Classify](/guides/nodes/classify) or [Split](/guides/nodes/split) node, each Extract sits on one branch and gets its own schema. See those pages for the `branch` argument. ## In Studio Click the Extract node on the canvas to open its panel. The **Schema** tab holds the fields. The **Config** tab holds the tier cards, the **Use Images** switch, and the **Lookup files**, **Lookup suggestion** and **Lookup matching effort** controls. Configuring the Extract node in Studio The **Config** tab holds the tier, **Use Images**, the lookup files and matcher settings, and the per-field **Lookup** toggles. Smart lookup settings on the Extract node ## Tiers | Tier | `mode` | What it does | When to use it | Credits / page | | --------------- | ---------- | -------------------------------------------------------------------------------------- | ---------------------------------------------------------------- | -------------- | | **Fast** (Beta) | `lite` | Standard extraction on a faster, cheaper model. | Simple documents at volume. Quality may vary on complex layouts. | 17 | | **Standard** | `standard` | Single-pass extraction. The default. | Most documents and layouts. Start here. | 35 | | **Agentic** | `agentic` | Multi-step extraction that maps every table to the schema and reasons across sections. | Dense or cross-page tables, values spread over several sections. | 150 | Start on Standard. Move down to Fast where it holds up, and up to Agentic only where Standard misses rows or mixes up columns. ## Options `extraction_schema` is required. Every other field is optional. Omit a field and the default applies. | Field | Type | Default | What it does | | ------------------------- | ---------------------------------------- | ---------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `extraction_schema` | object | required | `{ "fields": [...] }`. At least one field. Each field carries `name`, `description`, `data_type`, and optionally `source` and `persistent_id`. See [Field types](/concepts/field-types). | | `mode` | `standard` \| `agentic` \| `lite` | `standard` | The tier. `lite` is shown as **Fast** in the app. | | `use_images` | boolean | `false` | Send each PDF page's rendered image alongside its parsed text, so the model can read layout the text missed. Adds vision cost on every page. Standard and Fast only; no effect on Agentic or on non-PDF sources. | | `lookup_file_uploads` | array of `{ filename, content }` | `[]` | Reference files for [Smart lookup](/guides/nodes/smart-lookup), sent inline with `content` base64-encoded. Each one is uploaded and its URI is appended to `lookup_files`. Create-input only: it is not stored on the node. | | `lookup_files` | array of string | `[]` | URIs of the reference files already stored on the node. Read this back from `GET`; write `lookup_file_uploads` to add files. | | `lookup_suggestion` | string | `null` | Free-form hint shown to the lookup matcher, for example "Match supplier names ignoring legal suffixes like GmbH or Ltd". Applies to every lookup field in the node. | | `lookup_reasoning_effort` | `minimal` \| `low` \| `medium` \| `high` | `null` | How hard the lookup matcher works on noisy or inexact keys. `null` is the model default. Higher effort improves match reliability at higher latency and cost. Only used when the node has at least one lookup field. | A field's `source` decides where its value comes from: `extraction` (the document, the default), `smart_lookup` (the reference file, always) or `lookup_if_missing` (the document first, the reference file when extraction left it blank). The schema the API accepts is generated from the same source: [Extract node schema](/api-reference-v3/node-schemas#extract). ## What it returns Extract fills the `extractions` section of the [run results](/concepts/runs-and-results). A workflow with one Extract and no Split returns one entry, with `split_name` and `partition` set to `null`: ```json theme={null} "extractions": [ { "split_name": null, "partition": null, "fields": { "invoice_number": { "value": "INV-2024-0847", "value_override": null, "verification_status": "not_verified", "confidence": 97.0, "evidence": [{ "text": "Invoice #INV-2024-0847", "page_number": 1 }] }, "total_amount": { "value": "4087.50", "value_override": null, "verification_status": "not_verified", "confidence": 96.0, "evidence": [{ "text": "Total: $4,087.50", "page_number": 2 }] } } } ] ``` `fields` is keyed by field name. Each value carries `value` (a string on the wire, whatever the field's `data_type`; `null` when nothing was found), `value_override` (a human correction from review, or `null`), `verification_status`, `confidence` on a 0 to 100 scale, and `evidence`: the source snippets and the page each came from. **Value types on the wire.** Every `value` is a string or `null`, so parse it by the field's `data_type` on your side: * A `boolean` field returns the string `"True"` or `"False"`. * A `multi_select` field returns one comma-separated string, for example `"a, b, c"`, not a list. * A field the model could not find returns `{ "value": null, "value_override": null, "verification_status": "not_verified", "confidence": null, "evidence": [] }`. * An `object` field returns a list of rows. Each row is a dict from nested field name to the same `{ value, value_override, verification_status, confidence, evidence }` shape. After a Split node, `extractions` holds one entry per split and partition. See [Split](/guides/nodes/split#what-it-returns). ## Connects to | Direction | Nodes | | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- | | Fed by | [Parse](/guides/nodes/parse), [Classify](/guides/nodes/classify), [Split](/guides/nodes/split) | | Feeds | [Validate](/guides/nodes/validate), [If/Else](/guides/nodes/if-else), [Slack alert](/guides/nodes/slack-alert), [Knowledge](/guides/nodes/knowledge) | An Extract node has one outgoing edge at most. Add a Validate node to check its values, or an If/Else node to branch on them. ## Billing Billed per page at the tier's rate (table above). A node with at least one lookup field adds 75 credits per page for Smart Lookup. Schema size and field count do not change the price. Full price list: [How credits work](/concepts/how-credits-work). ## Examples * [Invoice processing](/examples/invoice-processing): the usual Parse to Extract shape, with line items as an object field. * [Resume parsing](/examples/resume-parsing): nested fields and multi-select. * [Contract analysis](/examples/contract-analysis): long documents, dates and enums. * [Bank statement processing](/examples/bank-statement-processing): Split, then one Extract per statement.