# Apify Tender Attachment Parser (`leonyu/apify-tender-attachment-parser`) Actor Parse SAM.gov and TED tender attachments (PDF, DOCX, XLSX, ZIP) into structured JSON with page-level citations and OCR for scanned files. - **URL**: https://apify.com/leonyu/apify-tender-attachment-parser.md - **Developed by:** [Leon Yu](https://apify.com/leonyu) (community) - **Categories:** Lead generation, Automation - **Security:** Limited permissions - **Stats:** 2 total users, 1 monthly users, 90.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $25.00 / 1,000 attachment parseds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ### What does Tender Attachment Parser do? **Tender Attachment Parser** turns public-procurement notice attachments into structured JSON. It reads **SAM.gov** opportunities through the official [Get Opportunities API](https://open.gsa.gov/api/get-opportunities-public-api/), **TED** notices through the anonymous [TED Search API](https://docs.ted.europa.eu/api/latest/index.html), or **direct file URLs** you already have. It downloads PDF, DOCX, XLSX, legacy DOC, and ZIP files, extracts text with page numbers, and OCRs scanned pages with Tesseract. Key fields, requirements, evaluation criteria, submission instructions, dates, and FAR/DFARS citations each include provenance: `{file, page, snippet}`. It does not log into SAM.gov or TED, and it does not bypass anti-bot challenges. Personal contact details are removed from the output. ### Why use Tender Attachment Parser? Small businesses bidding on US federal and EU tenders, and the consultants who support them, need the attachments, not just the notice list. List scrapers stop at the title and deadline. This Actor reads the files those notices point at. - Combine SAM.gov notice IDs or filters, a TED query, and your own file URLs in one run. - OCR for image-only pages, with the page marked `ocr` so you can tell it from digital text. - Every extracted value cites the file and page it came from. - A bad attachment is recorded as `status: "error"` and the run continues. - No paid LLM. Extraction is deterministic. There is no hidden model bill. - The document pipeline lives in `docpipe/` and does not import the Apify SDK, so a later datasheet Actor can reuse it. See [docpipe/README.md](docpipe/README.md). On Apify you can schedule runs, call the Actor from the API, and download the dataset as JSON, CSV, Excel, or HTML. ### What data can Tender Attachment Parser extract? Each dataset item is one notice. Attachment detail is nested on that item. | Field | What it is | | --- | --- | | `title`, `solicitationNumber`, `buyerName` | Title, solicitation number, agency or buyer | | `naics`, `cpv`, `naicsOrCpv` | NAICS and CPV codes | | `setAside` | Set-aside code or description | | `placeOfPerformance` | City, state, postal code, country. Street addresses from the API are omitted | | `submissionDeadline`, `qaDeadline`, `siteVisitDates` | Deadlines and site-visit lines | | `contractType`, `procedureType`, `estimatedValue`, `periodOfPerformance` | Contract and procedure text found by rules or returned by the API | | `fields` | The same values as a list, each with provenance | | `outline` | Section headings and the text under them | | `requirements` | Shall/must statements | | `evaluationCriteria`, `submissionInstructions`, `complianceMatrix` | Lines under those headings | | `farClauses` | FAR `52.xxx-x` and DFARS `252.xxx-xxxx` citations | | `dates` | Dates, with the label from the same line when there is one | | `attachments` | Per-file status, page text, OCR pages, and the same sections | | `status` | `ok`, `partial`, or `error` | Provenance looks like this: ```json {"file": "solicitation.pdf", "page": 1, "snippet": "Solicitation Number: W912QR-26-R-0042"} ``` `page` is null for a value that came from the SAM.gov or TED API rather than a file. DOCX content is reported as page 1. Each XLSX sheet is one page. ### How to parse SAM.gov and TED attachments 1. Open the Actor input. For SAM.gov, paste your own API key from SAM.gov Account Details. TED search does not use a key. 2. Add notice IDs, a TED publication number or expert query, and/or direct `https` file URLs. The three modes can be used together. 3. Leave OCR on if scans are possible. Set **Max notices** and **Max pages** so a wide search stays bounded. 4. Start the run. Set memory to **1024 MB** (the default) and the run timeout to at least **3600 seconds** for a batch. One digital file is much faster; OCR is about half a second per scanned page on a small machine. 5. Open the dataset. The **Notices** view is the summary table. Download JSON when you need provenance and clauses. The API tab runs the same input from your own code. SAM.gov only accepts a posted-date window of one year. If you omit the dates, the Actor uses the last 364 days ending today (UTC). A notice older than that needs an explicit window that still covers at most one year. ### How much will it cost? Pricing is pay per event. Amounts are **not configured yet**. Set them in the Apify Console against the event names below. Do not also enable the built-in `apify-default-dataset-item` event: this Actor already charges its own events and pushes dataset items without `charged_event_name`. Enabling both would bill each notice twice. Placeholder prices, to be replaced when you set Console pricing: | Event | When it is charged | Placeholder price | | --- | --- | --- | | `notice-processed` | A notice was fetched and a record was produced (`ok` or `partial`) | `$0.00` — set in Console | | `attachment-parsed` | One file, or one file inside a ZIP, extracted successfully | `$0.00` — set in Console | Failed downloads, anti-bot responses, and the SAM.gov notice-description text are not attachment charges. The description is still parsed and shown as a synthetic attachment. #### Measured compute Apify bills the **reserved** memory for the whole run, not the process RSS. This Actor reserves **1024 MB** by default (minimum 1024, maximum 8192). Parse timings below were measured on a 2-vCPU dev machine with Python 3.12 and Tesseract 5.3, using the synthetic fixtures in `tests/fixtures/`. Peak RSS includes the Python interpreter. A separate entrypoint run (Python 3.12, Tesseract 5.3) peaked at 165 MB RSS for a 40-page letter-size scan and 511 MB RSS for one 36×48 inch scanned sheet. Office files, including a 5 MB DOCX, an 80,000-row XLSX, and a 15 MB digital PDF, stayed under 200 MB. | Case | Wall time | Peak RSS | | --- | --- | --- | | Digital PDF, 2 pages, OCR off | 0.006 s | 91 MB | | Scanned PDF, 1 page, OCR on | 0.63 s | 120 MB | | Same scanned PDF, OCR off | 0.002 s | 91 MB | | 5 scanned pages, OCR on | 2.5 s | same class of process | OCR of a clean page is about **0.5 s**. A 20-page scan is on the order of **10 s** of parsing, plus download time. Digital PDFs are usually limited by the download, not by parsing. Illustrative compute, if a compute unit is $0.30 per GB-hour (check your plan; this is not a quote): `dollars ≈ 1 GB × seconds / 3600 × 0.30` | Work | Illustrative compute | 3× floor | | --- | --- | --- | | 1 scanned page (0.63 s) | $0.00005 | $0.00015 | | 5 scanned pages (2.5 s) | $0.0002 | $0.0005 | | A 30 s notice, including downloads, at 1 GB | $0.0025 | $0.0075 | Container startup is extra and is not in the table. Price on the value of the JSON as well as this floor. The constants that emit the events are `CHARGE_EVENTS_ENABLED`, `EVENT_NOTICE_PROCESSED` (`notice-processed`), and `EVENT_ATTACHMENT_PARSED` (`attachment-parsed`) in `tender_attachment_parser/charging.py`. ### Input See the input tab for every field. Modes can be combined. At least one of the following is required: - **SAM.gov.** `samApiKey` (secret) plus notice IDs and/or filters: posted dates, NAICS, title keywords, set-aside, notice type, state, solicitation number. The key is sent only to `api.sam.gov` and is redacted from logs. Requests are paced to **one per second**, with backoff on HTTP 429. Daily quota is enforced by SAM.gov and depends on the key's role. - **TED.** `tedNoticeNumbers` and/or `tedQuery` (expert search, for example `buyer-country=IRL AND publication-date>=20261001`). `tedPdfLanguage` defaults to `ENG`. - **Direct URLs.** `attachmentUrls` must be public `http` or `https` links. Literal private and metadata addresses are rejected. Other limits: `maxNotices` (default 10), `maxAttachmentsPerNotice` (5), `maxFileSizeMb` (25), `maxPages` (40), `ocrEnabled` (on), `ocrLanguages` (`eng`, plus `deu`, `fra`, `spa`, `ita` in the image), `outputSections`, `downloadTimeoutSecs` (60), `parseTimeoutSecs` (120). Example input is in [`examples/input.json`](examples/input.json). Replace `PASTE_YOUR_SAM_GOV_KEY` with your own key. Do not commit a real key. ```json { "samNoticeIds": ["5b345bbb7127b91a3ad577b203fc6f68"], "samPostedFrom": "01/01/2026", "samPostedTo": "10/29/2026", "tedNoticeNumbers": ["748773-2026"], "attachmentUrls": ["https://example.com/solicitation.pdf"], "maxNotices": 10, "ocrEnabled": true, "ocrLanguages": ["eng"] } ``` ### Output You can download the dataset as JSON, CSV, Excel, or HTML. The full fixture run is [`examples/output-fixtures.json`](examples/output-fixtures.json) (a digital PDF and the same text as a scanned page). A mocked SAM.gov run, with the contact block removed, is [`examples/sam-mocked-output.json`](examples/sam-mocked-output.json). A live anonymous TED search is [`examples/ted-live-sample.json`](examples/ted-live-sample.json). This excerpt is the digital fixture, with page text left out for length. The file above has the full pages. ```json { "source": "url", "noticeId": "fixture-solicitation.pdf", "status": "ok", "title": "Cloud Hosting and Support Services", "solicitationNumber": "W912QR-26-R-0042", "buyerName": "Department of the Navy", "naicsOrCpv": "541512", "setAside": "Total Small Business Set-Aside (FAR 19.5)", "placeOfPerformance": "Norfolk, VA 23511", "submissionDeadline": "March 15, 2026 2:00 PM Eastern", "qaDeadline": "March 1, 2026 4:00 PM Eastern", "siteVisitDates": "February 20, 2026 10:00 AM at Building 12", "contractType": "Firm-Fixed-Price", "estimatedValue": "$1,250,000", "periodOfPerformance": "12 months plus two 12-month options", "fields": { "solicitationNumber": [ { "value": "W912QR-26-R-0042", "provenance": { "file": "solicitation.pdf", "page": 1, "snippet": "Solicitation Number: W912QR-26-R-0042" } } ] }, "requirements": [ { "text": "C.1 The contractor shall provide a managed cloud hosting environment.", "provenance": { "file": "solicitation.pdf", "page": 1, "snippet": "C.1 The contractor shall provide a managed cloud hosting environment." } } ], "farClauses": [ { "system": "FAR", "clauseId": "52.212-1", "provenance": { "file": "solicitation.pdf", "page": 2, "snippet": "This solicitation incorporates FAR 52.212-1 Instructions to Offerors." } } ] } ``` The scanned fixture in the same file reports `"ocrPages": [1]`. ### Pricing events Events are defined in `tender_attachment_parser/charging.py`. - `notice-processed` — one charge after a SAM.gov, TED, or direct-URL notice is accepted and the record status is `ok` or `partial`. Idempotency key: `notice:{source}:{noticeId}`. - `attachment-parsed` — one charge per successfully parsed file, including each member of a ZIP. Idempotency key: `attachment:{source}:{noticeId}:{index}:{fileName}`. `CHARGE_EVENTS_ENABLED` turns emission on or off without renaming the events. Leave it `True` for a published Actor. Locally, with no pay-per-event price configured, `Actor.charge` logs that the charge was ignored and does not bill. Set `ACTOR_TEST_PAY_PER_EVENT=1` only on your own machine if you want a local charging log; do not set it on the platform. ### docpipe `docpipe` is the reusable package: download, type detection, PDF/DOCX/XLSX/DOC text, OCR, ZIP limits, PII redaction, section and clause segmentation, and provenance. Tender fields (NAICS, set-aside, FAR/DFARS, agency) stay in `tender_attachment_parser`. The public interface is documented in [docpipe/README.md](docpipe/README.md). ```text docpipe/ # no Apify dependency tender_attachment_parser/ # Actor entrypoint, SAM.gov, TED, assembly main.py # python -m tender_attachment_parser charging.py # pay-per-event names .actor/ # actor.json, input, dataset, and output schemas tests/fixtures/ # synthetic PDF, scanned PDF, DOCX, XLSX, ZIP examples/ # real outputs from those fixtures and from TED ``` ### Limitations - Rules miss values that are only inside a wrapped paragraph, a text box, or a table that does not become lines. The baseline is deterministic on purpose. - OCR quality depends on scan resolution and language. The image includes English, German, French, Spanish, and Italian. Other languages need a new Tesseract package in the Dockerfile. - A page is OCR'd when it has no text layer, or when it has fewer than 40 characters and contains an image. Short cover pages with a real text layer are not OCR'd. - DOCX has no reliable page numbers. Legacy DOC needs `antiword` and drops most formatting. - ZIP members are capped (30 files, depth 2, 100 MB uncompressed, compression ratio 100 above 10 KB). Path traversal and encrypted members are rejected. - Encrypted PDFs fail that file only. A parse timeout returns an error for that file; a stuck native parser thread is not killed, but Tesseract itself is limited to 30 seconds per page. - SAM.gov title search matches the notice title, not the attachment body. The API returns the latest active version of a notice. - TED buyer attachments are often not hosted by TED. The Search API returns a website PDF link. As of this writing that host answers with an AWS WAF challenge (HTTP 202, empty body) to this client. The Actor records that error and still returns the Search API fields. It does not try to solve the challenge. See `examples/ted-live-sample.json`. - Redaction removes emails, phone numbers with separators, and personal names that follow a label such as Point of Contact, contact point, or contracting officer. It can miss a name that is not labeled, and it can redact a two-word organization that sits in that label slot. DFARS numbers such as `252.204-7012` are kept. Organization names are kept. - SAM.gov point-of-contact objects (name, email, phone) are never copied into the output. Street addresses on the place of performance are omitted. ### Data sources and legality The Actor calls only official APIs and the file URLs you supply: - SAM.gov: `https://api.sam.gov/opportunities/v2/search` plus the description URL that the API returns. You supply the key. See the [GSA Opportunities API](https://open.gsa.gov/api/get-opportunities-public-api/). - TED: `https://api.ted.europa.eu/v3/notices/search`, which does not require a key. See the [TED API docs](https://docs.ted.europa.eu/api/latest/index.html). Notices are public procurement documents. The Actor does not log into either site and does not scrape pages that sit behind a login or an anti-bot challenge. It does not output personal contact data. Organization names are kept. You are responsible for complying with SAM.gov and TED terms, and with privacy rules if a file still contains personal data the redactor did not recognize. Our Actors are ethical and do not extract private user data such as personal email addresses. They only read public procurement notices and files you explicitly pass in. Personal data is protected by the GDPR in the European Union and by other laws elsewhere. Do not use the output to build a contact list of individuals. If you are unsure whether your use is legitimate, consult your lawyers. Questions and bugs can go to the Actor's Issues tab. ### 中文简介 **招标附件解析器**把美国 SAM.gov 与欧盟 TED 的公开采购公告附件（PDF、DOCX、XLSX、DOC、ZIP）解析成结构化 JSON。扫描件会走 Tesseract OCR。标题、编号、采购人、NAICS/CPV、预留、截止时间、需求条款（shall/must）、评标标准、FAR/DFARS 条款和日期都会带上来源：文件名、页码和原文片段。 不输出个人联系人姓名、邮箱和电话；机构名称会保留。SAM.gov 需要你自己的 API key，TED 搜索接口不需要密钥。规则抽取，默认不调用付费大模型。某个附件失败只会记在该文件的 `status` 和 `error` 里，不会让整次运行中断。 文档解析管线在 `docpipe/`，与招标字段分开，后续做规格书 PDF 解析时可以直接复用。 # Actor input Schema ## `samApiKey` (type: `string`): Your own public API key from SAM.gov Account Details. Required only for SAM.gov notice IDs or filters. The key is sent to api.sam.gov and is not written to the dataset or logs. Example: paste the key from your SAM.gov account. ## `samNoticeIds` (type: `array`): Opportunity notice IDs to fetch. Example: 5b345bbb7127b91a3ad577b203fc6f68. The API searches only a one-year posted-date window. If you omit dates, the Actor uses the last 364 days. ## `samSolicitationNumbers` (type: `array`): Solicitation numbers passed to the solnum parameter. Example: W912QR-26-R-0042. ## `samPostedFrom` (type: `string`): Start of the posted-date window, MM/DD/YYYY or YYYY-MM-DD. Required together with Posted to. The window cannot exceed one year. Example: 01/01/2026. ## `samPostedTo` (type: `string`): End of the posted-date window, MM/DD/YYYY or YYYY-MM-DD. Example: 10/29/2026. ## `samNaics` (type: `array`): NAICS codes for the SAM.gov ncode filter. One code is queried at a time. Example: 541512. ## `samKeywords` (type: `string`): Passed to the SAM.gov title parameter, which matches the notice title rather than the full attachment text. Example: cloud hosting. ## `samSetAside` (type: `string`): Set-aside code or description. Codes include SBA, SBP, 8A, 8AN, HZC, HZS, SDVOSBC, SDVOSBS, WOSB, WOSBSS, EDWOSB, EDWOSBSS, LAS, IEE, ISBEE, BICiv, VSA, and VSS. Example: SBA. ## `samNoticeTypes` (type: `array`): Procurement type codes (ptype). Example: o for solicitation, k for combined synopsis/solicitation. ## `samState` (type: `string`): Two-letter state code for the SAM.gov state filter. Example: VA. ## `tedNoticeNumbers` (type: `array`): TED publication numbers. No API key is required. Example: 722717-2026. ## `tedQuery` (type: `string`): Expert-search query combined with any publication numbers. Example: buyer-country=IRL AND publication-date>=20261001. ## `tedPdfLanguage` (type: `string`): Three-letter TED language code for the notice PDF. The Actor falls back to English, then to the first available language. Example: ENG. ## `attachmentUrls` (type: `array`): Public http(s) URLs of PDF, DOCX, XLSX, DOC, or ZIP files. Can be combined with SAM.gov and TED. The prefilled URL is a public W3C test PDF (not a live tender) so a run can be tried without an API key. ## `maxNotices` (type: `integer`): Maximum notices to return across SAM.gov, TED, and direct URLs, in that order. Example: 10. ## `maxAttachmentsPerNotice` (type: `integer`): Maximum downloaded files per notice. Files inside a ZIP count against the ZIP limits, not this number. Example: 5. ## `maxFileSizeMb` (type: `integer`): Skip a download or ZIP member larger than this. Example: 25. ## `maxPages` (type: `integer`): Stop reading a PDF after this many pages. Example: 40. ## `ocrEnabled` (type: `boolean`): Run Tesseract on pages that have no text layer. Leave this off to save time and memory when you know the files are digital PDFs. ## `ocrLanguages` (type: `array`): Tesseract language codes installed in the Actor image. Example: eng. Add deu for German TED scans. ## `outputSections` (type: `array`): Which extracted sections to include. Key fields, page text, and clause lists are omitted when unchecked. Status and errors are always included. ## `downloadTimeoutSecs` (type: `integer`): Timeout for one HTTP request, including SAM.gov, TED, and attachment downloads. Example: 60. ## `parseTimeoutSecs` (type: `integer`): Timeout for parsing one downloaded file, including OCR of its pages. Example: 120. ## Actor input object example ```json { "tedPdfLanguage": "ENG", "attachmentUrls": [ "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" ], "maxNotices": 10, "maxAttachmentsPerNotice": 5, "maxFileSizeMb": 25, "maxPages": 40, "ocrEnabled": true, "ocrLanguages": [ "eng" ], "outputSections": [ "keyFields", "pageText", "outline", "requirements", "evaluationCriteria", "submissionInstructions", "complianceMatrix", "farClauses", "dates" ], "downloadTimeoutSecs": 60, "parseTimeoutSecs": 120 } ``` # Actor output Schema ## `overview` (type: `string`): Summary of parsed notices. ## `attachments` (type: `string`): How many attachments were parsed for each notice. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "attachmentUrls": [ "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" ] }; // Run the Actor and wait for it to finish const run = await client.actor("leonyu/apify-tender-attachment-parser").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "attachmentUrls": ["https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"] } # Run the Actor and wait for it to finish run = client.actor("leonyu/apify-tender-attachment-parser").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "attachmentUrls": [ "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" ] }' | apify call leonyu/apify-tender-attachment-parser --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,leonyu/apify-tender-attachment-parser" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/yGVdCfsGoBUC75QUQ/builds/T5xU5m8HyorzEGJnK/openapi.json