What Data for This Category Looks Like
Documents related to residential development marketing mainly come from project on-site sales control ledgers, floor plan design manuals, regional supporting planning documents, competitive product benchmarking analysis reports, offline event execution plans, customer survey summary tables, and similar sources.
Update frequency follows this pattern: weekly updates of core parameters during project preparation, monthly synchronization of sales data after official opening, and temporary updates of marketing materials before event nodes.
Three types of document structures exist:
- Structured CSV/XLSX sales control tables, with fields including building number, unit type, gross floor area, filing unit price, and similar items.
- Semi-structured PDF/Word floor plan manuals, paired with text and image explanations.
- Unstructured marketing copy, event planning documents.
Fields and units are fixed. For example, gross floor area is measured in square meters, total price is measured in ten-thousand yuan units, and unit types are named using room-hall-bath combinations.
Constraints Imposed on Document Parsing and Chunking
Structured ledgers have strong field correlation. Chunking must ensure that information from the same row such as building, unit, and unit price is not split. Otherwise, complete sales information cannot be matched during retrieval.
Document lengths vary significantly. Some documents are just a few pages of floor plan descriptions, while others are dozens of pages of regional planning materials. Fixed chunk lengths cannot adapt to all scenarios.
Many proper nouns are used, such as "luxury building unit", "included area", "floor area ratio". Chunking must retain complete semantic units and avoid interrupting proper expressions.
A large number of documents are uploaded in batches, with high update frequency. The parsing process must support rapid identification of new file field structures to avoid repeated configuration.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_MAX_SIZE | 500 MB | High-definition floor plan atlases and regional planning PDFs for residential development can reach up to 500 MB per file. This value covers most scenarios |
maxChunkSize | 800–1200 characters | Adapts to long paragraphs of regional planning text while retaining complete semantics of short fields such as unit parameters and building information |
chunkOverlap | 100–150 characters | Ensures sufficient contextual overlap between adjacent chunks, preventing unit price and total price fields from being split into different chunks in sales control tables |
PARSE_CSV_USE_HEADER | Enabled | The first row of residential marketing CSV files uses standard field names. Enabling this setting automatically identifies the correspondence between columns and fields |
PARSE_TIMEOUT_SECONDS | 300 seconds | Parsing large regional planning PDFs takes a long time. This value prevents task interruption due to timeout mid-process |
PARSE_ENGINE | minerU (enable as needed) | When connecting to a third-party document parsing engine, specify this value to adapt to parsing requirements for scanned floor plan manuals |
UPLOAD_FILE_BATCH_LIMIT | 50 files per batch | Residential marketing documents are often uploaded in batches. This value balances parsing efficiency and server load |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Errors
- Phenomenon: An error is returned when uploading the same CSV sales control table after upgrading the version, with error code
422. Cause: The default value ofPARSE_CSV_DELIMITERin the new version has changed from comma to tab character. The original CSV uses comma separation, resulting in parsing failure. - Phenomenon: When uploading files directly to the large model in a workflow, the returned result is garbled or missing content. Cause: The system default text parsing switch is not turned off. The large model receives the original binary file without converting it to parsed text content.
- Phenomenon: When calling the create file collection API, specifying PDF parsing parameters does not take effect. Cause: The API parameter name is incorrect. The correct parameter is
pdf_parse_options. Using other names does not meet requirements.
How to Confirm Configuration Is Set Correctly
- Upload a high-definition floor plan PDF under 500 MB, check that the parsing task status is completed, and confirm that the parsed text contains core fields such as building number and unit parameters.
- Upload a test CSV sales control table, check that the parsed chunk content contains complete column names and corresponding values, with no field splitting errors.
- Call the create file collection API, pass the correct
pdf_parse_optionsparameter, and check that the returnedparseConfigfield contains the corresponding configuration content. - Add a file upload node in the workflow, configure to directly pass the parsed text to the large model, and check that the large model output contains complete semantic content of the document.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.