Document Parsing and Chunking for Refining and Marketing

What the Data for This Category Looks Like

Refining and marketing-related documents primarily come from product specifications, quarterly marketing plans, regional customer price ledgers, compliance notification letters, and industry meeting minutes of refining enterprises. Update frequency varies significantly by content type: product specifications are updated irregularly with capacity adjustments, marketing plans are updated quarterly or when major equipment changes occur, and price ledgers are updated daily with market oil price fluctuations. Most documents are multi-chapter technical descriptions or long table formats. Some are PDFs converted from scanned documents, and some contain multi-level directories and technical parameter appendices. Fields include equipment model, production capacity, raw material density, sulfur content, and similar metrics. Units are mostly tons/year, kg/m³, ppm, and similar standard units.

What Constraints Do These Characteristics Impose on Document Parsing and Chunking?

The characteristics of refining and marketing documents create multiple constraints for parsing and chunking. The structure of long tables and multi-chapter technical descriptions can cause misalignment during splitting by general parsing models. Targeted identification of table areas and chapter boundaries is required. Documents from multiple sources mix technical parameters and marketing language. Content domains must be distinguished to avoid mixed-block arrangement. Daily updated price ledger files have many lines and dense data. The content volume per chunk must be limited to avoid timeouts during the vectorization stage. PDFs converted from scanned documents may have garbled text. An OCR correction step must be added. Technical fields with specific units require retaining the association between parameters and units during chunking to prevent information breakage.

Configuration Settings

Configuration Item	Recommended Setting	Rationale
`UPLOAD_FILE_MAX_SIZE`	`1000 MB`	Refining and marketing documents often contain multi-page technical tables and ledgers. Single files can reach hundreds of MB in size. Raising the upload limit prevents file truncation.
`PARSE_FILE_TIMEOUT_SECONDS`	`900 seconds`	Parsing long ledgers and multi-chapter documents takes significant time. The default timeout is insufficient. Extending to 900 seconds covers the full parsing process.
`chunk_size`	`800–1200 characters`	Refining documents contain dense technical parameters and long explanatory sentences. A chunk length of 800–1200 characters preserves parameter associations and avoids semantic breakage from overly fine splitting.
`enable_table_parse`	`Enabled`	Refining and marketing documents mostly include product specification tables. Enabling table parsing preserves cell structure and data associations, preventing disordered splitting of table content.
`ocr_enable`	`Auto-trigger based on file type`	Scanned format marketing documents require OCR. Non-scanned documents can skip OCR to save parsing resources. Auto-triggering reduces configuration complexity.

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

Symptom: After uploading a refining and marketing document, the data processing status shows empty, and the console returns a 413 Payload Too Large error. Cause: The UPLOAD_FILE_MAX_SIZE configuration was not adjusted. The default upload limit cannot accommodate large files containing multi-page tables, leading to upload truncation and failure to trigger the parsing process.
Symptom: The knowledge base vectorization progress shows no change for an extended period, and a parse_timeout error appears in the logs. Cause: The PARSE_FILE_TIMEOUT_SECONDS configuration was not adjusted. Parsing time for long ledger documents exceeds the default duration, and the process is terminated by the system.
Symptom: Search tests return empty results, or chunked content loses association between technical parameters and units. Cause: enable_table_parse was not enabled. The general parsing model cannot identify specification tables in refining documents, splitting table content into meaningless scattered text and leading to loss of valid information.

How to Confirm Configurations Are Correct

Upload a single refining ledger document larger than 500 MB in size. Check that the upload progress shows no truncation prompts, confirming the UPLOAD_FILE_MAX_SIZE configuration is active.
Upload a document containing multi-page technical tables. Wait for parsing to complete, then view chunk details. Confirm that table content appears in complete cell structures, confirming enable_table_parse is enabled.
Check system logs to confirm no parse_timeout errors, confirming the PARSE_FILE_TIMEOUT_SECONDS configuration meets long document parsing requirements.
Randomly select chunked content, verify that technical parameters and their corresponding units are fully associated, confirming the chunk_size configuration does not break parameter-unit associations.

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.