What this category of data looks like
Data for refining and chemical research reports comes primarily from public monitoring data released by petroleum and petrochemical industry associations, quarterly operation announcements of refining and chemical enterprises, and in-depth analysis reports from third-party professional consulting institutions. The update schedule is monthly for basic industry operation data, quarterly for in-depth research reports, and annually for full industrial chain panoramic reports. Most documents are in PDF format, with wide variation in single-document length. It is recommended to confirm settings based on in-house sample statistics or actual testing. Documents include structured tables, device parameter tables, and cost accounting details. Core fields include daily processing volume (unit: tons), unit energy consumption (unit: kg standard coal), ex-factory unit price of products (unit: yuan/ton), and production capacity scale (unit: 10,000 tons/year). Some documents include monthly time-series data for raw material procurement cycles.
What constraints do these characteristics impose on the document parsing and chunking link
The mixed formats, long length, and structured field features of refining and chemical research reports impose multiple constraints on document parsing and chunking. First, mixed formats result in interleaved layouts of embedded tables and plain text paragraphs. Some older documents have non-editable text converted from scanned PDFs, so parsing must accurately identify the correspondence between table boundaries and text paragraphs. Second, single documents can be up to 80 pages long, making parsing prone to triggering timeout limits. Third, core fields are bound to specific units. Chunking must retain the association between fields and units to avoid losing semantics after splitting. Fourth, some documents include batch monthly time-series data. Chunking must retain contextual continuity for grouped data to prevent breaks in time-series logic.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Refining and chemical research reports can be up to 80 pages long with many embedded tables, so conventional parsing takes a long time. 600 seconds covers the parsing needs of most long documents. |
maxChunkSize | 800–1200 characters | Refining and chemical research reports contain a large number of numerical fields with specific units and long paragraph descriptions. This range retains the complete semantics of a single group of fields and their associated context. |
ENABLE_TABLE_PARSE | Enabled | Core operation and cost data of refining and chemical research reports are mostly presented in table form. Enabling this option accurately extracts cell content and associates it with table headers. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some annual panoramic research reports are lengthy, with file sizes up to hundreds of MB. This threshold covers the upload needs of most compliant documents. |
CHUNK_OVERLAP_RATE | 10–15% | Refining and chemical research reports have a large amount of time-series data and long paragraphs. Overlapping chunks ensure continuity of context recall and prevent key information from being split at chunk boundaries. |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on in-house samples before finalizing values.
Three Common Misconfigurations
- Phenomenon: When deploying the
marker_pdfparsing engine privately, FastGPT returns a parsing timeout error, but the parsing server logs show the task completed successfully. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted to a value suitable for long documents. The default timeout threshold is insufficient to cover the parsing time required for refining and chemical research reports. - Phenomenon: Unable to read uploaded Excel-format refining and chemical research report attachments in the workflow, returning null values or error prompts. Cause: Structured table parsing configuration was not enabled, and parsing rules for Excel file column formats were not configured, resulting in failure to correctly extract table data.
- Phenomenon: In simple mode of FastGPT 4.8.9 and later versions, some refining and chemical research reports are not automatically parsed, and only answers based on general training data are returned. Cause: Automatic parsing trigger rules were not configured, and the exclusive document type of refining and chemical research reports was not included in the automatic parsing scope.
How to Confirm Proper Configuration
- Upload the longest single refining and chemical research report document, check the parsing task status log, and confirm that the parsing time does not exceed the configured timeout threshold.
- Extract the segmented content after parsing, verify that core numerical fields and their corresponding units are fully retained in the same paragraph, and confirm that the chunk length meets expectations.
- Add a document recall node to the workflow, upload Excel-format refining and chemical production capacity data, and confirm that the node can return structured content within the table.
- Initiate a question-and-answer request based on refining and chemical research reports, and confirm that the generated answer includes proprietary data from the parsed documents and does not include general training content.
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.