What Data for This Category Looks Like
Gas marketing-related data primarily comes from marketing materials and business ledgers of gas operating enterprises. This includes offline event check-in sheets, online marketing material backups, regional user outreach ledgers, and gas appliance promotion product manuals. Update frequency varies by document type: event documents are updated per single event or quarterly, outreach ledgers are updated weekly, and product manuals are updated annually. Document structures include multi-column table ledgers, text-and-image mixed marketing posts, and PDF-format event plans. Fields include user addresses precise to building numbers, enumerated gas usage type values, outreach time, and feedback results. The unit for gas consumption fields is cubic meters, and the unit for amount fields is yuan.
How These Characteristics Create Constraints for Document Parsing and Chunking
The multi-column table feature of gas marketing data requires parsing tools to recognize more than just the default 2 columns of data. Otherwise, core business fields such as user addresses and gas usage types will be lost. Frequently updated outreach ledgers require retaining time and regional contextual associations during chunking, to avoid business logic breaks. For text-and-image mixed marketing materials, product description text attached to images must be bound to the main text, and cannot be split into unrelated chunks. Boolean-type feedback fields must retain their original data type. Otherwise, their validity will be lost in subsequent conditional judgments. In addition, long paragraphs in large multi-page PDF event plans must be split by business modules, not using fixed-length splitting. This ensures the complete logic of the marketing plan is preserved.
How to Configure the Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
excel_parse_max_columns | 20 columns | Gas marketing outreach ledgers typically contain multiple business fields such as user addresses, gas usage types, and outreach times. The default 2-column limit will cause core data to be lost |
chunk_size | 800–1000 characters | Gas marketing documents contain business fields and explanatory text. This length retains the complete context of a single regional outreach plan or single product promotion plan |
pdf_enhance_parse_api | mineru API | Gas marketing PDF materials contain multi-page tables and text-and-image mixed content. This API accurately extracts full-column table data and image-associated text |
parse_boolean_as_text | false | Boolean-type feedback fields in gas marketing documents must retain their original type, to avoid data loss during subsequent conditional judgments |
chunk_overlap | 100–150 characters | Gas marketing outreach ledgers are grouped by region. The overlap length retains the contextual association of regional groups, avoiding business logic breaks after chunking |
parse_file_timeout_seconds | 120 seconds | Parsing large Excel outreach ledgers and multi-page PDF documents requires sufficient time, to avoid parsing failures caused by timeouts |
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 the configuration.
Three Common Mistakes
- Phenomenon: After uploading a multi-column gas outreach ledger Excel, the knowledge base only recognizes the first 2 columns of data, and subsequent columns are lost. Cause: The
excel_parse_max_columnsparameter was not adjusted, and the default 2-column limit was used. - Phenomenon: After enabling PDF enhanced parsing, nested tables and full-column data in gas marketing PDFs cannot be extracted correctly. Cause: The
pdf_enhance_parse_apiparameter was not correctly configured to point to the mineru API, or API permission configuration was not completed. - Phenomenon: Boolean-type feedback fields parsed from business documents become null values when entering conditional judgment components. Cause: The
parse_boolean_as_textparameter was not configured asfalse, causing boolean values to be incorrectly converted or lost during the parsing process.
How to Confirm the Configuration Is Correct
- Upload a test gas outreach ledger Excel, check whether the number of fields stored in the knowledge base matches the original document, to confirm that the
excel_parse_max_columnsconfiguration takes effect. - Upload a test document containing boolean fields, check whether the parsed field types match the original data, to confirm that the
parse_boolean_as_textconfiguration is correct. - Upload a multi-page PDF marketing plan, check whether the extracted text contains all table columns and text-and-image associated content, to confirm that the
pdf_enhance_parse_apiconfiguration points to the correct service. - Test the retrieval effect after chunking, check whether corresponding chunks can be accurately recalled via region or outreach time, to confirm that the
chunk_sizeandchunk_overlapconfigurations meet business requirements.
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.