What the data for this category looks like
The data for professional services marketing content primarily comes from internal marketing material libraries, customer communication records, and product documents provided by partners. Update schedules fall into three categories: irregular (updated when new financial or insurance products launch), quarterly (for investment research reports), and monthly (for event promotional materials). Document types include multi-page PDF investment research reports, structured Excel customer or product lists, and Word-format marketing script templates. Fields include product code, expected return rate, risk level, effective date, and others. Units include percentage, yuan, annualized days, and others. The length of individual documents varies widely.
What constraints these characteristics impose on the "document parsing and chunking" workflow
Structured Excel lists have each row corresponding to independent customer or product information. Avoid splitting across merged rows, as this will cause errors in subsequent recall matching. Long PDF investment research reports have clear chapter hierarchies. Splitting by fixed character count will damage the logical integrity of product descriptions and risk warnings. Irregularly updated marketing materials require fast parsing. Support for bulk upload and automatic chunking is needed, with no manual adjustment required for individual document configurations. Documents containing unique identifier fields must retain field associations during chunking. Avoid splitting key information across fields, as this will affect subsequent precise matching.
How to set the configurations
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Matches the information density per chunk for professional services marketing documents, avoids splitting complete product descriptions across multiple entries |
chunk_overlap | 100–150 characters | Retains contextual information across chunks, for example, allows association of product risk warnings that span two chunks |
PARSE_EXCEL_SPLIT_BY_ROW | Enabled | Splits structured data by Excel rows, resolves issues where multiple rows are combined into a single chunk |
SIMILARITY_THRESHOLD | 0.75–0.85 | Filters low-relevance recall results, meets the precise matching requirements for professional services content |
PARSE_PDF_USE_HEADING | Enabled | Splits long documents by PDF heading hierarchies, preserves the chapter logic of marketing materials |
UPLOAD_FILE_MAX_SIZE | 500 MB | Adapts upload size limits for single dozens-of-page investment research reports or bulk marketing materials |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- After uploading an Excel-format marketing list, chunking results combine multiple rows into a single entry. This occurs because the
PARSE_EXCEL_SPLIT_BY_ROWconfiguration is not enabled. The system defaults to splitting by the overall document structure, and does not split by rows. - Specific chunked content exactly matches a query term but cannot be recalled. This occurs because
SIMILARITY_THRESHOLDis set too high, or unique identifier fields such as product code are lost during chunking. - After bulk uploading multiple PDF marketing documents, only one combined chunk is generated. This occurs because the
PARSE_PDF_SPLIT_BY_DOCconfiguration is not enabled, or the workflow does not include a multi-document traversal node.
How to Confirm Configurations Are Set Correctly
- Upload a single structured Excel test file, verify that the knowledge base chunking results map each row to an independent chunk.
- Upload a PDF investment research report with heading hierarchies, verify that chunking results split content by headings instead of fixed character counts.
- Adjust
SIMILARITY_THRESHOLDto 0.75, test the recall success rate for known matching content. - Bulk upload multiple PDF marketing documents, verify that the workflow processes each document individually and generates corresponding chunks.
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.