What the Data for This Use Case Looks Like
Target users for this use case include advertising platform compliance teams, agency legal teams, and brand marketing personnel. Documents handled daily include advertising review forms, qualification attachments, delivery records, and rectification notices. Data sources cover advertising platform backends, customer qualification libraries, contract systems, and publicly available regulatory rules. Update frequency adjusts per individual advertising campaign or monthly cycle. Individual documents may include structured fields and unstructured attachments. Some data sources are deployed on internal networks, so internal access permissions must be supported.
Constraints Imposed on Document Parsing and Chunking
Data sources include internally deployed systems and publicly available external resources. The parsing module must support internal access permission adaptation to avoid failures when parsing internal network pages. Individual documents may contain structured tables and unstructured text, so multi-format parsing logic must be supported. Update frequency adjusts with advertising campaigns. The parsing process must match lightweight processing rhythms to avoid delaying compliance filing time requirements. Compliance record-keeping requires complete data retention. The chunking process must retain key fields such as review ID, delivery time, and similar details, to prevent loss of critical information that would impact regulatory verification.
Configuration Settings
This configuration is adapted for FastGPT v4.17.0. Adjust all parameter values based on actual document scale:
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapt to the information density per chunk of advertising review forms and delivery records, avoid including too many unrelated compliance fields within a single chunk |
chunkSplitter | Split by paragraph + heading | Match the hierarchical structure of compliance documents, retain contextual connections for review processes and rectification requirements |
customPdfParse | Enabled | Support unstructured text extraction for qualification attachments and rectification notices, retain key identifiers from original formatting |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Address parsing time for single documents with thousands of pages, avoid timeout interruptions that cause loss of compliance data |
chunkSettingMode | Manual configuration | For Excel documents with tens of thousands of rows, customize chunking parameters to avoid overly large chunks, adapt to structured data splitting needs |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Cover the upload requirements for largest qualification attachments, meet full data retention requirements for compliance filing |
Three Common Misconfigurations
- Phenomenon: No parsed content after importing an internal Confluence page, parsed result fields are empty. Cause: Internal access permission adaptation rules are not configured, the parsing module only supports access to publicly available external resources.
- Phenomenon: After uploading a thousands-page PDF document, the large language model returns an incomplete response prompt. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set too low, parsing process times out and interrupts, only partial page content is extracted. - Phenomenon: After importing Excel-format delivery records, chunked content includes entire rows, with overly coarse granularity. Cause:
chunkSettingModeis not manually adjusted, default chunking parameters for general documents are used, without adapting to row-level splitting needs for structured tables.
How to Verify Proper Configuration
- Import a compliance document in internal Confluence format, check if parsed data fields include page titles and body content.
- Upload a PDF qualification file with more than 500 pages, wait for parsing to complete and check task logs to confirm no timeout errors occurred.
- Import an Excel delivery record table with headers and tens of thousands of rows, check if chunked results are split into small field groups without overly large chunks.
- Adjust the
chunkSizeparameter, compare the number of chunks and content integrity under different values, confirm compliance with information retention requirements for compliance documents.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.