What the data for this category looks like
Qualification compliance bidding data mainly comes from qualification scans submitted by bidders, public access documents released by regulatory authorities, and internal enterprise qualification ledgers. Data is updated per individual bidding project. Qualification data for each project is independent and cannot be reused across projects. Most documents are in multi-page PDF or Word format, containing text descriptions and scan attachments. Core fields include qualification certificate number, issuing authority, valid period, and business scope. The certificate number uses a string format, the valid period uses a standard date format, and there is no unified fixed length requirement.
What constraints these characteristics impose on model access and configuration
Multi-page documents with scan attachments require model access configuration to support OCR preprocessing and structured text extraction, to ensure content from scanned qualification files can be recognized. The per-project update feature requires configuration to support temporary indexing and avoid persistent storage, to prevent mixing of qualification data across different bidding projects. Fields include standardized entities such as certificate numbers and valid periods, so access configuration needs entity extraction matching rules to adapt to the format requirements of qualification fields. Dispersed data sources require configuration to support batch parsing of multiple files, to adapt to upload scenarios with multiple qualification files per project.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_OCR_ENABLE | Enabled | Most qualification documents contain scans, so OCR is needed to extract scanned text |
MAX_PARSE_PAGE_NUM | 50 pages | Single qualification files typically do not exceed 50 pages, to avoid parsing timeouts |
RECALL_CHUNK_SIZE | 800–1200 characters | Qualification fields are mostly short structured text, so precise chunking is needed to preserve field integrity |
SIMILARITY_THRESHOLD | 0.75–0.85 | Filter low-match non-qualification content to focus on core field extraction |
TEMP_INDEX_EXPIRE | 30 minutes | Qualification data is tied to individual bidding projects, so persistent storage is unnecessary |
UPLOAD_FILE_MAX_SIZE | 200 MB | Adapt to the reasonable size limit of single qualification files containing multiple scans |
The parameter values provided on this page are common recommended 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
- Phenomenon: Model calls return
404 Not Founderror. Cause: The/v1path was not added to the end of the configured AI model API address, causing requests to fail to match the model service endpoint. - Phenomenon: After uploading qualification files, the files are available for download but no valid text is returned after parsing. Cause: The
PARSE_FILE_OCR_ENABLEconfiguration was not enabled, so text content from scanned qualification files cannot be extracted. - Phenomenon: The interface prompts
null not uploadedbut file storage is normal. Cause: The temporary storage path for file uploads was not configured correctly, causing the indexing stage to fail to read the uploaded file's metadata.
How to confirm the configuration is complete
- Upload a single qualification document containing scans, verify that the parsed text covers core fields such as certificate number and valid period. Adjust related configurations based on field extraction results.
- Initiate a model call targeting qualification fields, check the status code returned by the interface to confirm there are no
404errors, and verify the correctness of the API address configuration. - Upload a test file with no valid qualification content, check if the workflow skips the knowledge base retrieval step. Adjust the handling logic for empty data based on business scenarios.
- View the file parsing log to confirm the number of parsed pages matches expectations. Adjust the value of
MAX_PARSE_PAGE_NUMto adapt to document length.
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.