What the data for this category looks like
Competitor quote data primarily comes from public bidding announcements, bid documents disclosed per industry compliance requirements, and internal quote ledgers from partner institutions. Update frequency aligns with bidding project cycles, with core quote data synced concentratedly before bid submission deadlines. Most documents are structured tables or formatted PDFs, and include fields such as bidder name, quote line items, unit price, total price, quote validity period, and qualification requirements. Pricing units include yuan, ten thousand yuan, and other valuation units.
Constraints on workflow orchestration from these characteristics
Dispersed data sources and concentrated update patterns require workflows to include scheduled trigger nodes adapted for short-cycle sync tasks, to avoid missing quote update windows. Mixed structured and unstructured document formats require workflows to include multi-format parsing nodes, to support PDF table extraction and text structured conversion. Fields that include pricing units and qualification requirements require workflows to include field validation nodes, to filter out quote data with invalid units or missing qualifications. Branch-based process requirements for bidding projects require workflows to support branch orchestration based on project type, to prevent cross-project data confusion.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_DOC_PRIORITY | Structured first | Most competitor quote documents are structured tables; prioritizing structured content improves field extraction accuracy |
MAX_PARSE_TIMEOUT | 600 seconds | Complex PDF table parsing requires sufficient time to avoid mid-process timeout interruptions |
WORKFLOW_TRIGGER_INTERVAL | 12 hours | During periods of concentrated bid quote updates, syncing every 12 hours covers core update windows |
FIELD_VALIDATION_RULES | Match units to yuan/ten thousand yuan; required fields include bidder name, quote line items | Ensures extracted quote data complies with pricing specifications and business field requirements |
PARALLEL_RUN_MAX_COUNT | 5 | Process quote parsing for multiple bidders under a single project in parallel, avoiding platform resource overload |
WORKFLOW_BRANCH_TRIGGER | Trigger by project classification tags | Adapts to branch process requirements for different bidding projects, avoiding cross-project data contamination |
The parameter values provided on this page are common starting points for configuration setup. Actual values are influenced by material format, data volume and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: JSON parsing errors occur when the workflow parses competitor quotes, with logs showing invalid escape characters. Cause: Special character escaping nodes are not configured, and unprocessed special characters such as double quotes and line breaks break the parsing format of structured data.
- Symptom: After configuring parallel processes, running speed does not improve, and resource preemption errors occur instead. Cause: The maximum number of parallel running nodes is not limited, exceeding platform resource thresholds leads to scheduling exceptions.
- Symptom: After the problem classification node triggers a branch, the process still returns to the classification node for looping. Cause: No process termination or jump node is configured at the end of the branch node, causing the process to default back to the starting node.
How to Verify Proper Configuration
- Upload a standard competitor quote document, and check if the fields output by the parsing node are complete and comply with preset validation rules.
- Trigger the scheduled sync task, and check if the data update time matches the preset trigger interval.
- Configure a branch test process, and verify that different classification tags correctly trigger corresponding branches.
- Run a benchmark test script, and verify parsing accuracy and operating efficiency under different configurations.
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.