What the data for this category looks like
Data sources for infrastructure engineering research reports include public bidding announcements, industry-specific consulting reports, engineering disclosure documents from local housing and transportation authorities, project ledgers of construction enterprises, and specialized infrastructure industry research report libraries of financial institutions. Update rhythms vary: bidding data updates in real time with project progress, special reports are released quarterly or semi-annually, and internal project ledgers are adjusted dynamically with construction cycles. Document structure includes fields such as project name, construction location, total investment amount, construction duration, main building material consumption, and acceptance standards. Corresponding units include yuan, square meters, days, tons, and others. Some documents are structured tables, while others are long-text analysis content.
What constraints do these characteristics impose on deployment and upgrade
The multi-source, heterogeneous nature of infrastructure engineering research reports requires configuring both structured data parsing and long-text chunking strategies during deployment. This prevents a single parsing rule from failing to adapt to unstructured content from financial institution report libraries and structured tables from bidding documents. Real-time updated bidding data requires deploying incremental synchronization tasks to ensure the timeliness of retrieval content, while balancing synchronization frequency and server resource usage. Structured data with multiple fields requires configuring precise field mapping during vector database indexing. This avoids redundant storage or missing fields, and meets precise retrieval needs in financial scenarios. The wide range of document lengths requires flexible adjustment of context chunking parameters during upgrades to adapt to retrieval needs in different scenarios.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Specialized infrastructure engineering research reports have longer length, so parsing time is significantly higher than general documents |
UPLOAD_FILE_MAX_SIZE | 2000 MB | The size of a single large infrastructure project ledger or special research report usually exceeds the upper limit of general documents |
maxContext | 8000–12000 characters | Meets the context extraction needs of long-text research reports, avoiding truncation of key information |
Recall Count | Top 8–12 results | Relevant retrieval results for infrastructure engineering research reports have high focus; too many entries will increase context load |
Similarity Threshold | 0.75–0.85 | Filters out reports unrelated to broad industries, retaining content highly matched to the target infrastructure topic |
Incremental Sync Interval | 15 minutes | Balances the timeliness of bidding data and server resource consumption |
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 Misconfigurations
- Symptom: A
401 Unauthorizederror is prompted when accessing the platform after deployment, and identity verification cannot be completed. Cause: TheENABLE_API_AUTHconfiguration item is not enabled, or a valid authentication key is not configured. - Symptom: The AI chat node in the workflow cannot obtain the output content of the code running node, and the corresponding field is empty. Cause: The correct output variable name is not configured in the code node, or the path of the variable is not correctly referenced in the chat node.
- Symptom: An error "image not found: fastgpt-sandbox" is prompted when starting the Docker container, and the image pull fails. Cause: The correct image repository address is not configured, or the image is not pulled to the local image library in advance.
How to Confirm Proper Configuration
- Upload a typical infrastructure engineering special research report, check that the parsed text chunks conform to the
maxContextconfiguration, with no excessive truncation or redundant chunks. - Start the incremental synchronization task, check the number of newly added data entries in the vector database, which should match the update volume of the data source.
- Initiate a retrieval request for a specific infrastructure project, check that the number of returned recall results conforms to the configured
Recall Count, and the results are highly relevant to the query topic. - Test the linkage between the code node and the chat node in the workflow, confirm that the chat node can correctly obtain the output result of the code run.
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.