What the data for this category looks like
Infrastructure construction project yield-related data primarily comes from internal enterprise project management systems, regional cost guideline databases, and project financial accounting modules. The data update rhythm aligns with project reporting cycles, typically updating every 15 days or monthly. Individual data documents use structured formats, containing fields such as project unique identifier, accounting period, cumulative completed project volume percentage, current period input cost, current period priced revenue, revenue coefficient for the corresponding accounting period, associated bid section, and construction subject identifier. The units for cost and revenue fields are yuan, and the unit for the revenue coefficient is 1.
What constraints do these characteristics impose on model integration and configuration
The characteristics of infrastructure construction data impose multiple constraints on model integration and configuration. First, the data update rhythm aligns with project reporting nodes rather than following a fixed cycle. Trigger rules for data source pulling must be configured to adapt to dynamic triggering logic, preventing missed updates of the latest project data. Second, structured data includes multi-dimensional associated fields. Field mapping parameters must be configured to bind fields from raw data such as project identifier and accounting period to model input parameters, ensuring the relevance of input data. Additionally, the data includes financial fields in yuan and revenue coefficients without percentage units. Preprocessing unit validation rules must be configured to avoid model calculation deviations caused by unit mismatches. Some projects have cross-bid section associations, so configuration items supporting multi-source data associated queries must be supported to ensure the completeness of input data.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
datasource_pull_trigger | Trigger by project reporting nodes, supports custom trigger times | Infrastructure construction data updates do not follow a fixed cycle; matching reporting nodes ensures pulling the latest data |
field_mapping_template | Bind the five core fields: project ID, accounting period, current period cost, current period revenue, revenue coefficient | These fields are the core inputs for model yield rate calculations, ensuring data completeness |
preprocess_unit_validate | Enable validation, configure unit rules for yuan and coefficients | The data includes financial fields in yuan and revenue coefficients without percentage units, preventing unit mismatches |
model_response_timeout | 600 seconds | Infrastructure construction data has multiple associated dimensions; model processing requires more time to avoid timeout interruptions |
rerank_model_enable | Enable, connect to a private reranking model | Infrastructure construction data has many fields; reranking models can improve the relevance filtering effect of input data |
api_compatible_mode | Configure request paths according to model service provider documentation | Resolves 405 request errors when connecting third-party models |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material forms, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Symptom: The model returns a
chat：llm—model—response-emptyempty response. Cause: Correct field mapping is not configured, leading to missing core data for model input and preventing valid output generation. - Symptom: A 405 status code is returned when connecting a third-party model using
api_compatible_mode. Cause: Request paths are not configured according to model service provider requirements, which do not match the request methods supported by the model. - Symptom: Reranking model return results do not meet expectations. Cause: Reranking parameters are not adjusted based on the associated dimensions of infrastructure construction data, leading to filtering logic that does not match business requirements.
How to verify a successful configuration
- Manually trigger a data source pull, and check if the pulled fields match the configured
field_mapping_template. - Submit test data, observe if the model's returned response includes expected calculation results, and check that no
chat：llm—model—response-emptyerror occurs. - Call the configured model interface, confirm that the returned status code is not 405.
- After enabling the reranking model, check the relevance of recalled results, and adjust reranking-related configurations to a range that meets business filtering requirements.
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.