What the Data for This Category Looks Like
Air governance revenue yield data primarily comes from regional environmental control platforms, enterprise emission accounting systems, and third-party monitoring institution databases. Data updates on a daily cycle, with full synchronization of the previous day’s dataset completed each early morning. Each dataset includes fields such as governance project code, facility operating duration, actual pollutant emission reduction volume, corresponding subsidy standard, regional control coefficient, operating cost, and accounting cycle. Pollutant emission reduction volume uses tons as its unit, subsidy standard uses yuan per ton, operating cost uses yuan per hour, and the control coefficient is a dimensionless value. Hierarchical associations exist between data fields: emission reduction volume directly binds to subsidy amount, and combining these values with operating cost allows calculation of the daily project revenue yield.
Constraints Imposed by Data Characteristics on Multi-turn Dialogue and Prompt Engineering
The daily update requirement mandates that multi-turn dialogue restricts retrieval to the previous day’s dataset, preventing cross-cycle data from appearing in results and ensuring the timeliness of revenue yield calculations. The multi-field association structure requires prompts to explicitly define the retrieval field range, avoiding confusion between emission reduction volumes, subsidy amounts, and operating costs of different projects and ensuring the accuracy of revenue yield accounting. The fixed unit requirement forces prompts to require returned results to include corresponding units, preventing calculation errors caused by mismatched values and units. The hierarchical associated field characteristic requires multi-turn dialogue to retain the previous round’s project code as context to reduce repeated inquiries, while also limiting the context window length to prevent redundant data from interfering with retrieval accuracy.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
recallTopK | Top 6-8 results | Air governance datasets have many fields; excessive recall increases context redundancy, while insufficient recall may miss key associated fields |
similarityThreshold | 0.72-0.78 | Balances the need for accurate matching of project codes and associated fields, avoiding low-relevance data from being included in core fields for revenue yield accounting |
rerankTopN | Top 3-4 results | Datasets have hierarchical associations; retaining core associated data after re-ranking meets the context requirements of multi-turn dialogue |
maxContext | 1200-1500 characters | Single entries in air governance datasets are moderately sized; limiting context length prevents the model from confusing accounting data across different cycles |
datasetUpdateTimeRange | Last 1 day | Data is updated daily, so only the previous day’s dataset needs to be retrieved to ensure the timeliness of revenue yield calculations |
http_display_output | Enabled | The output of HTTP requests must be displayed in the dialogue interface to meet the content display requirements of daily report broadcasts |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, 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 Misconfigurations
- Issue: Output content from HTTP nodes does not display in the dialogue interface. Cause: The
http_display_outputconfiguration item is not enabled, causing orchestration node output to be hidden. - Issue: Multi-turn dialogue automatically returns to the question classification node after completion, preventing continuous advancement of the revenue yield accounting process. Cause: No fixed branch jump is configured after dialogue completion in the orchestration node, causing the process to return to the initial classification node.
- Issue: Uploaded monitoring report images cannot be recognized when calling full-modal capabilities. Cause: The model’s full-modal call parameters are not configured correctly, resulting in only text dialogue being supported.
How to Confirm Successful Configuration
- Use the FastGPT 4.6.9 orchestration interface to initiate a test dialogue containing a specific project code, and verify that returned results only include corresponding data from the previous day.
- Trigger the HTTP orchestration node, and confirm that output content displays normally in the dialogue interface.
- Initiate multiple consecutive questions, and verify that the model retains the previous round’s project code context without requiring repeated inquiries.
- Adjust the similarity threshold value, and verify that the relevance of retrieval results meets business 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.