What This Category's Data Looks Like
Environmental monitoring research report data mainly comes from real-time data of national and provincial controlled stations in the national ecological environment monitoring network, special test reports from third-party environmental monitoring agencies, and regional environmental quality summary documents released by industry associations. Data update frequencies cover hourly (real-time station data), monthly (regional special reports) and annual (quality assessment reports). Each single document includes fields such as monitoring point number, longitude and latitude, pollutant concentration, monitoring time, compliance judgment, and region attribution. Concentration-related fields mostly use μg/m³ as the unit, while meteorological fields use m/s or ℃ as the unit. Document structure is arranged in groups by monitoring period and region.
Constraints Imposed by These Characteristics on Model Access and Configuration
The real-time performance and field standardization requirements of environmental monitoring research reports require configuring incremental synchronization trigger rules when accessing models, to avoid excessive computing resource occupation from full synchronization. The characteristics of multiple fields and fixed units require configuring data standardization mapping rules to ensure consistent units and consistent field meanings for monitoring data from different sources. The document structure grouped by region and period requires the retrieval process to recall by field groups, to avoid mixing cross-region and cross-period data. Large annual summary reports have a large volume, so longer parsing and upload timeout settings need to be adapted to avoid document parsing failures.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Environmental monitoring research reports contain multiple consecutive sets of monitoring data. An overly long chunk will damage data relevance, while an overly short chunk will lose field context |
| Recall Count | Top 6–10 entries | A single monitoring research report has many data entries. Too many recalled results will exceed the model context limit, while too few will miss key monitoring point data |
| Similarity Threshold | 0.75–0.85 | Monitoring data fields are clear, and a high similarity is required to avoid recalling monitoring records from unrelated regions |
| Reranked Return Count | Top 3–5 entries | The most relevant monitoring period data must be retained to avoid redundant information interfering with model inference |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large special monitoring research reports have more content, so extending the parsing timeout time avoids parsing failures |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports batch uploading of quarterly/annual summary monitoring reports, adapting to the access needs of large documents |
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 specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Errors
- Phenomenon: The model output includes <think> tags and cannot be parsed into structured retrieval results. Cause: Forced filtering of private inference tags in the model output format is not configured, resulting in unstructured content being mixed into the retrieval process.
- Phenomenon: Model calls return a 402 status code, or prompt insufficient interface quota. Cause: Third-party model keys and billing parameters are not configured correctly, or unauthorized model service interfaces are used.
- Phenomenon: Custom system prompts do not take effect, and the model does not retrieve environmental monitoring data as required. Cause: The system prompt forced enable switch is not turned on in the model configuration, or the system prompt is not placed in the correct context position.
How to Verify Proper Configuration
- Upload a small environmental monitoring research report, and confirm the parsed chunks are split according to fixed fields with no garbled characters or truncation.
- Submit a retrieval request containing specific monitoring point or pollutant keywords, and confirm the number of recalled results matches the configured recall count, and the similarity meets the set threshold.
- Enable the reranking function, and review the result ranking to confirm it prioritizes relevance to the retrieval keywords.
- Test the model output, and confirm private inference tags have been automatically filtered, with the output content being structured monitoring data conclusions.
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.