What the data for this category looks like
This category covers entities such as ecological environment law enforcement detachments, environmental monitoring stations, and third-party testing institutions. Daily processed documents include on-site inspection records, sampling records, monitoring reports, order for correction decisions, and administrative penalty decisions. Data sources include online monitoring platforms, automatic pollution source monitoring data, ecological environment law enforcement systems, and third-party test reports. Update frequency is daily. Document structures contain fields such as law enforcement time, location information, pollutant detection data, and law enforcement document numbers. Data formats from different sources have minor differences.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Multiple data sources and inconsistent formats require prompts to adapt to the field rules of different documents. This ensures the AI can accurately parse core information such as on-site working conditions and monitoring concentrations. Daily updated real-time data requires multi-turn dialogue to quickly call the latest monitoring and law enforcement records. This avoids reliance on outdated information. Multiple types of law enforcement documents require prompts to distinguish output formats for different scenarios. For example, order for correction decisions must clearly state rectification requirements. Administrative penalty decisions must match evidence chains. Errors in law enforcement and monitoring directly relate to public environmental safety. Prompts must add evidence verification logic to ensure output content is traceable.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Question Optimization | Enabled, add exclusive terms such as on-site inspection records and monitoring reports to the optimized thesaurus | Adapt to the high-frequency document types of this category, improve retrieval accuracy |
| Maximum Context Window | Calibrated via actual testing, recommended 3000–5000 token | Cover context requirements for multi-turn law enforcement dialogue, avoid truncation of critical law enforcement information |
| Single Search Limit | Top 8 results | Match the multi-source data volume updated daily in this category, balance retrieval efficiency and content completeness |
| Variable Injection | Bind the variables parameter, inject current law enforcement location ID and monitoring period | Accurately call online monitoring data and law enforcement records for the corresponding period |
| Conversation ID Association | Enable chatId binding | Retain law enforcement scenario context in multi-turn dialogue, avoid repeated confirmation of basic information |
| Input Guidance | Preset prompts such as "Please provide law enforcement location number" and "Please confirm monitoring period" | Guide users to supplement necessary information for law enforcement scenarios, reduce invalid dialogue |
Reference only; verify against the target FastGPT release and deployment documentation.
Three common configuration errors
- Format error prompts appear in the debug preview interface, and the custom thesaurus configuration does not take effect | The thesaurus file was not uploaded to the specified path, or the thesaurus content does not include high-frequency law enforcement and monitoring terms for this category
- The response length for a specific question is only 200 tokens, which does not match the preset maximum response of 3000 or more | The multi-turn dialogue context window is filled with non-core law enforcement data, and the system automatically triggers content truncation
- No corresponding monitoring report data is returned after calling the API interface associated with the knowledge base | The
variablesparameter was not correctly bound to inject retrieval conditions such as law enforcement location ID, resulting in overly large or invalid retrieval scope
How to confirm successful configuration
- Upload exclusive documents of this category to the knowledge base, trigger a question optimization test, confirm that the AI can accurately identify document types such as on-site inspection records and monitoring reports
- Enable multi-turn dialogue, enter queries for three different law enforcement locations in sequence, confirm that the context retains previous location information, and no repeated confirmation is required
- Call the interface associated with the knowledge base, pass in the
chatId,variables, andmessagesparameters, check whether the returned results include online monitoring data for the corresponding period - Adjust the maximum context window parameter to a reasonable range, initiate a long-text law enforcement scenario dialogue, confirm that the response length meets the preset requirements
The values provided here are common starting points, and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.