What the data for this category looks like
The core data for this category comes from online monitoring platforms, automatic pollution source monitoring data, ecological and environmental law enforcement systems, and third-party test reports, with a daily update frequency. Daily processed documents include on-site inspection records, sampling records, monitoring reports, rectification orders, and administrative penalty decisions. Document structures cover fields such as on-site operating condition records, sampling point information, pollutant concentration values, and law enforcement document numbers. Units include concentration, volume, and time categories. Field formats vary across different documents, and some documents require association with multiple data sources for cross-verification.
What constraints these characteristics bring to the "multi-turn dialogue and prompt engineering" link
The data for this category is updated daily and includes documents in multiple formats. This requires multi-turn dialogue to prioritize calling the latest online monitoring and law enforcement system data to avoid introducing outdated information. Different documents correspond to different business scenarios, so prompts must clearly distinguish usage rules for documents such as on-site inspection records and monitoring reports. The cross-verification requirement for multiple data sources means multi-turn dialogue must support step-by-step disassembly and comparison steps, guiding users to clearly specify data sources. The traceability requirement of law enforcement processes requires binding a unique identifier to each round of dialogue to ensure no context confusion.
How to configure
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| chatId | Bind a unique identifier for a single law enforcement task | Ensure multi-turn dialogue context for the same law enforcement event is not confused, meeting the traceability requirements of law enforcement processes |
| messages | Retain the first 7 rounds of dialogue context, automatically truncate excess content | Daily updated data has strong timeliness; overly long context will introduce outdated information. 7 rounds align with the typical communication rounds for a single law enforcement event |
| variables | Preset two variables: law enforcement subject type, data source type | Adapt to different business scenarios such as on-site inspection and sampling monitoring, quickly switching prompt templates |
| Maximum context length | 800–1200 characters | Single documents for this category are mostly under 500 characters; this length can accommodate 2-3 core law enforcement documents, complying with FastGPT v4.17.0 configuration specifications |
| Single recall limit | Top 4 entries | Law enforcement-related documents need to accurately match policy basis; excessive recall will interfere with judgment |
Three common misconfigurations
- Phenomenon: Token limit exceeded error occurs during dialogue, with return status code 413. Cause: The context rounds of
messagesare not restricted, and multiple days of outdated law enforcement data are introduced, exceeding the model's token capacity limit. - Phenomenon: Prompt that the file has expired when calling historical monitoring reports. Cause: The default
CHAT_FILE_EXPIRE_TIME=7is not adjusted, while law enforcement monitoring reports need to be retained for long-term reference; the 7-day expiration period does not meet business requirements. - Phenomenon: Multi-AI dialogue task execution results are disorganized in batch execution nodes, unable to complete tasks per assigned roles. Cause: Independent
chatIdis not bound to each dialogue task, leading to mutual interference of contexts and making parallel task division and execution impossible.
How to confirm the configuration is correct
- Initiate a simulated law enforcement dialogue, ask 3 consecutive questions about the same sampling record, confirm that the answers always match the document content with no context loss.
- Upload a monitoring report from 30 days ago, test whether it can be retrieved normally, verifying that the file expiration time configuration meets business requirements.
- Check the dialogue log to confirm that each task has a unique
chatId, with no context mixing across tasks. - Adjust the
variablesto switch the law enforcement subject type, confirm that the prompt template automatically adapts to the corresponding business scenario.
The values provided are common starting points and should be evaluated against individual use cases.
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.