What the Data for This Category Looks Like
The daily documents for this category include inspection plans, inspection target lists, inspection item checklists, on-site inspection records, rectification notices, and inspection result announcements. Data typically comes from the "Double Random, One Public" regulatory platform, enterprise credit information publicity system, industry regulatory systems, and law enforcement officer directory. The update frequency is monthly. Core fields include the unified social credit code of regulatory targets, law enforcement officer ID numbers, inspection item categories, rectification completion status, and more. Document structures primarily use structured lists and record forms.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Monthly updated data requires that the dialogue system supports regular synchronization of the inspection target database and law enforcement officer directory from the regulatory platform, to avoid using expired data. Structured document fields require that prompts clearly guide the extraction of specified business fields, ensuring that generated inspection tasks and records conform to required formats. Multi-turn dialogue must retain context for law enforcement officer assignment and inspection target extraction, to avoid repeated matching or missed constraint conditions. The content of inspection result announcements must fully match the entered inspection records, and generated announcement text must link to original inspection data fields.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Context window size | First 8000–12000 characters | Must accommodate batch data such as monthly updated inspection target lists and law enforcement officer directories, to avoid truncation of critical business information |
| Single dialogue timeout | 600 seconds | Prevents long dialogues from being interrupted by timeout, adapting to scenarios where law enforcement officers process inspection tasks in bulk |
messages field processing rules | Concatenate inspection tasks, target database entries, and historical conversations by turn | Ensures law enforcement officers can review confirmed inspection conditions and task progress during multi-turn dialogue |
variables configuration | Bind inspection plan number and regulatory department code | Reduces repeated input, ensuring generated inspection records are linked to correct business identifiers and traceability information |
chatId binding rule | Bind independent sessions to law enforcement officer accounts | Achieves isolation of dialogue context between different law enforcement officers, avoiding confusion between task assignments and records |
| Supported file upload formats | PDF, DOCX, CSV | Adapts to common document formats for this category, such as inspection target lists, on-site inspection records, and rectification notices |
Three Common Configuration Errors
- An error indicating missing application identifier is returned when calling the dialogue interface. This occurs because no application for the corresponding regulatory department was created via the API, or the application identifier was not correctly bound in the request.
- Structured content cannot be parsed after uploading an inspection target list file. This occurs because CSV format file upload support was not configured, while common list files for this category are typically stored in CSV format.
- No streaming response is returned after configuring an Ollama-deployed model. This occurs because the streaming response switch was not enabled, or the model's streaming output parameters were not correctly configured.
How to Verify Successful Configuration
- Upload a CSV-format inspection target list common to this category, confirm that the system can parse fields such as the unified social credit code and inspection target name.
- Initiate dialogue using different law enforcement officer accounts, confirm that after
chatIdbinding, their respective dialogue contexts do not interfere with each other. - Initiate a dialogue that includes inspection task generation, confirm that the
messagesfield sequentially concatenates historical tasks, target database information, and the current request. - After configuring an Ollama model, initiate a dialogue, confirm that segmented streaming response content is returned.
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.