What the Data for This Category Looks Like
The data for this category originates primarily from the food safety sampling and monitoring system, the State Administration for Market Regulation sampling results query system, laboratory LIMS, and enterprise ledgers. The update frequency is monthly. Daily documents include sampling plans, sampling slips, inspection reports, non-compliant food verification and disposal reports, and risk control notices. Data fields cover sampling location information, sample identification, inspection project results, non-compliance item determinations, disposal process nodes, and additional relevant details. Typical users include the food sampling division of market supervision bureaus, inspection institutions, grassroots supervision offices, and food producers and operators. Core data is generated around sample inspection and non-compliance disposal workflows.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
The monthly updated batch data requires multi-turn dialogue components to support batch association with historical sampling datasets, preventing repeated calls to a single data source. Mixed input of multiple types of structured documents requires prompts to clearly distinguish processing logic for different document types such as sampling plans, sampling slips, and inspection reports, and accurately extract corresponding fields. Core data revolves around sample inspection and non-compliance disposal workflows, so prompts must focus on core links including sampling location review, non-compliance item determination, and disposal progress tracking. Permission differences across user groups require multi-turn dialogue to automatically adapt data display scope based on the calling subject, while ensuring compliance of data calls.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique identifier of the current sampling task | Ensure multi-turn dialogue context is associated with the corresponding sampling task, avoiding cross-task data confusion |
messages | Retain the most recent 20 rounds of dialogue context | Cover the complete communication nodes of a single sampling process, while controlling context loading overhead |
variables | Inject preset fields such as sampling location and inspection institution for the current sampling task | Allow multi-turn dialogue to automatically associate task-specific data, reducing repetitive input operations |
| Question Optimization Switch | Enabled | Convert colloquial questions from grassroots supervision personnel into standardized retrieval instructions, adapting to the retrieval needs of structured sampling data |
| Single Retrieval Limit | Top 10 entries | Match the batch scale of monthly sampling data, avoiding excessive retrieval results that disrupt dialogue logic |
| Document Chunk Length | 1500–2000 characters | Adapt to the structured paragraph length of documents such as inspection reports and sampling slips, improving retrieval accuracy |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Misconfigurations
- Uncaught exception prompt pops up when calling the AI dialogue component. Cause: The configuration file was not properly configured in the private deployment environment, and the data storage path binding was not completed.
- Uploaded files such as sampling slips and inspection reports are not correctly associated with the dialogue context. Cause: The correct file storage path binding was not configured, and the associated field for file storage in
variableswas not specified. - After initiating an API dialogue via Python code, the returned result does not reference the inspection report content in the knowledge base. Cause: The prompt did not explicitly specify retrieval of sampling-related documents, or the context association retrieval configuration was not enabled.
How to Verify Proper Configuration
- Initiate a query containing sampling plan keywords, and check whether the returned result associates the exclusive sampling location information of the current task.
- Upload a single inspection report, and check whether the dialogue can accurately extract non-compliance items and disposal requirement fields.
- Initiate multiple consecutive queries, and check whether the context bound by
chatIdcontinuously retains the historical dialogue information of the current task. - Call the API interface to initiate a dialogue, and check whether the returned result includes the reference identifier of sampling-related documents in the knowledge base.
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.