What the Data for This Category Looks Like
This category of data is primarily sourced from local public data opening platforms, integrated big data platforms, departmental business databases, and electronic certificate repositories. The update frequency is once per month. Daily associated documents include public data resource catalogs, data opening lists, data item descriptions, desensitization rules, interface documents, and update frequency explanations. Data fields cover data item names, opening permissions, desensitization requirements, calling interface addresses, update cycles, and authorization boundaries. All are structured or semi-structured available open data assets.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The monthly update frequency requires multi-turn dialogue systems to regularly refresh cached public data catalogs and associated interface documents, preventing the return of expired opening rules or invalid interface addresses. Multi-source and heterogeneous data sources require prompts to clearly distinguish authorization conditions and desensitization requirements for data from different departments, avoiding calls to unauthorized data assets. Structured data fields require prompts to consistently extract specified fields such as data item names, interface addresses, and update cycles, preventing non-standardized output. Data opening boundary constraints require gradual guidance of users to confirm usage permissions during multi-turn dialogue, preventing unauthorized access to sensitive data.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
messages | First 8 turns of conversation content | Documents related to public data catalogs are voluminous. Limiting conversation turns avoids context overflow while maintaining contextual coherence for multi-turn interactions |
variables | Inject classified by data item name, interface address, and update frequency | This category of data uses structured fields. Classified variable injection allows prompts to accurately match corresponding data item information |
chatId | Bind departmental data permission scope | Public data has clear authorization boundaries. Associating permissions via chatId restricts different users to access corresponding open data |
| Context refresh cycle | Every 30 days | This category of data is updated once per month. Regularly refreshing the cache ensures the timeliness of returned information |
| Prompt variable injection timing | Pre-inject before conversation starts | Public data catalog information is relatively fixed. Pre-injection avoids repeated document loading and improves interaction speed |
Three Common Misconfigurations
- Phenomenon: After passing the
variablesparameter via API, the returned content does not associate preset data item information, which does not match the logic defined in the prompt. Cause: Parameters were not passed in the variable order declared in the prompt, or variable placeholders were not correctly configured in the prompt. - Phenomenon: Unable to locate the configuration entry for modifying the default message for new conversations, and the system always uses the initial default prompt. Cause: The default message configuration item is nested in the "System Configuration - Conversation Basic Settings" submenu and is not directly displayed on the main configuration interface.
- Phenomenon: After the "Text Content Extraction" node fails in a workflow, the configured "Specified Reply" does not trigger the link waiting for user input. Cause: No "Wait for User Input" component was added after the "Specified Reply" node, causing the workflow to end directly.
How to Verify Correct Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
- Initiate a test conversation, enter a query related to public data items, and verify whether the returned content includes preset structured fields such as interface addresses and update frequencies.
- Pass the
variablesparameter via an API call, and check whether variable placeholders in the prompt are correctly replaced in the conversation return result. - View the conversation detail log to confirm that the number of turns in the
messagescontext window meets the configuration requirements, and no context overflow prompt appears. - Wait one month before initiating a query, and verify whether the returned update frequency information matches the latest catalog data.
The values provided 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.