What the data for this category looks like
Daily documents for backend service development include interface design documents, database change tickets, code review records, and release notes. Data sources typically include code repositories, API gateway logs, databases, and configuration centers. Update frequency follows a daily or per-version release cycle. Document fields mostly include interface request parameters, response codes, transaction boundaries, and exception handling logic, among others. Units include request timeout (seconds), data storage capacity (MB), and interface call frequency (times/minute), among others. The structure primarily uses structured fields, supplemented by natural language descriptions of business rules.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering stage
Documents for backend service development have high structural complexity and are tied to exclusive business data. This requires multi-turn dialogue to accurately match core fields such as interface contracts and transaction boundaries, so the context scope must be limited to avoid introducing redundant historical logs or change tickets. Additionally, document update frequency is high, so the retention length of dialogue history must be controlled to prevent context overflow that causes model output deviations. Furthermore, data sources involve configurations and logs from multiple systems, so prompt engineering must inject exclusive business parameters to ensure the generated requirements and design documents comply with the current project’s technical specifications.
How to Configure Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Matches the typical length of a single interface design document for backend services, and aligns with the model context limit of FastGPT v4.17.0 |
| Number of retained dialogue history entries per session | Top 5 entries | Filters redundant code review records and historical logs, focusing on core content for current requirement drafting |
chatId binding rule | Bind to a single requirement drafting session | Isolates contexts for different interface designs, avoiding interference from irrelevant cross-session information on generation results |
messages role restriction | Only retain user and assistant roles | Filters irrelevant preset system role prompts, focusing on the generation logic for requirements and design documents |
variables injection toggle | Enabled | Passes exclusive data such as current project configuration center fields and code repository addresses, enhancing the targeting of prompt engineering |
| Session log storage | Enabled | Retains complete multi-turn dialogue records to facilitate subsequent troubleshooting of output deviations |
Three Common Configuration Mistakes
- The model only outputs Chinese even when the prompt explicitly requires English output. Cause: No language restriction parameter is injected into
variables, or no explicit output language is specified in the system prompt ofmessages, causing the model to default to the high-frequency language in its training data. - Parsing errors occur when uploading long documents such as database change tickets. Cause: No chunking rules configured to match backend service document formats, leading to incorrect truncation of long text and loss of key fields related to transaction boundaries.
- Internal dialogue details cannot be viewed after application invocation. Cause: Session log storage configuration is not enabled, or
chatIdis not correctly bound to the application invocation chain, leading to failure of proper log aggregation.
How to Verify Successful Configuration
- Upload an interface design document, and check whether the model output includes core backend service fields such as request parameters, response codes, and transaction boundaries.
- View the session details page, and confirm that the
messageslist only retains user and assistant interaction content, with no redundant information from irrelevant roles. - Trigger an application invocation, and check whether
chatIdis correctly displayed in the session details and that logs are fully recorded. - Inject a
variablesparameter that specifies English language restrictions, and verify that the model output meets the preset language requirements.
The values provided are common starting points and should be measured 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 2026-10-19.