What the Data for This Use Case Looks Like
This data primarily comes from GitHub or Gitee Issues, release notes, user environment information, and code repositories. Its update frequency is daily or weekly. Daily maintained documents include Issue templates, tag rules, response records, and problem reproduction instructions. Data fields include Issue numbers, classification tags, priority levels, reproduction steps, user environments, and more. The structure of individual data entries centers around problem descriptions and processing workflows. This explanation is based on the functional logic of FastGPT v4.17.0.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
The daily or weekly update frequency of this category’s data requires that dialogue context caching and processing match this rhythm, to avoid interference from redundant or expired data. Issue data from GitHub or Gitee has a fixed structure. Multi-turn dialogue must automatically associate fields such as Issue numbers and tag rules, to reduce manual repetitive input. Reproduction instructions and tag rules from daily maintained documents must be embedded into prompts, to guide dialogue to automatically complete issue triage and information completion. The public nature of data sources requires dialogue context to filter sensitive information, to comply with privacy norms for open source communities.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 800–1200 characters | Matches the average length of single GitHub Issue content, to avoid model context overflow |
| Number of Retained Conversation History Entries | First 6 entries | Aligns with typical interaction rounds for daily Issue handling, retains key problem and response records |
chatId Validity Period | 7 days | Matches the weekly update frequency of category data, fully retains the processing workflow for single Issues |
variables Bound Fields | Issue number, reproduction instructions | Associates use case-specific metadata, automatically supplements dialogue context |
messages Format Validation | Organized in the order of Issue fields | Unifies display and processing logic for conversation history |
| Prompt Embedding Rules | Reference local tag rules and Issue templates | Guides dialogue to automatically complete problem classification and information verification |
Three Common Configuration Mistakes
- Form input content cannot be displayed in dialogue. The cause is failure to bind form fields to the
variablesparameter, which prevents the dialogue context from reading configuration data. - File links and user question configuration items in the dialogue module do not take effect. The cause is failure to specify bound fields according to the category data structure, which prevents prompts from calling corresponding document content.
- Dialogue role settings are incorrect. The cause is failure to match the interaction logic of Issue triage, confusing the role definitions of system prompts and user inputs.
How to Verify Successful Configuration
- Submit a simulated Issue data entry, check whether the bound
variablesfield information is automatically loaded in the dialogue. - Send multi-turn interaction content, confirm that historical conversations associated with the
chatIdare normally loaded and displayed. - Input a question that includes classification requirements, check whether the prompt guides automatic matching of preset tag rules.
- View the configuration item validity period setting, confirm that historical data within the corresponding duration will not be automatically cleared.
The values provided are common starting points and should be measured against local 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.