What the Data for This Use Case Looks Like
This use case’s data comes from Party building learning archives at direct and branch grain reserve depots, Party building guidance documents released by higher-level state-owned assets supervision bodies and the grain and material reserve bureau, and minutes of internal Party day activities at reserve depots. Updates occur monthly, aligned with higher-level document releases and monthly Party building work summary archiving. Individual documents range from 1000 to 3000 characters. They split into three fixed modules: Learning Requirements, Practice Guidelines, and Assessment Standards. Fields include document number, issuing entity, applicable depot hierarchy, effective date, and units such as class hours, assessment score, and batch.
Constraints for Multi-turn Dialogue and Prompt Engineering
Documents are divided by module and include applicable hierarchy fields. Multi-turn dialogue must track the user’s associated depot hierarchy and currently focused learning module to avoid invalid matching across hierarchies or modules. Monthly updated data sources require the dialogue system to clearly mark the data update cycle in prompts. This prevents users from receiving outdated information. Documents involve specific assessment units. Prompts must guide users to explicitly mention the assessment scenario or hierarchy to avoid unit confusion. Individual documents are moderately sized. The multi-turn dialogue context window must stay within a reasonable range. chatId must bind to the context chain for a single conversation to ensure consistent cross-turn information.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 8000–12000 token | Grain reserve Party building documents are moderately sized per piece. Multi-turn dialogue needs to retain 3 to 5 rounds of context without exceeding the model’s processing limit |
| Question Optimization | Enabled | User questions may vaguely reference depot hierarchy or assessment scenarios. Optimization can supplement missing key information |
| Context Binding Identifier | Bound by chatId | Ensures consistent context across multi-turn dialogue in the same scenario. Avoids cross-dialogue information confusion |
| Prompt Template Variables | Pass "depot hierarchy", "current learning module" via variables | Matches applicable hierarchy fields and module divisions in documents to improve answer accuracy |
| Single Recall Limit | Top 6 entries | The number of Party building documents is limited. Excessive recall leads to redundant context and affects model understanding |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Configuration Errors
- Symptom: Dialogue works normally during debug preview, but prompts "no knowledge base selected" after deployment. Cause: The context chain bound to
chatIdis not linked to the officially deployed knowledge base. The deployment environment fails to load the corresponding knowledge base configuration. - Symptom: Context redundancy appears after multi-turn dialogue, and answers deviate from the Party building learning theme. Cause: Maximum context length is not limited. Irrelevant information from historical dialogue is included in model processing.
- Symptom: Outdated Party building requirements appear in dialogue. Cause: The knowledge base is not synchronized according to the monthly update cycle. The data update cycle is not marked in the prompt. Users receive outdated information.
How to Confirm Successful Configuration
- Initiate a multi-turn dialogue containing depot hierarchy keywords. Check whether the
messagesfield retains the hierarchy information. - View the knowledge base synchronization log. Confirm that Party building documents from the past month have completed updating.
- Test cross-turn questions. Verify whether answers are associated with the previously mentioned learning module.
- Check whether the
variablesconfiguration item passes the applicable depot hierarchy parameters.
The values given 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 2026-09-28.