What the Data for This Category Looks Like
Reference only; verify against the target FastGPT release and deployment documentation.
What Constraints Do These Characteristics Bring to Multi-turn Dialogue and Prompt Words
Daily updated multi-source data requires multi-turn dialogue to associate context by procurement project category, preventing rule conflicts across projects. Documents with mixed structures require prompt words to clearly define the retrieval scope, only accessing documents exclusive to government procurement. Variations in fields across multiple entities require actively confirming the current interacting entity’s role during dialogue, avoiding parameter confusion. The large volume of documents involved in a single interaction requires limiting the effective data length of the context window, preventing exceedance of the model’s processing limits.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Window | First 12000 characters | Matches the single-turn interaction data volume of government procurement documents, avoids exceeding the model's processing limit |
chatId Binding Rule | Bind by procurement project number | Ensures correct association of dialogue history for the same procurement project, avoids data confusion across projects |
messages Context Truncation Threshold | Retain 7 days of dialogue records | Matches the conventional processing cycle of government procurement business, filters expired and invalid history |
variables Preset Parameters | Preset procurement project type, regulatory department role | Provides fixed business background for prompt words, reduces repeated input |
| Single Retrieval Document Limit | First 8 entries | Balances retrieval comprehensiveness and model context load, meets conventional retrieval requirements for government procurement documents |
Three Common Misconfigurations
- Symptom: Unable to query dialogue history records in MongoDB. Cause: Did not bind
chatIdby procurement project number, resulting in dialogue history being stored under the wrong project index. - Symptom: Knowledge base search works correctly during debugging, but AI dialogue responses do not reference government procurement documents. Cause: Prompt words did not clearly limit the retrieval scope to government procurement documents, calling data sources from non-target categories.
- Symptom: Unable to implement combined output of multiple sets of prompt words for the same input. Cause: Did not configure multiple sets of preset prompt words via the
variablesparameter, and did not enable the link settings for multi-turn calls.
How to Verify Successful Configuration
- Access the dialogue history management interface, enter a procurement project number, verify that only interaction records for the corresponding project are displayed.
- Submit a question containing government procurement-specific terminology, check that the returned results only reference content from government procurement documents.
- Trigger the multi-set prompt word calling process, verify that the input content is synchronously applied to all preset prompt words.
- Initiate consecutive multi-turn questions, verify that the context automatically truncates expired records according to the preset cycle.
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 2026-09-28.