What data for this category looks like
Data for this category comes primarily from code repositories, documentation site build logs, user feedback, and version release records. Routinely maintained documentation includes installation guides, API documentation, migration guides, and FAQs. These documents are stored sorted by document type and version number. Updates follow a weekly schedule or are triggered by version releases. Core fields for individual documentation entries include version identifier, update time, associated code branch, and user feedback tags.
How these characteristics constrain multi-turn dialogue and prompts
The data characteristics of this category create constraints for multi-turn dialogue and prompts across three dimensions. First, data sources include version release records and code repositories. Multi-turn dialogue must link to the context of the current document version to avoid incorrect guidance across versions. Second, updates follow a weekly schedule or are triggered by version releases. Dialogue context requires regular refreshing to prevent loading outdated documentation content. Third, document types are diverse. Prompts must adjust output formats based on different types such as installation guides and API documentation, to ensure alignment with user query scenarios. Additionally, user feedback and build logs impact dialogue error correction logic. Historical interaction information must be retained to accurately adjust subsequent replies.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
messages | Retain the most recent 15–25 turns of dialogue context | Documentation updates occur weekly or per version; avoids expired context interfering with current queries, aligns with FastGPT v4.17.0 context management specifications |
variables | Inject current document version and document type variables | Data sources include version release records and document types; requires linking prompt configuration for corresponding scenarios |
chatId | Bind to documentation site-specific session ID | Must distinguish dialogue contexts across different documentation sites to prevent mixing of session data |
| Context refresh interval | Automatically refresh context cache every 7 days | Matches weekly update cadence, ensures loaded document content uses the latest version |
| Maximum token count per single dialogue | 8000–12000 tokens | Matches average length of daily documentation, avoids exceeding model context limits |
| Prompt template matching rule | Match document type via query keywords | Daily documentation includes multiple types, requires precise matching of corresponding output templates |
Three common errors
- Phenomenon: After selecting an Ollama-compatible model, preset guidance prompts do not take effect. Cause: Guidance prompt configuration parameters were not injected into
variables, resulting in prompts not being loaded correctly. - Phenomenon: Created dialogue applications cannot be connected to integrated plugins. Cause: The session identifier of the corresponding plugin was not bound via
chatId, resulting in context mismatch with the plugin. - Phenomenon: Using an API key for a knowledge base dialogue application still prompts unauthorized access. Cause: Authorization verification fields were not correctly passed in
messages, resulting in session permission verification failure.
How to confirm configuration is complete
- Initiate a query related to installation documentation, check if the reply includes accurate installation guidance for the current version, to verify that context refresh and version association configurations are active.
- Switch to different types of AI models, then initiate a query related to API documentation, confirm that the reply is based on the output of the new model, to verify that model switching configurations are active.
- Submit a test for an authorization error scenario, confirm that the authorization verification logic triggers normally, to verify the correctness of the API key configuration.
- View session logs, confirm that
chatId,messages, andvariablesparameters are all passed correctly, to verify that basic configurations are correct.
The values provided here 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.