What the data for this category looks like
Engineering consulting supervision documents and materials come primarily from on-site supervision ledgers, inspection submission materials from construction parties, instruction documents issued by the client, and sub-project acceptance reports. Data updates follow project node progress, with updates completed during each round of inspections, acceptance procedures, or change processes. A single document’s structure includes fixed fields such as project number, supervision section, record date, construction location, inspection status, rectification requirements, and acceptance conclusion. Common units include "item", "copy", "square meter", and "cubic meter", standard for engineering work. A single long document may contain multiple pages of sub-content.
Constraints imposed on multi-turn dialogue and prompt engineering
Since supervision documents are stored and classified by project and section, and document formats vary slightly across different projects, multi-turn dialogue must accurately limit recall scope to avoid confusion across project documents. Single documents have lengthy content, so multi-turn dialogue context capacity must adapt to long text segments to prevent exceeding model processing limits. Fields such as rectification requirements and acceptance conclusions have clear business orientations, so prompts must explicitly specify rules for extracting or generating corresponding fields, with no generic handling available. Data updates are completed in batches alongside project nodes, so dialogue context must stay synchronized with the current project’s latest data to avoid generating content using expired documents.
Configuration Guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
messages | Retain the most recent 10-15 rounds of dialogue context | Document drafting for engineering supervision requires consistent project background; excessive historical context interferes with accurate handling of current requirements |
variables | Bind two variables: project number and supervision section | Accurately limit recall scope, only call supervision documents for the current project to avoid interference from cross-project data |
| Single recall count | Top 8 entries | Single supervision documents have lengthy content; excessive recall exceeds context capacity limits, while this count ensures coverage of core business information |
| Maximum context length | 8000-12000 token | Adapt to the characteristic that supervision documents contain multiple document fragments, ensuring complete retention of business information |
chatId | Generate a unique identifier based on project + section | Isolate dialogue contexts across different projects to prevent cross-project confusion of session data |
| Question optimization | Enabled | Optimize question phrasing using supervision industry terminology to improve recall and generation accuracy |
Three Common Misconfigurations
- Phenomenon: After increasing the single recall count, the large model response does not reference any recalled content. Cause: Only the recall parameter was adjusted, and no requirement to generate content based on recalled documents was specified in the prompt, causing the model to ignore recall results.
- Phenomenon: After switching AI models, the dialogue cannot load historical context. Cause: The
chatIdparameter was not correctly bound, resulting in failure to isolate session contexts across different models, making historical data unassociated. - Phenomenon: An unauthorized prompt appears after using the knowledge base API key. Cause: The exclusive document library for the corresponding supervision project was not bound to the current application, or the permission scope of the API key does not cover this knowledge base.
How to Confirm Proper Configuration
- Enter a query that includes a specific project number, check that recall results only include supervision documents for that project.
- View the dialogue history panel, confirm that only the most recent specified number of dialogue rounds are retained.
- Call the API interface, verify that the returned response carries the preset
variablesparameter values. - Enable the streaming output switch, confirm that dialogue content is returned segment by segment.
The values provided here are common starting points and should be measured against applicable operational 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.