What this category of data looks like
Data primarily comes from review archives for survey and design projects, including survey outlines, geotechnical investigation reports, preliminary design drawings, review application forms, approval opinions at all levels, and more. Update frequency follows project review milestones; archive materials for individual projects are supplemented and modified alongside approval stages. Document structure includes structured fields and unstructured attachments. Structured fields include project number, survey phase, review batch number, approval status, and others. Unstructured attachments are mostly PDF-format design documents and CAD drawings. Field units involve square meters, meters, project section numbers, and similar.
What constraints do these characteristics impose on the multi-turn dialogue and prompts workflow
The presence of structured fields requires that multi-turn dialogue gradually guide users to confirm required items such as project number and survey phase, to avoid missing declaration requirements. Most unstructured attachments are large files, which limits the context length that can be carried in a single dialogue turn; the scope of submitted archive materials must be strictly controlled. The characteristic that review materials are updated alongside approval milestones requires that prompts explicitly specify calling the latest version of archive data first, to avoid using expired content. Declaration material formats must comply with industry review specifications; prompts must consistently match the field order and filling requirements of the review form.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind project number, survey phase variables | Automatically populate structured declaration fields during multi-turn dialogue to reduce manual input |
messages | Limit historical turns to 3–5 | Adapt to the context length of survey and design archives, avoiding interference from redundant information |
chatId | Bind project-specific ID | Associate archive materials for the corresponding project, ensuring accurate matching of dialogue context |
| Maximum context | 8000–12000 characters | Match the average character count of a single batch of declaration materials, ensuring complete loading of key content |
| Single recall limit | Top 6 archive documents | Control the number of documents loaded per turn to avoid context overflow |
| Question optimization | Enabled, set to 2 optimization passes | Adapt to the step-by-step confirmation process for multi-field declarations, improving dialogue efficiency |
Reference only; verify against the target FastGPT release and deployment documentation.
Three common configuration mistakes
- Symptom: The workflow hangs or terminates directly after reaching the AI dialogue step. Cause: The historical turn limit for
messageswas not set, causing context length to exceed processing limits. - Symptom: Declaration material key fields are missing from dialogue response results. Cause:
variableswere not bound, and project-specific information was not passed to the dialogue context. - Symptom: Non-streaming API returns or no results during API calls. Cause:
chatIdwas not configured to associate archive data for the corresponding project, resulting in recalled documents that do not match the current review scenario.
How to verify correct configuration
- Initiate a test dialogue, enter the project number and survey phase, confirm that bound variables are automatically populated into the dialogue context.
- Upload a single batch of declaration materials, check whether the number of documents loaded by the dialogue matches the single recall limit setting.
- Test consecutive multi-turn questions, confirm that the dialogue historical turn limit is active and no redundant information interferes.
- Call the API to initiate a dialogue, confirm that the returned context includes archive materials for the current project.
The values provided here are common starting points and should be evaluated against samples relevant to the specific use case.
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.