What the data for this category looks like
Core data for this category comes from project document libraries, configuration lists, meeting minutes, and test reports. Daily produced documents include completion documents, configuration manuals, training records, and acceptance certificates. Data updates are triggered at the end of a project phase or when the overall project wraps up. Documents are typically stored classified by project number, phase node, and delivering entity. Fields include project number, delivery date, signing party, version number, and no fixed mandatory units. Values must match actual project conditions. Typical users include project managers, implementation consultants, and customer archive administrators. Core work focuses on the completeness and traceability of delivery evidence.
How these characteristics impose constraints on multi-turn dialogue and prompts
Data sources for this category are scattered, and update nodes are concentrated. Multi-turn dialogue must associate document content from different phases. A stable context binding mechanism is needed. Documents contain strongly validated fields such as version number and signing party. Prompts must explicitly require checking field consistency. They must also avoid missing key deliverables such as acceptance certificates and configuration manuals. Data update frequency is tightly bound to project progress. Multi-turn dialogue must support triggering document sorting by phase. It must also retain historical interaction records for version traceability. Format differences across documents are significant. Prompts must guide a unified output structure. This structure facilitates subsequent archiving and signing processes.
How to configure settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Maximum Context Length | 8000–12000 characters | Matches the total character count of a single project’s documents, to avoid truncating key version information |
chatId Binding Rules | Generate a fixed identifier based on project number | Ensures multi-turn dialogue for the same project is associated with the same context, to avoid permission or context loss |
variables Preset Fields | Include project number, delivery phase, and document type | Passes metadata required for archiving, and supports workflow-triggered export operations |
| Multi-turn Dialogue Trigger Threshold | Auto-validate after 3 rounds of interaction | Matches the multi-phase validation requirements of project document handover |
messages Context Retention Count | Retain the last 20 interaction records | Covers the entire project cycle’s interaction process, to facilitate backtracking of version check details |
| FastGPT Version | v4.17.0 | Adapts to the context binding and workflow trigger logic of the current version |
Three common configuration errors
- A "No permission to operate this conversation record" message appears in the chat interface. The cause is that a fixed
chatIdwas not generated based on project number, leading to context association failure and failed permission validation. - The workflow fails to create a Word export download link at the bottom of the chat. The cause is that document metadata parameters were not configured in
variables, and the export trigger conditions were not activated. - Chat records are lost after page refresh when upgrading to FastGPT v4.17.0. The cause is that the
messagescontext persistence rules were not configured correctly, leading to historical interactions not being stored properly.
How to verify successful configuration
- Enter a project number and historical document keywords, initiate a multi-turn dialogue, and check if subsequent interactions associate context content for the same project.
- Trigger the preset document export workflow, and verify if a downloadable Word file link is generated at the bottom of the chat interface.
- Refresh the current chat page, and check if historical interaction records are fully retained and not displayed as a new conversation.
- Upload test documents to the document library specified by the system prompt, and check if the AI can correctly read the document content and complete field validation.
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 2026-10-19.