What this category's data looks like
This category's data mainly comes from customer interview records, internal ticketing systems, publicly available competitor requirement pages, and product event tracking dashboards. Daily produced documents include requirement research minutes, official PRD documents, user story lists, and requirement change orders. Data is updated once per week or during each version iteration cycle. Document structures typically include fields such as requirement ID, business goal, acceptance criteria, associated business scenarios, and change version identifier. There is no unified mandatory format, and documents must align with the team's internal R&D process specifications.
Constraints for multi-turn dialogue and prompt engineering
The diversity of data sources requires multi-turn dialogue to adapt to different input formats such as colloquial interview records and structured ticketing content, to avoid prompts that only work with a single text type. Frequently updated requirement change orders can cause context bloat, so the effective range of dialogue context must be limited. Non-uniform document structures require prompts to support extraction and validation of custom fields, and cannot rely on fixed templates. Additionally, scenarios where confirming requirement boundaries takes a long time need multi-turn dialogue to gradually guide users to supplement unclear business rules, to avoid missing key information in single-turn outputs.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Max context length | 8000–12000 characters | Adapts to the standard length of a single PRD document, covers the last 3 requirement changes and core interview content, and matches the context processing limit of FastGPT v4.17.0 |
| Dialogue record retention period | 30 days | Matches the standard iteration cycle for requirement changes, retains complete requirement communication trails to facilitate subsequent backtracking of acceptance basis |
| Prompt variables | Use variables to pass the current project's PRD identifier | Quickly associate the dialogue with exclusive requirement materials, avoid cross-project context confusion, and improve the accuracy of requirement analysis |
| Knowledge base recall limit | Top 3 entries | Core reference content for requirement analysis is usually a small number of core interview minutes and historical PRDs; excessive recall will interfere with boundary condition confirmation |
Project-exclusive chatId | Bind to the unique chatId of the corresponding product | Isolate requirement dialogue contexts across different products, prevent cross-project requirement information from interfering with each other |
Three common misconfigurations
- Phenomenon: Requirement dialogue content from different projects is mixed together, or dialogue records are cleared prematurely. Cause: No exclusive
chatIdconfigured to isolate project contexts, or dialogue record retention period not set correctly. - Phenomenon: Recalled knowledge base content includes unauthorized team materials. Cause: No exclusive knowledge base permission group configured for PRD documents, causing the dialogue to call full knowledge base content.
- Phenomenon: Long-text requirement analysis task throws error "The value of \"offset\" is out of range". Cause: Single dialogue
messagesarray length not limited, causing context overflow and triggering offset validation error.
How to verify correct configuration
- The dialogue configuration page can be reviewed to confirm that the max context length value aligns with the average length of the team's current PRD documents.
- The
variablesparameter can be tested to verify that the dialogue automatically associates the corresponding project's PRD materials without mixing irrelevant content. - A dialogue containing multiple rounds of requirement changes can be initiated to check that the context only retains valid iteration content without redundant historical information interfering.
- An analysis task containing a long-text PRD can be triggered to confirm that no offset-related error logs are output.
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.