What data for this category looks like
The data for this category comes primarily from the daily work outputs of internet product teams, business analysts, and product managers. This includes requirement research notes, PRD documents, user story lists, and requirement change forms. Data sources cover customer interview records, internal ticketing systems, public competitor pages, and event tracking dashboards. Update frequency follows weekly cycles or product version iterations. The most time-consuming processing steps are categorizing interview information, confirming boundary conditions, and synchronizing requirement changes. The document structure includes three core fields: business objectives, acceptance criteria, and functional boundaries. There are no uniform mandatory units, and some fields require supplementary explanations based on business scenarios. Business objectives are typically defined first before proceeding with subsequent steps. The overall confidence level of the data generally aligns with industry-wide standards.
What constraints do these characteristics impose on HTTP interfaces and external systems
The data characteristics of this category impose clear constraints on HTTP interface and external system integration. Semi-structured documents from multiple sources require interfaces to support multi-format data access, compatible with plain text, tables, and structured fields. Weekly or version-level update frequencies require interfaces to support incremental synchronization mechanisms to avoid excessive resource usage from full pulls. Core fields include acceptance criteria and functional boundaries. Interface responses must retain the original field structure, and field names or content must not be modified arbitrarily. Additionally, the data’s association with business scenarios requires external systems to pass corresponding business context parameters during calls, ensuring that Q&A results match specific requirement scenarios.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| API call timeout | 30–60 seconds | Matches the single-item processing duration of requirement documents, avoids long waits that cause external system blocking |
| Context window size | 8000–12000 token | Adapts to the average length of PRD documents and user story lists, ensuring full coverage of requirement context |
Authorization | Fixed secret key string | Complies with FastGPT v4.17.0 secure calling specifications, prevents unauthorized access |
variables | Bind business scenario identifiers | Used to pass information such as the product and version to which the requirement belongs, enabling accurate matching of corresponding knowledge base content |
responseData | Return only core fields | Reduces redundant data received by external systems, focusing on acceptance criteria and functional boundary information |
| Data source synchronization frequency | Every 12 hours | Aligns with the weekly update rhythm of this category, balancing data timeliness and resource consumption |
Three common misconfigurations
- Empty response after API call. The external system receives an empty response with no requirement-related information. The cause is failure to correctly bind the
variablesparameter and pass the product or version identifier to which the requirement belongs, so the system cannot match PRD documents and user story lists in the corresponding knowledge base. - API call timeout with 504 status code. The external system receives a timeout error after waiting beyond the preset duration. The cause is that the configured API call timeout is too short, not matching the average processing duration of documents in this category, causing the Q&A logic to be interrupted before completion.
- Chat application continues loading without response after connecting the plugin. Users see no content returned after submitting a question, and backend logs show the API call did not complete. The cause is failure to configure a reasonable data source synchronization frequency, with full pulls of historical data consuming excessive resources and causing interface response blocking.
How to confirm configurations are properly set
- Initiate an API call, check if the fields returned in
responseDatainclude core content such as business objectives and acceptance criteria. Adjust filtering rules until only the required fields are retained. - Pass different
variablesparameters when calling the API, verify that the returned Q&A content matches the requirement documents for the corresponding product or version, and confirm that context binding is working. - Simulate an update to a requirement change form, trigger data source synchronization, check if the interface can pull the latest change content, and confirm the synchronization mechanism is operating normally.
- View API call logs, confirm that the
Authorizationparameter is correctly included, and that no errors appear in the identity verification step, ensuring normal call permissions.
The values listed above are common starting points. They should be evaluated against the sample data used in the specific deployment.
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.