Data Profile for This Category
Core data for this category originates from customer interview records, ticketing systems, public competitor pages, and analytics dashboards. Four standard document types are regularly generated: requirement research summaries, PRD documents, user story lists, and requirement change forms. Data is typically updated weekly or per version iteration. Documents include fields such as business objectives, acceptance criteria, functional boundaries, and change records. No uniform mandatory units apply, and field content is adjusted dynamically based on the current requirement phase.
Constraints on Context and Token Configuration
Heterogeneous multi-source data, phased update frequencies, and segmented field characteristics for this category create multiple constraints for context and token workflows. Multi-source interview, ticketing, and analytics data have inconsistent formats, so unified context recall rules are required to avoid wasted token consumption. Weekly or per-version update cycles require context windows to be limited to recent iteration periods, preventing expired requirement content from being called. Documents include segmented fields such as business objectives and acceptance criteria, so precise matching of corresponding segments is needed to avoid irrelevant content occupying token quotas. The dynamic nature of requirement changes requires context to flexibly adjust recall ranges, preventing outdated change records from interfering with analysis.
Configuration Setup
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
| Maximum Context Window | 8000–12000 token, calibrated via testing | Adapts to the multi-field, multi-source context content of PRD documents, avoiding token limit breaches in single calls |
| Single Segment Context Token Limit | 1000–1500 token | Splits requirement documents into reasonable segments, ensuring single-segment content fully covers individual requirement modules |
| Context Recall Count | Top 3–5 entries | Matches high-frequency associated content for requirement analysis, avoiding excessive irrelevant segments consuming resources |
| Context Time Range | Recent 1–2 version cycles | Adapts to weekly or per-version update frequencies, filtering expired requirement change records |
maxContext | Matches the maximum context window | Follows platform native parameter rules to ensure configuration takes effect |
quoteMaxToken | 1200 token | Limits token usage per recalled context segment, balancing recall accuracy and resource consumption |
Three Common Configuration Mistakes
- An error displaying Reached the max retries p occurs when the context window is configured too small. Multiple recall attempts fail to cover the full content needed for requirement analysis, triggering the retry limit.
- Recalled context includes expired requirement change forms when the context time range is not limited. Old data beyond the version cycle is recalled, interfering with current requirement judgments.
- Long PRD documents cannot be split properly when the single segment context token limit is not configured. Segments exceeding platform token limits fail to process.
How to Verify Successful Configuration
- Upload a complete PRD document, and confirm that recent requirement change records appear in the context recall results to verify the time range configuration is active.
- Review console logs to confirm single-call token usage does not exceed the configured maximum context window, verifying token quota settings are reasonable.
- Test multi-turn requirement conversations, and confirm prior requirement research summary content is correctly associated to verify the context recall logic is active.
- Check error logs to confirm no Reached the max retries related prompts appear, verifying the context configuration meets content coverage requirements for requirement analysis.
The values provided are common starting points and should be evaluated 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.