What the data for this category looks like
Daily documents for this category typically include growth experiment plans, user segmentation tables, outreach copy, and retention analysis reports. Data sources include user behavior logs, push systems, experiment platforms, and CRM systems. Update frequencies are mostly daily or weekly. Data fields include user segmentation tags, outreach channels, experiment variables, retention rate metrics, and more. Common units are person-times, percentages, and outreach counts. The most time-consuming daily work steps are user segmentation, outreach rhythm design, and experiment result attribution.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Data sources come from multiple internal systems. Multi-turn dialogue prompts must adapt to the field naming rules of each system, to prevent errors in segmentation rule generation caused by field mismatches. Daily or weekly update frequencies require dialogue context to support historical data recall by time periods. This avoids analysis bias from relying only on recent conversations. The variety of daily document types requires prompts to use distinct processing logic. This adapts separately to the validation rules of user segmentation tables, outreach copy, and retention analysis reports. Serious error consequences require the dialogue link to have clear error trigger conditions. This prevents incorrect results from directly impacting user operation actions.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 8000–12000 characters | Adapts to processing needs for long documents such as retention analysis reports and user segmentation tables |
messages | Retain the last 20 conversation turns | Matches standard conversation cycles for daily or weekly operation analysis |
variables | Auto-populate based on document type | Adapts to field requirements for different documents such as growth experiment plans and outreach copy |
| Tool Call Timeout | 600 seconds | Adapts to data pull durations from user behavior logs and CRM systems |
| Abnormal Result Trigger | Retry triggered after 2 consecutive empty results | Corresponds to scenarios where the large language model returns empty or throws an error |
| Version Adaptation | Use FastGPT v4.17.0 | Ensures compatibility and functional completeness of configuration items |
Three common mistakes
- Empty charts are generated after tool calls. The cause is that the prompt fails to explicitly require binding field parameters from the user segmentation table, leading to missing necessary segmentation tag data during tool calls.
- No error handling is triggered after the large language model returns empty or throws an error. The cause is that no abnormal result trigger rules are configured, and empty results are directly returned to the front-end page.
- Conversation records cannot be deleted via POST request. The cause is that the
chatIdparameter is not passed correctly, resulting in mismatched conversation identifiers and failed deletion operations.
How to confirm the configuration is correct
- Initiate a query that includes user segmentation table fields, and check if the dialogue context automatically associates historical conversation analysis results.
- Simulate a scenario where the large language model returns empty, and confirm if the preset retry or fallback process is triggered.
- Call the POST request with the correct
chatIdparameter, and verify if conversation records can be deleted normally. - After configuring variable injection rules, upload an outreach copy document, and check if the prompt automatically populates the corresponding channel fields.
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.