What the data for this category looks like
Data for this category primarily comes from advertising platforms, CRM systems, attribution SDKs, and form systems. Data update frequency is typically daily or weekly. Daily associated documents include attribution rule configuration tables, lead distribution tables, channel effect reports, and abnormal lead checklists. Data fields include channel unique identifiers, lead source parameters, sales attribution accounts, conversion timestamps, lead status, and more. There is no unified cross-system field naming standard, so alignment must be achieved via custom mapping rules.
What constraints do these characteristics impose on the multi-turn dialogue and prompt engineering link
Because data sources are scattered and field naming is inconsistent, multi-turn dialogue must include field mapping verification logic in each interaction to avoid attribution errors caused by cross-system field differences. Data update frequency is daily or weekly, so prompts must support dynamic loading of the latest attribution rule documents as context to ensure responses match currently active configurations. Daily associated documents have large volume, so a reasonable upper limit must be set for the multi-turn dialogue context window to avoid redundant data interfering with core logic. Channel parameter verification and duplicate lead deduplication are the most time-consuming steps, so prompts must prioritize triggering corresponding verification processes to convert manual intervention pre-steps into automatic checks.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to the unique identifier of channel leads | Ensure coherent context for multi-turn dialogue of the same lead |
messages | Store grouped by channel type, maximum 5 historical interactions per group | Avoid confusion across channel dialogue contexts, control per-group data volume |
variables | Pass the active version number of current attribution rules | Ensure prompts call the latest rule configurations |
| Maximum context length | First 8000 characters | Based on FastGPT v4.17.0 context management rules, adapts to average volume of daily attribution documents and reports |
| Timeout threshold | 60 seconds | Matches typical response duration of channel data interfaces |
| Question trigger mode | Trigger via keyword matching | Supports one-click jump to dialogue flows for custom questions |
Three common mistakes
- Phenomenon: Online dialogue interface returns empty data or abnormal status codes. Cause:
chatIdis not correctly bound to the unique identifier of channel leads, causing context to fail to associate attribution data for the corresponding lead. - Phenomenon: Custom questions cannot trigger preset flows with one click. Cause: The
variablesparameter is not passed with the currently active attribution rule version, so prompts cannot match the correct trigger logic. - Phenomenon: All results are output at once after a short text query, without streaming segmented returns. Cause: A reasonable context window is not set based on channel data volume, causing the system to load all associated documents at once before outputting results.
How to confirm configurations are set correctly
- Generate a test lead carrying channel parameters and sales attribution information, initiate an interaction via the dialogue interface, and verify that
chatIdis correctly bound to the lead identifier. - Upload the latest attribution rule document, pass the version number via the
variablesparameter, initiate a test query, and verify that responses match the currently active rules. - Initiate a short text test query with fewer than 10 characters, observe whether output uses streaming segmented returns, and confirm that the context window is set appropriately.
- Click a preset custom question button, verify that it directly jumps to the corresponding dialogue flow and loads the preset prompt.
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.