What the data for this category looks like
Data for this category primarily comes from advertising platforms, CRM systems, attribution SDKs, and form systems. Regularly produced core documents include attribution rule configuration tables, lead distribution tables, channel performance reports, and abnormal lead checklists. Data update frequencies are mostly daily or weekly. A single document typically includes fields such as channel identifier, lead generation time, assigned sales ID, and conversion amount. Field units are mostly natural numbers, timestamps, and percentages.
Constraints imposed by these characteristics on multi-turn dialogue and prompt engineering
Dispersed data sources require multi-turn alignment of field mappings across different systems. For example, channel codes from advertising platforms must be matched one-to-one with lead IDs from CRM systems. Daily or weekly update frequencies require prompts to adapt to batch data processing, avoiding overload from single calls. Fixed document structures but inconsistent field naming require multi-turn dialogue to guide unified field formatting. Time-consuming steps including duplicate lead deduplication and sales assignment confirmation require prompts to preset verification logic, reducing manual intervention steps. Strict matching of preset rules is required for channel parameter verification. Prompts must include trigger conditions for field verification.
How to set the configuration
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
messages | Concatenate in the order of attribution rules and lead data | Ensure multi-turn dialogue context is passed according to business logic, avoiding logical confusion |
variables | Inject fields such as channel ID and assigned sales ID | Adapt to the fixed field structure of documents in this category, improving matching accuracy |
| Single search limit | Top 5 entries | Data sources for this category are fixed, no excessive recall needed, reducing redundant information |
| Maximum context length | 800–1200 characters | Adapt to the typical length of attribution reports and distribution tables, reducing context load |
| Timeout duration | 600 seconds | Match the processing requirements of daily batch data, avoiding mid-process interruptions |
| Question optimization | Enabled | Automatically optimize verification question formats, adapting to multi-turn parameter verification scenarios |
Three common mistakes
- Phenomenon: Obvious output delay occurs after multi-turn dialogue completes. Cause: The timeout parameter was not adjusted, and the short timeout setting from general scenarios was used, which cannot adapt to the processing rhythm of batch attribution data.
- Phenomenon: Displayed images of channel reports are incomplete when calling the MCP tool associated with the prompt. Cause: A reasonable context interception range was not set, causing the latter half of long document data to be truncated.
- Phenomenon: Files cannot be correctly identified when passing lead distribution tables via the API interface. Cause: The platform’s required file parameter packaging rules were not followed, leading to file transfer failures.
How to confirm the configuration is correct
- Initiate a simulated daily data call, check whether the output result includes all preset attribution rule fields.
- Trigger the multi-turn dialogue parameter verification link, confirm that each round of questions can accurately match the currently processed document type.
- Adjust the timeout duration, verify that batch data processing can be completed within the set range without mid-process interruptions.
- Track a complete multi-turn dialogue via
chatId, confirm that context transfer and variable injection meet expectations.
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.