This configuration guide is written based on the feature logic of FastGPT v4.17.0.
What the data for this category looks like
This category’s data primarily comes from advertising platform backends, user profile databases, budget scheduling sheets, and attribution tools. Daily deliverable documents include campaign setup plans, targeting setting rules, budget allocation plans, and conversion tracking configuration items. Data update frequency is daily or triggered per individual campaign activity. Data fields include targeted audience package identifiers, budget amounts, conversion event types, attribution model parameters, and more, with corresponding units such as yuan, visits, event type identifiers, and more. This step covers account structure configuration before ad launch, distinct from post-launch campaign performance optimization services. The most time-consuming steps are audience targeting configuration, budget allocation, and conversion event validation. Configuration errors will lead to budget waste, missing conversion data, or failed campaign launch.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
This category’s data is scattered and highly correlated. Multi-turn dialogue requires pulling information across multiple data sources, so unique identifiers for each data source must be bound within the dialogue flow to avoid context confusion. Document structures are fixed and fields are clearly defined, so prompts must accurately match the field names of documents such as campaign plans and targeting settings to avoid generating content that does not conform to business format requirements. Data update frequencies are flexible, so the dialogue flow must support on-demand data refreshing and cannot rely on static caching. In addition, the consequences of configuration errors are relatively severe, so multi-turn dialogue must include a pre-validation step to verify whether budget values, targeting rules, and other items meet business requirements.
How to set the configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Bind advertising platform account ID, budget sheet path, conversion event ID | Match the scattered multi-data-source characteristics of this category, ensuring accurate retrieval of corresponding business data during dialogue |
messages | Limit the context window to the first 8 historical conversations | Avoid information overload caused by overly long contexts, adapting to the short-process business scenario of campaign setup |
chatId | Generate a unique identifier per single campaign task | Distinguish dialogue contexts for different campaign plans, avoiding parameter confusion across tasks |
| Maximum context length | 800–1200 characters | Adapt to the single-page content length of campaign plan documents, avoiding truncation of key configuration fields |
| Question optimization | Enabled | Convert colloquial questions into standard queries that match business fields, improving data retrieval accuracy |
| Pre-validation trigger | Split into budget, targeting, and conversion three links | Match the three most time-consuming configuration links of this category, pre-validating configuration legality |
Three Common Misconfigurations
- Phenomenon: When using a generic global key to initiate cross-application dialogue, the returned campaign plan data does not match the current task’s account configuration. Cause: The account identifier of the corresponding application is not bound via
chatId, causing the context to call an incorrect data source. - Phenomenon: It is impossible to configure both Chinese and English opening lines in the same workflow. Cause: No language recognition branch logic is configured in
messages, making it impossible to automatically switch to the corresponding language prompt based on user input. - Phenomenon: After importing a Word document of a campaign plan, the converted Markdown image links lack domain names. Cause: No image domain name replacement rule is configured in the document preprocessing flow, causing static links to fail to load properly.
How to Confirm Proper Configuration
- Initiate a query that includes campaign budget and targeting audience keywords, check whether the returned results match the data source content corresponding to the bound
variablesparameter. - Initiate dialogues for two different campaign tasks, check whether
chatIdautomatically switches contexts and does not mix configuration information from different tasks. - Trigger the tool call flow, check whether the output only contains organized campaign plan content with no original tool execution logs included.
- Input a mixed Chinese and English query, check whether the system automatically adapts to the corresponding language prompt logic and returns configuration suggestions that conform to business format requirements.
The values provided here 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.