What the data for this category looks like
This category of data mainly comes from advertising platform backends, customer qualification documents, contract systems, and publicly available regulatory rules. Daily processed documents include advertising review forms, qualification attachments, delivery records, and rectification notices. Data updates follow single advertising campaigns or monthly cycles. Relevant roles including advertising compliance, agency legal affairs, and brand marketing are responsible for collection. Data fields include delivery time periods, qualification numbers, review results, rectification requirements, and others. There is no unified fixed format, and it adjusts according to the specific scenario of a single campaign.
What constraints these characteristics impose on the context and token link
Decentralized data sources lead to an uncertain number of multi-source documents that must be called in a single operation. Reasonably limit the context loading scope to avoid excessive token consumption. Updates follow campaigns or monthly cycles. The number of documents associated with a single context changes with campaign scale. Adapt to fluctuating token consumption rhythms. Most documents have no unified format and contain a large amount of unstructured content. Avoid redundant text that occupies too many tokens. Time-sensitive documents such as delivery records and rectification notices must load the latest content first. Prevent tokens from being occupied by expired data. At the same time, compliance scenarios require complete evidence chains. Do not arbitrarily delete valid context. Balance token usage and evidence integrity.
How to configure the settings
These configurations are based on FastGPT v4.17.0, as detailed below:
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the total token consumption of multiple compliance documents associated with a single advertising campaign, balances evidence retention and platform token limits |
quoteMaxToken | 1500–2000 token | Matches the typical length of single documents such as advertising review forms and delivery records, prevents a single document from occupying too much context space |
| Context recall count | Top 6 entries | Covers core compliance evidence for a single campaign, avoids excessive redundant data occupying tokens |
| Single document chunk length | 1000–12000 characters | Adapts to the typical paragraph structure of compliance documents, reduces token loss from context splicing |
| Token overflow handling rules | Calibrated based on actual testing | Meets the evidence retention requirements of compliance scenarios, prioritizes retaining the latest delivery records, review results, and rectification notices, truncates non-core historical data |
Three common mistakes
- Phenomenon: After deploying bge-reranker, compliance documents associated with the context fail to load correctly. Cause: No correct configuration parameters added under the environment section of docker-compose.yml. This causes a mismatch between the model and context token configuration, corresponding to community issues related to docker deployment.
- Phenomenon: The context recall count does not match the configured value, and the number of returned results deviates significantly. Cause: The recall threshold is not adjusted based on the evidence coverage requirements of the advertising compliance scenario. The general scenario's recall count is directly applied by mistake.
- Phenomenon: Token configurations are not synchronized after switching teams. Cause: Token configurations are not bound and stored with team data. This causes compliance scenario configurations for different teams to fail to take effect independently, corresponding to community issues related to team data storage.
How to confirm the configuration is complete
- Context loading logs on the FastGPT platform can be reviewed to confirm that recalled documents match the review form and delivery records of the current advertising campaign. The number of recalled entries can be checked against the configured requirements.
- A query in the compliance scenario can be initiated to verify that token consumption values fall within the range set by
maxContext, with no abnormal overflow prompts. - Switching between different team accounts allows confirmation that token configurations are synchronized with team data, with no cross-team configuration confusion.
- Uploading a single compliance document allows verification that the token length after chunking falls within the set interval of
quoteMaxToken.
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.