Data Profile for This Use Case
The typical users of this use case are information feed optimizers, creative teams, and growth teams. Daily deliverables include creative scripts, material test sheets, delivery data reports, and iteration checklists. Data sources include advertising platforms, material libraries, user interaction data, and conversion data. Update frequency is typically daily or weekly. Common document fields include material type, delivery time slot, variable combination, conversion cost, and additional relevant metrics. Content length per document varies based on test scale. Most content consists of fragmented test records and aggregated data.
Constraints on Context and Token Workflows
Fragmented test records and multi-source data require the context window to cover complete variable combinations and historical iteration logic. This prevents loss of critical comparison information due to context truncation. Frequently updated delivery data and test results need dynamic context range adjustments. This stops token consumption from exceeding set thresholds. Mixed retrieval across multiple document types requires limiting the token length of individual citations. This prevents redundant content from crowding out valid context space. Errors in creative testing directly impact delivery performance. Context and token configurations must be strictly controlled. This prevents test conclusion bias from missing content or token overages.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Information feed creative testing requires coverage of multiple variable combinations and historical iteration records. A complete context ensures coherent review logic |
quoteMaxToken | 1500–2000 token | Limits the length of individual cited materials or data. This prevents overall token overflow from overly long single content entries |
| Chunk Length | 4000–5000 characters | Matches the single-page content length of creative scripts and test sheets. Reduces token waste from fragmented retrieval |
| Single Search Limit | Top 6 entries | The number of variable combinations for information feed testing is limited. Excessive retrieval results add context redundancy |
Common Misconfigurations
- Setting
quoteMaxTokento 1500 still results in individual cited content exceeding the limit. The cause is failure to synchronously adjust the knowledge base chunk length. This means retrieved chunks themselves exceed thequoteMaxTokenthreshold. - Workflows cannot clear context history per preset conditions. The cause is incorrect binding of context trigger nodes and judgment conditions, or failure to use the correct version of context reset configuration.
- Token usage for individual question-and-answer sessions cannot be viewed. The cause is failure to enable global token statistics logs, or failure to enable the statistics feature in the corresponding panel for FastGPT v4.17.0.
How to Verify Proper Configuration
- View the global token statistics panel in FastGPT v4.17.0. Confirm that token consumption values for each question-and-answer session match the configured
maxContextandquoteMaxTokenranges. - Launch a test query with multiple sets of creative variables. Verify that the length of retrieved cited content does not exceed the
quoteMaxTokensetting. - Trigger the condition judgment node in the workflow. Confirm that context history can be retained or cleared per preset rules.
- Adjust the knowledge base chunk length. Verify the completeness of retrieval results and the rationality of overall token consumption.
The values provided are common starting points. They 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.