What Data for This Category Looks Like
This category's data primarily comes from financial systems, project management systems, contract ledgers, and business department requirements. Daily output documents include annual budget sheets, project proposal documents, project portfolio dashboards, and investment review reports. Common fields include budget amount, project ID, priority marker, revenue expectation value, and other related items. Data updates follow monthly, quarterly, or annual cycles. Each single update covers adjusted project and budget information for the current period. Document formats and field details across different cycles remain relatively consistent.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
Data for this category originates from multiple heterogeneous systems with significant format differences. Multi-turn dialogue must retain context identifiers from different data sources. This prevents mixing of project information across systems. Data update cycles are relatively long. Prompts must explicitly specify the dataset scope for the current statistical cycle. This prevents calling expired data. Document fields include detailed items such as budget amount and priority. Multi-turn dialogue must gradually guide users to clarify field extraction rules. This ensures accuracy of statistics and reviews. Code change reviews must link project budgets and change content. Prompts must preset the association logic between projects and change tickets. This assists with matching verification.
Configuration Settings
These configurations are developed based on FastGPT v4.17.0.
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
messages | Keep the most recent 20 interaction records per conversation turn | This category has long data update cycles; excessive historical records will dilute current project context |
variables | Preset three variables: budget cycle, project type, associated system | This category's data updates by cycle; variables can quickly narrow the scope of statistics and reviews |
| Max Context | 8000–12000 token | Daily documents include multi-field tabular content, requiring sufficient context to accommodate complete data fragments |
chatId | Bind project ID as the unique identifier | Must distinguish review dialogues across different projects to avoid context interference |
| Single Dialogue Match Limit | Top 10 matched data entries | This category's documents have many fields; excessive data will exceed model processing thresholds |
Three Common Misconfigurations
- Symptom: Uploaded annual budget sheets are not included in the dialogue model's statistical scope. Returned results do not include corresponding content from the uploaded data. Cause: The prompt fails to explicitly define parsed fields and usage rules for uploaded files. The model cannot recognize the valid range of the uploaded data.
- Symptom: Calling the multimodal interface when processing project dashboard images returns a 400 invalid image error. Cause: The uploaded image format does not match the model's supported types. Or the image file size exceeds the preset threshold.
- Symptom: Review contexts across different projects interfere with each other during multi-turn dialogue. Results show cross-project budget data confusion. Cause: No unique
chatIdidentifier is bound to each dialogue. Contexts across different projects are merged for processing.
How to Verify Proper Configuration
- Upload a test annual budget sheet. Ask the dialogue to request a summary of specified fields. Check if the returned result includes corresponding information from the uploaded data.
- Call the API to initiate a multi-turn dialogue. Include the
chatIdparameter bound to the test project ID. Check if subsequent dialogues retain context information for that project. - After configuring the
variables, call the preset variables in the dialogue interface. Confirm that the system correctly reads and applies the variable values. - Test the multimodal interface by uploading a project dashboard image. Check that the returned status code is normal. No invalid image related errors are returned.
Final Note
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.