What this category’s data looks like
Data originates from daily business documents of skincare, haircare, makeup, and special cosmetics manufacturers. These documents include formula work instructions, weighing and feeding records, emulsification and filling records, cleaning and site clearance records, semi-finished and finished product inspection reports, and label review documents. Data sources cover registered and filed formulas, raw material safety materials, production equipment, ERP/MES systems, laboratory data, and packaging material version information. Update frequency follows each production batch or each line change. Documents contain fields such as formula raw materials, restricted substances, production parameters, packaging material claims, and batch numbers, and must strictly align with filing requirements.
Constraints on model access and configuration
The batch-based updates, filing compliance requirements, and multi-document correlation characteristics of this category’s data impose multiple constraints on model access and configuration. Batch data requires configuration that supports dynamic reading of the latest production batch documents, to prevent use of expired filing or production data. The strict verification requirement for filing-matching fields demands the model to accurately identify associated fields such as formula raw materials, restricted substances, and label claims, to avoid inconsistent filing risks. Overlapping single-batch documents and historical data may exceed the model’s context limit, so reasonable context truncation and slicing rules must be configured. Tool calls must adapt to specific scenarios including raw material review, parameter verification, to ensure call logic matches business processes.
Configuration Settings
This configuration is based on FastGPT v4.17.0. Specific parameters are listed below:
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the combined context of single-batch production documents, historical filing data, and bid documents, to avoid exceeding the model’s supported context limit |
maxTokens | 2000–3000 token | Controls the length of single output content, to ensure generated bid documents and quotations meet format specifications and content completeness requirements |
quoteMaxToken | 1500 token | Limits the length of referenced business document fragments, prioritizing retention of core verification fields such as formula raw materials, restricted substances, and filing claims |
| Workflow/API tool selection | auto | Supports automatic identification of tools corresponding to business needs, adapting to different bid stages such as formula review, parameter verification, and label checking |
temperature | 0.2–0.4 | Reduces output randomness, ensuring consistency and accuracy of results for critical links such as filing matching and field verification |
AIPROXY_API_ENDPOINT | Fill in according to deployment environment | Adapts to API access paths for local or private deployments, ensuring secure transmission of business data |
Three Common Misconfigurations
- Symptom: After multiple batch formulas and filing documents are uploaded, the conversation interface returns a context overflow error. Cause: The
maxContextparameter adapted to the batch-based multi-document characteristics of cosmetics manufacturing is not configured, and the general scenario context threshold is used directly, without reasonable slicing of long documents. - Symptom: Field errors where formula raw materials do not match filing requirements appear in generated bid documents. Cause: The
temperaturevalue falls outside the 0.2–0.4 range, leading to excessive output randomness from the model, which cannot strictly match the precise field requirements of filing data. - Symptom: Tool calls only trigger a single verification link, and cannot automatically identify the need to simultaneously review formulas and label claims. Cause:
toolChoiceis fixed to a specified tool, without adapting to the multi-link linkage requirements of bid preparation.
How to Confirm Correct Configuration
- A single batch’s formula work instruction and filing documents can be uploaded, and generated context fragments can be checked to confirm they include core business fields, and that context length meets configured requirements.
- A tool call action can be triggered, to confirm the system can automatically identify and call matching verification tools, covering links required for bids such as raw material review and label claim verification.
- Multiple test bid document fragments can be generated, and the field consistency of output results can be verified, to confirm the
temperaturevalue meets business precision requirements. - API interface access and permission verification can be tested, to confirm that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations can normally call the target model.
The values provided are common starting points and should be measured against applicable local samples.