Reference only; verify against the target FastGPT release and deployment documentation.
What data looks like for this category
Commodity trade declaration material and case file data mainly comes from business documents such as trade contracts, customs declarations, ownership certificates, and settlement documents. It is generated and updated with individual trade processes, with no fixed batch update cycle. Documents include structured multi-column tables, scanned PDF files, and structured forms. Fields include goods name, specification, quantity, unit price, origin, customs declaration number, bill of lading number, and more. Units include tons, cubic meters, US dollars, RMB, and others.
What constraints these characteristics impose on model access and configuration
Multi-column structured documents require configuration adjustments to support multi-field splitting, to avoid automatic segmentation disrupting column correspondence. Scanned case files require enabling visual recognition capabilities to extract text. Individual business documents have many fields and high information density, requiring context windows adapted for long text. Sensitive information such as customs declaration numbers and ownership information requires additional filtering rules. When accessing custom channels, format verification logic for different documents must be matched to ensure parameters adapt to business data volume.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the context requirements of multi-field, long-text trade documents |
maxTokens | 2000–3000 token | Controls the output length of single review results, to avoid exceeding interface limits |
quoteMaxToken | 1500–2000 token | Retains sufficient case file original text fragments for review basis matching |
vision | Enabled | Supports text extraction from scanned case files such as customs declarations and ownership certificates |
temperature | 0.1–0.3 | Reduces randomness to ensure consistency and compliance of review results |
AIPROXY_API_ENDPOINT | Fill in the actual deployed proxy address | Adapts to the interface call path for custom channels |
AIPROXY_API_TOKEN | Fill in the assigned secret key | Completes identity verification for custom channels |
Three common configuration errors
- A 400 error is returned after calling a custom channel, prompting that the context length exceeds the limit. The cause is failure to adjust the
maxContextparameter for long commodity trade documents, resulting in the passed case file text exceeding the interface limit. - Automatic segmentation of multi-column Excel files is chaotic, with fields corresponding to each row split into different blocks. The cause is failure to adapt the splitting rules for multi-column structured documents, using the default automatic segmentation logic which leads to loss of column correspondence.
- Sensitive word filtering fails, with compliance-related trade information misidentified or not filtered. The cause is failure to configure dedicated filtering rules for commodity trade-specific sensitive words such as customs declaration numbers and ownership information, only using a general sensitive word library.
How to confirm configuration is complete
- Upload a single multi-column Excel trade document, check that the segmentation result retains the complete field combination for each row, with no cross-row or cross-column splitting.
- Upload a scanned customs declaration file, confirm that the model can extract key information such as customs declaration number and goods name.
- Call the custom channel interface, check that the token count of the returned result falls within the configured
maxTokensrange, with no truncation. - After configuring sensitive word filtering rules, input test text containing sensitive information, confirm that the filtering result meets expectations.
The values provided 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 2026-09-28.