What the data for this category looks like
Data sources for snack food intelligent due diligence reports include supplier qualification documents, raw material purchase ledgers, production quality inspection records, terminal sales performance reports, third-party compliance test reports, and more. This scenario supports financial institutions’ credit due diligence for snack food enterprises.
Data update frequencies vary:
- Raw material purchase ledgers are updated with daily purchasing activities
- Production batch records are generated alongside production plans
- Terminal sales performance reports are summarized weekly
- Compliance test reports are updated immediately after each sampling inspection
Document formats include structured CSV tables, Excel reports, scanned PDF files, and more. Fields include raw material batch numbers, supplier unified social credit codes, number of qualified sampling items, terminal store codes, weekly sales revenue, inventory turnover days, and more. Some fields include unit identifiers such as kg, box, and yuan.
Constraints imposed on model access and configuration
Multi-source, heterogeneous data formats require the model access module to support parsing of multiple file types. Parsing rules adapted to different document formats must be configured.
Data with different update cycles require configured incremental sync trigger strategies. This avoids ineffective high-frequency syncs or delayed updates.
Specific field units and coding rules require preset corresponding formats in the data validation link. This prevents non-standardized data from entering the model processing workflow.
Long documents and structured content with multiple fields will consume significant model context space. Segment length and context length parameters must be adjusted to ensure processing stability.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Snack food compliance test reports often contain multi-page scanned documents, which take longer to parse. This duration covers the parsing needs of most files |
UPLOAD_FILE_MAX_SIZE | 800 MB | A single snack food due diligence report includes multiple traceability documents and reports, with a total size typically not exceeding 800 MB |
chunkSize | 1000–1500 characters | Snack food due diligence data contains structured content with multiple fields. This segment length preserves the associated information between fields |
maxContext | 8000–12000 characters | Adapts to the multi-field content length of snack food due diligence reports, preventing model context overflow |
API_BASE_URL | Fill in the full interface path of the locally deployed model | When connecting to locally deployed models such as DeepSeek8B, ensure the path includes the specific model calling endpoint |
API_AUTH_TOKEN | Fill in the authorization token obtained from the model gateway | Verifies identity permissions for model calls, ensuring data access security |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: An insufficient permissions error is returned in the FastGPT test page. Cause:
API_AUTH_TOKENis not configured correctly, or the authorization token does not have access permissions for the corresponding model. - Symptom: An HTTP 404 status code is returned when calling the model. Cause:
API_BASE_URLonly includes the basic deployment address, and does not include the specific path of the model interface. - Symptom: No streaming return results are shown when calling a custom code module in a workflow. Cause: The
stream_output_enableconfiguration item is not enabled, or the code does not return data in streaming format.
How to confirm the configuration is complete
- Enter sample snack food raw material traceability data in the FastGPT model test panel, and verify whether the model can correctly identify and return parsing results for the corresponding fields.
- Upload a multi-page snack food compliance test report, and check whether the parsing module extracts all text content from all pages completely.
- Start the configured workflow, and check the model call logs to confirm that the response format meets streaming output requirements.
- Cross-check the
API_BASE_URLandAPI_AUTH_TOKENconfiguration parameters to ensure they match the actual parameters of the model deployment or gateway.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.