Tool Calling and Plugins for Snack Food Intelligent Due

What the Data for This Category Looks Like

Data for snack food intelligent due diligence reports comes from four main sources:

The National Food Safety Sampling and Inspection Information System
Public product compliance documents from food production enterprises
Supply chain raw material traceability platforms
Product detail pages on e-commerce platforms

Three data update cycles apply:

Regulatory sampling data is updated monthly
Enterprise new product documents are updated when products launch
E-commerce sales-related data is updated weekly

Document structures use structured tables primarily. Fields include product name, ingredient composition, allergen labeling, production license number, shelf life, storage conditions, and raw material batch number. Shelf life uses days or months as units. Storage conditions are enumerated values. Raw material batch numbers use string format.

Constraints on Tool Calling and Plugins

Multi-source snack food data requires cross-source data deduplication rules during tool calling. This prevents duplicate product information from interfering with due diligence results. Monthly updated regulatory sampling data requires a 30-day recent data source filter parameter during tool calling. Only the latest compliant inspection results are called. Enumerated allergen fields require plugins to match a preset allergen list when extracting ingredients. This ensures recognition results meet compliance requirements. String-formatted raw material batch numbers require field validation logic during tool calling. This filters batch information with invalid characters. Weekly updated e-commerce data requires scheduled plugin pull tasks to run once weekly. This avoids repeated pulling of old data.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`plugin_call_timeout`	`300 seconds`	Cross-source data pulling and integration for snack food typically takes 100-250 seconds. This setting reserves sufficient time to complete the full calling process
`data_source_filter_days`	`30 days`	Regulatory sampling data is updated monthly. Only the latest 30 days of compliant inspection results need to be called
`field_validation_enabled`	`Enabled`	Raw material batch numbers use string format. Field format validity must be verified to filter invalid information
`plugin_schedule_interval`	`7 days`	E-commerce-related data is updated weekly. Frequent pulling of duplicate old data is unnecessary
`rag_recall_top_k`	`Top 3 entries`	Snack food due diligence reports focus on core compliance information. Too many recall results will interfere with content generation
`max_context_length`	`1200 characters`	Core information for a single snack food product document typically falls within 800-1000 characters. This setting avoids context overflow

The parameter values provided on this page are common recommended 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 Misconfigurations

Phenomenon: Tool calling returns a 408 Request Timeout error code, and the calling task shows a failed status. Cause: plugin_call_timeout is not set to a sufficient duration. Cross-source pulling of snack food multi-source data takes longer than the default setting, causing the calling process to interrupt.
Phenomenon: Plugin execution order is disordered. E-commerce sales data is retrieved before regulatory sampling data, leading to compliance information in the due diligence report lagging behind sales data. Cause: plugin_execution_order is not configured to bind execution dependencies. Execution order is not set based on data source priority, resulting in random tool calling order.
Phenomenon: Invalid allergen information appears in the due diligence report, including undefined enumerated values or empty fields. Cause: field_validation_enabled is not enabled. Allergen field validity is not verified, leading to recognition of non-preset abnormal content.

How to Confirm Configuration Is Properly Set Up

The FastGPT tool calling log page is accessed. Recent plugin calling records are reviewed, all calls are confirmed to have no timeout errors, and calling durations are checked to match actual data pulling requirements.
A full data pull task is manually triggered. The returned raw material batch number field format is verified to conform to preset rules, with no invalid characters or abnormal content.
The plugin execution order configuration page is accessed. Execution priorities and dependencies for each tool are confirmed to be bound according to data source requirements, with no disordered situations.
A test snack food due diligence report is generated. Content for fields such as allergens and shelf life is checked to conform to preset enumerated or format requirements.

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.