What Data for This Category Looks Like
Data for this category typically comes from ERP systems integrated with project procurement, supplier shipping documents, logistics tracking information, and device vendor backend management portals. Daily produced documents include purchase orders, arrival acceptance slips, serial number lists, and invoice materials. Fields cover purchase order numbers, device models, serial numbers, arrival dates, acceptance statuses, and supplier information. Data updates follow single-project delivery cycles. One purchase order corresponds to one data update. For regular bulk arrival scenarios, full batch data is synced once per week.
Constraints Imposed by These Characteristics on Context and Token Handling
Differences in data formats across multiple sources require field alignment before context concatenation. This prevents invalid mixed information from occupying token quotas. The single-project single-batch update rhythm requires limiting the context scope to the current purchase or arrival batch under review. This prevents expired historical data from interfering with reviews. Core fields such as device models, serial numbers, and purchase order numbers are high-priority context content and must be retained first. Non-critical logistics tracking notes can be simplified. Multi-item data in bulk arrival scenarios requires context token allocation to match the scale of items in a single batch. This prevents loading too much data at once and exceeding context limits.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 800–1200 characters | Matches the total field count of single-batch arrival data, avoids exceeding model token limits |
quoteMaxToken | 1500–2000 tokens | Prioritizes covering core fields of purchase orders and serial number lists, meets context completeness required for reviews |
| Chunk Length | 300–500 characters | Matches the average length of a single document such as a single arrival acceptance slip, prevents context breaks caused by overly fragmented chunks |
| Overlap Length | 50–100 characters | Ensures key information across chunks such as device models is not lost during splitting |
| Context Filter Threshold | Calibrated via actual testing | Filters historical batch data unrelated to the current review task, reduces invalid token consumption |
| Single Recall Count | Top 3 entries | Matches core supplier and equipment data for the current project under review, avoids recalling too many redundant entries |
This document is written based on the configuration logic of FastGPT v4.17.0.
Three Common Configuration Errors
- Failing to set context filtering when configuring
maxContext, and pulling full historical data directly. This causes duplicate device model entries in returned results, triggering database duplicate key errors. The root cause is failing to limit the context scope to the current batch under review, and including expired data in the context. - Failing to adjust chunk length, and using default values directly to process Excel source data. This causes excessive token consumption per data block, triggering token limit exceeded errors. The root cause is the chunk length not matching the average field length of single-device data for this category, leading to redundant data within blocks.
- Failing to properly configure
quoteMaxToken, leading to request retry limit exceeded errors due to insufficient token quota when calling proxy interfaces. The root cause is failing to adjust token quotas based on the total field count of core documents, causing single requests to exceed interface limits.
How to Verify Proper Configuration
- Import a single purchase order document, check that the concatenated context only includes core fields of the current batch, with no expired historical data.
- Submit a change review task, check the token consumption statistics, confirm that the value of
quoteMaxTokendoes not exceed the single request limit of the current model. - Trigger a chunk processing test, check that each data block length matches the preset chunk length, with no overly split or oversized blocks.
- Submit a test request via the proxy interface, confirm that the interface returns no duplicate entries, and that recalled content is strongly related to the current review task.
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.