This document is written for FastGPT v4.17.0.
What the Data for This Category Looks Like
Technical documents for pulp and paper scenarios include batching sheets, beating records, paper machine operation records, online quality curves, laboratory reports, and sheet break and product change records. Data sources include wood pulp and waste paper batch ledgers, DCS/QCS control systems, paper machine online measurement equipment, laboratory testing systems, energy and water treatment systems. Data update frequencies cover three dimensions: real-time, per shift, and per roll. Core fields include pulp ratio, beating degree, paper machine speed, grammage, and moisture content, with corresponding units of %, °SR, m/min, g/㎡, and %.
Constraints for HTTP Interfaces and External Systems
Real-time quality data requires interfaces with low-latency response to avoid disrupting continuous paper machine production. Batch per-shift and per-roll records need interfaces that support paginated pulling or bulk submission to prevent overload from single large transfers. Field differences across documents require interfaces to support dynamic parameter mapping, to adapt to field formats for documents like batching sheets and quality curves. High-priority requirements for emergency records such as sheet breaks mean interfaces must support configurable trigger priorities, to prioritize processing of abnormal data.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {AIPROXY_API_TOKEN} | Complies with identity authentication standards for external industrial systems, meets interface security requirements for pulp and paper systems |
| Request timeout | 30–60 seconds | Adapts to response latency needs for real-time quality data, avoids disrupting continuous paper machine operation |
variables | Bind corresponding fields of documents such as batching sheets and beating records | Enables automatic mapping of body parameters to business document fields, meets dynamic parameter transfer requirements |
responseData | Extract the first 10 matching core business fields | Balances data processing efficiency and review completeness, adapts to bulk data scenarios for pulp and paper |
| Request batch size | 50–100 records per batch | Matches the record volume range per paper roll, balances interface load and transmission efficiency |
Three Common Configuration Mistakes
- Skipping the HTTP request node during workflow runtime and directly generating AI responses. Cause: The HTTP request node was not set as a pre-execution node for the workflow, or the trigger rule was not configured via
variables. - Empty body field for HTTP requests, making it impossible to obtain paper machine operation-related data. Cause: Fields from external documents were not bound to workflow
variables, leading to incorrect parameter transmission. - Interface returns 401 Unauthorized status code. Cause: Incorrect token format in the
Authorizationheader, missing the Bearer prefix, or an invalid token value.
How to Verify Proper Configuration
- View workflow runtime logs to confirm the HTTP request node successfully sent the request and returned a 200 status code.
- Check that fields extracted via
responseDatainclude core business data for pulp and paper scenarios, such as pulp ratio and beating degree. - Simulate triggering a batching sheet review workflow to confirm the workflow executes the HTTP request and AI review steps in sequence.
- Call the health check interface of the external interface to verify that the token in the
Authorizationheader is valid.
The values provided are common starting points and should be measured against the reader's own samples.