Pulp and Paper Bidding Documents and Quotation Preparation: Deployment and Upgrade

Business data for the pulp and paper category comes primarily from wood pulp and waste paper batch ledgers, DCS/QCS control systems, on-paper

What the data for this category looks like

Business data for the pulp and paper category comes primarily from wood pulp and waste paper batch ledgers, DCS/QCS control systems, on-paper measurement equipment, laboratory testing systems, and energy and water treatment systems. Daily stored documents include pulp preparation sheets, beating operation records, paper machine operation logs, online quality curves, laboratory quality inspection reports, and sheet break and product change ledgers. Data update frequencies cover real-time, per shift, and when each paper roll is completed. Departments involved in pulp preparation, paper machine operation, and quality control generate corresponding field data. This includes pulp ratio parameters, sheet grammage, moisture content, and sheet break duration.

What constraints these characteristics impose on deployment and upgrade

Data sources for this category are scattered, and update rhythms vary significantly. Real-time production data requires low-latency cache and index links during deployment. This avoids synchronization delays that affect the timeliness of bidding documents and quotation preparation. Coexistence of multiple document types requires the upgrade process to support unified parsing rules for structured ledgers and unstructured curves and reports. This prevents field extraction discrepancies across different document types. Dynamic adjustment of data fields along production links requires reserving flexible field mapping configuration items during deployment. Upgrades must be compatible with old data formats to prevent historical bidding data from being unusable. High-speed continuous production brings high data throughput. Sufficient storage and computing resources must be reserved during deployment to avoid data accumulation that affects system operation stability.

Configuration settings

This configuration applies to FastGPT v4.17.0. Specific configuration items are listed below:

Configuration ItemRecommended SettingRationale
REDIS_URLredis://:custom password@redis host address:6379/0Real-time production data for pulp and paper requires low-latency caching. This configuration specifies the Redis connection address, authentication information, and database index to meet real-time data synchronization requirements.
DB_MAX_LINK20–30The volume of documents and data for this category grows with production batches. This value balances connection resource usage and concurrent access capabilities, based on actual measurements.
MONGODB_URImongodb://username:custom password@mongo host address:27017/fastgpt?authSource=adminStoring bidding documents and historical production data requires a highly reliable document database. This configuration specifies authentication information and the target database name to meet multi-type data storage requirements.
STORAGE_S3_ENDPOINTofficial access address of object storage serviceThis configuration specifies the object storage access endpoint to ensure stable upload and download of unstructured large-volume documents such as online quality curves and laboratory reports.
ROOT_KEYrandom string of no less than 16 charactersThis configuration specifies the system root key to prevent the root account from triggering the default reset mechanism and ensure access security after deployment.
FE_DOMAINlegitimate domain address for system external accessThis configuration generates legitimate system callback and login redirect URIs, avoiding incorrectly formatted access links.

Three common mistakes

  • Symptom: Container pull of the Redis image fails during deployment, or logs prompt Redis connection timeout or authentication failure after startup. Cause: The access password, host address, or port in the REDIS_URL configuration is not correctly set, causing FastGPT to fail to establish a cache connection.
  • Symptom: The system returns {"code":500,"message":"URI malformed"} error when logging in. Cause: The FE_DOMAIN configuration contains invalid characters or is not set to a valid domain name, causing the generated redirect URI to have an incorrect format.
  • Symptom: The root account password is automatically reset to 123456 approximately every 1 day. Cause: The ROOT_KEY parameter is not configured, and the system uses the default root key to trigger the built-in temporary password reset mechanism, causing the password to revert to the default value periodically.

How to confirm the configuration is correct

  • Run the docker ps command to confirm that dependent containers such as Redis and MongoDB are running, with no abnormal restart records.
  • Access the configured FE_DOMAIN address, try logging in to the system with the root account, and verify that there are no 500 errors or format error prompts.
  • Upload a pulp preparation sheet document to test whether the system can correctly extract fields such as pulp ratio and batch number, and verify that the data parsing and storage process is normal.
  • Check the system operation logs to confirm that there are no error prompts such as Redis connection failure or database connection abnormality.

The values provided are common starting points and should be evaluated against the reader's own samples.