What the data for this category looks like
Snack food profit yield and market data comes from offline retail POS systems, online e-commerce sales backends, and supply chain inventory management systems. Update rhythms vary: offline store data syncs after daily closing, online channel data updates hourly, and cross-channel aggregated data is generated daily in the early morning. Each data document includes fields such as SKU ID, product name, packaging specification, purchase unit price, selling unit price, daily sales volume, daily sales revenue, remaining inventory, and inventory turnover cycle. Field units are as follows: unit price is yuan per packaging unit, sales volume is pieces or bags, sales revenue is yuan, and remaining inventory is kilograms or cases.
What constraints do these characteristics impose on deployment and upgrade
Snack food category data has scattered sources and distinct update rhythms. During deployment, configure cross-source data scheduling priorities and time alignment rules to avoid time deviations in cross-channel data aggregation. Individual data fields are rich, and overall data volume grows rapidly with the number of SKUs. During deployment, adjust vector storage sharding thresholds and index refresh frequencies to prevent retrieval delays. When adding new statistical dimensions or connecting new sales channels, the upgrade process must be compatible with existing data cleaning rules to avoid synchronization interruptions caused by incompatible historical data formats.
How to set configurations
| Config Item | Recommended Value | Rationale |
|---|---|---|
MONGO_CONNECTION_STRING | mongodb://username:password@host:27017/fastgpt?authSource=admin | Adapts to the database connection format for version 4.8.22, must match the parameters of the locally deployed MongoDB instance |
SYNC_SCHEDULE_CRON | 0 2 * * * and 0 * * * * configured in two groups | Offline data syncs at 2 AM daily, online data syncs hourly, matching the dual-channel update rhythm of snack foods |
PARSE_DATA_TIMEOUT | 600 seconds | Processes cross-channel aggregated data to avoid parsing timeouts caused by excessive data volume |
RECALL_TOP_K | Top 8–12 entries | Snack foods have a large number of SKUs, requiring a balance between retrieval accuracy and response speed |
MODEL_API_KEY_PATH | /etc/fastgpt/model_keys.json | Stores keys according to the official configuration path for version 4.8.22, facilitating unified management during upgrades |
UPLOAD_FILE_MAX_SIZE | 500 MB | Supports batch import of SKU price tags, sales reports and other documents, preventing upload failures caused by oversized files |
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: The Docker container is in an up state, but accessing port 3000 prompts that the database cannot be connected. The log shows MongoDB connection failure, and manually logging into MongoDB using the configured account password also returns an authentication error. Cause: The authentication parameters of MongoDB were not aligned with the configuration in
MONGO_CONNECTION_STRINGduring deployment, or the MongoDB instance did not enable identity verification. - Symptom: After starting the service locally with pnpm, the oneAPI access entry cannot be found, and there is no corresponding menu in the interface. Cause: The oneAPI function switch was not enabled in the environment variables, or the corresponding module compilation and packaging steps were not completed.
- Symptom: After adding the Doubao model in version 4.8.22, an error occurs during retrieval indicating missing model parameters. Cause: The API key for the corresponding model was not added to the configuration file specified by
MODEL_API_KEY_PATH, or the key format does not meet platform requirements.
How to confirm the configuration is complete
- Execute the command
mongo --username <configured username> --password <configured password> --authenticationDatabase adminto confirm successful connection to the local MongoDB instance. - Call the data synchronization interface to check whether the cross-channel aggregated data results include required fields such as SKU, sales volume, and sales revenue, and whether the time range matches the configured scheduling rules.
- Add the specified model in the platform interface, enter a test API key, and initiate a small-batch retrieval request to confirm that no parameter errors are returned in the results.
- Check the service logs to confirm there are no error messages such as data parsing timeouts or vector storage index refresh failures.
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.