What data this category includes
Data for this category comes from centralized treasury payment systems, unified budget management systems, electronic invoice platforms, and contract management systems. Update frequency is daily. Daily processed documents include payment applications, fund appropriation plans, invoices, contracts, acceptance receipts, reimbursement approval forms, and payment vouchers. These cover all materials required for full-chain compliance review of single-bill fund payments. Data fields include budget indicator codes, economic classification codes, payment amounts, review statuses, and more. Storage uses a mix of structured and unstructured data.
Constraints for deployment and upgrade
Reference only; verify against the target FastGPT release and deployment documentation.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://<db-user>:<db-pass>@<db-host>:27017/fastgpt_fiscal?authSource=admin&replicaSet=rs0 | Category data requires high-availability storage; replica set configuration ensures stability of concurrent read/write operations for daily updated data, and adapts to storage needs for multi-system docking |
REDIS_URL | redis://:<redis-pass>@<redis-host>:6379/0 | Caches session information and vector index results, ensures response speed for party building learning Q&A and review queries, and adapts to high-frequency access scenarios |
PG_URL | postgresql://<pg-user>:<pg-pass>@<pg-host>:5432/fastgpt_metadata | Stores metadata for category documents and review process records, adapts to query and management needs for structured data |
| Local knowledge base chunk length | 800–1200 characters | Category documents include long-text contracts and structured invoices; this range balances context integrity and retrieval accuracy |
| Number of single retrieval results | Top 5 entries | Review scenarios require precise matching of compliance basis for single-bill payments; too many results increase screening burden for review staff |
| Session cache validity period | 7200 seconds | Adapts to session duration requirements for party building learning and daily reviews, avoids frequent reconnection |
Three common misconfigurations
- Symptom: Error logs related to MongoDB replica set configuration appear when starting the service, prompting that replica set members cannot be found. Cause: The replica set is not configured according to the storage requirements of category data, or the replica set initialization step is skipped, leading to failed concurrent read/write operations for daily updated data.
- Symptom: After local deployment, category documents are uploaded for knowledge base training, and the data processing steps show as empty. Cause:
REDIS_URLis not correctly configured, leading to cache failure, orPG_URLconnection permissions are insufficient, making it impossible to read document metadata information. - Symptom: After the service is packaged as a Docker image and run, all vector retrieval scores are identical, and document relevance cannot be distinguished. Cause: The local vector model cache directory is not correctly mounted, causing the model to be reinitialized each time the service starts, or the chunk length configuration for category documents is not applied.
How to confirm configurations are correct
- Run database connectivity test scripts to verify the connection status of
MONGODB_URI,PG_URL, andREDIS_URL, with no timeout or permission error messages. - Upload a single category document such as a reimbursement approval form for knowledge base training, confirm that the data processing steps generate valid segments, and no null value errors occur.
- Initiate queries related to party building learning and fiscal review, verify that the number of vector retrieval results meets the configured single retrieval limit, and the results have relevance differences.
- Simulate the daily data synchronization process, write new category documents to the database, confirm that the service can normally read and process the new data, and no abnormal logs are generated.
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 2026-09-28.