What the data for this category looks like
Data sources for document and material drafting in the basic chemical industry include internal enterprise process specifications, safety data sheets, raw material quality inspection reports, production record ledgers, compliance documents, and more. Data update frequency changes dynamically with production batches, monthly compliance audits, and quarterly process adjustments.
Document structure falls into two categories: structured fields and unstructured text. Structured fields mostly include material codes, batch numbers, density, viscosity, and similar items. Units used include tons, kilograms, percentages, megapascals, and others.
Unstructured text covers process steps, exception handling instructions, and similar content. Single document length varies widely, from a few lines of compliance prompts to hundreds of pages of full process manuals.
Constraints on Deployment and Upgrade Posed by These Characteristics
The multi-source, heterogeneous data nature of the basic chemical industry requires support for both relational and non-relational database storage during deployment. Corresponding data connection parameters must be configured.
Frequently updated production and compliance data require ensuring index rebuilding compatibility during upgrades, to avoid interrupting document generation services.
The chunking and storage needs of long document files require adjusting relevant storage configurations to support large file imports.
Compliance requirements for chemical industry data also demand configuring dedicated storage endpoints to safeguard data security. During upgrades, storage-related configuration parameters must be updated synchronously to prevent abnormal data access permissions.
The following configurations apply to FastGPT v4.17.0.
How to Set the Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://fastgpt:xxx@10.0.0.5:27017/chemical_docs?authSource=admin | Stores unstructured long text data such as process specifications and safety data sheets, adapting to large text chunking storage requirements |
PG_URL | postgresql://fastgpt:xxx@10.0.0.6:5432/chemical_meta | Stores structured metadata such as material codes, inspection batches, and compliance numbers, supporting complex query operations |
STORAGE_S3_ENDPOINT | s3://chemical-storage-cn?max-size=1000 MB | Stores original chemical industry document files, meeting enterprise compliance storage requirements and limiting maximum single file storage capacity |
DB_MAX_LINK | 20–30 concurrent connections | Meets concurrent demand for simultaneous reading of multi-source data, preventing database connection pool exhaustion |
REDIS_URL | redis://:xxx@10.0.0.7:6379/0?timeout=300 seconds | Caches frequently called compliance document content, reducing database load and improving retrieval speed |
Three Common Misconfigurations
- Issue: After upgrading fastgpt-mcp-server, FastGPT service fails to start normally. Logs show database connection failure. Cause: Configuration parameters for
MONGODB_URIorPG_URLwere not updated synchronously. The newly deployed server cannot access the original chemical industry document database instance. - Issue: After triggering document retrieval, the reranking model always returns false, with no valid sorting content. Cause:
REDIS_URLis not configured, leading to insufficient cache space. Temporary data from the reranking model cannot be stored normally. - Issue: Chinese garbled characters appear when importing CSV-format raw material quality inspection reports. Manual adjustment of character encoding settings does not resolve the issue. Cause: The encoding rules for
FILE_TOKEN_KEYwere not configured correctly, leading to failure to properly parse Chinese chemical terms in CSV files.
How to Verify Configurations Are Correct
- Log in to the FastGPT admin backend, go to the data source configuration page, and test the connection status of
MONGODB_URIandPG_URLone by one. Confirm that a connection success prompt is returned. - Upload a small chemical industry process document to the knowledge base, perform a retrieval test, and check whether the reranking model's return results include valid sorting scores. Confirm that the reranking function works normally.
- Import a test CSV-format quality inspection report, check that Chinese fields are displayed normally with no garbled characters.
- After starting the FastGPT service, check the system logs to confirm there are no error messages such as database connection timeouts or cache loading failures. Verify that the service starts normally.
The values provided are common starting points and should be evaluated 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.