What the Data for This Category Looks Like
Data sources include real-time pollutant monitoring data from environmental protection department monitoring stations, operation and maintenance logs of enterprise air emission equipment, environmental impact assessment (EIA) approval documents, and emission reduction marketing plan documents for industrial scenarios. Update frequencies fall into three categories:
- Real-time sensor data updates every minute
- Operation and maintenance logs are generated in real time as equipment runs
- EIA and marketing documents are updated according to project cycles or policies
Standardized fields are included in document structures:
- Monitoring data contains timestamp, device ID, pollutant concentration (unit: mg/m³), and monitoring point
- Marketing documents contain applicable industry, emission reduction technical parameters, and project implementation cycle
Constraints Imposed by These Characteristics on Deployment and Upgrade
Real-time high-frequency monitoring data requires support for high-concurrency streaming data access during deployment to avoid data packet loss. Large-volume operation and maintenance logs and EIA documents require higher upload and parsing timeout thresholds to prevent task interruptions. Industry-specific marketing content needs to be paired with dimension-based recall rules to improve content matching accuracy. For intranet deployment scenarios, configure local image sources instead of pulling from the public network to resolve network access restriction issues. When upgrading plugins or core services, pause non-core data synchronization tasks to avoid damaging vector indexes or real-time data links during the upgrade process.
How to Set Configurations
| Configuration Item | Recommended Value | Basis for This Value |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000–2000 MB | This air pollution control scenario includes large files such as EIA reports and quarterly operation and maintenance logs, so the single-file upload limit needs to be adapted |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long-cycle operation and maintenance logs take a long time to parse, so extend the timeout period to avoid forced task termination |
Recall count | Top 8–12 entries | Balance content coverage and inference overhead, avoid excessive low-relevance content interfering with model output |
Similarity threshold | 0.75–0.85 | Distinguish professional emission reduction plans from general environmental science popularization content, improve the accuracy of recalled content |
REDIS_IMAGE | registry.cn-hangzhou.aliyuncs.com/library/redis:7.0.15 | Intranet environments cannot access public network image repositories, use Alibaba Cloud official image acceleration for pulling |
PGVECTOR_PLUGIN_VERSION | 0.6.0 | Adapt to FastGPT 4.9.7 version, avoid plugin and platform version incompatibility |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Phenomenon: Pulling the Redis image fails when running docker-compose up -d, and the console returns a "connection timed out" error. Cause: No intranet-accessible image source is configured, and public network pull requests are blocked by the intranet firewall.
- Phenomenon: After upgrading the PgVector plugin, the original vector recall task returns an "index does not exist" error. Cause: The original vector index was not backed up before the upgrade, and the database table structure was overwritten during the upgrade.
- Phenomenon: After configuring the Deepseek API interface, the call returns a 403 status code. Cause: No proxy or local image is configured in the intranet environment, making it impossible to access the Deepseek public network API service.
How to Confirm the Configuration Is Successful
- Run the docker-compose ps command to check that the Redis and pgvector plugin container statuses are Up.
- Upload a complete EIA report document, verify that the system parsing task status is successful, and the extracted fields include pollutant type, project number, and applicable industry.
- Create a test application, input "ultra-low emission transformation plan for thermal power industry", check that the matching degree of the recalled marketing content meets the set similarity threshold.
- Call the configured Deepseek API interface, receive a normal text response with no authentication or network error prompts.
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.