What This Category of Data Entails
Refining investment research data sources include exploration and development technical reports, refining unit process specifications, crude oil quality inspection batch data, finished product delivery indicator documents, industry supply and demand analysis weekly reports, and real-time collected unit operating parameters.
Update rhythms vary widely. Static process manuals and specification documents have low update frequencies. Batch quality inspection data updates with production cycles. Real-time operating parameters are pushed per second. Industry weekly reports update weekly.
Document formats include long-text technical documents in PDF, structured quality inspection data in CSV, and real-time time-series data pushed via API interfaces. Fields include unit load, crude oil density, product octane number, and other metrics, with clear unit identifiers attached.
Constraints Imposed on Database and Operations Workflows
A high proportion of long-text technical documents requires support for large-capacity unstructured data storage and efficient word segmentation indexing. Structured batch quality inspection data and real-time operating parameters require strongly consistent transaction processing and high-concurrency write capabilities. Multiple data sources increase metadata complexity, requiring a unified field and unit management mechanism. Backup and recovery must cover both unstructured documents and structured database metadata. Single-file backup cannot cover the complete knowledge base state. Concurrent high-frequency writes of real-time data and batch retrieval of historical documents coexist, requiring proper configuration of database connection pools and concurrency handling strategies.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Refining process documents typically have long lengths, leading to extended single-parsing times. This setting avoids timeout interruptions of parsing tasks. |
UPLOAD_FILE_MAX_SIZE | 2000 MB | PDF documents containing complete unit flowcharts and long process descriptions have large file sizes. This allows a higher single-file upload limit. |
MAX_CHUNK_LENGTH | 1500–2000 characters | Refining technical documents include long process descriptions. Splitting text to this length retains sufficient context for accurate retrieval in investment research scenarios. |
DB_CONNECTION_POOL_SIZE | 32 | Balances concurrent requirements for real-time operating parameter writes and historical document retrieval, preventing task failures caused by exhausted connections. |
RECALL_TOP_K | 10–15 | Refining investment research needs to cover multiple types of information including process parameters, industry reports, and quality inspection data. Too few recall results lead to insufficient retrieval coverage, while too many increase retrieval latency. |
BACKUP_RESTORE_STRATEGY | Full file backup + incremental backup of PG database metadata | Ensures recovery completeness for both unstructured documents and structured knowledge base metadata. |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: An
Invalid array lengtherror occurs during knowledge base question answering splitting, and it occurs consistently. Cause: Only project files were imported during backup recovery, and the PG database's knowledge base metadata array field was not restored synchronously. An empty field causes a validation failure. - Symptom: Database connection exhaustion errors appear during batch import of structured quality inspection data or real-time operating parameters. Cause: The database connection pool size was not adjusted. Concurrent write tasks occupy too many connections, preventing core tasks such as index construction from obtaining database connections.
- Symptom: After modifying database or service passwords via docker deployment, restarting the container does not apply the changes. Cause: New passwords were not passed via docker startup command environment variables or mounted configuration files. Directly modifying configuration files inside the container will be restored after the container restarts.
How to Verify Correct Configuration
- Upload a single refining process PDF document larger than 1000 MB in size, confirm no timeout errors occur for parsing tasks.
- Batch import 100 pieces of structured quality inspection data, confirm no database connection exhaustion errors occur during database writes.
- Perform a knowledge base question answering splitting operation, confirm no
Invalid array lengthfield validation errors occur. - Modify the database connection password, restart the service, confirm normal connection to the database and retrieval of knowledge base content.
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.