What Data for This Category Looks Like
Data for thermal industry research reports comes primarily from public industry operation data disclosed by provincial energy regulatory agencies, regional heating associations, and power trading centers, plus in-depth analysis reports published by third-party energy research institutes. Update cadences fall into two categories: fixed schedule and event-triggered. Fixed schedule updates include monthly industry operation briefings and quarterly in-depth reports. Event-triggered updates include temporary reports issued for events such as coal price adjustments and heating policy changes. Document structures include core metric fields: total heating area, unit heat consumption, coal consumption rate, heating cycle days, and unit heating cost. Corresponding units are 10,000 square meters, gigajoules per square meter, tons of standard coal per megawatt-hour, days, and yuan per gigajoule. Single document lengths range from hundreds of words for briefings to over 10,000 words for in-depth analyses.
Constraints Imposed on Deployment and Upgrade
Scattered data sources and varied update cadences require adapting format validation and synchronization logic for multi-source data during deployment. This avoids parsing failures caused by field mismatches. Wide variation in document lengths, from hundreds of words to over 10,000 words, requires configuring flexible text segmentation rules during deployment. This adapts to different document splitting needs. Specific metric units require preset unit normalization logic in the parsing stage. This prevents unit confusion during retrieval. Event-triggered temporary reports allow flexible adjustment of scheduled task and event listening configuration items during upgrades. No full synchronization process rebuild is needed. Thermal industry data has strong timeliness. Reasonable cache expiration durations must be configured during deployment to ensure real-time retrieval results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single in-depth thermal industry research report is typically no larger than 800 MB. Reserved redundant space adapts to batch upload scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | In-depth research reports contain large amounts of text and metric fields. Sufficient time is needed to complete parsing and format conversion |
maxContext | 8000–12000 characters | Adapts to the core content length of split thermal industry research reports. Prevents truncation of key metrics and analysis |
Number of Retrieved Results | Top 8–12 | Thermal industry research reports have high effective information density. Excessive retrieved results introduce redundant content |
Similarity Threshold | 0.75–0.85 | Filters low-relevance general industry articles. Retains retrieval results that accurately match thermal industry metrics |
VECTOR_MLA_ENABLE | true | Enabling MLA vector acceleration reduces retrieval latency for DeepSeek models. Adapts to high-frequency retrieval demands for thermal industry research reports |
The parameter values provided on this page are general 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. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: When uploading a thermal industry research report file around 2 MB, the interface prompts upload failure, and the console returns a
413 Request Entity Too Largeerror. Cause: TheUPLOAD_FILE_MAX_SIZEparameter was not adjusted. The default upload size threshold is lower than the actual file size. - Phenomenon: After upgrading to v17, when calling the gpt-4o-mini model via the OneAPI channel, the conversation returns a
model not founderror. Cause: The model mapping rules adapted for v17 were not updated in the model channel configuration, causing model name recognition to fail. - Phenomenon: When pulling deployment images in a Linux environment, there is a long period of no response followed by a
network timeouterror. Cause: No domestic mirror source was configured. The download speed of the official mirror source does not meet local deployment requirements.
How to Confirm Configuration is Correct
- Upload the longest single thermal industry research report file, check the upload progress and interface prompts to confirm that no
413errors are triggered. - After configuring the data synchronization scheduled task, manually trigger a synchronization to check that data source fields are fully imported with no missing or formatted errors.
- Call the test interface of the model channel, enter specified thermal industry keywords, and check the relevance of returned results and model call status.
- View the vector database retrieval logs to confirm that the number of retrieved results and similarity threshold configurations match the preset values.
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.