What This Type of Data Looks Like
Data sources for power industry intelligent due diligence reports include publicly disclosed documents from power regulatory authorities, operation logs submitted by power generation enterprises, transaction records from power trading centers, and grid connection acceptance materials. Data update frequencies fall into three categories: real-time transaction data, monthly operation statistics, and annual compliance reports. Document structures mix structured tables and unstructured technical descriptions. Structured fields include unit rated capacity, power generation, on-grid electricity price, and similar items, with corresponding units of MW, MWh, and yuan per thousand kilowatt-hours. The unstructured section includes long text content such as project approval documents and environmental protection inspection reports.
Constraints Imposed on Model Access and Configuration
The mixed structure and specific unit requirements of power due diligence data first require adapting the model access link to structured field verification rules, to avoid parsing errors caused by mismatched parameter units. Differences in update frequencies across multiple data sources require configuring different recall update cycles, to distinguish call frequencies for real-time transaction data and periodic reports. The proportion of long-text compliance documents requires adjusting model context window parameters to adapt to the length limits of single documents. At the same time, the compliance attributes of power data require configuring strict permission verification for model calls, to prevent sensitive data leaks.
How to Set Configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Power due diligence reports contain long compliance descriptions and multiple sets of structured data spliced together; exceeding the default context length of the base model will cause content truncation |
Recall Count | Top 10–15 items | Power data fields are closely related; too many recalls will introduce redundant non-core parameters, while too few will miss key generating units or transaction data |
similarityThreshold | 0.75–0.85 | Power parameter units are strictly regulated; a threshold that is too low will introduce irrelevant industry data, while a threshold that is too high will miss matching compliance clauses and technical details |
rerankTopN | Top 5 items | The reranking link needs to focus on core power transaction and unit data, to avoid non-critical information interfering with the accuracy of model output |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | A single power due diligence report contains multiple attached documents, and parsing takes longer than general documents |
vectorStoreBatchSize | 20 items/batch | Power data has many structured fields; an overly large batch will cause abnormalities in vector storage index generation |
The parameter values provided on this page are all conventional recommendations used as starting points 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 Misconfigurations
- Phenomenon: A 401 Unauthorized error is returned when calling the model, and the reranking function fails after deploying the bge-rerank-base image. Cause: The key verification rules of the model proxy are not configured correctly, the model deployed via the image does not have public access permissions enabled, or the key is not bound to the call permissions of the corresponding model.
- Phenomenon: The AI model dropdown list in the workflow is empty, and available models cannot be selected for configuration. Cause: The model access channel is not configured in the platform backend, or the proxy service has not synchronized the available model list cache, causing the frontend to fail to pull optional model options.
- Phenomenon: After configuring the oneapi proxy, a prompt appears stating that the model has expired, and newly accessed models cannot be called. Cause: The oneapi model list cache is not updated regularly, or the proxy service has not been updated to a version that supports the latest model protocol, causing expired models to remain in the optional list.
How to Confirm Proper Configuration
- Upload a standard power industry due diligence report, check whether the parsed structured fields are correctly extracted, and confirm that the field names match their corresponding units.
- Initiate a vector recall test, verify that the number of returned documents matches the configured recall count, and check that the similarity scores fall within the preset range.
- Call the model to complete a due diligence summary generation, check that the output contains core power parameters and compliance points, with no irrelevant content interfering.
- View the model call logs in the platform backend, confirm that there are no error codes such as 401 or timeouts, and that the proxy service request link is normal.
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.