What the data for this category looks like
Energy and metal research report sources include domestic non-ferrous metal industry association public data, reports from leading securities firm industry research institutes, financial reports of overseas mining companies, and spot quotation platforms of domestic futures exchanges. Update frequencies vary by content type: regular securities research reports are updated weekly or monthly, event-driven research reports are released in real time alongside industry policies or production capacity changes, and corporate announcement data is updated immediately. Document structures include core indicator tables, supply and demand balance sheets, industrial chain breakdowns, policy summaries and other modules. Fields cover metal name, origin, quotation, inventory level, and production capacity data. Common units include yuan/ton, ton, cubic meter, etc., with no universal format.
What Constraints These Characteristics Impose on Model Access and Configuration
The multi-source and dispersed nature of energy and metal research reports requires configuring multi-source recall rules to avoid missing segmented data across platforms. The high proportion of long documents and structured tables requires adjusting file parsing timeout and segmentation parameters to prevent parsing failures or content truncation. The presence of specialized fields and exclusive units requires configuring dedicated prompt templates to constrain model output, avoiding unit confusion or field recognition errors. The frequently updated spot and production capacity data requires setting a reasonable vector database refresh cycle to ensure the timeliness of retrieved content.
How to Set the Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | The core content of a single energy and metal research report is mostly 5000-10000 characters, requiring retention of complete analytical logic |
RECALL_TOP_K | Top 10–15 results | Energy and metal research reports have strong relevance; excessive recall will dilute valid information, while insufficient recall will miss segmented data |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Research reports contain multiple structured tables and industrial chain data, with significantly higher parsing time than general documents |
PROMPT_TEMPLATE | Restrict to professional energy and metal context, strictly match input fields and units | Exclusive professional units and fields exist in energy and metal materials, to avoid confusion in model output |
VECTOR_DB_REFRESH_INTERVAL | Every 6 hours | Spot quotations and production capacity dynamic data have high update frequencies; regular synchronization ensures retrieval timeliness |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports batch upload of multiple research report collections, adapting to the bulk management needs of industry data |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Phenomenon: When calling a model deployed via Ollama, the returned content does not match the professional energy and metal context. Cause: No segmented domain constraint is bound in the model's
PROMPT_TEMPLATEconfiguration, and the model only uses the general system prompt. - Phenomenon: When deploying and configuring a model locally on FastGPT, submitting the
API_BASE_URLandAPI_KEYfields triggers a required field error. Cause: Valid format is not filled according to platform requirements, for example,API_BASE_URLlacks a port suffix or has an incorrect format. - Phenomenon: When accessing the platform via a domain name, the configured model parameters do not take effect, and the configuration status differs from that when accessing via IP. Cause: The corresponding access domain name is not added in the platform's domain name configuration, causing configuration data to fail to synchronize to domain name access nodes.
How to Verify Successful Configuration
- Upload a single energy and metal research report, initiate a retrieval and question-and-answer session, and check whether the returned content matches the professional fields and units in the research report, with no unit confusion or missing fields.
- Adjust the
RECALL_TOP_Kparameter, initiate a batch retrieval, and verify that the number of recall results falls within the configured value range. - View the platform's scheduled task logs to confirm that the vector database refresh task executes normally according to the configured interval.
- Call the configured model interface to verify that the returned result has no format errors and complies with the preset professional context constraints.
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.