Model Access and Configuration for Thermal Coal Yield and Market Trend Reports

Thermal coal market trend and yield data is sourced from public APIs of domestic coal spot trading platforms and industry monitoring institutions.

What the data for this category looks like

Thermal coal market trend and yield data is sourced from public APIs of domestic coal spot trading platforms and industry monitoring institutions. Data updates follow a fixed schedule: daily port spot quotes are updated at a fixed time each day, and weekly average price data is updated once per week. Data documents are presented in structured format, including fields such as thermal coal variety identifier, origin, circulation port, pricing unit, daily price, and statistical cycle. The pricing unit is uniformly yuan/ton, and no percentage-based relative change indicators are included. Individual core data documents are appropriately sized, with clear field hierarchies and no redundant nesting.

Constraints imposed by these data characteristics on model access and configuration

Since the pricing unit for thermal coal data is fixed as yuan/ton, field validation rules must be configured to filter invalid data with non-standard units. Since data is updated on fixed daily and weekly cycles, scheduled pull tasks must be aligned with data source update times to avoid pulling outdated, unupdated data. Since the data includes multi-dimensional origin and port fields, targeted field recall filtering must be configured to retain only core information required for reporting. Since data sources are public APIs that may experience temporary connection fluctuations, reasonable retry and timeout mechanisms must be configured to ensure pull stability. Additionally, the structured data characteristics require adapting to standard format data source parsing logic.

Configuration Settings

Configuration ItemRecommended SettingRationale
Scheduled Task Trigger Time16:30 dailyThermal coal daily quotes are updated before 16:00, and a 30-minute buffer ensures the latest data is pulled
API Request Timeout15 secondsPublic data source APIs typically respond within 10 seconds, and 15 seconds covers common network fluctuation scenarios
Field Validation RulesValidate that the pricing unit is yuan/ton and the value is greater than 0Thermal coal quotes are positive values with yuan/ton as the standard pricing unit, which filters invalid data
Recall Field FilterRetain origin, port, and daily price fieldsYield and market trend daily reports only require price and origin information for core circulation links
Model Context Window Configuration8000 charactersThe core data volume of a single thermal coal daily report is approximately 2000 characters, reserving sufficient context space for the model to generate report content
API Retry Count2 retriesPublic data sources occasionally experience temporary connection failures, and 2 retries reduces the rate of data pull failures

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 case-by-case analysis, and it is recommended to test against your own samples before finalizing settings.

Three Common Configuration Errors

  • The symptom is a 500 Internal Server Error returned by model calls. The cause is that the local model port mapping was not configured correctly, preventing FastGPT from connecting to the locally deployed model service.
  • The symptom is empty fields in pulled thermal coal data. The cause is that no field validation rules were configured, resulting in invalid data with non-standard pricing units being filtered out, leaving no valid content to return.
  • The symptom is missing core price fields in the generated report. The cause is incorrect recall field filter configuration, where the daily price field was accidentally excluded from the recall scope.

How to Verify Successful Configuration

  • Scheduled task run logs are reviewed to confirm that thermal coal data was successfully pulled at the specified daily time, and that pulled fields match configured recall fields.
  • A single model call test is initiated to check that returned report content includes configured core fields, with no missing fields or formatting errors.
  • An API connection failure scenario is simulated to confirm that the system automatically triggers the retry mechanism and resumes normal data pulling after retries.
  • Model context window configuration is verified to confirm that loaded data source content is not truncated by the context window.

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.