What the Data for This Category Looks Like
Thermal coal financing daily report data is sourced from domestic coal spot trading platforms, northern port scheduling logs, and financial institution supply chain financing logs, and is updated each morning. The document structure includes that day’s production area listed prices, northern port free on board (FOB) prices, cross-region transportation volumes, supply chain financing reference cost ranges, and summaries of that day’s financing transaction cases. Price fields use yuan/ton as the unit. Transportation volume fields use 10,000 metric tons as the unit. Financing-related fields are presented as specific amount ranges from that day’s transaction cases, with no fixed standardized percentage format.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The daily update requirement means multi-turn dialogue must only call that day’s data sources to avoid returning expired information. The scattered multi-field structure results in user questions only covering some query dimensions, requiring multi-turn dialogue to gradually guide the supplementation of parameters including production area, port, and financing type. The non-standardized presentation of daily financing transaction case summaries requires prompts to explicitly limit extraction to that day’s content, and prohibit referencing historical data. The unit differences across fields require clear explanations of unit meanings during dialogue to prevent user confusion.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Thermal coal financing daily reports contain multiple scattered fields, so previously obtained query parameters from multi-turn dialogue must be retained |
systemPrompt | Only use the daily updated thermal coal financing daily report data to answer questions. Prompt the user to supplement query dimensions when corresponding data is not obtained | Aligns with the daily update property of the data, and limits the data source scope |
toolCallMaxRetries | 2 times | Balances tool call success rate and timeout risk, and avoids resource occupation from repeated calls |
retrievalSimilarityThreshold | 0.75–0.85 | Filters low-relevance historical data to accurately recall that day’s financing-related content |
voiceRecognitionModel | Official built-in speech-to-text model | Adapts to the platform’s native capabilities, and resolves the issue of no text conversion in voice conversations |
maxTokens | 2000–3000 characters | Covers the output requirements of multiple sets of financing data, and prevents content truncation |
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 specific analysis, and it is recommended to test on relevant internal samples before finalizing settings.
Three Common Misconfigurations
- Symptom: No text conversion content is generated after voice conversations when voice input is enabled. Cause: The
voiceRecognitionModelparameter is not configured, or an unadapted third-party model is used. - Symptom: Query parameters extracted during multi-turn dialogue do not match the user’s actual needs. Cause: The system prompt does not explicitly guide gradual supplementation of query dimensions, or the
maxContextconfiguration is too small, resulting in loss of previously obtained parameters from the conversation context. - Symptom: Returned results include non-current historical thermal coal financing data. Cause: The
retrievalSimilarityThresholdis set too low, resulting in recall of expired documents, or the system prompt does not limit usage to only that day’s data.
How to Verify Correct Configuration
- Initiate a voice query, confirm that the transcribed content matches the submitted voice input, and adjust the
voiceRecognitionModelconfiguration until the expected outcome is achieved. - Initiate multi-turn queries: first ask about thermal coal financing conditions for a specific production area, then supplement with port query data, check if the conversation context retains the previously submitted query parameters, and adjust the
maxContextconfiguration until the expected outcome is achieved. - Initiate a query for that day’s thermal coal financing data, confirm that the returned results only include that day’s updated content, and adjust the
systemPromptconfiguration until the expected outcome is achieved. - Simulate a tool call failure scenario, confirm that the configured number of retries is executed, and adjust the
toolCallMaxRetriesconfiguration until the expected outcome is achieved.
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.