What the Data for This Category Looks Like
Data sources for cultural and entertainment product yield rates and market trend data include:
- Compliant cultural and entertainment category collection and trading databases
- Publicly available e-commerce platform transaction APIs
- Transaction records published by offline auction institutions
Data updates follow a fixed schedule:
- Same-day transaction data is synced after daily market close
- During new product launch cycles, pre-launch category reference market trends are updated 1 to 3 business days in advance
The structure of a single data document includes these fields: Unique product identifier, product name, specification model, transaction date, transaction unit price, transaction quantity, circulation channel, market reference guide price.
Unified field units apply to all entries:
- Transaction unit price: CNY per item
- Transaction quantity: measured in items
- Market reference guide price: CNY per item
- Circulation channel: enumeration value (online/offline)
What Constraints Do These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Decentralized data sources require multi-turn dialogue workflows to first verify the compliance of requested data sources. This prevents calling unauthorized interfaces that return incorrect data. Fixed update schedules require prompts to explicitly specify calls to the latest same-day transaction dataset. Default calls to 7-day historical data are prohibited. Multiple fields and enumerated units require prompts to strictly limit the returned field scope. Only content from user-specified fields may be output, and unit descriptions must be unified. Pre-launch data updates require multi-turn dialogue to actively ask users whether they need pre-launch category market trend data. This avoids returning non-valid data that has not officially entered circulation. Context association requirements require dialogue workflows to retain user-specified product identifiers and time ranges. This prevents repeated requests for full datasets.
Configuration Settings
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
maxContext | 1200–1800 characters | Cultural and entertainment product data has many fields, so sufficient context must be retained to associate product identifiers and time ranges across multi-turn dialogues |
systemPromptTemplate | Call the same-day compliant data source based on user-specified product category and time range, only return specified fields | Match the multi-field constraints of this category’s data, avoid returning irrelevant content |
WORKFLOW_MAX_RUN_TIMES | 1500 | Accommodate requirements for multiple data calls during multi-turn dialogue, higher than the default configuration to adapt to concurrent scenarios |
mcpConcurrencyLimit | 1–2 requests per second | Adapt to the call limits of this category’s data interface, avoid triggering rate limiting and returning none |
responseAppendMode | Disabled | Avoid variable superposition of historical replies and current replies in multi-turn dialogue, match user’s actual output requirements |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Accommodate time-consuming requirements for batch cultural and entertainment product data parsing, avoid task interruption due to timeout |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: When MCP is called concurrently 2-3 times per second, workflow nodes return none. Cause: The
mcpConcurrencyLimitconfiguration was not adjusted, exceeding the concurrent load threshold of the data source interface and triggering rate limiting interception. - Phenomenon: The latest AI reply in the conversation superimposes variable content from historical replies, including the previous round’s result A and current result B. Cause: The
responseAppendModeconfiguration was not disabled, and the system retains the default variable superposition logic for multi-turn dialogues. - Phenomenon: Conversation replies do not include the large model’s thought process, only outputting the final result. Cause: The
enableThoughtDisplayconfiguration was not enabled, and no thought process output requirement was added to thesystemPromptTemplate.
How to Verify Proper Configuration
- Initiate 2-3 concurrent MCP calls per second, check that returned results are valid data with no none values.
- Initiate two consecutive dialogues: first request the same-day yield rate of a specific cultural and entertainment product, second request the transaction quantity of that product. Check that the second reply only includes transaction quantity, with no superimposed content from historical replies.
- View conversation logs, confirm that the large model’s thought process is displayed in the reply (if the corresponding configuration is enabled).
- Initiate a batch cultural and entertainment product data parsing task, check that parsing time does not exceed the threshold set by
PARSE_FILE_TIMEOUT_SECONDS, with no timeout errors.
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.