What data for this category looks like
Data for this category typically originates from national public resource trading platforms, natural resource trading systems, property right exchange systems, and state-owned assets supervision systems. Updates occur daily. Common documents include transfer announcements, trading guidelines, bid applications, margin vouchers, transaction confirmation documents, listing result announcements, and property right transfer specifications. Data fields center on transaction subject ownership information, trading process nodes, fund details, and subject information. No unified cross-platform field format exists. Some system data must be retrieved through interface synchronization.
What constraints these characteristics impose on multi-turn dialogue and prompt words
Disparate data sources and lack of unified formats require multi-turn dialogue to support dynamic calls of context fragments from different systems, to avoid field conflicts. Daily update frequency requires embedding data timeliness verification logic in prompt words, to ensure summarized ledgers reference the latest synchronized transaction information. Differentiated structures across multiple document types require preset field extraction rules in prompt words for different document types, to reduce manual verification costs. Transaction subject ownership is a core verification point. Multi-turn dialogue must guide users to supplement missing information related to ownership restriction conditions, to lower subsequent error risks.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
messages historical conversation storage limit | First 20 conversation records | This category has multiple nodes in the trading process. Retaining recent core conversations avoids context redundancy while covering key trading node information |
variables preset variable configuration | Transaction subject type, ownership number, update date | Used to dynamically populate prompt words, adapting to ledger extraction requirements for different transaction categories |
| Single search limit | Top 8 recalled results | This category has numerous and dispersed data fields. Limiting the number of recalled results avoids irrelevant information interfering with core ledger generation |
| Prompt word template refresh cycle | Every 1 day | Matches the daily data update frequency, ensuring verification rules in prompt words align with latest trading requirements |
chatId session isolation configuration | Isolate by transaction project number | Prevents confusion of conversation contexts across different trading projects, ensuring ledger summary only associates documents and conversations for the corresponding project |
Three common misconfigurations
- Attempting to configure a single prompt trigger per conversation may fail. The symptom is repeated identical prompt steps during conversations. The root cause is incorrect setup of multi-turn dialogue trigger nodes, resulting in repeated calls of the prompt word template.
- Non-current trading project document content appears in conversation replies, or error prompts are returned after execution. Symptoms include irrelevant land or property information in ledgers, or interface timeouts and abnormal interface status codes displayed. The cause is failure to use
variablesto limit the associated document scope for the current session, and failure to set a reasonable storage limit formessageshistorical conversations, leading to failed data filtering or exceeded context processing thresholds. - Unable to retrieve complete conversation records for a specified trading project. The symptom is partial missing or no data returned after calling the interface. The root cause is failure to configure
chatIdsession identification rules based on transaction project numbers, leading to failure to match historical data for the corresponding session.
How to confirm proper configuration
- Upload a single target trading document, initiate a conversation that includes field extraction requirements, and verify that the reply content only associates information from that document, with no irrelevant trading data.
- Initiate a conversation that includes multi-step process confirmation, check that historical conversation storage adheres to the preset limit rules, with no redundant early irrelevant conversations.
- Enter the identifier of a specified trading project, call the conversation record retrieval interface, and verify that the returned results include complete conversation data for that project.
- Simulate abnormal input, check that the conversation returns expected error prompts, with no unhandled exception cases.
The values provided here are common starting points, and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.