What This Category of Data Looks Like
Market and yield daily report data for investment platforms comes from exchange market data push APIs, reconciliation data from custody and clearing institutions, and the platform’s own transaction records. The update schedule completes full data collection after market close on trading days; only static position data is updated on non-trading days. Each daily report is a structured CSV or JSON file, with each data entry containing the product code, product type, position quantity, daily yield value, cumulative yield value, and transaction date fields. Field units include shares, CNY, and ISO 8601 format timestamps; no percentage-based values are included.
Constraints Imposed on Multi-turn Dialogue and Prompting
The fixed data update schedule requires prompts to explicitly restrict queries to the latest data updated after that day’s market close, to prevent the model from retrieving old data from non-trading days or pre-market hours. The standardized design of structured fields requires multi-turn dialogue to guide users to explicitly specify a product code or position name, to reduce errors from fuzzy matching. Because yield values are measured in CNY, prompts must clearly explain the meaning of the numerical values, to avoid users confusing them with percentage-based yields. The large number of data entries in single daily report documents requires limiting the number and volume of context recalls, to prevent dialogue process timeouts or lag. The lack of market data on non-trading days requires dialogue logic to include corresponding result prompts, to avoid returning empty data or error messages.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Investment platform daily reports include multiple sets of product data, and multi-turn dialogue needs to retain context from historical interactions and multiple matching results |
UPLOAD_FILE_MAX_SIZE | 500 MB | Full trading day daily reports contain thousands of product data entries, so file volumes are typically large, and upload limits must be accommodated |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Structured file parsing requires traversing a large number of product entries, which takes significant time, so the timeout threshold must be extended |
recall_top_k | Top 10–15 entries | Users typically only focus on yield data for key position products, and excessive recalls will disrupt dialogue logic |
similarity_threshold | 0.75–0.85 | High similarity requirements for investment data field matching prevent irrelevant products from being recalled |
system_prompt_template | Match data by product code or position name, prioritize returning yield values updated after that day’s market close, and clearly state that the unit is CNY | Adapt to the standardized fields and unit requirements of investment platform data, and clarify query rules |
The parameter values provided on this page are common starting points for configuration. 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 Mistakes
- A 503 Service Unavailable error is returned when uploading a daily market report document via the dialogue interface. Background logs show the file upload process completes but parsing is not triggered. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration value is smaller than the actual uploaded file volume, causing the server to trigger rate limit interception. - When a user asks a yield-related question during multi-turn dialogue, the returned results include old data from non-trading days. Cause: The prompt does not explicitly restrict queries to the latest data updated after that day’s market close, so the model retrieves cached old historical data.
- The number of yield data entries returned after uploading a file during a dialogue is far lower than expected. Cause: The
recall_top_kconfiguration value is too low, or thesimilarity_thresholdis set too high, filtering out matching product data.
How to Verify Proper Configuration
- Upload a test structured daily report document, and check that the interface normally displays the parsed field list with no error prompts.
- Initiate a single-turn dialogue, specify a known product code, and verify that the returned yield value unit matches the field unit in the document.
- Initiate a multi-turn dialogue, ask for yield data for different products in sequence, and check that context is correctly retained and historical interactions are not truncated.
- Simulate a query initiated on a non-trading day, and check that the dialogue returns the expected prompt for no market data.
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.