What Data for This Category Looks Like
Securities financing daily report data comes from public margin trading data disclosed by Shanghai, Shenzhen, and Beijing Stock Exchanges after daily market close, plus compliant on-exchange trading statistics. The data updates once per day. It covers full market individual stock margin trading details for the current day. The core format is structured tables. Fields include security code, security name, margin purchase amount, margin balance, short sale volume, short sale remaining quantity, short sale balance, and more. All amount fields use RMB yuan as their unit. Quantity fields use shares or ten thousand shares. Some daily reports include aggregated industry margin trading statistics for the day.
Constraints Imposed by These Characteristics on Vector Models and Indexing
Structured tables form the core of the data. Standard unstructured vector models have insufficient extraction accuracy for table field associations. Select a vector model that supports structured text encoding. The daily update rhythm requires the index to support incremental indexing. This avoids performance losses from rebuilding full data every day. Fields have clear units and numerical attributes. When chunking, retain the binding relationship between fields and their corresponding values. Splitting fields and values causes semantic loss. A single daily report covers thousands of individual stocks, so single document length is large. Set chunk boundaries reasonably to avoid chunks that are too long or too fragmented. The system must also adapt to indexing write efficiency for batch data.
Configuration Settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
embedding_model | Aliyun Tongyi multimodal-embedding-v1 | Supports semantic encoding of structured tables and numerical fields, adapts to the structured data characteristics of securities financing daily reports |
chunk_size | 800–1200 characters | A single daily report contains data for multiple individual stocks. 800-1200 characters can cover the complete field combination of 1 to 2 individual stocks, avoiding splitting the binding relationship between fields and values |
chunk_overlap | 100–150 characters | Retains field association information across chunks, prevents semantic breaks caused by chunk boundaries |
index_incremental_mode | Enabled | Securities financing daily reports update full data daily. Incremental indexing avoids the performance overhead of rebuilding the full index every day |
retrieve_top_k | Top 20–30 entries | A single daily report covers thousands of individual stocks. A sufficient number of individual stock data must be recalled to cover query needs, while avoiding excessive recall that causes performance losses |
similarity_threshold | 0.75–0.85 | Distinguishes valid and invalid individual stock data matching results, filters low-correlation non-target individual stock entries |
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 values.
Three Common Errors
- Phenomenon: Calling chunk indexing-related APIs in FastGPT 4.8.10 returns an empty array. Cause: Chunk parameters are not configured correctly, or fields and values of structured tables are not bound as independent semantic units, resulting in no valid content being generated for the index.
- Phenomenon: An error indicating the model is not authorized appears when adding the
阿里multimodal-embedding-v1vector model. Cause: Correct API key and access address are not filled in the platform's model management page, or the call permission for the corresponding model is not activated. - Phenomenon: The securities financing daily report indexing task takes longer than expected and does not complete. Cause: Incremental indexing mode is not enabled, and a single daily report covers full data for thousands of individual stocks, triggering full index rebuilding which causes excessive time consumption.
How to Confirm Proper Configuration
- View configured vector models on the platform's model management page. Confirm the target vector model has been correctly added and permission verification completed.
- Upload a test securities financing daily report document. Check the chunk preview interface to confirm each chunk binds the complete fields and numerical content of one individual stock.
- Initiate a simulated retrieval request. Check the number of recalled entries and similarity matching results of the returned content. Confirm the recall rules and similarity threshold match the preset configuration.
- Submit an updated test daily report. Check the indexing task's execution logs to confirm the incremental indexing mode is active and task time consumption meets business requirements.
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.