What the data for this category looks like
The data sources for professional services funding daily reports include public funding announcements from professional services institutions, daily funding updates from industry news platforms, and record disclosure information from regulatory authorities. Updates occur daily. Each daily report primarily uses structured fields, with a small amount of unstructured original announcement text attached. Core fields include service institution name, funding amount (unit: ten thousand yuan), funding round, investor institutions, disclosure date, and service associated fields. Some entries include a brief description of funding use.
Constraints imposed by these characteristics on vector models and indexing
The daily update requirement mandates that indexes support incremental updates, eliminating resource consumption and latency from full index rebuilding. The clear units and fixed field structure of structured fields require vector encoding to retain field association information, preventing recall bias caused by unit confusion of funding amounts across different institutions. Unstructured original announcement text must be indexed alongside structured fields, ensuring that recall can match both subject information and specific funding details. The large number of fields requires controlling vector dimensions to avoid index bloat, while supporting precise filtering by specified fields.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to structured field splitting and semantic integrity of announcement text, avoiding fragmentation of financial terms after splitting |
vector_dim | 1536 | Matches the output dimension of mainstream general-purpose text vector models, ensuring alignment of cross-field vectors |
index_refresh_interval | 1 hour | Matches the daily update rhythm of funding daily reports, balancing index real-time performance and resource consumption |
filter_fields | service institution name, funding amount, disclosure date | Set based on the fixed fields of daily reports, enabling precise filtering and recall by subject and time |
similarity_threshold | 0.75–0.85 | Filters low-relevance funding updates, preventing funding information from non-target institutions from mixing into results |
enable_incremental_index | Enabled | Adapts to daily incremental update of report data, reducing resource usage from full index rebuilding |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, 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
- Phenomenon: Calling the index configuration interface returns a 400 error, with the prompt "invalid vector dimension parameter". Cause: Did not match the number of fields in professional services funding daily reports, incorrectly used the 1024 dimension from general knowledge bases, resulting in incompatibility with the vector storage structure.
- Phenomenon: Recall results include non-current-day funding information, exceeding the expected number of entries. Cause: Did not set the disclosure date filtering condition in
filter_fields, or thesimilarity_thresholdvalue was too low, causing irrelevant historical data to be recalled. - Phenomenon: Parsed document fields are empty, making it impossible to generate valid vectors. Cause: Did not bind structured fields with unstructured announcement text, only encoded plain text content, losing key information such as funding subject and amount.
How to Confirm the Configuration Is Correct
- Upload a single test funding daily report document, and check if the parsed fields are fully displayed in the knowledge base management interface.
- Initiate a vector recall test, enter keywords for the specified service institution and disclosure date, and verify that the field information of the recall results matches the input conditions.
- Submit incrementally updated daily report data, and check if the update status in the index management interface is displayed as "Completed" with no error logs.
- Adjust
similarity_thresholdto the boundary values of the range, and verify that the relevance of recall results meets expectations, with no low-relevance entries mixed in.
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.