What data for this category looks like
The data for education service financing daily reports comes primarily from public financing announcements of educational institutions, financing filing information disclosed by industry self-regulatory organizations, and private education financing filing records published by regulatory authorities. Data is updated once per working day. Each single entry has a fixed document structure, including fields such as full name of the financing party, type of school-running business, financing amount, investor entity, financing round, information disclosure date, and school-running qualification filing number. Financing amount is measured in ten thousand yuan or hundred million yuan, and date fields use the ISO 8601 standard format.
What constraints these characteristics impose on the "model access and configuration" link
The fields of education service financing daily reports include unique school-running qualification filing numbers, multi-type business identifiers, and amount units. This creates three core configuration constraints. First, the unique qualification number must serve as the core association field. Configure a field weight parameter to raise recall priority, preventing dilution by other general fields. Second, data updates follow a working day cycle. Configure a timed synchronization task trigger frequency that matches this cycle to avoid ineffective runs. Third, financing amounts use two units: ten thousand yuan and hundred million yuan. Configure a custom field processing prompt to complete automatic unit conversion. Additionally, each single entry has a moderate length, so adaptation to the vector model's input length limit is required to avoid truncating key information.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
embedding_model | text-embedding-ada-002 or locally deployed m3e-base | Adapts to semantic extraction of structured fields for education service financing daily reports; local deployment can meet data compliance requirements |
chunk_max_length | 800–1200 characters | The length of each single financing daily report entry is moderate. This range can fully retain field information and avoid truncation of key content |
recall_top_k | Top 5–8 entries | The volume of data per batch for education service financing daily reports is moderate. This number of recalled entries can cover core associated information and avoid redundancy |
similarity_threshold | 0.75–0.85 | Semantic similarity for structured fields must maintain a relatively high threshold to avoid recalling irrelevant financing records |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Sufficient parsing time must be reserved when processing financing daily report data in batches to avoid mid-run timeouts |
custom_field_weight | school-running qualification filing number:1.5, financing amount:1.2 | Increases the recall weight of core unique fields and amount fields to match data characteristics |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to conduct actual tests on your own samples before finalizing the configuration.
Three common misconfigurations
- Phenomenon: When accessing a locally deployed m3e vector model, the interface continuously displays an "indexing" status with no progress. Cause: The API access port and authentication key for the model are not configured, or the local model service is not started normally.
- Phenomenon: After configuring
embedding_modelastext-embedding-ada-002, the knowledge base recall results are empty. Cause: The API key and access address for this model are not correctly bound in channel management, or the key permissions are insufficient. - Phenomenon: Empty values are returned when extracting school-running qualification numbers from financing daily reports. Cause:
custom_field_weightis not configured to increase the weight of this field, causing the model to prioritize recalling non-core field information and miss the school-running qualification number.
How to confirm the configuration is complete
- Enter the model management interface, check the status of the configured vector model, and confirm that it is in normal running state.
- Upload a single sample of education service financing daily report data, perform a parsing test, and check whether the parsed fields fully match the preset structure.
- Initiate a knowledge base recall test, and verify whether the number and similarity of recall results conform to the preset configuration range.
- Check the system logs to confirm that there are no error records such as vector model call failures or parsing timeouts.
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.