What this type of data looks like
Data sources include public project announcements from local ecological environment departments, credit announcements from financial institutions, and environmental project financing filing information from the national public resource trading platform. The update schedule is daily updates for new air pollution control projects and financing changes for existing projects from the previous day. Each data entry includes project ID, project name, air pollution control sub-type (such as industrial waste gas treatment, dust comprehensive treatment), implementing entity, financing amount, funding source, filing date, and affiliated administrative region. For field units: financing amount is measured in RMB ten thousand yuan, dates use ISO standard format, and administrative regions are marked at the province, city, and county three-level hierarchy.
Constraints on the vector models and indexing workflow
This data set imposes several constraints on the vector models and indexing workflow:
- The data includes both structured fields and unstructured project description text, requiring joint vectorization and indexing for multi-modal vectors.
- The daily incremental update feature requires the indexing system to support incremental building, to avoid resource consumption from full reindexing.
- The financing amount is a numeric field that must participate in vector matching alongside text fields, so indexing rules that support multi-field fusion must be configured.
- Administrative region and project type are high-frequency filter fields, so a secondary index should be built to improve filtering efficiency.
- Text length varies widely across individual data entries, so a flexible chunking strategy must be adjusted to fit content of different lengths.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Fits the average length of air pollution control project descriptions, avoids vector detail loss from overly long text, and prevents context breakage from overly short text |
UPLOAD_CHUNK_OVERLAP | 100–150 characters | Retains contextual connection between adjacent chunks, fits the coherent expression of project background and financing information in financing daily reports |
VECTOR_MODEL_NAME | text-embedding-3-large | Supports multi-field vector fusion, meets the requirements of joint vectorization for structured fields and unstructured text |
INDEX_INCREMENTAL_ENABLE | Enabled | Fits daily incremental update of financing data, avoids resource consumption from full index rebuilding |
RECALL_TOP_K | Top 10–15 entries | Balances recall coverage and query latency, fits the multi-condition retrieval requirements of financing daily reports |
SIMILARITY_THRESHOLD | 0.72–0.85 | Filters low-relevance search results, fits the semantic matching accuracy requirements for fields such as project names and funding sources |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common configuration mistakes
Phenomenon 1
After uploading air pollution control project documents larger than 10MB, some chunks show vectorization failure, and partial recovery occurs after repeatedly clicking retry. Cause: No reasonable chunk_overlap parameter is set, leading to breakage of key context after chunking, and vector generation for some short chunks triggers exceptions from model boundary thresholds.
Phenomenon 2
After the server crashes and restarts due to a large number of file uploads, the status of the created financing daily report knowledge base stays at "not ready", and no automatic index trigger logs are present. Cause: The INDEX_AUTO_RECOVER_ON_CRASH configuration is not enabled, so incomplete index tasks are not automatically recovered after restart.
Phenomenon 3
After updating the platform version from 4.9 to 4.10, vector retrieval for the original air pollution control financing daily report knowledge base returns no results. Cause: The embedding dimension of the vector model changes after the version upgrade, and the documents in the existing knowledge base are not re-vectorized and reindexed.
How to confirm the configuration is correct
- Upload a single air pollution control project document larger than 10MB, check whether the background logs contain
chunk_vectorize_successsuccess logs, and there are no abnormal error fields. - Manually trigger an incremental indexing task, verify that the number of documents returned after indexing is consistent with the number of uploaded documents.
- Enter a combined search term that includes the project name and financing amount range, verify that the sorting logic of the search results meets the expectations of semantic matching and field filtering.
- Restart the platform service, check whether the knowledge base status automatically changes from "not ready" to "ready", without requiring manual index triggering.
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.