What the data for this category looks like
Industrial park investment research data primarily comes from park operators’ investment promotion ledgers, settled enterprise operating reports, local industrial policy documents, and monthly park energy consumption and rent statistical reports. Update cycles vary significantly: data related to investment promotion signings and rent payments updates daily or in real time, while industrial policy and park planning documents are released on an irregular basis. Documents include structured tables such as settled enterprise revenue details and per-mu tax statistics, semi-structured policy files, and long-text industrial analysis reports. Core fields include settled enterprise name, per-mu tax, park floor area ratio, contracted amount, and more. Units are mostly ten thousand yuan, mu, and square meters.
What constraints these characteristics impose on model access and configuration
The high proportion of structured data requires model access to adapt to parsing and vectorization of tabular text. Preprocessing rules that support structured splitting must be configured. Significant differences in data update cycles require configuring trigger conditions for incremental synchronization to avoid wasting resources from full re-runs. Long-text industrial analysis reports account for a notable share, so context window parameters must be adjusted to support long document processing. Core fields carry specific units, so unit information for fields must be retained during recall and model invocation to prevent unit confusion in investment research conclusions.
How to set configurations
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
maxContext | 8000–16000 characters | Meets context length requirements after splicing long-text industrial park reports and structured tables |
CHUNK_SIZE | 800–1200 characters | Balances semantic integrity of split structured tables and accuracy of vector recall |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Meets parsing time requirements for large industrial planning documents and multi-page structured ledgers |
RECALL_TOP_K | Top 8–12 entries | Covers multiple core investment research data dimensions including park investment promotion, revenue, policies, and energy consumption |
SIMILARITY_THRESHOLD | 0.75–0.85 | Accurately distinguishes similar park business data and avoids recall of irrelevant content |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports upload of large files such as industrial analysis reports and annual operating ledgers |
The parameter values provided on this page are standard recommendations to serve as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: A 404 error is returned in the interface when accessing a locally deployed model via a third-party forwarding service. Cause:
baseURLis not correctly configured as the interface address of the forwarding service, or theauthorizationfield does not carry a valid access key. - Symptom: An error occurs during the recall process after the vector model is configured, and the interface prompts a model invocation exception. Cause: Exclusive parameters for the vector model are not specified, or the selected vector model cannot adapt to text splitting and vectorization of park structured tables.
- Symptom: Custom model calls in the workflow cannot output streaming response results. Cause: The streaming response switch for the workflow node is not enabled, or the code running module does not correctly handle the return format of streaming data.
How to confirm configurations are properly set
- Upload a park industrial planning document, check if the parsed text segments fall within the configured segment length range, to confirm that the preprocessing rules are active.
- Initiate a query related to park investment research, verify that the number of recall results matches the configured recall quantity requirement, to confirm that the recall logic is running normally.
- Call the configured model, check if the returned results retain the unit information of park data, to confirm that the context parameters and field processing rules are active.
- Upload a large park operating ledger, confirm that the upload and parsing process does not trigger a timeout error, to verify the effectiveness of the timeout configuration.
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.