What the data for this category looks like
Data sources for industrial park research reports include official public park documents, special survey materials from industry associations, and park analysis reports from third-party industrial consulting institutions. Update frequencies follow monthly releases of operational data, quarterly updates on investment promotion activities, and annual revisions to industrial plans. Document structures typically include basic park overview, industrial cluster layout, settled enterprise analysis, supporting policy details, and operational efficiency metrics. Fields include park land area, number of settled enterprises, tax per mu, and industrial category, with units: square meters, count, ten thousand yuan/mu, and category name.
What constraints these characteristics impose on deployment and upgrade
The multi-source, dispersed nature of industrial park research report data requires that the deployment phase supports combined configuration of batch local document import and API pulling of official public data. Long document length and fixed structure will prolong single-file parsing time, so parsing timeout thresholds need adjustment to adapt. The monthly/quarterly update rhythm requires that the upgrade phase’s trigger logic supports incremental synchronization, without using full re-scanning, to reduce resource consumption. Specific operational fields and units require pre-configured custom extraction rules to avoid missing fields or format chaos after parsing.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Industrial park research reports have long single-file length; default timeout values are insufficient for complete parsing |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Park research reports often include multi-page charts and supporting attachments; single-file size is usually larger than general documents |
maxContext | 8000–12000 characters | Research report content is dense and topic-focused; a sufficient context window is needed to carry complete parsing fragments |
Recall count | Top 8–12 results | Industrial park research reports focus on narrow sub-topics; excessive recall will introduce non-core redundant content |
Custom extraction fields | Configure as Park land area, number of settled enterprises, tax per mu, industrial category | Matches core operational fields of industrial park research reports to avoid missing fields or format chaos after parsing |
Incremental sync trigger cycle | Weekly | Adapts to the update rhythm of park operational data, balancing data timeliness and system resource consumption |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- After uploading a large industrial park research report, the system shows a
Parsing timed outstatus. The cause is failure to adjust thePARSE_FILE_TIMEOUT_SECONDSparameter, using the default shorter timeout value. - After configuring a large model API key, a
401 Unauthorizederror occurs during calls. The cause is failure to correctly configure the key’s permission scope, or a mismatch between the region bound to the key and the calling region. - Answers returned by a locally deployed large model for research reports have lower accuracy than cloud-hosted versions. The cause is that the locally deployed model has not loaded fine-tuned weights for the target domain, or the context window configuration is insufficient.
How to confirm the configuration is complete
- Verify that the deployment environment is Ubuntu Server 24.04, and system dependency packages are fully configured.
- Upload a typical industrial park research report, and check whether the parsed results include the preset custom extraction fields with expected formats.
- Initiate a research report retrieval request, and confirm that the number of returned recall results falls within the configured recall count range.
- Manually trigger an incremental sync task, and confirm that the system only updates park public data from the corresponding cycle, with no full re-scanning behavior.
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.