What the data looks like
Industrial park marketing content data is mainly sourced from investment promotion brochures, settled enterprise directories, industrial support policy documents, event announcements from the park operation backend, and location introduction materials from partner channels. Data update cycles are irregular. Investment policies are updated in batches quarterly or monthly. Settled enterprise changes are synchronized weekly or monthly. Temporary event announcements are triggered in real time.
The data includes two categories: structured and unstructured. Structured data mostly includes fields such as park ID, industrial direction, available office area, rent standard, etc. Unstructured data includes text and image posts, PDF investment promotion brochures, event video scripts, etc. Field units are mostly square meters, yuan/square meter/month, and dates in YYYY-MM-DD format.
Constraints Imposed on HTTP Interfaces and External Systems
The multi-source nature, irregular update cycles, and multi-format characteristics of park marketing data impose multiple constraints on HTTP interface and external system integration.
Multi-source data requires interfaces to support unified authentication for multiple data sources such as park operation systems and partner channel backends. Irregular update cycles require interfaces to support both scheduled pulling and webhook real-time triggering synchronization modes. Multi-format data requires interfaces to be compatible with JSON structured data and multipart/form-data file uploads. Numeric fields with units require interfaces to have built-in parameter verification logic to avoid matching errors caused by inconsistent units.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
API_KEY | 32-character random string | Used for identity verification when connecting to external services such as park operation systems and WeChat official accounts, to ensure data access security |
SYNC_FREQUENCY | 300 seconds or webhook trigger | Adapts to the update cycle of park marketing data. Batch policy updates are suitable for scheduled synchronization, while temporary event announcements are suitable for webhook real-time triggering |
REQUEST_TIMEOUT | 60 seconds | Covers the transmission and parsing time of large files such as park investment promotion brochure PDFs and settled enterprise directory Excel files |
REQUIRED_DATA_FIELDS | ["园区名称", "可用办公面积(平方米)", "产业类型"] | Ensures that synchronized marketing content includes core decision-making fields. Missing fields will cause knowledge base matching failures |
PARSE_CONTENT_FORMAT | auto | Adapts to the multi-format characteristics of park marketing content, supports parsing of structured JSON data and unstructured text, image, and PDF documents |
FRP_TRANSFER_PORT | Configured according to the deployment environment | Adapts to port configuration for local Linux server penetration via frp, must match the access port of the external system |
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 on-site analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Symptom: The interface shows a loading spinner with no clear error message, and finally returns a connection timeout. Cause: FastGPT deployed on a local Linux server does not have external API ports open, or the port mapping configuration during frp penetration is incorrect, preventing external systems from establishing a valid connection with the FastGPT service.
- Symptom: Calling the external marketing data interface returns a 401 Unauthorized error. Cause: The correct
API_KEYparameter is not configured, or the passed key does not match the verification key of the park operation system, causing identity verification to fail. - Symptom: Synchronized park marketing content lacks unit fields, resulting in invalid knowledge base matching results. Cause: Unit-related fields are not configured in
REQUIRED_DATA_FIELDS, or the external system returned data does not carry core fields with units such as可用办公面积(平方米).
How to Confirm Correct Configuration
- Call the configured external data interface, check if the returned JSON data includes all fields configured in
REQUIRED_DATA_FIELDS, and that the field formats match expectations. - Simulate an update to park marketing content, trigger synchronization via webhook or scheduled task, and check if corresponding content is added or updated in the FastGPT knowledge base.
- Initiate an API request locally or from the external system, check that a normal response is returned with no timeout or permission errors.
- Configure the agent's internet search logic, trigger a scenario where the knowledge base has no matches, and check that the HTTP interface can be called normally and return search results.
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.