What the data for this use case looks like
Data sources for investment research include internal credit management ledgers, regional agricultural business entity operation monitoring data, policy documents released by local regulatory authorities, regional economic research minutes, and public disclosure information of enterprises within the region. Update rhythms include daily updated credit business data, monthly updated regional economic monitoring data, and irregularly updated regulatory policy documents. Document structures include structured business reports, semi-structured notices and announcements, unstructured research minutes and reports. Fields include institution code, loan five-category classification, operating entity revenue, regional growth rate, and others. Units include ten thousand yuan, percentage points, number of households, and others.
What constraints these characteristics impose on deployment and upgrade
Mixed-structure documents require deployment to support multi-format parsing and structured field extraction, and upgrades to support compatibility with updates of parsing plugins for different formats. Differentiated update frequencies require deployment to support flexible configuration of scheduled synchronization tasks, and upgrades to ensure incremental synchronization functions do not interrupt daily business. Regional and sensitive business data require deployment to configure local data access permissions and encrypted transmission rules, and upgrades to synchronously update compliance configuration items. Differences in business fields across entities require deployment to support custom field mapping, and upgrades to retain user-customized field configurations.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Investment research documents include long-text credit ledgers and regional economic research reports. Default timeout durations cannot cover full parsing requirements |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports batch uploading multiple PDF reports and ledger files for regional economic research, meeting the needs of batch importing business data |
maxContext | 8000–12000 characters | Adapts to the long-paragraph structure of investment research documents, avoiding truncation of text fragments containing key business fields |
Retrieval Count | Top 8 entries | Balances the relevance of investment research data and retrieval efficiency, adapting to the limited volume of regional segmented data |
ENABLE_ENV_IN_WORKFLOW | Enabled | For versions v4.8.17 and above, this configuration item is disabled by default. Manual enabling is required to support calling custom environment variables configured during docker deployment in workflows |
AI_PROXY_URL | Local vLLM deployment address | Connect to a self-deployed large language model, meeting the compliance requirements for financial data |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common misconfigurations
- Symptom: A curl connection timeout error with status code 500 appears shortly after starting the
aiproxycontainer. Cause:AI_PROXY_URLis not correctly configured to point to the locally deployed large language model address via vLLM, causing the proxy to fail to forward requests normally. This issue is more prominent in the proxy logic updated in version v4.9.0 and above. - Symptom: Custom environment variables cannot be read in workflows, with empty field returns. Cause: The
ENABLE_ENV_IN_WORKFLOWconfiguration item is not enabled, causing workflows to fail to call externally configured environment variables. This issue is common in scenarios where upgrading from v4.8.17 to a newer version. - Symptom: Structured table fields are lost after parsing batch-uploaded credit ledgers. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted. Long-text parsing times out, causing task interruption and failure to complete extraction of some structured fields.
How to confirm configurations are correct
- Enter the proxy configuration page in FastGPT system settings, verify that
AI_PROXY_URLmatches the deployment address of the local vLLM service, and initiate a test request to confirm the return result is normal. - Create a test workflow, insert an environment variable call node, enter a pre-configured custom environment variable name, and check that the node return value matches the variable content set during deployment.
- Upload a regional economic research document containing structured tables, check that the parsed text retains the original table fields with no obvious truncation.
- Enable an incremental synchronization task, wait for the specified duration, then check the synchronization logs to confirm only newly added business data is synchronized to the knowledge base, with no full duplicate synchronization records.
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.