What the data for this category looks like
The data for chemical raw material research reports targeting the finance, insurance, and wealth management sector comes primarily from public industry association reports, regular listed company announcements, customs import and export monitoring data, and specialized analysis from third-party consulting firms. Update cycles include regular monthly supply and demand reports, quarterly capacity inventory reports, and real-time tracking reports released after sudden raw material price shifts or policy changes. Individual document lengths vary widely: some are short price briefs of several thousand words, while others are full industrial chain analysis reports spanning tens of thousands of words. Core fields include product common name, CAS number, current market price, monthly capacity, upstream and downstream related categories, and policy impact entries. Some reports include structured monthly price fluctuation annotations. Most field units follow standard chemical measurement conventions, such as yuan/ton and ten thousand tons/year.
What constraints do these characteristics impose on deployment and upgrade?
The multi-source and heterogeneous data characteristics of chemical raw material research reports set clear requirements for document parsing capabilities during deployment. Parsing must support structured extraction of professional fields such as CAS numbers and capacity units. Data sources with different update cycles require configuration of incremental synchronization scheduling rules during deployment, to distinguish pulling logic between regular periodic reports and emergency incident reports. The standardized storage requirement for professional fields requires reserving dedicated metadata fields in the vector database configuration, to match product identifiers and measurement units. The high proportion of long documents increases adaptation costs for context window tuning and segmented recall strategies during the upgrade phase.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Some long chemical raw material research reports contain multi-chapter industrial chain data, requiring longer parsing time to avoid mid-process interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some full industrial chain special research reports have large single-file sizes, requiring adaptation for large file uploads |
maxContext | 8000–12000 characters | Segmented processing of long research reports requires sufficient context to associate information about upstream and downstream categories |
recall_count | Top 10 results | There are many specialized chemical raw material categories, so a sufficient number of relevant reports must be recalled for subsequent screening |
similarity_threshold | 0.75–0.85 | Semantic similarity requirements for professional terms are high, to avoid recalling general chemical reports unrelated to the target category |
rerank_count | Top 3 results | Professional research reports require precise presentation of top results, reducing the cost of user screening for professional content |
The parameter values provided on this page are general recommendations used as a starting point 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 Configuration Mistakes
- Symptom: When using a third-party large model key, configuration succeeds but calling fails, returning a
401 Unauthorizederror. Cause: The exclusive domain whitelist for the corresponding large model was not added in the FastGPT platform key configuration, or the key was not bound to correct calling permissions. - Symptom: FastGPT V4.9.1 deployed via Docker Compose or Saleos cannot access the registration page or create new users. Cause: The
ENABLE_SIGNUPenvironment variable was not enabled during deployment, or database initialization user permission parameters were not configured correctly. - Symptom: After power loss and restart, PostgreSQL and MongoDB containers fail to start, prompting a
connection refusederror. Cause: Persistent mounting of container data volumes was not configured. Power loss caused corruption of database files inside the containers, making it impossible to read locally stored database data after restart.
How to Confirm Proper Configuration
- Upload a locally saved chemical raw material research report, check if the parsed metadata includes dedicated fields such as CAS number and price unit, and verify that the field extraction results match the original text.
- Trigger an incremental synchronization task, check if the synchronization log distinguishes the pulling time between regular periodic reports and emergency incident reports, to confirm that the scheduling rule takes effect.
- Initiate a retrieval request for a specific chemical raw material, check if the number of returned results and similarity matching degree conform to the verification logic of the preset configuration.
- Restart the deployment service, verify that all containers (including databases, parsing services, application services) start normally, with no connection refused or timeout errors.
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.