Deployment and Upgrade for Coking Coal Investment Research

What this category of data looks like

Coking coal investment research data sources include Dalian Commodity Exchange public market data, China Coal Transportation and Marketing Association monthly reports, major port spot price systems, and steel mill purchase ledgers. Update cadence has multiple tiers: futures market data updates in real time, spot prices update daily, supply and demand balance sheets and industrial policy documents update weekly or monthly. Document formats primarily include structured tables, PDF industry reports, and API-pushed structured data. It includes dedicated fields such as coking coal grade, dry base ash content (%), total sulfur content (%), flat warehouse price (yuan/ton), port inventory (10,000 tons), and delivery benchmark price. Units strictly follow general industry specifications.

Constraints on Deployment and Upgrade Phases

The multi-source heterogeneous characteristics of coking coal data require deployment to adapt to access and parsing of multiple data formats. Configure separate parsing rules for structured tables and unstructured reports. Data with different update frequencies require differentiated vector update strategies. Real-time market data must support incremental synchronization. Monthly reports must support full batch updates. The upgrade phase must support switching between these two modes. Industry-specific fields and units are easily confused with general text. Adjust text chunking logic during deployment to prevent incorrect splitting of units. Some sensitive port procurement data requires encrypted transmission. Configure SSL certificates and fine-grained access permissions during deployment.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Coking coal industry single monthly supply and demand report typically does not exceed 300 MB, with reasonable buffer space reserved
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Long-period coking coal industry reports contain multi-page complex tables, requiring sufficient time for complete parsing
`Recall count`	`Top 8 entries`	Coking coal investment research requires covering multi-dimensional data including spot, futures, and policy. 8 entries balance recall coverage and response speed
`Similarity threshold`	`0.75`	Coking coal data has strong professionalism. This threshold filters low-correlation general text and retains professionally matched content
`UPLOAD_ALLOWED_EXTENSIONS`	`["pdf", "csv", "xlsx", "json"]`	Common formats for coking coal investment research data are PDF reports, CSV market tables, Excel ledgers, and API interface JSON data
`FASTGPT_BASE_PATH`	`/fastgpt`	Complies with private deployment path access specifications, adapts to unified reverse proxy configurations

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. It is recommended to test on your own samples before finalizing settings.

Three Common Configuration Mistakes

Symptom: After modifying the ROOT_PASSWORD environment variable, login still uses the default password, and the system cannot be accessed. Cause: The FastGPT container was not restarted to apply the configuration, or the environment variable was not correctly overwritten in the configuration file.
Symptom: After Docker deployment, accessing http://localhost:3000 results in a loading spinner followed by failure, with the console returning 502 Bad Gateway. Cause: The database container failed to start normally, or port mapping configuration is incorrect, preventing service connectivity.
Symptom: After private deployment, the application cannot be accessed via the /fastgpt path, while accessing the root path works normally. Cause: The FASTGPT_BASE_PATH parameter was not configured correctly, or the reverse proxy did not synchronously update path rules.

How to Confirm Configurations Are Correct

Upload a coking coal monthly supply and demand report. Check if parsed text retains dedicated fields including dry base ash content and flat warehouse price. Verify that UPLOAD_ALLOWED_EXTENSIONS and UPLOAD_FILE_MAX_SIZE configurations take effect.
Initiate a knowledge base recall query. Confirm the number of returned results matches the Recall count configuration. Verify the filtering effect of the Similarity threshold meets expectations.
View container logs. Confirm the ROOT_PASSWORD environment variable has been loaded. Log in to the system to verify password modifications take effect.
Configure the reverse proxy. Access the application via the /fastgpt path. Confirm redirection and loading work normally. Verify the FASTGPT_BASE_PATH configuration is correct.

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.