What the data for this category looks like
This category uses customer interviews, bidding documents, vendor product materials, and historical project plans as data sources. Updates occur per order or weekly. Daily deliverables include technical proposal documents, customer requirement research forms, quotation lists, and demo scripts. Core fields cover proposal technical routes, implementation boundaries, quotation configuration items, customer requirement matching points, and more. Data centers on pre-sales requirements for a single customer project, and updates synchronize with requirement clarification and plan adjustments as the project progresses. All data must strictly match the customer’s bidding requirements and implementation boundaries.
What constraints these characteristics impose on the deployment and upgrade link
Unique data characteristics of individual projects in this category require the deployment process to support configuring independent knowledge base association rules for each pre-sales project. This prevents mixing of plan document data across different projects. High-frequency update requirements mandate that the upgrade process support hot updates or zero-downtime switching. This stops upgrade interruptions to pre-sales demo progress. Requirements for structured processing of multiple document types require deployment configurations to support access to data sources in formats like technical proposal documents and demo scripts. Configurations must also strictly match mapping rules for proposal boundary fields. This prevents over-scope commitment of proposal content caused by configuration deviations, which can lead to bid scoring losses or project loss risks.
How to set the configurations
These configuration items apply to the deployment and upgrade scenarios of FastGPT v4.17.0:
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
DB_MAX_LINK | 100–200 connections | Adapts to the high-frequency query scenario of pre-sales proposal documents, avoiding knowledge base access failures caused by connection pool exhaustion |
MONGODB_URI | Fill in according to the project-specific database instance | Meets the independent data storage requirement for single pre-sales projects, isolating proposal data from different projects |
REDIS_URL | Configure the local cache instance address | Accelerates session caching for internal work order Q&A, improving response speed during pre-sales demos |
ROOT_KEY | Random 32-bit string | Ensures background access security for deployment, complying with permission control requirements for pre-sales projects |
FE_DOMAIN | Fill in the access domain name of the pre-sales demo environment | Matches the frontend display path of demo scripts, ensuring normal page loading |
FILE_TOKEN_KEY | Random 16-bit string | Used for signature verification of internal work order attachments, ensuring access security for pre-sales proposal documents |
Three common mistakes
- After upgrading to a new version, knowledge base queries run normally but the model produces no output. Knowledge base recall results appear normal, but the model returns empty content or no valid output. The root cause is that the
REDIS_URLconfiguration resets after the upgrade, clearing the session context cache so the model cannot access the query context. - After Docker deployment, the 3000 port page fails to load, while the 3001 port works correctly. The host’s 3000 port shows no response, but the 3001 port loads the frontend page normally. The issue stems from incorrect frontend service port mapping: the container’s internal 3000 port is not mapped to the corresponding port on the host machine.
- After Linux deployment, modifying the configuration file does not take effect. Corresponding functions do not change after configuration edits. The root cause is failure to restart the relevant service process, or the modified configuration item does not match the loading path in the startup script.
How to confirm the configuration is complete
- Access the configured
FE_DOMAINto verify the frontend page loads normally, with no resource loading failure errors. - Run a database connection test to confirm the instances configured via
MONGODB_URIandREDIS_URLconnect successfully. - Log in to the backend management interface using
ROOT_KEYto verify the permission control function operates correctly. - Upload a pre-sales proposal document, trigger a knowledge base query, and confirm results output normally to the model and display correctly.
The values provided here are common starting points, and should be evaluated against the reader’s own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.