What Data for This Category Looks Like
Data for this category primarily comes from customer interviews, bidding documents, vendor product materials, and historical project plans. Daily produced documents include technical proposal books, customer requirement survey forms, quotation lists, and demo scripts. Each entry includes fields such as customer business scenarios, technical routes, implementation boundaries, and quotation details. The data update frequency is per order or weekly, with single updates mostly focused on adjustments to customer requirements or refinement of project boundaries.
Constraints Imposed on Database and Operations Maintenance
The data characteristics of this category impose multiple constraints on the database and operations maintenance link. First, the mixed storage requirement for multiple types of documents means the database must support both structured and unstructured data, while adapting to both the text content of technical proposals and the numerical fields of quotation lists. Second, the high-frequency updates per order or weekly require the database connection pool configuration to adapt to sudden write and retrieval requests, avoiding connection exhaustion. Third, the time-consuming requirement clarification and boundary design process means fast retrieval of similar historical project plans is needed, which places requirements on database index optimization and caching capabilities. Finally, the consequences of errors directly affect project success or failure, requiring data read-write consistency and availability to meet standards, and avoiding overpromising in proposals due to data errors.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://fastgpt:securepass@db-host:27017/pre-sales-proposal-library?authSource=admin | Stores unstructured text data from technical proposal books and demo scripts |
PG_URL | postgresql://fastgpt:securepass@db-host:5432/plan-metadata | Stores structured numerical and associated fields from customer requirement survey forms and quotation lists |
DB_MAX_LINK | 20–30 | Adapts to the per-order or weekly update frequency, avoiding database connection exhaustion during business peaks |
REDIS_URL | redis://:securepass@cache-host:6379/0 | Caches frequently retrieved historical plan fragments to reduce query latency during requirement clarification |
| Database index configuration | Create a composite index for the business scenario field of technical proposal books | Accelerates similar scenario retrieval of historical plans, addressing the time-consuming pain point of requirement clarification |
Three Common Misconfigurations
- Only creating MongoDB and vector database images during startup and deployment, without starting the sandbox container. This causes a dependency service not ready error when demo scripts are executed, preventing local link verification from completing. The sandbox is required to simulate the customer business environment during pre-sales proposal demonstrations; without deployment, test interfaces cannot be called.
- After replacing the MongoDB image with
mongo:4.4.29, historical plan retrieval times out, and the interface returns status code 500. FastGPT v4.17.0 has specific dependencies on MongoDB versions, and older versions do not support some aggregate query syntax, leading to data retrieval failures. - Not configuring Redis caching, leading to repeated reads from the database when querying the same historical plan multiple times, resulting in retrieval latency exceeding 10 seconds during proposal preparation. Pre-sales proposals frequently call historical project data, and without caching, database load increases and operation latency is extended.
How to Verify Successful Configuration
- Use a database client to connect to the database specified by
MONGODB_URI, and verify that historical plan documents and demo scripts can be properly written and retrieved. - Connect to the database specified by
PG_URL, and verify that associated fields of customer requirement survey forms and quotation lists can be properly read. - Check database connection logs to confirm that the
DB_MAX_LINKconfiguration does not trigger connection exhaustion errors during business peaks. - Call the cache query interface, and verify that the service specified by
REDIS_URLcan properly store and retrieve frequently retrieved plan fragments.
The values given are common starting points and should be measured 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.