What data this category includes
This category’s data primarily comes from normative documents, policy interpretations, and implementation rules officially released by the State Council, industry competent ministries and commissions, and local governments. Data updates have no fixed cycle. New or revised policies trigger additions or overwrites of existing data. Each document typically includes fields for policy document number, title, issuing authority, release date, main body, and attachments. The main body uses plain text characters as its unit. Document numbers follow standard administrative document numbering formats, and no additional custom fields are included.
What constraints these characteristics impose during deployment and upgrade
Decentralized sources of official policy documents require deployment to adapt to multi-source crawling format rules, and compatibility with document layout differences across different ministries and commissions. No fixed update cycle requires configuring a flexible trigger synchronization mechanism during upgrades. Updates are triggered by push signals from official release channels instead of fixed polling. Fixed document field structures require preset field mapping rules to prevent missing or misaligned fields during parsing. Long main body content requires configuring sufficient storage and word segmentation processing resources during deployment to meet vector generation and storage requirements for large text.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:securepass@192.168.1.20:27017/policy_db?authSource=admin | Stores policy document metadata and vector indexes; must match the database address and authentication information of the deployment environment |
REDIS_URL | redis://:redispass@192.168.1.20:6379/1 | Caches policy parsing results and session contexts; must adapt to the Redis service port and database index of the deployment node |
STORAGE_S3_ENDPOINT | http://192.168.1.20:9000 | Stores policy document attachments and large text fragments; must point to a local or private cloud object storage service address |
DB_MAX_LINK | 800–1200 entries | Limits the number of policy document links crawled per batch to avoid exceeding server concurrent processing capacity; calibrated based on actual testing |
FILE_TOKEN_KEY | 64-bit random hexadecimal string | Configures the access token key for policy document attachments to ensure secure file access |
Three common misconfigurations
- Symptom: Unable to connect when accessing the public IP + port of the deployment node, but local access via 127.0.0.1 works normally. Cause: The service’s public network listening address was not configured, and only the local loopback address was bound, preventing external requests from connecting.
- Symptom: Tool calls cannot be triggered after configuring model associations, and Q&A results only return fragments of original policy documents. Cause: The model’s tool call parameters were not correctly configured, or the tool call switch was not enabled in the system, preventing the model from calling the policy matching tool.
- Symptom: Timeout errors occur when batch crawling policy documents, and some documents fail to sync. Cause: The value of
DB_MAX_LINKis too high, exceeding the server’s concurrent processing limit, causing crawling tasks to time out and interrupt.
How to verify successful configuration
- Run the system’s built-in database connectivity test script to confirm that the connection status of
MONGODB_URIandREDIS_URLis normal. - Manually trigger a policy document crawling task, check the task logs for parsing results without formatting errors, and confirm that the field mapping rules are active.
- Access the configured
FE_DOMAINaddress, confirm that the front-end interface can normally load and display the policy Q&A related function modules. - Generate a test question related to policy, check whether the system’s returned results include matching policy document fragments, and confirm that the vector index and recall logic are working normally.
The values provided are common starting points and should be evaluated against samples relevant to the specific deployment.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.