Reference only; verify against the target FastGPT release and deployment documentation.
What Data Looks Like for This Category
Data for this category primarily originates from internal enterprise onboarding management documents, job-specific onboarding handbooks, office system operation guides, welfare policy documents, and cross-departmental docking process descriptions. Updates are triggered by enterprise organizational structure adjustments, policy changes, or new job additions, with no fixed cycle. Individual document update frequency is low. Most documents are structured text, divided into chapters by department and job category. Fields include job name, docking department, processing time limit, required material list, system operation steps, and unit identifiers such as working days, quantity, and permission level.
Constraints Imposed by These Characteristics on the Vector Models and Indexing Stage
Structured documents divided by job and department require index libraries to be split by business dimension during the indexing stage, to avoid invalid cross-job recall. The low update frequency of documents allows reducing the frequency of full index refreshes, cutting down on computing resource consumption. Fields with unit identifiers require vector models to recognize basic unit semantics, preventing confusion between "3 days" and "3 hours". Individual document content focuses on a specific onboarding process, so chunking must retain the full process logic to avoid semantic breaks from truncation.
Configuration Guidelines
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | New hire onboarding documents are mostly process-based text; this length preserves the complete semantics of a single process |
| Overlap Length | 100–150 characters | Prevents chunk truncation of process steps and ensures coherent semantics across chunks |
maxToken | 16000 | Adapts to the input limit of mainstream embedding models and covers complete onboarding document content |
| Similarity Threshold | 0.75–0.85 | Accurately matches job-related onboarding guidance and filters irrelevant cross-job content |
| Single Search Limit | Top 3 results | New hire questions mostly focus on single processes; a small number of recalls can cover requirements |
defaultToken | 4096 | Matches the default input parameters of basic embedding models and ensures stable index generation |
Three Common Misconfigurations
- Phenomenon: Timeouts occur when calling the employee service desk, and the interface shows search time exceeding the preset threshold. Cause: Incorrectly attributing slow search speed to the vector model, without troubleshooting delays in the language model call chain or recall delays caused by unreasonable index sharding.
- Phenomenon: After configuring text-embedding-ada-002 in the system, a "no relevant" type error pops up when using the knowledge base. Cause: The embedding model was not correctly bound to the vector index channel of the employee service desk, or configuration parameters were not synchronized to service instances.
- Phenomenon: After connecting a local m3e embedding model, the system permanently displays the "indexing" status with no changes. Cause: Access timeout parameters for the local model were not configured, or the local model lacked sufficient loading resources, causing the index generation process to block.
How to Confirm Successful Configuration
- View vector index generation logs to confirm that embedding model call requests match configuration items.
- Submit a test question and verify that the number of recall results matches the configured single search limit.
- Simulate high-frequency new hire questions and check that the recalled documents' job and department correspond to the question scenario.
- View the system monitoring panel to confirm that index refresh time meets preset resource occupancy requirements.
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 2026-09-28.