What the data for this category looks like
Core data for this category comes from the national integrated government service platform item database, administrative licensing item list, departmental business approval systems, and electronic certificate repository. Data updates daily. Daily processed documents include service guides, application forms, commitment letters, acceptance notices, correction notification letters, administrative licensing decision letters, and license certificates. Documents are bounded by statutory licensing items, and include fields such as item setting basis, handling conditions, application material lists, approval processes, and certificate styles. Some documents are structured forms, others are unstructured text, with no unified fixed format.
What constraints these characteristics impose on the vector models and indexing link
Decentralized data sources update daily. Systems must support incremental indexing to avoid repeated processing of full government data. Mixed document types include both structured forms and unstructured text. Vector models must support mixed-format text splitting logic. The characteristic of being bounded by statutory licensing items requires indexes to be grouped by item dimension to avoid cross-item matching errors. Approval-related documents such as correction notification letters and licensing decision letters have strong timeliness. Index retrieval must support real-time performance, and must strictly match item setting basis and handling conditions to ensure retrieval results meet statutory requirements.
How to set configurations
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the length of mixed documents such as service guides and application forms, avoid semantic breaks in single chunks |
| Overlap Length | 100–150 characters | Ensure semantic coherence across chunks, avoid loss of key information in short documents such as correction notification letters |
| Similarity Threshold | 0.72–0.80 | Meet the strict matching requirements for administrative licensing items, filter low-correlation non-licensing documents |
| Single Search Limit | Top 8 entries | Cover multiple types of approval documents under a single item, avoid excessive redundant results interfering with approval opinion drafting |
defaultToken | 2000 | Adapt to the context length of approval documents, ensure retrieval results can be fully used for document drafting |
maxToken | 4096 | Adapt to the input limit of mainstream vector models, avoid model errors caused by overly long contexts |
Three common misconfigurations
- Phenomenon: No models appear in the text understanding model dropdown when creating a knowledge base. Cause: The index model and language model are not bound to their respective configuration items separately, or the model deployment path is not correctly mapped to the FastGPT container.
- Phenomenon: The indexing process takes too long. Cause: No reasonable chunk length and single processing limit are set, and incremental indexing mode is not enabled, resulting in full repeated indexing of daily updated government data.
- Phenomenon: Retrieval results include irrelevant non-administrative licensing documents. Cause: Index data is not grouped by statutory licensing item dimension, and the similarity threshold is set too low, leading to incorrect matching of cross-category documents.
How to confirm the configuration is correct
- Enter the model management page of FastGPT v4.17.0, confirm that the added ollama qwen2.5 language model and bge-m3 index model both show as available.
- Upload a single service guide document, perform manual indexing, check that the indexing progress bar completes within 1 minute, with no timeout errors.
- Retrieve the handling conditions for a specified administrative licensing item, confirm that the returned results include official document fragments for the corresponding item, with no irrelevant content.
- View the indexing logs, confirm that the daily incremental update task triggers automatically, only synchronizes newly added government data on the day, with no full repeated indexing records.
The values listed above 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.