Reference only; verify against the target FastGPT release and deployment documentation.
What This Category of Data Looks Like
Data primarily comes from internal enterprise declaration systems and archived files from the Ministry of Agriculture and Rural Affairs filing platform. A single declaration material includes four document types: product formula sheets, third-party test reports, production qualification scan copies, and filing application forms. Files are categorized and archived by registration certificate number and production batch. Updates follow declaration batch timelines, with single batch import volumes reaching dozens of documents. Fields include active ingredient content, production batch number, test date, and approval status. Units include grams per liter, percentage, tons, and other standard units.
Constraints on Vector Models and Indexing From These Characteristics
Mixed document types in declaration materials and files require indexing to support vector mapping of both unstructured text and structured fields. Wide variation in single-document length requires flexible configuration for long text chunking and short text completion. The categorization logic by registration certificate number and production batch requires vector databases to store data partitioned by business dimensions, to avoid vector confusion across batches. High single-batch import volume from bulk declarations requires indexing configurations to support concurrent write threshold adjustments. Unit differences in structured fields require field standardization mapping before vector generation, to ensure accurate vector matching.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the average text length of test reports and application forms in declaration materials, prevents single chunk token count from exceeding model limits |
| Overlap Length | 50–100 characters | Preserves contextual connections between chunks of long documents, ensures logical coherence during review |
| Similarity Threshold | 0.75–0.85 | Distinguishes valid declaration materials from abnormal file matches, aligns with strict fertilizer and pesticide registration standards |
| Single Search Limit | Top 10 entries | Matches the number of files per declaration batch, avoids returning excessive redundant results |
defaultToken | 4096 | Matches the input token limit of mainstream open-source vector models, ensures complete vector generation for long texts |
maxToken | 8192 | Covers full vector generation requirements for long documents, prevents truncation of critical review information |
Three Common Misconfigurations
- Phenomenon: When calling a vector model accessed via Ollama, FastGPT returns a connection refused error, but curl commands can normally retrieve vectors. Cause: Ollama's API port does not have cross-domain access enabled, or the FastGPT configured API address does not include the port suffix.
- Phenomenon: Duplicate registration certificate number file entries still appear after index merging. Cause: Deduplication configuration by business primary key (such as registration certificate number) is not enabled, only fuzzy matching of text content is performed.
- Phenomenon: Unable to directly manage vector database add/delete operations via an external MongoDB system. Cause: FastGPT's vector database only opens built-in management interfaces by default, and access permissions for external systems are not configured.
How to Verify Proper Configuration
- A single typical declaration material is uploaded, and the number of generated vector chunks is checked against the document length. Chunk length may be adjusted to a reasonable range.
- A simulated review request is submitted, and the number of returned matching files is verified against the single search limit configuration.
- An attempt is made to initiate vector database add/delete operations via an external system, and permission configurations are confirmed to take effect.
- Multiple files with the same registration certificate number are imported, and whether deduplication logic is triggered during index merging is checked.
The values provided 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 2026-09-28.