What the Data for This Category Looks Like
This category supports petition matter handling workflows. The system sources data from national petition information systems, local petition systems, the 12345 citizen hotline platform, grassroots governance platforms, and historical petition archives. The system updates this data daily. Commonly generated and circulated documents include petition registration forms, acceptance notices, transfer and assignment letters, handling opinions, review and re-examination applications, and resolution plans. Data fields cover request content, acceptance numbers, responsible units, handling progress, policy basis, and other relevant items. The size of individual data entries varies based on the complexity of the petition request.
Constraints Imposed on Vector Models and Indexes
Scattered data sources update daily, so the system must adapt to multi-source heterogeneous document formats. Index construction must support incremental updates to match the daily synchronization rhythm. Petition-related documents contain fixed fields related to legal procedures. The system must ensure vector retrieval results associate with corresponding fields, and avoid missing key business information such as acceptance numbers and responsible units. Historical archive data has a large volume, so index sharding must support batch import requirements, while remaining compatible with historical documents in different formats. There is a significant semantic difference between request content and policy basis. Vector models must adapt to long-text Chinese scenarios to ensure the accuracy of semantic recall.
How to Configure Settings
These configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the length of single-segment petition requests and policy texts in petition-related documents, avoiding overloading single chunks |
| Overlap Length | 100–200 characters | Retains contextual association across chunks, ensuring that policy basis and request details are not split apart |
maxToken | 8192 | Aligns with the input limit of mainstream Chinese vector models, avoiding truncation of ultra-long texts and loss of key information |
| Similarity Threshold | 0.72–0.85, calibrated via actual testing | Distinguishes valid petition requests from irrelevant content, and adapts to the semantic similarity distribution of petition data |
| Single Search Limit | Top 10 entries | Controls the volume of retrieval results, avoiding exceeding the context carrying capacity of business workflow guidance |
defaultToken | 1024 | Sets the default context window, balancing the information completeness of retrieval recall and answer generation |
Three Common Misconfigurations
- Phenomenon: Retrieval results include unassociated auxiliary documents, and key business fields are empty. Cause: Auxiliary data was not excluded from the petition-specific index, or field mapping rules were not configured, resulting in loss of key information such as acceptance numbers and responsible units.
- Phenomenon: Index construction fails, with a prompt about vector dimension mismatch. Cause: The vector model embedding dimensions used locally and on the server are inconsistent, and model configurations were not unified in advance, resulting in incompatible vector formats.
- Phenomenon: After generating multiple sets of vectors for a single data entry, retrieval results appear repeatedly. Cause: Multi-vector association rules were not configured correctly, resulting in repeated recall of multiple sets of vectors from the same data entry.
How to Verify Correct Configuration
- Import a single petition registration form document, and check whether the index chunk results match the preset chunk length and overlap length.
- Initiate a petition request retrieval, and verify that returned result fields include key business information such as acceptance numbers and responsible units.
- Test the import process for different vector models, confirm that vector dimensions match and there are no truncation error messages.
- Simulate a daily incremental update scenario, check whether the index can normally append new petition data without overwriting historical content.
The values provided are common starting points, and should be evaluated against the user’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.