Reference only; verify against the target FastGPT release and deployment documentation.
What data in this category looks like
Data for this category comes from enterprise contract management systems, compliance risk databases, legal and regulatory repositories, case management systems, and reporting platforms. Daily documents include compliance risk lists, legal review opinions for contracts, legal opinions on major matters, compliance review forms, and investigation reports on violation reports. Data is updated monthly. Most documents contain specialized fields such as compliance clauses, risk levels, and handling opinions. There are no unified fixed units. Individual document lengths vary widely, ranging from hundreds to tens of thousands of characters.
What constraints these characteristics impose on embedding models and indexing workflows
Data sources are scattered across different business systems. Adapt vector conversion for multi-format documents to ensure accurate semantic extraction for compliance-related text. The monthly update frequency requires indexes to support incremental updates, reducing operational costs and time investment without full reconstruction. Documents contain specialized compliance fields. Embedding models must adapt to legal professional semantics, avoiding semantic deviations from generic models for compliance terminology. Individual document lengths vary widely. Set reasonable chunking rules to retain key compliance information, preventing important risk points from being split and missed. Since errors have severe consequences, index recall results must have high confidence, avoiding missed critical compliance risks.
How to set configurations
For local deployment scenarios, fill in the connection address and authentication information for external indexing models to ensure connectivity with compliance-related data sources. Free open-source indexing models must adapt to legal professional semantics, and can be accessed through compliant channels. The following configurations are adapted to the business data characteristics of this category:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the length of specialized paragraphs in compliance documents, retains complete compliance clauses and risk descriptions |
| Overlap Length | 100–200 characters | Prevents key compliance information from being truncated by chunking, ensures semantic coherence across chunks |
| Similarity Threshold | 0.75–0.85 | Filters low-relevance general legal text, focuses on this enterprise’s exclusive compliance data and risk information |
| Single Search Limit | Top 8 results | Balances coverage of compliance information recall and retrieval response efficiency |
defaultToken | 4096 | Adapts to the long-text processing needs of legal professional documents, retains complete context |
maxToken | 8192 | Supports merging context content from multiple compliance-related documents, covers complex risk analysis scenarios |
Three common misconfigurations
- Phenomenon: An error occurs when calling the language model after creating the indexing model, prompting that the corresponding model cannot be found. Cause: The binding relationship between the indexing model and the language model is accidentally disconnected, or the language model is incorrectly replaced with the indexing model for configuration.
- Phenomenon: No retrieval results appear after vector storage migration, with logs showing connection failure. Cause: Connection configuration parameters for the vector storage are not updated, or vector data of original compliance-related documents are not synced to the new storage service.
- Phenomenon: Retrieved compliance documents contain a large amount of irrelevant general legal text, and the recall rate of critical risk documents is insufficient. Cause: The similarity threshold is set too low, or the chunk length does not match the specialized paragraphs of compliance documents, leading to insufficient semantic matching accuracy.
How to confirm correct configuration
- Upload a standard compliance document of this category, check if the chunked text retains complete compliance clauses and risk descriptions.
- Initiate a retrieval related to compliance risks, verify if the number and content relevance of returned results match the expected configuration direction.
- Check the connection status of the vector storage, confirm normal connectivity with the configured storage service.
- Upload a new monthly compliance document, test the incremental update function, and check if the index completes the update automatically.
The values provided 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.