What data falls under this category
The data for this category primarily comes from enterprise contract management systems, compliance risk databases, law and regulation repositories, case management systems, and reporting platforms. Daily processed documents include compliance risk lists, contract legal review opinions, major issue legal opinions, compliance review forms, and violation report investigation results. Data is updated once per month. Most individual documents contain structured fields such as compliance clauses, risk levels, review opinions, and handling results. Some documents also include identification fields like case numbers and compliance item names.
What constraints these characteristics impose on model access and configuration
Data sources are scattered, and most content is structured and unstructured data accumulated from internal business systems. This requires adapting to format compatibility rules for multi-source data access. The fixed monthly update feature demands configuring automatic synchronization mechanisms to prevent data lag from impacting real-time compliance judgments. Document types cover lists, review opinions, investigation reports and other diverse formats. This requires adapting chunking and retrieval logic for different documents. Compliance content requires extremely high accuracy. Model calls must strictly control output boundaries, while supporting traceability verification of retrieved content to prevent compliance risks caused by incorrect citations.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Meets the long-text context requirements of compliance documents, avoiding truncation of key compliance clauses or original policy text |
maxTokens | 4000–6000 token | Ensures complete output for compliance Q&A, covering full content of policy interpretations and risk analyses |
quoteMaxToken | 2000–3000 token | Limits the reference length of retrieved documents, ensuring referenced content is precise and not redundant |
toolChoice | auto | Supports automatic tool calls to complete policy document retrieval and compliance verification, adapting to multi-source data retrieval needs |
temperature | 0.1–0.3 | Reduces output randomness, ensuring accuracy and rigor of compliance Q&A |
AIPROXY_API_ENDPOINT | Fill in the official address provided by the model service provider | Meets the stability requirements of model calls in compliance scenarios, avoiding connection exceptions caused by custom endpoints |
AIPROXY_API_TOKEN | Fill in the key assigned by the model service provider | Ensures valid identity verification for model calls, preventing unauthorized access or call failures |
Three common misconfigurations
- Issue: The model can normally process chat Q&A, but parsing fails or output is empty after loading compliance documents. Cause: The
toolChoiceparameter is not configured for the structured format of compliance documents, preventing the file parsing tool from being triggered. - Issue: No image understanding model option appears when creating a new knowledge base after local deployment. Cause: The configuration switch for visual models is not enabled. Most documents in compliance scenarios are in text format, so the pre-check step for this configuration is easily overlooked.
- Issue: An error occurs during model call testing, and the specified large model cannot be connected. Cause: The
AIPROXY_API_TOKENconfiguration is incorrect, or the endpoint address does not adapt to network restrictions in compliance scenarios, preventing normal model calls.
How to confirm configurations are complete
- Run a model call test to verify that compliance policy documents in the database can be normally retrieved and corresponding responses can be generated.
- Upload a compliance risk list document, check that the parsed text content is complete, with no obvious truncation or garbled text.
- Adjust the
temperatureparameter and compare the consistency of two responses, confirming that output randomness meets the rigor requirements of compliance scenarios. - Check the configurations of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKEN, and use an interface debugging tool to verify that the connection is normal.
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.