LLManager's core functionality and intelligent approval mechanism
LLManager is an intelligent approval management tool that combines AI automation with manual review, and its core functionality consists of three levels:
- Automated Approval Engine: extract 10 similar cases from historical data based on semantic search, and dynamically generate approval recommendations through sample less learning techniques
- human-computer interface: Provide a visualization panel through Agent Inbox to support manual acceptance/modification/rejection of AI proposals
- Continuous optimization of the system: Adoption of reflective mechanisms to analyze manual modification behaviors and generate improvement reports to be deposited in the knowledge base
The process of realizing smart approvals is divided into the following technical stages:
- Building inference subgraphs using the LangGraph framework to dynamically assemble cue words containing historical cases
- Calling a configured language model (e.g., Claude 3) to generate approval proposals that carry the reasoning process
- Reflection mechanism is triggered when a decision is modified manually, and error types are analyzed through the explanation_reflection or full_reflection nodes
- Storing optimized data into a vector database to continuously improve semantic search accuracy
This answer comes from the articleLLManager: a management tool that combines intelligent automated process approvals with human reviewsThe
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