Open LLM End User: Downstream Applications

This track focuses on application scenarios and system integration after obtaining generated content from open-source models. We welcome sharing practical experiences on transforming AI capabilities into actual tools to solve real-world problems. Topics include, but are not limited to:

1. RAG & System Integration Share implementations of RAG (Retrieval-Augmented Generation) architectures, applications of vector databases, and how to integrate LLMs into existing software workflows.
2. AI Agents & Automation Workflows Explore building AI Agents with task planning and execution capabilities using open-source models, and automation practices within various industry scenarios.
3. Application Evaluation & Security Discuss evaluating the quality of generated content (e.g., hallucination detection), optimization of prompt engineering, and privacy protection mechanisms at the application level.