# Technical Document Extraction: CI Pipeline Root Cause Analysis & Solution Generation System ## Overview The diagram illustrates a two-stage CI/CD pipeline analysis system combining offline preprocessing with online LLM-driven root cause analysis and solution generation. The system is divided into **Offline** (pink) and **Online** (blue) components, with bidirectional data flow between stages. --- ## Offline Processing (Preprocessing) ### Prep. 1: Success Log Template Deduplication 1. **Input**: Original Failed CI Log 2. **Processing Steps**: - **Keyword Filtering**: Extracts keywords and log tail from CI logs - **Log Diff Analysis**: Compares with latest success logs - **Token Overflow Pruning**: Applies context window expansion and density-based ranking 3. **Output**: Critical Log Blocks + RCA Prompt Template ### Prep. 2: Offline Knowledge Base Construction 1. **Input**: Enterprise Document 2. **Processing Steps**: - **Chunking**: Splits documents into embeddable units - **Embedding Model**: Converts chunks to vector representations - **Vector Database**: Stores embeddings for retrieval 3. **Output**: Vector Database with enhanced knowledge blocks --- ## Online Processing (Execution) ### Stage 1: Root Cause Analysis 1. **Input**: Critical Log Blocks + RCA Prompt Template 2. **Processing Steps**: - **LLM Initial Analysis**: Generates preliminary root cause hypotheses - **Knowledge Retrieval**: Cross-references with vector database 3. **Output**: Root Cause Analysis Report ### Stage 2: Solution Generation & Execution 1. **Input**: Root Cause Analysis Report 2. **Processing Steps**: - **Solution Generation**: Creates executable solutions using LLM - **Customized Tools**: Maps solutions to available CI tools - **Tool Execution**: Implements solutions via pipeline rerun 3. **Output**: CI Pipeline Fixed status --- ## Key Components & Flow 1. **Offline-Online Integration**: - Offline components prepare templates and knowledge bases - Online components use LLMs for dynamic analysis and solution generation 2. **Data Flow**: - Failed CI logs → Offline preprocessing → Online analysis → Solution execution - Knowledge base updates feed into both stages --- ## Technical Architecture - **Offline System**: - Success Log Template Deduplication Engine - Knowledge Base Construction Pipeline - **Online System**: - LLM-Driven Root Cause Analysis Module - Automated Solution Generation Framework - CI Pipeline Execution Controller --- ## Critical Data Points 1. **Log Processing**: - Keyword extraction from failed CI logs - Temporal comparison with latest success logs 2. **Knowledge Base**: - Embedding model converts enterprise documents to vector representations - Vector database enables semantic search for solution retrieval 3. **LLM Workflow**: - Initial root cause hypothesis generation - Solution proposal and tool mapping - Pipeline rerun execution --- ## Process Flow Diagram ``` [Original Failed CI Log] → [Keyword Filtering] → [Token Overflow Pruning] → [Critical Log Blocks] → [RCA Prompt Template] → [LLM Root Cause Analysis] → [Knowledge Retrieval] → [Solution Generation] → [Customized Tools] → [Tool Execution] → [CI Pipeline Fixed] ``` --- ## Implementation Notes 1. **Offline Preprocessing**: - Success log template deduplication reduces noise - Knowledge base construction enables context-aware analysis 2. **Online Analysis**: - LLM combines log analysis with knowledge base retrieval - Solution generation uses tool-specific prompt templates 3. **Execution**: - Customized tools interface with CI/CD pipelines - Pipeline rerun validates solution effectiveness This system architecture enables automated root cause analysis and solution implementation for CI/CD failures through integrated offline preprocessing and online LLM-driven processing.