readme

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README.md

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-# codeDaddy
 
-AI-Pr reviewer
+
+
+## 🧠 High-Level System Design
+
+The following diagram illustrates the high-level architecture of the **CodeDaddy PR Review Workflow**, showing how pull requests and commits are processed asynchronously and analyzed by multiple AI agents in parallel.
+
+![System Design](./codedaddy.excalidraw)
+
+### ⚙️ Flow Overview
+
+1. **Webhook Trigger** — When a Pull Request or Commit event occurs, a webhook receives the event payload.  
+2. **Background Processing** — The event is pushed into a Python RQ (Redis Queue) background job (`GITHUB_PR_PROCESS`).  
+3. **Workers** — Multiple workers clone the repository, parse source files, build semantic graphs, and prepare contextual data.  
+   - Each worker uploads its processed context to S3.  
+4. **Context Initialization** — A controller process downloads context from S3 and sets up the state for LangGraph nodes.  
+5. **Parallel Agent Execution** — Several agents run concurrently:
+   - `code_quality_agent`  
+   - `performance_agent`  
+   - `security_agent`  
+   - `test_agent`  
+6. **Aggregation Phase** — The `aggregator_agent` combines insights from all agents.  
+7. **Comment Update** — The aggregated output replaces the initial loading comment with a comprehensive final PR review comment.
+
+---
+
+### 🧩 Key Characteristics
+
+- **Event-driven:** Triggered by GitHub webhooks.  
+- **Asynchronous:** Uses background workers for parallel processing.  
+- **Scalable:** Each worker operates independently.  
+- **AI-powered:** Multi-agent architecture performs different aspects of code analysis.  
+- **Automated Feedback:** Automatically updates PR comments with contextual insights.
+
+---
+