🚀 Self-Evolving CI/CD System Architecture & Implementation#81
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- Automated setup script for local Postgres exposure via Cloudflare Workers - Creates dedicated database and read-only user for Codegen - Deploys Cloudflare Worker proxy with health endpoints - Saves credentials to .env file for easy integration - Includes Windows batch and PowerShell scripts for easy setup - Comprehensive testing and status reporting - Full documentation with troubleshooting guide
- Add support for multiple authentication methods - Try common default passwords automatically - Support environment variables for admin credentials - Add interactive password prompt as fallback - Update documentation with authentication troubleshooting - Handle Windows authentication scenarios
- Switch from API token to Global API Key authentication - Add support for Cloudflare email requirement - Update environment variables and batch scripts - Create specialized script with user's credentials - Fix Cloudflare Worker creation authentication
- Add detailed architecture documentation with system layers and components - Implement complete database schemas for tasks, codebase, prompts, and analytics - Create SQL operations for all major database functions - Add comprehensive Python implementation example with graph-sitter integration - Include Codegen SDK integration for automated improvements - Add self-evolution capabilities with learning mechanisms - Implement comprehensive code analysis with metrics and recommendations - Add automated PR generation and improvement workflows - Include security, monitoring, and deployment considerations - Add complete README with usage examples and getting started guide This provides a complete foundation for building a self-evolving CI/CD system that can automatically analyze, improve, and evolve codebases using AI.
Reviewer's GuideThis PR introduces a fully self-evolving CI/CD system by defining a modular layered architecture, comprehensive database schemas, example implementation for automated code analysis and improvements, and overhauling the documentation and README to reflect the new system. Sequence Diagram: Codebase Analysis and Improvement FlowsequenceDiagram
actor User
participant System as SelfEvolvingCICDSystem
participant GS as Graph-Sitter
participant DB as Database
participant CGAgent as Codegen Agent
participant GH as GitHub
User->>System: analyze_and_improve_codebase(repo_name)
System->>GS: Codebase.from_repo(repo_name)
GS-->>System: codebase object
System->>System: get_comprehensive_codebase_context(codebase)
System->>DB: store_analysis_results(repo_name, context)
DB-->>System: analysis_session_id
System->>System: generate_improvement_tasks(context, codebase)
System-->>System: improvement_tasks
loop For each improvement task
System->>System: build_improvement_prompt(task, repo_name)
System-->>System: prompt
System->>CGAgent: run(prompt for task)
CGAgent-->>System: agent_task_result
end
alt Successful improvements
System->>System: build_improvement_prompt for PR
System-->>System: pr_prompt
System->>CGAgent: run(pr_prompt)
CGAgent-->>System: pr_task_result (PR URL)
Note over CGAgent, GH: PR created on GitHub
else No/Failed improvements
System-->>User: Result (No PR created)
end
System-->>User: Result (Analysis, Improvements, PR link)
Sequence Diagram: Executing an Improvement Task via Codegen AgentsequenceDiagram
participant System as SelfEvolvingCICDSystem
participant CGAgent as Codegen Agent
System->>System: build_improvement_prompt(task, repo_name)
System-->>System: prompt
System->>CGAgent: run(prompt)
activate CGAgent
loop Poll for task completion
System->>CGAgent: agent_task.refresh()
CGAgent-->>System: status (e.g., in_progress, completed)
end
deactivate CGAgent
CGAgent-->>System: agent_task.result
System-->>System: {task, result, status, execution_time}
Entity Relationship Diagram: Codebase Management SchemaerDiagram
codebases {
UUID id PK
VARCHAR name
VARCHAR github_url
}
codebase_files {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
VARCHAR file_path
file_type_enum file_type
}
codebase_functions {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
UUID file_id FK "Ref: codebase_files.id"
VARCHAR function_name
}
codebase_classes {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
UUID file_id FK "Ref: codebase_files.id"
VARCHAR class_name
}
codebase_imports {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
UUID file_id FK "Ref: codebase_files.id"
TEXT import_statement
}
analysis_sessions {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
VARCHAR session_type
analysis_status_enum status
}
codebases ||--|{ codebase_files : "has"
codebases ||--|{ codebase_functions : "has"
codebases ||--|{ codebase_classes : "has"
codebases ||--|{ codebase_imports : "has"
codebases ||--|{ analysis_sessions : "has"
codebase_files ||--|{ codebase_functions : "contains"
codebase_files ||--|{ codebase_classes : "contains"
codebase_files ||--|{ codebase_imports : "contains"
Entity Relationship Diagram: Analytics SchemaerDiagram
codebases {
UUID id PK
VARCHAR name
}
analysis_sessions {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
VARCHAR session_type
analysis_status_enum status
}
code_metrics {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
UUID analysis_session_id FK "Ref: analysis_sessions.id"
metric_type_enum metric_type
FLOAT metric_value
}
dependency_graph {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
UUID analysis_session_id FK "Ref: analysis_sessions.id"
VARCHAR source_symbol
VARCHAR target_symbol
}
analysis_results {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
UUID analysis_session_id FK "Ref: analysis_sessions.id"
analysis_type_enum analysis_type
JSONB results
}
code_issues {
UUID id PK
UUID codebase_id FK "Ref: codebases.id"
UUID analysis_session_id FK "Ref: analysis_sessions.id"
VARCHAR issue_type
issue_severity_enum severity
}
codebases ||--|{ analysis_sessions : "has"
analysis_sessions ||--|{ code_metrics : "generates"
analysis_sessions ||--|{ dependency_graph : "generates"
analysis_sessions ||--|{ analysis_results : "generates"
analysis_sessions ||--|{ code_issues : "identifies"
code_metrics }o--|| codebases : "belongs_to"
dependency_graph }o--|| codebases : "belongs_to"
analysis_results }o--|| codebases : "belongs_to"
code_issues }o--|| codebases : "belongs_to"
Class Diagram: SelfEvolvingCICDSystem and Core ComponentsclassDiagram
class AnalysisConfig {
+org_id: str
+token: str
+db_connection_string: str
+github_token: str
+linear_token: str
+anthropic_api_key: str
}
class SelfEvolvingCICDSystem {
-config: AnalysisConfig
-codegen_agent: Agent
-db_connection: psycopg2.connection
-analysis_history: List
+initialize() None
+get_comprehensive_codebase_context(codebase: Codebase) Dict
+get_function_context(function: Any) Dict
+calculate_function_metrics(function: Any) Dict
+calculate_cyclomatic_complexity(function: Any) float
+calculate_halstead_volume(function: Any) float
+calculate_maintainability_index(halstead: float, cyclo: float, loc: int) int
+build_dependency_graph(codebase: Codebase) Dict
+find_circular_dependencies(dependencies: List[Dict]) List[Dict]
+calculate_quality_metrics(codebase: Codebase) Dict
+generate_function_recommendations(function: Any, context: Dict, metrics: Dict) List[str]
+generate_codebase_recommendations(codebase: Codebase) List[str]
+analyze_and_improve_codebase(repo_name: str) Dict
+store_analysis_results(repo_name: str, context: Dict) str
+generate_improvement_tasks(context: Dict, codebase: Codebase) List[Dict]
+execute_improvement_task(task: Dict, repo_name: str) Dict
+build_improvement_prompt(task: Dict, repo_name: str) str
+create_improvement_pr(improvements: List[Dict], repo_name: str) Dict
}
class Agent {
+org_id: str
+token: str
+run(prompt: str) AgentTask
+refresh() None
}
class Codebase {
+files: List
+functions: List
+classes: List
+imports: List
+from_repo(repo_name: str) Codebase
}
class psycopg2.connection {
+cursor() Cursor
+commit() None
}
SelfEvolvingCICDSystem *-- "1" AnalysisConfig : uses
SelfEvolvingCICDSystem *-- "1" Agent : uses
SelfEvolvingCICDSystem o-- "1" psycopg2.connection : uses
SelfEvolvingCICDSystem ..> Codebase : uses
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Overview
This PR implements a comprehensive Self-Evolving CI/CD Software Development System that combines Linear & GitHub integration, advanced codebase analysis, and automated improvement capabilities.
🏗️ Architecture Components
Core System Layers
Database Schemas
🔧 Key Features
Comprehensive Code Analysis
Automated Improvements
Graph-Sitter Integration
Codegen SDK Integration
📊 Implementation Highlights
Self-Evolution Mechanisms
Comprehensive SQL Operations
Example Usage
📁 Files Added
docs/SELF_EVOLVING_CICD_ARCHITECTURE.mddatabase/schemas/examples/self_evolving_system.py🎯 Benefits
This provides a complete foundation for building a production-ready self-evolving CI/CD system that can autonomously analyze, understand, and improve codebases while maintaining full integration with existing development workflows.
🔄 Next Steps
Ready to revolutionize automated software development! 🚀
💻 View my work • About Codegen
Summary by Sourcery
Implement a self-evolving CI/CD system with a modular, layered architecture, integrating Linear and GitHub, advanced static code analysis, automated code improvements, and self-learning capabilities.
New Features:
Enhancements:
Documentation: