Architecture Overview
Architecture Overview
This document describes the high-level architecture of Insight Ingenious, an enterprise-grade Python library designed for rapid deployment of AI agent CHAT_INTERFACE[๐ฌ IChatService Interface]PIs with tight Microsoft Azure integrations and comprehensive debugging capabilities.
System Architecture
Insight Ingenious is architected as a production-ready library with enterprise-grade features including seamless Azure service integrations, robust debugging tools, and extensive customization capabilities. The system consists of the following main components:
graph TB
subgraph "Client Layer"
UI[Web UI<br/>Chainlit Interface]
API_CLIENT[API Clients<br/>External Applications]
end
subgraph "API Gateway"
API[FastAPI<br/>REST Endpoints]
AUTH[Authentication<br/>& Authorization]
end
subgraph "Core Engine"
AGENT_SERVICE[Agent Service<br/>Conversation Manager]
PATTERN_SERVICE[Pattern Service<br/>Conversation Orchestrator]
LLM_SERVICE[LLM Service<br/>Azure OpenAI Integration]
end
subgraph "Extension Layer"
CUSTOM_AGENTS[Custom Agents<br/>Domain Specialists]
PATTERNS[Conversation Patterns<br/>Workflow Templates]
TOOLS[Custom Tools<br/>External Integrations]
end
subgraph "Storage Layer"
CONFIG[Configuration<br/>YAML Files]
HISTORY[Chat History<br/>SQLite Database]
FILES[File Storage<br/>Documents & Assets]
end
subgraph "External Services"
AZURE[Azure OpenAI<br/>GPT Models]
EXTERNAL_API[External APIs<br/>Data Sources]
end
UI --> API
API_CLIENT --> API
API --> AUTH
AUTH --> AGENT_SERVICE
AGENT_SERVICE --> PATTERN_SERVICE
AGENT_SERVICE --> LLM_SERVICE
PATTERN_SERVICE --> PATTERNS
AGENT_SERVICE --> CUSTOM_AGENTS
CUSTOM_AGENTS --> TOOLS
LLM_SERVICE --> AZURE
TOOLS --> EXTERNAL_API
AGENT_SERVICE --> HISTORY
PATTERN_SERVICE --> CONFIG
AGENT_SERVICE --> FILES
classDef clientLayer fill:#e1f5fe
classDef apiLayer fill:#f3e5f5
classDef coreLayer fill:#e8f5e8
classDef extensionLayer fill:#fff3e0
classDef storageLayer fill:#fce4ec
classDef externalLayer fill:#f1f8e9
class UI,API_CLIENT clientLayer
class API,AUTH apiLayer
class AGENT_SERVICE,PATTERN_SERVICE,LLM_SERVICE coreLayer
class CUSTOM_AGENTS,PATTERNS,TOOLS extensionLayer
class CONFIG,HISTORY,FILES storageLayer
class AZURE,EXTERNAL_API externalLayer
Detailed Component Architecture
Multi-Agent Framework
The heart of Insight Ingenious is its multi-agent framework, which enables sophisticated AI conversations:
graph LR
subgraph "Agent Service"
MANAGER[Conversation Manager]
COORDINATOR[Agent Coordinator]
STATE[State Manager]
end
subgraph "Agent Types"
CLASSIFICATION_AGENT[Classification Agent]
KNOWLEDGE_AGENT[Knowledge Base Agent]
SQL_AGENT[SQL Manipulation Agent]
CUSTOM[Custom Extension Agents]
end
subgraph "Conversation Flows"
CLASSIFICATION[Classification Flow]
KNOWLEDGE[Knowledge Base Flow]
SQL[SQL Manipulation Flow]
CUSTOM_FLOW[Custom Extension Flows]
end
MANAGER --> COORDINATOR
COORDINATOR --> STATE
COORDINATOR --> CLASSIFICATION_AGENT
COORDINATOR --> KNOWLEDGE_AGENT
COORDINATOR --> SQL_AGENT
COORDINATOR --> CUSTOM
MANAGER --> CLASSIFICATION
MANAGER --> KNOWLEDGE
MANAGER --> SQL
MANAGER --> CUSTOM_FLOW
classDef service fill:#e3f2fd
classDef agents fill:#f1f8e9
classDef patterns fill:#fff8e1
class MANAGER,COORDINATOR,STATE service
class CLASSIFICATION_AGENT,KNOWLEDGE_AGENT,SQL_AGENT,CUSTOM agents
class CLASSIFICATION,KNOWLEDGE,SQL,CUSTOM_FLOW patterns
API Layer Architecture
The API layer provides secure, scalable access to the system:
sequenceDiagram
participant Client
participant FastAPI
participant Auth
participant AgentService
participant LLM
participant Storage
Client->>FastAPI: POST /api/chat
FastAPI->>Auth: Check Authentication
Auth-->>FastAPI: โ
Authorized
FastAPI->>AgentService: Process Request
AgentService->>Storage: Load Chat History
Storage-->>AgentService: Previous Context
AgentService->>LLM: Generate Response
LLM-->>AgentService: AI Response
AgentService->>Storage: Save Response
AgentService-->>FastAPI: Formatted Response
FastAPI-->>Client: JSON Response
Web UI Integration
The Chainlit integration provides an intuitive user experience:
graph TD
subgraph "๐ฅ๏ธ Frontend"
CHAINLIT[๐จ Chainlit UI]
COMPONENTS[๐งฉ UI Components]
CHAT[๐ฌ Chat Interface]
end
subgraph "๐ WebSocket Layer"
WS[๐ WebSocket Handler]
SESSION[๐ Session Manager]
end
subgraph "๐ค Backend Services"
CHAT_SERVICE[๐ฌ Chat Service]
FILE_SERVICE[๐ File Service]
AUTH_SERVICE[๐ Auth Service]
end
CHAINLIT --> COMPONENTS
COMPONENTS --> CHAT
CHAT --> WS
WS --> SESSION
SESSION --> CHAT_SERVICE
SESSION --> FILE_SERVICE
SESSION --> AUTH_SERVICE
classDef frontend fill:#e8eaf6
classDef websocket fill:#f3e5f5
classDef backend fill:#e8f5e8
class CHAINLIT,COMPONENTS,CHAT frontend
class WS,SESSION websocket
class CHAT_SERVICE,FILE_SERVICE,AUTH_SERVICE backend
Storage Architecture
The storage layer provides flexible, cloud-aware persistence and configuration management:
graph TB
subgraph "โ๏ธ Configuration"
CONFIG_YML[๐ config.yml<br/>Project Settings]
PROFILES_YML[๐ profiles.yml<br/>API Keys & Secrets]
ENV_VARS[๐ Environment Variables<br/>Runtime Configuration]
end
subgraph "๐ Chat Storage"
HISTORY_SQLITE[๐ฌ Chat History<br/>SQLite Database]
HISTORY_AZURE[๐ฌ Chat History<br/>Azure SQL Database]
SESSIONS[๐ค User Sessions<br/>In-Memory Storage]
MEMORY_MGR[๐ง Memory Manager<br/>Conversation Context]
end
subgraph "๐ File Storage Abstraction"
STORAGE_INTERFACE[๐ IFileStorage Interface]
LOCAL_STORAGE[๐พ Local Storage<br/>Development & Testing]
AZURE_BLOB[โ๏ธ Azure Blob Storage<br/>Production & Scale]
end
subgraph "๐ Storage Categories"
PROMPTS[๏ฟฝ Prompt Templates<br/>Revision Management]
DATA_FILES[๐ Data Files<br/>Analysis Results]
UPLOADS[โฌ๏ธ File Uploads<br/>User Content]
MEMORY_FILES[๐ง Memory Context<br/>Thread-Specific Data]
end
subgraph "๐ Data Operations"
READ[๐ Read Operations<br/>Async/Sync Support]
WRITE[โ๏ธ Write Operations<br/>Cloud Persistence]
DELETE[๐๏ธ Delete Operations<br/>Cleanup Management]
LIST[๐ List Operations<br/>Directory Browsing]
CACHE[โก Caching Layer<br/>Performance Optimization]
end
CONFIG_YML --> STORAGE_INTERFACE
PROFILES_YML --> STORAGE_INTERFACE
ENV_VARS --> STORAGE_INTERFACE
STORAGE_INTERFACE --> LOCAL_STORAGE
STORAGE_INTERFACE --> AZURE_BLOB
LOCAL_STORAGE --> PROMPTS
LOCAL_STORAGE --> DATA_FILES
LOCAL_STORAGE --> UPLOADS
LOCAL_STORAGE --> MEMORY_FILES
AZURE_BLOB --> PROMPTS
AZURE_BLOB --> DATA_FILES
AZURE_BLOB --> UPLOADS
AZURE_BLOB --> MEMORY_FILES
MEMORY_MGR --> STORAGE_INTERFACE
HISTORY_SQLITE --> READ
HISTORY_AZURE --> READ
SESSIONS --> READ
PROMPTS --> READ
DATA_FILES --> READ
UPLOADS --> READ
MEMORY_FILES --> READ
HISTORY_SQLITE --> WRITE
HISTORY_AZURE --> WRITE
SESSIONS --> WRITE
PROMPTS --> WRITE
DATA_FILES --> WRITE
UPLOADS --> WRITE
MEMORY_FILES --> WRITE
READ --> CACHE
WRITE --> CACHE
DELETE --> CACHE
LIST --> CACHE
classDef config fill:#fff3e0
classDef chat fill:#e8f5e8
classDef storage fill:#e3f2fd
classDef categories fill:#f3e5f5
classDef operations fill:#e1f5fe
class CONFIG_YML,PROFILES_YML,ENV_VARS config
class HISTORY_SQLITE,HISTORY_AZURE,SESSIONS,MEMORY_MGR chat
class STORAGE_INTERFACE,LOCAL_STORAGE,AZURE_BLOB storage
class PROMPTS,DATA_FILES,UPLOADS,MEMORY_FILES categories
class READ,WRITE,DELETE,LIST,CACHE operations
Storage Features
Multi-Backend Support:
- Local Storage: Fast development and testing with filesystem access
- Azure Blob Storage: Production-ready cloud storage with enterprise features
- Transparent Switching: Change backends via configuration without code changes
Memory Management:
- Thread-Specific Memory: Isolated conversation context per user/thread
- Automatic Truncation: Maintain memory within configurable word limits
- Cloud Persistence: Memory survives application restarts and scales across instances
- Async Operations: Non-blocking memory operations for better performance
File Storage Categories:
- Prompts (
revisions
container): Template versioning and prompt management - Data Files (
data
container): Analysis results, functional test outputs - Memory Context: Conversation state and context files
- Uploads: User-submitted files and documents
Authentication Methods:
- Connection String: Simple development setup with full connection details
- Managed Identity: Production Azure authentication without credential management
- Service Principal: Application-specific authentication with client secrets
- Default Credential: Automatic Azure credential discovery
Data Flow Architecture
Request Processing Flow
flowchart TD
START([๐ User Request]) --> INPUT_VALIDATION{๐ Validate Input}
INPUT_VALIDATION -->|โ
Valid| LOAD_CONTEXT[๐ Load Context]
INPUT_VALIDATION -->|โ Invalid| ERROR_RESPONSE[โ Error Response]
LOAD_CONTEXT --> SELECT_WORKFLOW{๐ฏ Select Workflow}
SELECT_WORKFLOW --> CLASSIFICATION_WORKFLOW[๐ Classification Agent]
SELECT_WORKFLOW --> EDUCATION_WORKFLOW[๐ Education Expert]
SELECT_WORKFLOW --> KNOWLEDGE_WORKFLOW[๐ Knowledge Base Agent]
SELECT_WORKFLOW --> SQL_WORKFLOW[๐๏ธ SQL Manipulation Agent]
CLASSIFICATION_WORKFLOW --> AGENT_COORDINATION[๐ฅ Agent Coordination]
EDUCATION_WORKFLOW --> AGENT_COORDINATION
KNOWLEDGE_WORKFLOW --> AGENT_COORDINATION
SQL_WORKFLOW --> AGENT_COORDINATION
AGENT_COORDINATION --> LLM_PROCESSING[๐ง LLM Processing]
LLM_PROCESSING --> RESPONSE_FORMATTING[๐ Format Response]
RESPONSE_FORMATTING --> SAVE_HISTORY[๐พ Save to History]
SAVE_HISTORY --> SEND_RESPONSE[๐ค Send Response]
ERROR_RESPONSE --> END([๐ End])
SEND_RESPONSE --> END
classDef startEnd fill:#f8bbd9
classDef process fill:#b3e5fc
classDef decision fill:#fff9c4
classDef workflow fill:#c8e6c9
classDef error fill:#ffcdd2
class START,END startEnd
class LOAD_CONTEXT,AGENT_COORDINATION,LLM_PROCESSING,RESPONSE_FORMATTING,SAVE_HISTORY,SEND_RESPONSE process
class INPUT_VALIDATION,SELECT_WORKFLOW decision
class CLASSIFICATION_WORKFLOW,EDUCATION_WORKFLOW,KNOWLEDGE_WORKFLOW,SQL_WORKFLOW workflow
class ERROR_RESPONSE error
Multi-Agent Conversation Flow
sequenceDiagram
participant User
participant API
participant Manager
participant Agent1 as ๐ Classification Agent
participant Agent2 as ๐ Knowledge Agent
participant Agent3 as ๐๏ธ SQL Agent
participant LLM as ๐ง Azure OpenAI
User->>API: "Help me understand database design"
API->>Manager: Route to classification-agent workflow
Note over Manager: Initialize conversation pattern
Manager->>Agent1: Classify user intent
Agent1->>LLM: Request intent analysis
LLM-->>Agent1: Intent: Database query
Agent1-->>Manager: Route to appropriate agent
opt If knowledge search needed
Manager->>Agent2: Search knowledge base
Agent2->>LLM: Knowledge retrieval request
LLM-->>Agent2: Additional resources
Agent2-->>Manager: Supporting materials
end
opt If SQL processing needed
Manager->>Agent3: Execute SQL query
Agent3->>LLM: Generate SQL statement
LLM-->>Agent3: Query results
Agent3-->>Manager: Processed data
end
Manager-->>API: Complete response
API-->>User: Comprehensive educational response
Extension Points & Customization
Extension Architecture
graph TB
subgraph "๐ญ Core Framework"
CORE_API[๐ง Core API]
CORE_FLOWS[๐ค Base Conversation Flows]
CORE_PATTERNS[๐ Base Patterns]
end
subgraph "๐ฏ Extension Interface"
FLOW_INTERFACE[๐ค IConversationFlow Interface]
PATTERN_INTERFACE[๐ IConversationPattern Interface]
CHAT_INTERFACE[๏ฟฝ IChatService Interface]
end
subgraph "๐ Custom Extensions"
CUSTOM_FLOW[๐ฅ Custom Flow<br/>Domain Expert]
CUSTOM_PATTERN[๐ญ Custom Pattern<br/>Workflow Logic]
CUSTOM_TOOLS[โ๏ธ Custom Tools<br/>External Integration]
end
subgraph "๐ฆ Extension Registry"
NAMESPACE_LOADER[๐ Namespace Utils]
DYNAMIC_LOADER[โก Dynamic Loader]
CONFIG_VALIDATOR[โ
Config Validation]
end
CORE_API --> FLOW_INTERFACE
CORE_FLOWS --> FLOW_INTERFACE
CORE_PATTERNS --> PATTERN_INTERFACE
FLOW_INTERFACE --> CUSTOM_FLOW
PATTERN_INTERFACE --> CUSTOM_PATTERN
CHAT_INTERFACE --> CUSTOM_TOOLS
CUSTOM_FLOW --> NAMESPACE_LOADER
CUSTOM_PATTERN --> NAMESPACE_LOADER
CUSTOM_TOOLS --> NAMESPACE_LOADER
NAMESPACE_LOADER --> DYNAMIC_LOADER
NAMESPACE_LOADER --> CONFIG_VALIDATOR
classDef core fill:#e3f2fd
classDef interface fill:#f1f8e9
classDef custom fill:#fff3e0
classDef registry fill:#fce4ec
class CORE_API,CORE_FLOWS,CORE_PATTERNS core
class FLOW_INTERFACE,PATTERN_INTERFACE,CHAT_INTERFACE interface
class CUSTOM_FLOW,CUSTOM_PATTERN,CUSTOM_TOOLS custom
class NAMESPACE_LOADER,DYNAMIC_LOADER,CONFIG_VALIDATOR registry
Key Classes and Interfaces
Core Agent Framework
classDiagram
class IConversationPattern {
<<interface>>
+execute(context: ConversationContext)
+validate(input: Any)
+get_pattern_type()
}
class IConversationFlow {
<<interface>>
+start_conversation(query: str)
+process_step(step: ConversationStep)
+finalize_conversation()
}
class IChatService {
<<interface>>
+get_chat_response(request: ChatRequest)
+process_message(message: str)
}
class AgentMarkdownDefinition {
+title: str
+description: str
+system_prompt: str
+tasks: List[str]
}
class CustomExtensionFlow {
+custom_domain_logic()
+extend_functionality()
+implement_patterns()
}
class KnowledgeBaseAgentFlow {
+search_knowledge()
+retrieve_information()
+format_results()
}
class SqlManipulationAgentFlow {
+parse_nl_query()
+generate_sql()
+execute_query()
+format_results()
}
class MultiAgentChatService {
+conversation_flows: Dict[str, IConversationFlow]
+patterns: Dict[str, IConversationPattern]
+orchestrate_conversation()
+manage_state()
}
class ConversationPattern {
+execute_in_sequence()
+handle_dependencies()
}
class ClassificationAgentFlow {
+classify_intent()
+route_to_agent()
+handle_routing()
}
IConversationFlow <|.. ClassificationAgentFlow
IConversationFlow <|.. CustomExtensionFlow
IConversationFlow <|.. KnowledgeBaseAgentFlow
IConversationFlow <|.. SqlManipulationAgentFlow
IConversationPattern <|.. ConversationPattern
IChatService <|.. MultiAgentChatService
MultiAgentChatService --> IConversationFlow
MultiAgentChatService --> IConversationPattern
MultiAgentChatService --> AgentMarkdownDefinition
Configuration Architecture
Configuration Management
graph TB
subgraph "๐ Configuration Sources"
CONFIG_FILE[๐ config.yml<br/>Project Configuration]
PROFILES_FILE[๐ profiles.yml<br/>Environment Secrets]
ENV_VARS[๐ Environment Variables]
CLI_ARGS[โจ๏ธ Command Line Args]
end
subgraph "๐ Configuration Processing"
LOADER[๐ Configuration Loader]
VALIDATOR[โ
Schema Validator]
MERGER[๐ Configuration Merger]
end
subgraph "๐พ Runtime Configuration"
APP_CONFIG[โ๏ธ Application Config]
AGENT_CONFIG[๐ค Agent Configurations]
SERVICE_CONFIG[๐ง Service Settings]
end
CONFIG_FILE --> LOADER
PROFILES_FILE --> LOADER
ENV_VARS --> LOADER
CLI_ARGS --> LOADER
LOADER --> VALIDATOR
VALIDATOR --> MERGER
MERGER --> APP_CONFIG
MERGER --> AGENT_CONFIG
MERGER --> SERVICE_CONFIG
classDef source fill:#e8f5e8
classDef process fill:#fff3e0
classDef runtime fill:#e3f2fd
class CONFIG_FILE,PROFILES_FILE,ENV_VARS,CLI_ARGS source
class LOADER,VALIDATOR,MERGER process
class APP_CONFIG,AGENT_CONFIG,SERVICE_CONFIG runtime
Deployment Architecture
Deployment Options
graph TB
subgraph "๐ฅ๏ธ Local Development"
LOCAL_API[๐ง FastAPI Dev Server]
LOCAL_UI[๐จ Chainlit Dev UI]
LOCAL_DB[๐พ SQLite Database]
end
subgraph "๐ณ Docker Deployment"
DOCKER_API[๐ฆ API Container]
DOCKER_UI[๐ฆ UI Container]
DOCKER_DB[๐ฆ Database Container]
DOCKER_COMPOSE[๐ง Docker Compose]
end
subgraph "โ๏ธ Cloud Deployment"
CLOUD_API[๐ API Service]
CLOUD_UI[๐จ Web App]
CLOUD_DB[๐พ Managed Database]
CLOUD_STORAGE[๐ Object Storage]
end
subgraph "๐ง External Services"
AZURE_OPENAI[๐ง Azure OpenAI]
MONITORING[๐ Application Insights]
LOGGING[๐ Centralized Logging]
end
LOCAL_API --> LOCAL_UI
LOCAL_API --> LOCAL_DB
DOCKER_COMPOSE --> DOCKER_API
DOCKER_COMPOSE --> DOCKER_UI
DOCKER_COMPOSE --> DOCKER_DB
CLOUD_API --> CLOUD_UI
CLOUD_API --> CLOUD_DB
CLOUD_API --> CLOUD_STORAGE
LOCAL_API --> AZURE_OPENAI
DOCKER_API --> AZURE_OPENAI
CLOUD_API --> AZURE_OPENAI
CLOUD_API --> MONITORING
CLOUD_API --> LOGGING
classDef local fill:#e8f5e8
classDef docker fill:#e3f2fd
classDef cloud fill:#fff3e0
classDef external fill:#fce4ec
class LOCAL_API,LOCAL_UI,LOCAL_DB local
class DOCKER_API,DOCKER_UI,DOCKER_DB,DOCKER_COMPOSE docker
class CLOUD_API,CLOUD_UI,CLOUD_DB,CLOUD_STORAGE cloud
class AZURE_OPENAI,MONITORING,LOGGING external
Security Architecture
Security Model
graph TB
subgraph "๐ก๏ธ Authentication Layer"
BASIC_AUTH[๏ฟฝ HTTP Basic Authentication]
CONFIG_AUTH[โ๏ธ Configurable Authentication]
NO_AUTH[๏ฟฝ Anonymous Access Option]
end
subgraph "๏ฟฝ Data Protection"
AZURE_SECRETS[๏ฟฝ๏ธ Azure Service Keys]
CONFIG_SECRETS[๏ฟฝ Profile Configuration]
ENV_VARS[๐ Environment Variables]
end
subgraph "๐ Network Security"
HTTPS[๐ HTTPS/TLS]
CORS[๐ CORS Policy]
FASTAPI_SEC[โก FastAPI Security]
end
subgraph "๐ External Service Security"
AZURE_AUTH[๐ง Azure OpenAI Authentication]
SEARCH_AUTH[๏ฟฝ Azure Search Authentication]
SQL_AUTH[๐๏ธ Database Authentication]
end
BASIC_AUTH --> CONFIG_AUTH
CONFIG_AUTH --> NO_AUTH
AZURE_SECRETS --> CONFIG_SECRETS
CONFIG_SECRETS --> ENV_VARS
HTTPS --> CORS
CORS --> FASTAPI_SEC
AZURE_AUTH --> SEARCH_AUTH
SEARCH_AUTH --> SQL_AUTH
classDef auth fill:#e8f5e8
classDef data fill:#fff3e0
classDef network fill:#e3f2fd
classDef external fill:#fce4ec
class BASIC_AUTH,CONFIG_AUTH,NO_AUTH auth
class AZURE_SECRETS,CONFIG_SECRETS,ENV_VARS data
class HTTPS,CORS,FASTAPI_SEC network
class AZURE_AUTH,SEARCH_AUTH,SQL_AUTH external
Performance & Scalability
Performance Architecture
graph TB
subgraph "โก Caching Strategy"
MEMORY[๏ฟฝ In-Memory Cache]
FILE_CACHE[๏ฟฝ File-based Cache]
CDN[๐ CDN Cache]
end
subgraph "๐ Load Balancing"
LOAD_BALANCER[โ๏ธ Load Balancer]
API_INSTANCES[๐ง API Instances]
HEALTH_CHECK[โค๏ธ Health Checks]
end
subgraph "๐ Async Processing"
ASYNC_HANDLERS[๐ Async Request Handlers]
BACKGROUND_TASKS[๐ท Background Tasks]
SCHEDULER[โฐ Task Scheduler]
end
subgraph "๐ Monitoring"
METRICS[๐ Performance Metrics]
ALERTS[๐จ Alert System]
DASHBOARDS[๐ Monitoring Dashboard]
end
MEMORY --> FILE_CACHE
FILE_CACHE --> CDN
LOAD_BALANCER --> API_INSTANCES
LOAD_BALANCER --> HEALTH_CHECK
ASYNC_HANDLERS --> BACKGROUND_TASKS
BACKGROUND_TASKS --> SCHEDULER
METRICS --> ALERTS
ALERTS --> DASHBOARDS
API_INSTANCES --> MEMORY
API_INSTANCES --> ASYNC_HANDLERS
API_INSTANCES --> METRICS
classDef cache fill:#e8f5e8
classDef balance fill:#fff3e0
classDef async fill:#e3f2fd
classDef monitor fill:#fce4ec
class MEMORY,FILE_CACHE,CDN cache
class LOAD_BALANCER,API_INSTANCES,HEALTH_CHECK balance
class ASYNC_HANDLERS,BACKGROUND_TASKS,SCHEDULER async
class METRICS,ALERTS,DASHBOARDS monitor
Extension Development
The system is designed for extensibility at several key points:
- ๐ค Custom Agents: Create specialized agents for specific domains
- ๐ Conversation Patterns: Define new ways agents can interact
- ๐ Conversation Flows: Implement domain-specific conversation flows
- ๐ Custom API Routes: Add new API endpoints
- ๐ Custom Models: Define domain-specific data models
- ๐ ๏ธ Custom Tools: Integrate with external systems and APIs
Development Best Practices
- ๐๏ธ Modular Design: Keep components loosely coupled
- ๐งช Test Coverage: Maintain comprehensive test suites
- ๐ Documentation: Document all public APIs and interfaces
- ๐ Security: Follow security best practices for all extensions
- โก Performance: Consider performance implications of custom code
- ๐ Compatibility: Ensure backward compatibility when possible
For detailed development instructions, see the Development Guide.
Next Steps
- ๐ Read the Getting Started Guide to begin using the system
- ๐ ๏ธ Follow the Development Guide to start extending the framework
- ๐ง Check the Configuration Guide for setup details
- ๐ก Explore the API Documentation for integration options