# Mfumo wa Uratibu wa Wakala Wengi - Foundry Local Mfumo wa hali ya juu wa wakala wengi unaotumia Microsoft Foundry Local unaoonyesha uratibu wa wakala wenye akili, ugawaji wa kazi maalum, na mifumo ya kutatua matatizo kwa ushirikiano. ## Muhtasari Mfano huu unaonyesha jinsi ya kujenga mifumo ya wakala wa AI yenye ustadi kwa kutumia Foundry Local, ukitekeleza mifumo rasmi ya Microsoft kwa kuita kazi, uratibu wa wakala, na mtiririko wa kazi wa AI kwa ushirikiano. ## Muundo ``` ┌─────────────────────────────────────────────────────────────────┐ │ Agent Orchestration System │ ├─────────────────┬─────────────────┬─────────────────┬───────────┤ │ Coordinator │ Specialist │ Function │ Context │ │ Agent │ Agents │ Registry │ Manager │ │ │ │ │ │ │ • Task Analysis │ • Code Expert │ • Tool Calling │ • Memory │ │ • Agent Router │ • Data Analyst │ • Validation │ • History │ │ • Workflow Mgmt │ • Research Bot │ • Error Handle │ • State │ │ • Result Merge │ • Writing Aid │ • Type Safety │ • Context │ └─────────────────┴─────────────────┴─────────────────┴───────────┘ │ ▼ ┌─────────────────────────────────────────────────────────────────┐ │ Microsoft Foundry Local Service │ │ │ │ • Multi-Model Support • Function Calling API │ │ • Concurrent Inference • Tool Integration │ │ • Context Preservation • Performance Monitoring │ └─────────────────────────────────────────────────────────────────┘ ``` ## Vipengele Muhimu ### 🤖 **Uratibu wa Wakala Wenye Akili** - Uchambuzi wa kazi kwa njia ya nguvu na uteuzi wa wakala - Usambazaji wa mzigo wa kazi kiotomatiki - Muunganiko wa matokeo na muhtasari - Itifaki za mawasiliano kati ya wakala ### 🔧 **Aina Maalum za Wakala** - **Mtaalamu wa Nambari**: Kuprogramu, kusahihisha hitilafu, ukaguzi wa nambari - **Mchambuzi wa Takwimu**: Usindikaji wa takwimu, uonyeshaji, maarifa - **Msaidizi wa Utafiti**: Kukusanya taarifa, muhtasari - **Mtaalamu wa Uandishi**: Uundaji wa maudhui, uhariri, nyaraka - **Mtatuzi wa Matatizo**: Ufikiri wa hali ngumu, kufanya maamuzi ### ⚡ **Kuita Kazi kwa Hali ya Juu** - Mifumo ya Microsoft Foundry Local ya kuita kazi - Ufafanuzi wa zana salama kwa aina - Uthibitishaji wa vigezo kiotomatiki - Kushughulikia hitilafu na urejeshaji - Muunganiko wa zana na muundo ### 🎯 **Uelekezaji wa Kazi kwa Akili** - Uainishaji wa nia na uchambuzi - Ulinganishaji wa uwezo wa wakala - Usawazishaji wa mzigo na uboreshaji - Kushughulikia hali ya dharura na kurudia ## Mahitaji ya Awali ### Mahitaji ya Mfumo - **Python**: 3.9+ yenye msaada wa asyncio - **Kumbukumbu**: 16GB+ inapendekezwa kwa wakala wengi - **Hifadhi**: 15GB+ kwa miundo mingi - **CPU/GPU**: Kichakataji cha msingi nyingi, GPU inapendekezwa ### Vitegemezi ```bash pip install foundry-local-sdk openai aiohttp asyncio pydantic rich typer ``` ### Usanidi wa Foundry Local ```powershell # Install and verify Foundry Local winget install Microsoft.FoundryLocal foundry --version # Download recommended models for agents foundry model download phi-4-mini foundry model download qwen2.5-coder-0.5b foundry model download phi-3.5-mini ``` ## Kuanza Haraka ### 1. Mtiririko wa Kazi wa Wakala Wengi wa Msingi ```python from agentic_system import AgentOrchestrator, CodeAgent, ResearchAgent # Initialize the orchestrator orchestrator = AgentOrchestrator() # Add specialized agents await orchestrator.add_agent(CodeAgent("phi-4-mini")) await orchestrator.add_agent(ResearchAgent("qwen2.5-coder-0.5b")) # Execute a complex task result = await orchestrator.execute_task( "Create a Python script that analyzes web traffic data and generates a report" ) print(result.summary) ``` ### 2. Uundaji wa Wakala Maalum ```python from agentic_system import BaseAgent, tool class DataAnalystAgent(BaseAgent): """Specialized agent for data analysis tasks.""" @tool async def analyze_dataset(self, data_path: str, analysis_type: str) -> dict: """Analyze a dataset and return insights.""" # Implementation here pass @tool async def create_visualization(self, data: dict, chart_type: str) -> str: """Create data visualizations.""" # Implementation here pass # Use the custom agent agent = DataAnalystAgent("qwen2.5-0.5b") result = await agent.analyze_dataset("sales_data.csv", "trend_analysis") ``` ### 3. Muunganiko wa Kuita Kazi ```python # Define tools following Microsoft patterns tools = [ { "name": "web_search", "description": "Search the web for information", "parameters": { "query": {"description": "Search query", "type": "string"}, "max_results": {"description": "Maximum results", "type": "integer"} } }, { "name": "code_analyzer", "description": "Analyze code quality and suggest improvements", "parameters": { "code": {"description": "Code to analyze", "type": "string"}, "language": {"description": "Programming language", "type": "string"} } } ] # Register tools with orchestrator orchestrator.register_tools(tools) ``` ## Muundo wa Mradi ``` 09/ ├── README.md # This documentation ├── requirements.txt # Python dependencies ├── agentic_system/ │ ├── __init__.py # Package initialization │ ├── orchestrator.py # Main orchestrator class │ ├── base_agent.py # Base agent implementation │ ├── specialized_agents/ │ │ ├── __init__.py │ │ ├── code_agent.py # Programming specialist │ │ ├── research_agent.py # Research specialist │ │ ├── data_agent.py # Data analysis specialist │ │ ├── writing_agent.py # Content creation specialist │ │ └── solver_agent.py # Problem solving specialist │ ├── tools/ │ │ ├── __init__.py │ │ ├── function_registry.py # Tool management │ │ ├── web_tools.py # Web interaction tools │ │ ├── file_tools.py # File system tools │ │ ├── code_tools.py # Code analysis tools │ │ └── data_tools.py # Data processing tools │ ├── coordination/ │ │ ├── __init__.py │ │ ├── task_router.py # Task routing logic │ │ ├── result_merger.py # Result aggregation │ │ ├── context_manager.py # Context and memory │ │ └── workflow_engine.py # Workflow management │ └── utils/ │ ├── __init__.py │ ├── foundry_client.py # Foundry Local integration │ ├── logging_config.py # Logging setup │ └── validation.py # Input validation ├── examples/ │ ├── basic_coordination.py # Simple multi-agent example │ ├── complex_workflow.py # Advanced workflow example │ ├── custom_agents.py # Custom agent creation │ ├── function_calling.py # Tool integration example │ └── interactive_demo.py # Interactive demonstration ├── tools/ │ ├── web_search.py # Web search implementation │ ├── code_analyzer.py # Code analysis tools │ ├── data_processor.py # Data processing tools │ └── file_manager.py # File system operations └── tests/ ├── test_orchestrator.py # Orchestrator tests ├── test_agents.py # Agent tests ├── test_tools.py # Tool tests └── test_integration.py # Integration tests ``` ## Uchambuzi wa Aina za Wakala ### 1. Wakala Mtaalamu wa Nambari ```python class CodeAgent(BaseAgent): """Expert in programming, debugging, and code review.""" specialties = [ "code_generation", "debugging", "code_review", "refactoring", "testing", "documentation" ] @tool async def generate_code(self, specification: str, language: str) -> str: """Generate code from specifications.""" @tool async def debug_code(self, code: str, error_message: str) -> dict: """Debug code and suggest fixes.""" @tool async def review_code(self, code: str, criteria: list) -> dict: """Perform comprehensive code review.""" ``` ### 2. Wakala Msaidizi wa Utafiti ```python class ResearchAgent(BaseAgent): """Specialized in information gathering and analysis.""" specialties = [ "web_research", "information_synthesis", "fact_checking", "summarization", "trend_analysis" ] @tool async def research_topic(self, topic: str, depth: str) -> dict: """Research a topic comprehensively.""" @tool async def summarize_information(self, sources: list, style: str) -> str: """Summarize information from multiple sources.""" @tool async def fact_check(self, claims: list) -> dict: """Verify factual claims.""" ``` ### 3. Wakala wa Uchambuzi wa Takwimu ```python class DataAgent(BaseAgent): """Expert in data processing and analysis.""" specialties = [ "data_analysis", "statistical_analysis", "visualization", "pattern_recognition", "predictive_modeling" ] @tool async def analyze_data(self, dataset: str, analysis_type: str) -> dict: """Perform data analysis.""" @tool async def create_visualization(self, data: dict, viz_type: str) -> str: """Create data visualizations.""" @tool async def statistical_test(self, data: dict, test_type: str) -> dict: """Perform statistical tests.""" ``` ## Mifumo ya Uratibu ### 1. Mtiririko wa Kazi wa Mfululizo ```python # Define a sequential workflow workflow = orchestrator.create_workflow("sequential") workflow.add_step("research", ResearchAgent, "gather_requirements") workflow.add_step("design", CodeAgent, "create_architecture") workflow.add_step("implement", CodeAgent, "write_code") workflow.add_step("test", CodeAgent, "create_tests") result = await workflow.execute("Build a REST API for user management") ``` ### 2. Utekelezaji Sambamba ```python # Execute tasks in parallel parallel_tasks = [ ("research_market", ResearchAgent, "analyze_market_trends"), ("analyze_competitors", DataAgent, "competitor_analysis"), ("technical_feasibility", CodeAgent, "assess_technical_requirements") ] results = await orchestrator.execute_parallel(parallel_tasks) synthesized = await orchestrator.synthesize_results(results) ``` ### 3. Uteuzi wa Wakala kwa Njia ya Nguvu ```python # Automatic agent selection based on task analysis task = "Create a machine learning model to predict customer churn" # Orchestrator analyzes task and selects appropriate agents selected_agents = await orchestrator.analyze_task_requirements(task) # Returns: [DataAgent, CodeAgent, ResearchAgent] result = await orchestrator.execute_with_agents(task, selected_agents) ``` ## Muunganiko wa Kuita Kazi ### Mifumo ya Microsoft Foundry Local ```python # Define tools following Microsoft's function calling schema def define_foundry_tools(): return [ { "name": "analyze_code_quality", "description": "Analyze code quality and suggest improvements", "parameters": { "code": { "description": "The source code to analyze", "type": "string" }, "language": { "description": "Programming language", "type": "string" }, "criteria": { "description": "Analysis criteria", "type": "array", "items": {"type": "string"} } } }, { "name": "search_documentation", "description": "Search technical documentation", "parameters": { "query": {"description": "Search query", "type": "string"}, "source": {"description": "Documentation source", "type": "string"} } } ] # Integration with Foundry Local async def setup_function_calling(): tools = define_foundry_tools() # Configure Foundry Local for function calling client = openai.OpenAI( base_url=manager.endpoint, api_key=manager.api_key ) # Use tools in conversation response = await client.chat.completions.create( model=manager.get_model_info("phi-4-mini").id, messages=[ {"role": "user", "content": "Analyze this Python code for quality issues"} ], tools=[{"type": "function", "function": tool} for tool in tools], tool_choice="auto" ) ``` ## Vipengele vya Uratibu wa Hali ya Juu ### 1. Usimamizi wa Muktadha ```python class ContextManager: """Manages shared context across agents.""" async def share_context(self, agent_id: str, context: dict): """Share context with specific agent.""" async def get_shared_memory(self) -> dict: """Retrieve shared memory state.""" async def update_global_state(self, updates: dict): """Update global orchestrator state.""" ``` ### 2. Muhtasari wa Matokeo ```python class ResultMerger: """Intelligently merge results from multiple agents.""" async def merge_analyses(self, results: list) -> dict: """Merge analysis results.""" async def resolve_conflicts(self, conflicting_results: list) -> dict: """Resolve conflicting agent outputs.""" async def create_summary(self, all_results: dict) -> str: """Create comprehensive summary.""" ``` ### 3. Uhakikisho wa Ubora ```python class QualityController: """Ensures output quality and consistency.""" async def validate_output(self, result: dict, criteria: list) -> bool: """Validate agent output quality.""" async def cross_check_facts(self, claims: list) -> dict: """Cross-verify facts across agents.""" async def ensure_consistency(self, outputs: list) -> dict: """Ensure consistent outputs.""" ``` ## Uboreshaji wa Utendaji ### 1. Usawazishaji wa Mzigo wa Miundo ```python # Distribute models across agents for optimal resource usage model_allocation = { "code_tasks": "phi-4-mini", "research_tasks": "qwen2.5-coder-0.5b", "analysis_tasks": "phi-3.5-mini", "general_tasks": "phi-4-mini" } orchestrator.configure_model_allocation(model_allocation) ``` ### 2. Kuhifadhi na Kumbukumbu ```python # Implement intelligent caching cache_config = { "response_cache": True, "context_cache": True, "tool_result_cache": True, "cache_ttl": 3600 # 1 hour } orchestrator.configure_caching(cache_config) ``` ### 3. Utekelezaji Sambamba ```python # Optimize for parallel processing concurrency_config = { "max_concurrent_agents": 4, "agent_pool_size": 8, "task_queue_size": 100, "timeout_seconds": 300 } orchestrator.configure_concurrency(concurrency_config) ``` ## Mifano ya Matumizi ### Mfano 1: Mtiririko wa Kazi wa Maendeleo ya Programu ```python async def software_development_workflow(): """Complete software development using multiple agents.""" # Initialize orchestrator with specialized agents orchestrator = AgentOrchestrator() await orchestrator.add_agent(ResearchAgent("qwen2.5-coder-0.5b")) await orchestrator.add_agent(CodeAgent("phi-4-mini")) await orchestrator.add_agent(DataAgent("phi-3.5-mini")) # Define the development task task = """ Create a web application that: 1. Analyzes user behavior data 2. Provides real-time analytics dashboard 3. Includes user authentication 4. Has comprehensive tests """ # Execute coordinated workflow result = await orchestrator.execute_workflow( task=task, workflow_type="software_development", quality_gates=["code_review", "testing", "security_check"] ) return result ``` ### Mfano 2: Utafiti na Uchambuzi ```python async def comprehensive_research(): """Multi-agent research coordination.""" research_query = "Impact of AI on software development productivity" # Parallel research execution tasks = [ ("literature_review", ResearchAgent, research_query), ("data_analysis", DataAgent, "productivity_metrics"), ("case_studies", ResearchAgent, "ai_adoption_cases"), ("technical_analysis", CodeAgent, "ai_tool_evaluation") ] results = await orchestrator.execute_parallel(tasks) # Synthesize findings final_report = await orchestrator.synthesize_research( results=results, format="comprehensive_report", include_recommendations=True ) return final_report ``` ### Mfano 3: Kikao cha Kutatua Matatizo ```python async def collaborative_problem_solving(): """Multi-agent collaborative problem solving.""" problem = """ A company's API response times have increased 300% over the past month. Analyze the issue and propose solutions. """ # Deploy specialist agents investigation_plan = await orchestrator.create_investigation_plan(problem) agents_deployed = [ (CodeAgent, "analyze_code_performance"), (DataAgent, "analyze_performance_metrics"), (ResearchAgent, "research_similar_issues"), (SolverAgent, "propose_solutions") ] # Coordinate investigation findings = await orchestrator.coordinate_investigation( problem=problem, agents=agents_deployed, investigation_plan=investigation_plan ) # Generate action plan action_plan = await orchestrator.create_action_plan(findings) return action_plan ``` ## Usanidi na Urekebishaji ### Usanidi wa Wakala ```python # Configure individual agents agent_configs = { "CodeAgent": { "model": "phi-4-mini", "temperature": 0.3, "max_tokens": 2000, "specialization_level": "expert" }, "ResearchAgent": { "model": "qwen2.5-coder-0.5b", "temperature": 0.7, "max_tokens": 1500, "research_depth": "comprehensive" } } orchestrator.configure_agents(agent_configs) ``` ### Urekebishaji wa Mtiririko wa Kazi ```python # Custom workflow definitions custom_workflows = { "data_science_project": [ "data_collection", "exploratory_analysis", "model_development", "validation_testing", "deployment_preparation" ], "security_audit": [ "vulnerability_scan", "code_review", "penetration_testing", "compliance_check", "remediation_plan" ] } orchestrator.register_workflows(custom_workflows) ``` ## Ufuatiliaji na Uchambuzi ### Ufuatiliaji wa Utendaji ```python # Monitor orchestrator performance metrics = await orchestrator.get_performance_metrics() print(f"Tasks Completed: {metrics.tasks_completed}") print(f"Average Response Time: {metrics.avg_response_time}s") print(f"Success Rate: {metrics.success_rate}%") print(f"Agent Utilization: {metrics.agent_utilization}") ``` ### Vipimo vya Ubora ```python # Track output quality quality_report = await orchestrator.generate_quality_report() print(f"Output Consistency: {quality_report.consistency_score}") print(f"Factual Accuracy: {quality_report.accuracy_score}") print(f"Completeness: {quality_report.completeness_score}") ``` ## Matokeo ya Kujifunza Baada ya kukamilisha mfano huu, utaelewa: 1. **Muundo wa Mfumo wa Wakala Wengi** - Mifumo ya uratibu wa wakala - Mikakati ya usambazaji wa kazi - Mbinu za muhtasari wa matokeo - Usimamizi wa muktadha kati ya wakala 2. **Muunganiko wa Microsoft Foundry Local** - Utekelezaji wa kuita kazi - Mifumo ya muunganiko wa zana - Uratibu wa miundo mingi - Uboreshaji wa utendaji 3. **Uratibu wa AI wa Hali ya Juu** - Ubunifu na utekelezaji wa mtiririko wa kazi - Mifumo ya uhakikisho wa ubora - Kushughulikia hitilafu na urejeshaji - Mazingatio ya upanuzi 4. **Ubunifu wa Mfumo wa Uzalishaji** - Ufuatiliaji na uchambuzi - Usimamizi wa usanidi - Mazoea bora ya usalama - Urekebishaji wa utendaji ## Hatua Zifuatazo - **Mfano 10**: Foundry Local kama Muunganiko wa Zana - **Mada za Hali ya Juu**: Uundaji wa wakala maalum - **Upanuzi**: Mifumo ya wakala iliyosambazwa - **Muunganiko**: Muunganiko wa mtiririko wa kazi wa biashara ## Kuchangia Tazama miongozo ya hazina kuu kwa maelekezo ya kuchangia. ## Leseni Mfano huu unafuata leseni sawa na mradi wa Microsoft Foundry Local. ---