🛠️ Tool Executor Module¶

🔐 Licensed Component - Contact: bajpaikrishna715@gmail.com for licensing

Tool Executor Architecture¶

graph TB
    subgraph "Tool Management"
        A[Tool Registry]
        B[Tool Discovery]
        C[Tool Validation]
        D[Tool Execution]
    end

    subgraph "Quantum Enhancement"
        E[Quantum Tool Selection]
        F[Parallel Execution]
        G[Entangled Coordination]
        H[Superposition Planning]
    end

    subgraph "Execution Environment"
        I[Secure Sandbox]
        J[Resource Management]
        K[Error Handling]
        L[Result Processing]
    end

    subgraph "Integration Layer"
        M[Chain Integration]
        N[Agent Coordination]
        O[Memory Interaction]
        P[Vector Store Access]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

    I --> M
    J --> N
    K --> O
    L --> P

🌟 Core Features¶

Quantum Tool Selection¶

graph LR
    subgraph "Classical Selection"
        A[Sequential Evaluation]
        B[Rule-Based Logic]
        C[Single Tool Choice]
        D[Limited Context]
    end

    subgraph "Quantum Selection"
        E[Superposition Evaluation]
        F[Quantum Logic Gates]
        G[Multi-Tool Coherence]
        H[Rich Context Understanding]
    end

    subgraph "Hybrid Benefits"
        I[Optimal Tool Choice]
        J[Context-Aware Selection]
        K[Parallel Evaluation]
        L[Enhanced Performance]
    end

    A --> I
    B --> J
    C --> K
    D --> L

    E --> I
    F --> J
    G --> K
    H --> L

🔧 Implementation¶

Basic Tool Executor¶

from quantumlangchain.tools import QuantumToolExecutor
from quantumlangchain.tools.base import QuantumTool

# Initialize tool executor
executor = QuantumToolExecutor(
    quantum_selection=True,
    parallel_execution=True,
    error_correction=True
)

# Register tools
calculator = QuantumTool(name="calculator", func=calculate)
searcher = QuantumTool(name="search", func=web_search)
analyzer = QuantumTool(name="analyzer", func=analyze_data)

executor.register_tools([calculator, searcher, analyzer])

# Execute with quantum enhancement
result = await executor.execute(
    "Calculate the square root of 144 and search for its applications",
    quantum_coordination=True
)

Advanced Multi-Agent Tool Execution¶

from quantumlangchain.tools import DistributedQuantumToolExecutor

class AdvancedToolSystem:
    def __init__(self):
        self.executor = DistributedQuantumToolExecutor(
            agents=["coordinator", "executor", "validator"],
            quantum_coordination=True,
            fault_tolerance=True
        )

        # Tool categories
        self.computational_tools = [
            "quantum_calculator",
            "symbolic_math",
            "numerical_solver"
        ]

        self.data_tools = [
            "data_analyzer",
            "pattern_recognizer",
            "visualization_engine"
        ]

        self.ai_tools = [
            "language_model",
            "image_generator",
            "code_assistant"
        ]

    async def complex_task_execution(self, task_description):
        """Execute complex tasks using quantum-coordinated tools."""
        # Quantum task decomposition
        subtasks = await self.executor.quantum_decompose_task(
            task_description
        )

        # Parallel tool execution with entanglement
        results = []
        for subtask in subtasks:
            optimal_tools = await self.executor.quantum_tool_selection(
                subtask
            )
            result = await self.executor.entangled_execution(
                subtask, optimal_tools
            )
            results.append(result)

        # Quantum result synthesis
        final_result = await self.executor.quantum_synthesis(results)
        return final_result

Quantum Tool Coordination¶

class QuantumToolCoordinator:
    def __init__(self, tools):
        self.tools = tools
        self.quantum_state = QuantumState(len(tools))

    async def coordinate_tool_execution(self, task):
        """Coordinate multiple tools using quantum entanglement."""
        # Create quantum superposition of tool combinations
        tool_combinations = await self.create_tool_superposition(task)

        # Execute in quantum parallel
        quantum_results = await self.quantum_parallel_execution(
            tool_combinations
        )

        # Measure optimal result
        optimal_result = await self.quantum_measurement(
            quantum_results
        )

        return optimal_result

    async def adaptive_tool_learning(self):
        """Learn optimal tool usage patterns."""
        # Analyze historical execution patterns
        patterns = await self.analyze_execution_history()

        # Update quantum model
        await self.update_quantum_model(patterns)

        # Optimize tool selection strategies
        await self.optimize_selection_strategies()

🎯 Tool Categories¶

Computational Tools¶

graph TB
    subgraph "Mathematical Tools"
        A[Quantum Calculator]
        B[Symbolic Math Engine]
        C[Numerical Solver]
        D[Statistical Analyzer]
    end

    subgraph "Scientific Tools"
        E[Physics Simulator]
        F[Chemistry Modeler]
        G[Biology Analyzer]
        H[Materials Designer]
    end

    subgraph "AI/ML Tools"
        I[Model Trainer]
        J[Data Preprocessor]
        K[Feature Extractor]
        L[Prediction Engine]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

Integration Tools¶

# Tool integration examples
TOOL_REGISTRY = {
    "computational": {
        "quantum_calculator": {
            "description": "Quantum-enhanced mathematical calculations",
            "input_types": ["numbers", "expressions"],
            "output_types": ["results", "visualizations"],
            "quantum_advantage": True
        },
        "symbolic_solver": {
            "description": "Symbolic mathematics and equation solving",
            "input_types": ["equations", "expressions"],
            "output_types": ["solutions", "proofs"],
            "quantum_advantage": False
        }
    },

    "data_analysis": {
        "pattern_recognizer": {
            "description": "Quantum pattern recognition in data",
            "input_types": ["datasets", "images", "text"],
            "output_types": ["patterns", "insights"],
            "quantum_advantage": True
        },
        "data_visualizer": {
            "description": "Advanced data visualization",
            "input_types": ["data", "specifications"],
            "output_types": ["charts", "graphs", "interactive"],
            "quantum_advantage": False
        }
    },

    "ai_assistance": {
        "code_generator": {
            "description": "AI-powered code generation",
            "input_types": ["requirements", "specifications"],
            "output_types": ["code", "documentation"],
            "quantum_advantage": True
        }
    }
}

📊 Performance Optimization¶

Execution Performance¶

graph LR
    subgraph "Classical Execution"
        A[Sequential Processing]
        B[Single Tool Focus]
        C[Limited Coordination]
        D[Resource Conflicts]
    end

    subgraph "Quantum Execution"
        E[Parallel Processing]
        F[Multi-Tool Coherence]
        G[Quantum Coordination]
        H[Resource Optimization]
    end

    subgraph "Performance Gains"
        I[Speed Improvement]
        J[Quality Enhancement]
        K[Resource Efficiency]
        L[Scalability]
    end

    A --> I
    B --> J
    C --> K
    D --> L

    E --> I
    F --> J
    G --> K
    H --> L

Tool Performance Analytics¶

class ToolPerformanceAnalyzer:
    def __init__(self, executor):
        self.executor = executor
        self.metrics_collector = MetricsCollector()

    async def analyze_tool_performance(self):
        """Analyze performance of individual tools and combinations."""
        # Collect execution metrics
        metrics = await self.metrics_collector.get_execution_metrics()

        # Analyze quantum vs classical performance
        quantum_performance = await self.analyze_quantum_performance(
            metrics
        )

        # Identify optimization opportunities
        optimizations = await self.identify_optimizations(metrics)

        return {
            "quantum_advantage": quantum_performance,
            "optimization_suggestions": optimizations,
            "performance_trends": await self.analyze_trends(metrics)
        }

    async def optimize_tool_selection(self):
        """Optimize tool selection based on performance data."""
        # Machine learning on tool performance
        model = await self.train_selection_model()

        # Update quantum selection algorithms
        await self.executor.update_selection_algorithm(model)

        # Validate improvements
        improvements = await self.validate_optimizations()
        return improvements

🔒 License Integration¶

Tool Access Restrictions¶

graph LR
    subgraph "License Tiers"
        A[Basic - 5 Tools]
        B[Professional - 20 Tools]
        C[Enterprise - 100+ Tools]
        D[Research - Unlimited]
    end

    subgraph "Execution Features"
        E[Basic Execution]
        F[Quantum Selection]
        G[Parallel Execution]
        H[Custom Tools]
    end

    A --> E
    B --> F
    C --> G
    D --> H

License Enforcement¶

from quantumlangchain.licensing import requires_license

class QuantumToolExecutor(LicensedComponent):
    @requires_license(tier="basic")
    def __init__(self, **kwargs):
        """Initialize with license validation."""
        super().__init__(
            required_features=["tool_execution"],
            required_tier="basic"
        )

        # Validate tool limits
        max_tools = self._get_max_tools()
        if len(kwargs.get("tools", [])) > max_tools:
            raise LicenseError(
                f"Tool limit exceeded. License allows {max_tools} tools. "
                f"Contact: bajpaikrishna715@gmail.com"
            )

    @requires_license(tier="professional")
    def enable_quantum_selection(self):
        """Enable quantum tool selection (Professional+ only)."""
        pass

    @requires_license(tier="enterprise")
    def enable_parallel_execution(self):
        """Enable parallel tool execution (Enterprise+ only)."""
        pass

📚 API Reference¶

Core Tool Executor Classes¶

class QuantumToolExecutor:
    def __init__(self, tools=None, quantum_selection=True, **config):
        """Initialize quantum tool executor."""

    async def execute(self, task: str, tools: List[str] = None, **kwargs) -> Any:
        """Execute task using selected tools."""

    def register_tool(self, tool: QuantumTool) -> None:
        """Register a new tool."""

    def register_tools(self, tools: List[QuantumTool]) -> None:
        """Register multiple tools."""

    async def quantum_tool_selection(self, task: str) -> List[str]:
        """Select optimal tools using quantum algorithms."""

class QuantumTool:
    def __init__(self, name: str, func: Callable, description: str = "", **metadata):
        """Initialize quantum tool."""

    async def arun(self, *args, **kwargs) -> Any:
        """Run tool asynchronously."""

    def run(self, *args, **kwargs) -> Any:
        """Run tool synchronously."""

🔮 Future Enhancements¶

Planned Tool Features¶

graph TB
    subgraph "Near Future"
        A[More Tool Types]
        B[Better Selection]
        C[Enhanced Performance]
        D[Improved Security]
    end

    subgraph "Medium Term"
        E[Self-Modifying Tools]
        F[Quantum Tool Networks]
        G[Adaptive Learning]
        H[Auto-Tool Generation]
    end

    subgraph "Long Term"
        I[Conscious Tools]
        J[Universal Tool Interface]
        K[Quantum Tool Ecosystem]
        L[AI Tool Evolution]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

🔐 License Requirements¶

Basic Tools: Basic license tier (up to 5 tools)
Professional Tools: Professional license tier (up to 20 tools)
Enterprise Tools: Enterprise license tier (100+ tools)
Research Tools: Research license tier (unlimited tools)

Contact bajpaikrishna715@gmail.com for licensing.

Tool Executor provides quantum-enhanced tool management and execution capabilities for advanced AI automation and problem-solving.