"""Agent implementations for Socratic AI LangGraph."""

from typing import Any, Dict, List, Optional
from socratic_core import SocratesConfig, EventEmitter, EventType


class BaseAgent:
    """Base agent class."""

    def __init__(self, name: str, emitter: Optional[EventEmitter] = None):
        """Initialize agent.

        Args:
            name: Agent name
            emitter: Event emitter for publishing events
        """
        self.name = name
        self.emitter = emitter or EventEmitter()

    def emit_event(self, event_type: EventType, data: Dict[str, Any]) -> None:
        """Emit event."""
        self.emitter.emit(event_type, data)


class CodeAnalysisAgent(BaseAgent):
    """Agent that analyzes code."""

    def __init__(self, emitter: Optional[EventEmitter] = None):
        """Initialize code analysis agent."""
        super().__init__("code_analyzer", emitter)

    def analyze(self, code: str) -> Dict[str, Any]:
        """Analyze code.

        Args:
            code: Code to analyze

        Returns:
            Analysis results
        """
        self.emit_event(
            EventType.AGENT_START,
            {"agent": self.name, "task": "code_analysis"}
        )

        # Simulated analysis
        result = {
            "complexity": "medium" if len(code) > 100 else "low",
            "lines": len(code.split('\n')),
            "issues": ["missing error handling"] if "try" not in code else [],
            "suggestions": ["add type hints", "improve variable names"],
            "quality_score": 7.5
        }

        self.emit_event(
            EventType.AGENT_COMPLETE,
            {"agent": self.name, "result": result}
        )

        return result


class CodeGenerationAgent(BaseAgent):
    """Agent that generates code."""

    def __init__(self, emitter: Optional[EventEmitter] = None):
        """Initialize code generation agent."""
        super().__init__("code_generator", emitter)

    def generate(self, prompt: str) -> str:
        """Generate code based on prompt.

        Args:
            prompt: Code generation prompt

        Returns:
            Generated code
        """
        self.emit_event(
            EventType.AGENT_START,
            {"agent": self.name, "task": "code_generation", "prompt": prompt}
        )

        # Simulated code generation
        generated_code = f"""# Generated from: {prompt}
def solution():
    \"\"\"Implementation based on: {prompt}\"\"\"
    # TODO: Implement based on requirements
    pass
"""

        self.emit_event(
            EventType.CODE_GENERATED,
            {"agent": self.name, "lines": len(generated_code.split('\n'))}
        )

        return generated_code


class KnowledgeRetrievalAgent(BaseAgent):
    """Agent that retrieves knowledge using RAG."""

    def __init__(self, emitter: Optional[EventEmitter] = None):
        """Initialize knowledge retrieval agent."""
        super().__init__("knowledge_retrieval", emitter)

    def retrieve(self, query: str) -> List[Dict[str, str]]:
        """Retrieve relevant knowledge.

        Args:
            query: Knowledge query

        Returns:
            List of relevant documents
        """
        self.emit_event(
            EventType.AGENT_START,
            {"agent": self.name, "task": "knowledge_retrieval", "query": query}
        )

        # Simulated retrieval
        results = [
            {
                "source": "documentation",
                "content": "Relevant documentation...",
                "relevance": 0.95
            },
            {
                "source": "examples",
                "content": "Example code...",
                "relevance": 0.87
            },
        ]

        self.emit_event(
            EventType.KNOWLEDGE_LOADED,
            {"agent": self.name, "count": len(results)}
        )

        return results
