"""
Simple example of using the forensic agent with streaming output.
"""

import sys
from pathlib import Path

# Add src to path
sys.path.insert(0, str(Path(__file__).parent.parent))

from src.agents import ForensicAgent


def main():
    # Example: Analyze an image
    # Replace with your image path
    # Get project root
    use_tools = "--tools" in sys.argv  # default to vision-only simple prompt
    use_streaming = "--no-stream" not in sys.argv  # default to streaming
    # Image path is the first non keyword argument, should not take --tools as argument
    
    # Filter out keyword arguments to find the image path
    keyword_args = {"--tools", "--no-stream"}
    non_keyword_args = [arg for arg in sys.argv[1:] if arg not in keyword_args]
    
    if not non_keyword_args:
        print("Error: Please provide an image path as an argument.")
        print("Usage: python example.py [--tools] [--no-stream] <image_path>")
        sys.exit(1)
    
    image_path = non_keyword_args[0]
    
    print("Initializing forensic agent...")
    agent = ForensicAgent(llm_model="gpt-5.1", temperature=None, reasoning_effort="medium")
    
    mode = "full (with tools)" if use_tools else "vision-only (no tools)"
    stream_mode = "with streaming" if use_streaming else "without streaming"
    print(f"\nAnalyzing image: {image_path} [{mode}, {stream_mode}]")
    print("-" * 60)
    
    try:
        if use_streaming:
            # Use streaming mode
            print("\n[STREAMING MODE]\n")
            accumulated_text = ""
            tool_calls_seen = set()
            
            for event in agent.analyze_stream(image_path, use_tools=use_tools):
                event_type = event.get('type')
                
                if event_type == 'status':
                    print(f"\n{event.get('content', '')}")
                    sys.stdout.flush()
                
                elif event_type == 'tool_call':
                    tool_name = event.get('tool_name', 'unknown')
                    if tool_name not in tool_calls_seen:
                        print(f"\n{'='*60}")
                        print(f"🔧 [TOOL CALL] {event.get('content', '')}")
                        tool_args = event.get('tool_args', {})
                        if tool_args:
                            print(f"   Arguments: {tool_args}")
                        print(f"{'='*60}")
                        sys.stdout.flush()
                        tool_calls_seen.add(tool_name)
                
                elif event_type == 'tool_result':
                    print(f"\n{'='*60}")
                    print(f"✅ [TOOL RESULT] {event.get('content', '')}")
                    tool_result = event.get('tool_result', '')
                    if tool_result:
                        # Show preview of result
                        preview = str(tool_result)[:150]
                        print(f"   Full result: {tool_result}")
                        print(f"   Preview: {preview}{'...' if len(str(tool_result)) > 150 else ''}")
                    print(f"{'='*60}\n")
                    sys.stdout.flush()
                
                elif event_type == 'llm_chunk':
                    # Stream LLM output character by character for better UX
                    chunk = event.get('content', '')
                    print(chunk, end='', flush=True)
                    accumulated_text += chunk
                
                elif event_type == 'final':
                    final_result = event.get('final_result', {})
                    print("\n\n" + "=" * 60)
                    print("ANALYSIS COMPLETE")
                    print("=" * 60)
                    print(f"\nTools used: {', '.join(final_result.get('tool_usage', [])) if final_result.get('tool_usage') else 'None'}")
                    print("\n" + "=" * 60)
        else:
            # Use non-streaming mode
            result = agent.analyze(image_path, use_tools=use_tools)
            
            print("\nAnalysis Results:")
            print("=" * 60)
            print(result['conclusion'])
            print("\nTools used:", result['tool_usage'] if result['tool_usage'] else "None")
        
    except FileNotFoundError:
        print(f"\nError: Image file not found: {image_path}")
        print("Please update the image_path variable with a valid image path.")
    except Exception as e:
        print(f"\nError: {e}")
        import traceback
        traceback.print_exc()


if __name__ == "__main__":
    main()