王子睿

restructure + add files

8c10cf2 11 months ago

13.8 kB

#!/usr/bin/env python3
"""
Analyze RETRY patterns in MarkdownValidator-MCP project
Statistics on error locations, RETRY counts, RETRY rates, etc.
"""

import os
import re
from pathlib import Path
from collections import defaultdict
import json
import csv

# Define base path and model list
BASE_DIR = Path("/Users/wzr/TOSEM-2025/RESULTS")
MODELS = [
    "DeepSeek-R1",
    "DeepSeek-V3-1",
    "GPT-4o-mini",
    "GPT-5",
    "Gemini-2.5-flash",
    "Gemini-2.5-flash-nothinking",
    "Qwen3-235b",
]
PROJECT_NAME = "MarkdownValidator-MCP"


def extract_error_info(line: str) -> dict:
    """Extract error information from error line
    Returns:
        {'has_error': bool, 'node_type': str, 'node_name': str, 'error_msg': str}
    """
    # Remove tree structure characters
    clean = re.sub(r"^[│├└\-\s]+", "", line).strip()

    # Check for error marker
    if "❌" not in clean:
        return {"has_error": False}

    # Remove error marker
    clean = clean.split("❌", 1)[1].lstrip()

    # Extract node type and name
    node_match = re.match(
        r"\[(SPAN|Chain|AGENT|Tool|LLM)\]\s+([^\[\]]+?)(?:\s+\[ERROR:(.*))?$",
        clean,
    )
    if not node_match:
        return {
            "has_error": True,
            "node_type": "Unknown",
            "node_name": "Unknown",
            "error_msg": "",
        }

    node_type = node_match.group(1)
    node_name = node_match.group(2).strip()
    error_msg = node_match.group(3).strip() if node_match.group(3) else ""

    # Clean node name
    if node_type == "AGENT":
        node_name = re.sub(r"\._execute_core$", "", node_name)
    elif node_type == "Tool":
        node_name = re.sub(r"\._use$", "", node_name)
    elif node_type == "Chain":
        node_name = re.sub(r"Crew_[a-f0-9\-]+\.kickoff", "Crew***.kickoff", node_name)

    return {
        "has_error": True,
        "node_type": node_type,
        "node_name": node_name,
        "error_msg": error_msg,
    }


def extract_retry_info(line: str) -> dict:
    """Extract RETRY information from RETRY line
    Returns:
        {'is_retry': bool, 'retry_number': int, 'node_type': str, 'node_name': str}
    """
    # Remove tree structure characters
    clean = re.sub(r"^[│├└\-\s]+", "", line).strip()

    # Check for RETRY marker: (retry N) or [RETRYN]
    retry_match = re.search(r"\(retry\s+(\d+)\)", clean)
    if not retry_match:
        retry_match = re.search(r"\[RETRY(\d+)\]", clean)

    if not retry_match:
        return {"is_retry": False}

    retry_number = int(retry_match.group(1))

    # Extract node type and name
    node_match = re.match(
        r"\[(SPAN|Chain|AGENT)\]\s+([^\[\]]+?)(?:\s+\(retry\s+\d+\))?(?:\s+\[RETRY\d+\])?\s*(?:\[.*)?$",
        clean,
    )
    if not node_match:
        return {
            "is_retry": True,
            "retry_number": retry_number,
            "node_type": "Unknown",
            "node_name": "Unknown",
        }

    node_type = node_match.group(1)
    node_name = node_match.group(2).strip()

    return {
        "is_retry": True,
        "retry_number": retry_number,
        "node_type": node_type,
        "node_name": node_name,
    }


def analyze_session(md_file: str) -> dict:
    """Analyze execution_path.md for a single session
    Returns:
        {
            'has_error': bool,
            'has_retry': bool,
            'max_retry_number': int,
            'total_retries': int,
            'errors': [{'node_type': str, 'node_name': str, 'error_msg': str}, ...],
            'retries': [{'retry_number': int, 'node_type': str, 'node_name': str}, ...]
        }
    """
    if not os.path.exists(md_file):
        return None

    with open(md_file, "r", encoding="utf-8") as f:
        content = f.read()

    # Extract Execution Path Tree section
    tree_match = re.search(
        r"## Execution Path Tree.*?```\n(.*?)```", content, re.DOTALL
    )
    if not tree_match:
        return None

    tree_content = tree_match.group(1)

    errors = []
    retries = []

    for line in tree_content.split("\n"):
        if not line.strip():
            continue

        # Check for errors
        error_info = extract_error_info(line)
        if error_info["has_error"]:
            errors.append(
                {
                    "node_type": error_info.get("node_type", "Unknown"),
                    "node_name": error_info.get("node_name", "Unknown"),
                    "error_msg": error_info.get("error_msg", ""),
                }
            )

        # Check for RETRY
        retry_info = extract_retry_info(line)
        if retry_info["is_retry"]:
            retries.append(
                {
                    "retry_number": retry_info["retry_number"],
                    "node_type": retry_info["node_type"],
                    "node_name": retry_info["node_name"],
                }
            )

    max_retry = max([r["retry_number"] for r in retries]) if retries else 0

    return {
        "has_error": len(errors) > 0,
        "has_retry": len(retries) > 0,
        "max_retry_number": max_retry,
        "total_retries": len(retries),
        "errors": errors,
        "retries": retries,
    }


def collect_model_stats(model_name: str) -> dict:
    """Collect RETRY statistics for a single model
    Returns:
        {
            'model': str,
            'total_sessions': int,
            'sessions_with_error': int,
            'sessions_with_retry': int,
            'total_retry_attempts': int,
            'retry_rate': float,
            'error_by_agent': {agent_name: count},
            'error_types': {error_msg: count},
            'max_retry_number': int,
            'session_details': [...]
        }
    """
    test_results_dir = BASE_DIR / model_name / PROJECT_NAME / "test_results"

    if not test_results_dir.exists():
        return None

    stats = {
        "model": model_name,
        "total_sessions": 0,
        "sessions_with_error": 0,
        "sessions_with_retry": 0,
        "total_retry_attempts": 0,
        "error_by_agent": defaultdict(int),
        "error_by_node_type": defaultdict(int),
        "error_types": defaultdict(int),
        "max_retry_number": 0,
        "session_details": [],
    }

    for session_dir in sorted(test_results_dir.iterdir()):
        if not session_dir.is_dir():
            continue

        exec_path_file = session_dir / "execution_path.md"
        if not exec_path_file.exists():
            continue

        stats["total_sessions"] += 1

        analysis = analyze_session(str(exec_path_file))
        if not analysis:
            continue

        # Count errors and RETRYs
        if analysis["has_error"]:
            stats["sessions_with_error"] += 1

        if analysis["has_retry"]:
            stats["sessions_with_retry"] += 1
            stats["total_retry_attempts"] += analysis["total_retries"]
            stats["max_retry_number"] = max(
                stats["max_retry_number"], analysis["max_retry_number"]
            )

        # Count error locations
        for error in analysis["errors"]:
            if error["node_type"] == "AGENT":
                stats["error_by_agent"][error["node_name"]] += 1
            stats["error_by_node_type"][error["node_type"]] += 1

            # Extract short error type description
            error_msg = error["error_msg"]
            if error_msg:
                # Take first 100 characters as error type identifier
                error_type = (
                    error_msg[:100]
                    if len(error_msg) <= 100
                    else error_msg[:100] + "..."
                )
                stats["error_types"][error_type] += 1

        # Save session details
        stats["session_details"].append(
            {
                "session": session_dir.name,
                "has_error": analysis["has_error"],
                "has_retry": analysis["has_retry"],
                "retry_count": analysis["total_retries"],
                "errors": analysis["errors"],
                "retries": analysis["retries"],
            }
        )

    # Calculate RETRY rate
    stats["retry_rate"] = (
        (stats["sessions_with_retry"] / stats["total_sessions"] * 100)
        if stats["total_sessions"] > 0
        else 0
    )
    stats["error_rate"] = (
        (stats["sessions_with_error"] / stats["total_sessions"] * 100)
        if stats["total_sessions"] > 0
        else 0
    )

    # Convert defaultdict to regular dict
    stats["error_by_agent"] = dict(stats["error_by_agent"])
    stats["error_by_node_type"] = dict(stats["error_by_node_type"])
    stats["error_types"] = dict(stats["error_types"])

    return stats


def print_summary(all_stats):
    """Print statistics summary"""
    print("\n" + "=" * 100)
    print(f"RETRY Pattern Analysis Summary - {PROJECT_NAME}")
    print("=" * 100 + "\n")

    # Overall statistics table
    print("## Model Statistics\n")
    print(
        f"{'Model':<35} {'Total Sessions':<15} {'Error Rate':<12} {'RETRY Rate':<12} {'Total RETRYs':<13} {'Max RETRY':<10}"
    )
    print("-" * 100)

    for stats in all_stats:
        if stats:
            print(
                f"{stats['model']:<35} {stats['total_sessions']:<15} "
                f"{stats['error_rate']:>10.1f}% {stats['retry_rate']:>10.1f}% "
                f"{stats['total_retry_attempts']:<13} {stats['max_retry_number']:<10}"
            )

    print("\n" + "=" * 100)

    # Detailed information for each model
    for stats in all_stats:
        if not stats or stats["sessions_with_error"] == 0:
            continue

        print(f"\n### {stats['model']}\n")
        print(f"- Total Sessions: {stats['total_sessions']}")
        print(
            f"- Sessions with Errors: {stats['sessions_with_error']} ({stats['error_rate']:.1f}%)"
        )
        print(
            f"- Sessions with RETRY: {stats['sessions_with_retry']} ({stats['retry_rate']:.1f}%)"
        )
        print(f"- Total RETRY Attempts: {stats['total_retry_attempts']}")
        print(f"- Max RETRY Number: {stats['max_retry_number']}")

        if stats["error_by_agent"]:
            print(f"\nErrors by AGENT:")
            for agent, count in sorted(
                stats["error_by_agent"].items(), key=lambda x: x[1], reverse=True
            ):
                print(f"  - {agent}: {count} times")

        if stats["error_by_node_type"]:
            print(f"\nErrors by Node Type:")
            for node_type, count in sorted(
                stats["error_by_node_type"].items(), key=lambda x: x[1], reverse=True
            ):
                print(f"  - {node_type}: {count} times")

        if stats["error_types"]:
            print(f"\nError Types (Top 5):")
            for error_type, count in sorted(
                stats["error_types"].items(), key=lambda x: x[1], reverse=True
            )[:5]:
                print(f"  - [{count}x] {error_type}")

        print("\n" + "-" * 100)


def save_results(all_stats):
    """Save results to files"""
    output_dir = Path(__file__).parent

    # Save detailed JSON
    json_file = output_dir / "retry_analysis.json"
    json_data = []
    for stats in all_stats:
        if stats:
            json_data.append(stats)

    with open(json_file, "w", encoding="utf-8") as f:
        json.dump(json_data, f, indent=2, ensure_ascii=False)
    print(f"\nJSON results saved: {json_file}")

    # Save CSV summary
    csv_file = output_dir / "retry_summary.csv"
    with open(csv_file, "w", newline="", encoding="utf-8") as f:
        writer = csv.writer(f)
        writer.writerow(
            [
                "Model",
                "Total_Sessions",
                "Sessions_With_Error",
                "Error_Rate(%)",
                "Sessions_With_Retry",
                "Retry_Rate(%)",
                "Total_Retry_Attempts",
                "Max_Retry_Number",
            ]
        )

        for stats in all_stats:
            if stats:
                writer.writerow(
                    [
                        stats["model"],
                        stats["total_sessions"],
                        stats["sessions_with_error"],
                        f"{stats['error_rate']:.2f}",
                        stats["sessions_with_retry"],
                        f"{stats['retry_rate']:.2f}",
                        stats["total_retry_attempts"],
                        stats["max_retry_number"],
                    ]
                )

    print(f"CSV summary saved: {csv_file}")

    # Save error location statistics
    error_csv_file = output_dir / "error_by_agent.csv"
    with open(error_csv_file, "w", newline="", encoding="utf-8") as f:
        writer = csv.writer(f)
        writer.writerow(["Model", "Agent_Name", "Error_Count"])

        for stats in all_stats:
            if stats and stats["error_by_agent"]:
                for agent, count in sorted(
                    stats["error_by_agent"].items(), key=lambda x: x[1], reverse=True
                ):
                    writer.writerow([stats["model"], agent, count])

    print(f"Error location statistics saved: {error_csv_file}")


if __name__ == "__main__":
    print(f"Starting RETRY pattern analysis - {PROJECT_NAME}...")

    all_stats = []
    for model in MODELS:
        print(f"\nAnalyzing model: {model}")
        stats = collect_model_stats(model)
        if stats:
            all_stats.append(stats)
            print(
                f"  Completed: {stats['total_sessions']} sessions, "
                f"{stats['sessions_with_error']} errors, "
                f"{stats['sessions_with_retry']} retries"
            )
        else:
            print(f"  Skipped (directory not found)")

    print_summary(all_stats)
    save_results(all_stats)

    print("\n" + "=" * 100)
    print("Analysis completed!")
    print("=" * 100)

	#!/usr/bin/env python3
	"""
	Analyze RETRY patterns in MarkdownValidator-MCP project
	Statistics on error locations, RETRY counts, RETRY rates, etc.
	"""

	import os
	import re
	from pathlib import Path
	from collections import defaultdict
	import json
	import csv

	# Define base path and model list
	BASE_DIR = Path("/Users/wzr/TOSEM-2025/RESULTS")
	MODELS = [
	"DeepSeek-R1",
	"DeepSeek-V3-1",
	"GPT-4o-mini",
	"GPT-5",
	"Gemini-2.5-flash",
	"Gemini-2.5-flash-nothinking",
	"Qwen3-235b",
	]
	PROJECT_NAME = "MarkdownValidator-MCP"


	def extract_error_info(line: str) -> dict:
	"""Extract error information from error line

	Returns:
	{'has_error': bool, 'node_type': str, 'node_name': str, 'error_msg': str}
	"""
	# Remove tree structure characters
	clean = re.sub(r"^[│├└\-\s]+", "", line).strip()

	# Check for error marker
	if "❌" not in clean:
	return {"has_error": False}

	# Remove error marker
	clean = clean.split("❌", 1)[1].lstrip()

	# Extract node type and name
	node_match = re.match(
	r"\[(SPAN\|Chain\|AGENT\|Tool\|LLM)\]\s+([^\[\]]+?)(?:\s+\[ERROR:(.*))?$",
	clean,
	)
	if not node_match:
	return {
	"has_error": True,
	"node_type": "Unknown",
	"node_name": "Unknown",
	"error_msg": "",
	}

	node_type = node_match.group(1)
	node_name = node_match.group(2).strip()
	error_msg = node_match.group(3).strip() if node_match.group(3) else ""

	# Clean node name
	if node_type == "AGENT":
	node_name = re.sub(r"\._execute_core$", "", node_name)
	elif node_type == "Tool":
	node_name = re.sub(r"\._use$", "", node_name)
	elif node_type == "Chain":
	node_name = re.sub(r"Crew_[a-f0-9\-]+\.kickoff", "Crew***.kickoff", node_name)

	return {
	"has_error": True,
	"node_type": node_type,
	"node_name": node_name,
	"error_msg": error_msg,
	}


	def extract_retry_info(line: str) -> dict:
	"""Extract RETRY information from RETRY line

	Returns:
	{'is_retry': bool, 'retry_number': int, 'node_type': str, 'node_name': str}
	"""
	# Remove tree structure characters
	clean = re.sub(r"^[│├└\-\s]+", "", line).strip()

	# Check for RETRY marker: (retry N) or [RETRYN]
	retry_match = re.search(r"\(retry\s+(\d+)\)", clean)
	if not retry_match:
	retry_match = re.search(r"\[RETRY(\d+)\]", clean)

	if not retry_match:
	return {"is_retry": False}

	retry_number = int(retry_match.group(1))

	# Extract node type and name
	node_match = re.match(
	r"\[(SPAN\|Chain\|AGENT)\]\s+([^\[\]]+?)(?:\s+\(retry\s+\d+\))?(?:\s+\[RETRY\d+\])?\s(?:\[.)?$",
	clean,
	)
	if not node_match:
	return {
	"is_retry": True,
	"retry_number": retry_number,
	"node_type": "Unknown",
	"node_name": "Unknown",
	}

	node_type = node_match.group(1)
	node_name = node_match.group(2).strip()

	return {
	"is_retry": True,
	"retry_number": retry_number,
	"node_type": node_type,
	"node_name": node_name,
	}


	def analyze_session(md_file: str) -> dict:
	"""Analyze execution_path.md for a single session

	Returns:
	{
	'has_error': bool,
	'has_retry': bool,
	'max_retry_number': int,
	'total_retries': int,
	'errors': [{'node_type': str, 'node_name': str, 'error_msg': str}, ...],
	'retries': [{'retry_number': int, 'node_type': str, 'node_name': str}, ...]
	}
	"""
	if not os.path.exists(md_file):
	return None

	with open(md_file, "r", encoding="utf-8") as f:
	content = f.read()

	# Extract Execution Path Tree section
	tree_match = re.search(
	r"## Execution Path Tree.?```\n(.?)```", content, re.DOTALL
	)
	if not tree_match:
	return None

	tree_content = tree_match.group(1)

	errors = []
	retries = []

	for line in tree_content.split("\n"):
	if not line.strip():
	continue

	# Check for errors
	error_info = extract_error_info(line)
	if error_info["has_error"]:
	errors.append(
	{
	"node_type": error_info.get("node_type", "Unknown"),
	"node_name": error_info.get("node_name", "Unknown"),
	"error_msg": error_info.get("error_msg", ""),
	}
	)

	# Check for RETRY
	retry_info = extract_retry_info(line)
	if retry_info["is_retry"]:
	retries.append(
	{
	"retry_number": retry_info["retry_number"],
	"node_type": retry_info["node_type"],
	"node_name": retry_info["node_name"],
	}
	)

	max_retry = max([r["retry_number"] for r in retries]) if retries else 0

	return {
	"has_error": len(errors) > 0,
	"has_retry": len(retries) > 0,
	"max_retry_number": max_retry,
	"total_retries": len(retries),
	"errors": errors,
	"retries": retries,
	}


	def collect_model_stats(model_name: str) -> dict:
	"""Collect RETRY statistics for a single model

	Returns:
	{
	'model': str,
	'total_sessions': int,
	'sessions_with_error': int,
	'sessions_with_retry': int,
	'total_retry_attempts': int,
	'retry_rate': float,
	'error_by_agent': {agent_name: count},
	'error_types': {error_msg: count},
	'max_retry_number': int,
	'session_details': [...]
	}
	"""
	test_results_dir = BASE_DIR / model_name / PROJECT_NAME / "test_results"

	if not test_results_dir.exists():
	return None

	stats = {
	"model": model_name,
	"total_sessions": 0,
	"sessions_with_error": 0,
	"sessions_with_retry": 0,
	"total_retry_attempts": 0,
	"error_by_agent": defaultdict(int),
	"error_by_node_type": defaultdict(int),
	"error_types": defaultdict(int),
	"max_retry_number": 0,
	"session_details": [],
	}

	for session_dir in sorted(test_results_dir.iterdir()):
	if not session_dir.is_dir():
	continue

	exec_path_file = session_dir / "execution_path.md"
	if not exec_path_file.exists():
	continue

	stats["total_sessions"] += 1

	analysis = analyze_session(str(exec_path_file))
	if not analysis:
	continue

	# Count errors and RETRYs
	if analysis["has_error"]:
	stats["sessions_with_error"] += 1

	if analysis["has_retry"]:
	stats["sessions_with_retry"] += 1
	stats["total_retry_attempts"] += analysis["total_retries"]
	stats["max_retry_number"] = max(
	stats["max_retry_number"], analysis["max_retry_number"]
	)

	# Count error locations
	for error in analysis["errors"]:
	if error["node_type"] == "AGENT":
	stats["error_by_agent"][error["node_name"]] += 1
	stats["error_by_node_type"][error["node_type"]] += 1

	# Extract short error type description
	error_msg = error["error_msg"]
	if error_msg:
	# Take first 100 characters as error type identifier
	error_type = (
	error_msg[:100]
	if len(error_msg) <= 100
	else error_msg[:100] + "..."
	)
	stats["error_types"][error_type] += 1

	# Save session details
	stats["session_details"].append(
	{
	"session": session_dir.name,
	"has_error": analysis["has_error"],
	"has_retry": analysis["has_retry"],
	"retry_count": analysis["total_retries"],
	"errors": analysis["errors"],
	"retries": analysis["retries"],
	}
	)

	# Calculate RETRY rate
	stats["retry_rate"] = (
	(stats["sessions_with_retry"] / stats["total_sessions"] * 100)
	if stats["total_sessions"] > 0
	else 0
	)
	stats["error_rate"] = (
	(stats["sessions_with_error"] / stats["total_sessions"] * 100)
	if stats["total_sessions"] > 0
	else 0
	)

	# Convert defaultdict to regular dict
	stats["error_by_agent"] = dict(stats["error_by_agent"])
	stats["error_by_node_type"] = dict(stats["error_by_node_type"])
	stats["error_types"] = dict(stats["error_types"])

	return stats


	def print_summary(all_stats):
	"""Print statistics summary"""
	print("\n" + "=" * 100)
	print(f"RETRY Pattern Analysis Summary - {PROJECT_NAME}")
	print("=" * 100 + "\n")

	# Overall statistics table
	print("## Model Statistics\n")
	print(
	f"{'Model':<35} {'Total Sessions':<15} {'Error Rate':<12} {'RETRY Rate':<12} {'Total RETRYs':<13} {'Max RETRY':<10}"
	)
	print("-" * 100)

	for stats in all_stats:
	if stats:
	print(
	f"{stats['model']:<35} {stats['total_sessions']:<15} "
	f"{stats['error_rate']:>10.1f}% {stats['retry_rate']:>10.1f}% "
	f"{stats['total_retry_attempts']:<13} {stats['max_retry_number']:<10}"
	)

	print("\n" + "=" * 100)

	# Detailed information for each model
	for stats in all_stats:
	if not stats or stats["sessions_with_error"] == 0:
	continue

	print(f"\n### {stats['model']}\n")
	print(f"- Total Sessions: {stats['total_sessions']}")
	print(
	f"- Sessions with Errors: {stats['sessions_with_error']} ({stats['error_rate']:.1f}%)"
	)
	print(
	f"- Sessions with RETRY: {stats['sessions_with_retry']} ({stats['retry_rate']:.1f}%)"
	)
	print(f"- Total RETRY Attempts: {stats['total_retry_attempts']}")
	print(f"- Max RETRY Number: {stats['max_retry_number']}")

	if stats["error_by_agent"]:
	print(f"\nErrors by AGENT:")
	for agent, count in sorted(
	stats["error_by_agent"].items(), key=lambda x: x[1], reverse=True
	):
	print(f" - {agent}: {count} times")

	if stats["error_by_node_type"]:
	print(f"\nErrors by Node Type:")
	for node_type, count in sorted(
	stats["error_by_node_type"].items(), key=lambda x: x[1], reverse=True
	):
	print(f" - {node_type}: {count} times")

	if stats["error_types"]:
	print(f"\nError Types (Top 5):")
	for error_type, count in sorted(
	stats["error_types"].items(), key=lambda x: x[1], reverse=True
	)[:5]:
	print(f" - [{count}x] {error_type}")

	print("\n" + "-" * 100)


	def save_results(all_stats):
	"""Save results to files"""
	output_dir = Path(__file__).parent

	# Save detailed JSON
	json_file = output_dir / "retry_analysis.json"
	json_data = []
	for stats in all_stats:
	if stats:
	json_data.append(stats)

	with open(json_file, "w", encoding="utf-8") as f:
	json.dump(json_data, f, indent=2, ensure_ascii=False)
	print(f"\nJSON results saved: {json_file}")

	# Save CSV summary
	csv_file = output_dir / "retry_summary.csv"
	with open(csv_file, "w", newline="", encoding="utf-8") as f:
	writer = csv.writer(f)
	writer.writerow(
	[
	"Model",
	"Total_Sessions",
	"Sessions_With_Error",
	"Error_Rate(%)",
	"Sessions_With_Retry",
	"Retry_Rate(%)",
	"Total_Retry_Attempts",
	"Max_Retry_Number",
	]
	)

	for stats in all_stats:
	if stats:
	writer.writerow(
	[
	stats["model"],
	stats["total_sessions"],
	stats["sessions_with_error"],
	f"{stats['error_rate']:.2f}",
	stats["sessions_with_retry"],
	f"{stats['retry_rate']:.2f}",
	stats["total_retry_attempts"],
	stats["max_retry_number"],
	]
	)

	print(f"CSV summary saved: {csv_file}")

	# Save error location statistics
	error_csv_file = output_dir / "error_by_agent.csv"
	with open(error_csv_file, "w", newline="", encoding="utf-8") as f:
	writer = csv.writer(f)
	writer.writerow(["Model", "Agent_Name", "Error_Count"])

	for stats in all_stats:
	if stats and stats["error_by_agent"]:
	for agent, count in sorted(
	stats["error_by_agent"].items(), key=lambda x: x[1], reverse=True
	):
	writer.writerow([stats["model"], agent, count])

	print(f"Error location statistics saved: {error_csv_file}")


	if __name__ == "__main__":
	print(f"Starting RETRY pattern analysis - {PROJECT_NAME}...")

	all_stats = []
	for model in MODELS:
	print(f"\nAnalyzing model: {model}")
	stats = collect_model_stats(model)
	if stats:
	all_stats.append(stats)
	print(
	f" Completed: {stats['total_sessions']} sessions, "
	f"{stats['sessions_with_error']} errors, "
	f"{stats['sessions_with_retry']} retries"
	)
	else:
	print(f" Skipped (directory not found)")

	print_summary(all_stats)
	save_results(all_stats)

	print("\n" + "=" * 100)
	print("Analysis completed!")
	print("=" * 100)