Task task7_log_parser

You'll find a log file called `application.log` in the current directory. Parse this log file and extract the following information:

1. Count the total number of ERROR and WARNING level messages
2. Extract all unique IP addresses that appear in the logs
3. Find all timestamps where errors occurred
4. Identify the most common error message (if any patterns exist)

Generate a JSON file called `log_analysis.json` with the following structure:

```json
{
"total_errors": <number>,
"total_warnings": <number>,
"unique_ips": ["ip1", "ip2", ...],
"error_timestamps": ["timestamp1", "timestamp2", ...],
"most_common_error": "<error message or null>"
}
```

Make sure to handle different log formats gracefully and extract the relevant information accurately.

PS: You are currently working in an automated system and cannot ask any question or have back and forth with an user.

Results

15
Models Tested
66.7%
Success Rate
1m 34s
Avg Duration
28s - 10m 0s
Duration Range

Details

Score Model Duration Session (KB) test_1_file_exists.sh test_2_valid_json.sh test_3_correct_counts.sh test_4_unique_ips.sh test_5_error_timestamps.sh test_6_most_common_error.sh
100.0% openrouter/google/gemini-3-pro-preview 2m 8s 99.1
100.0% openrouter/anthropic/claude-opus-4.5 33s 44.9
100.0% openrouter/openai/gpt-oss-120b 40s 165.2
100.0% openrouter/x-ai/grok-3-mini 55s 49.4
100.0% openrouter/google/gemini-2.5-pro 1m 15s 176.2
100.0% openrouter/openai/gpt-oss-20b 1m 13s 494.4
100.0% openrouter/anthropic/claude-haiku-4.5 29s 54.3
100.0% openrouter/deepseek/deepseek-v3.1-terminus 40s 99.6
100.0% openrouter/anthropic/claude-sonnet-4.5 48s 58.9
100.0% openrouter/x-ai/grok-code-fast-1 28s 39.7
83.3% openrouter/openai/gpt-4o-mini 41s 56.0
66.7% litellm/GLM-4.5-Air-FP8-dev 2m 44s 112.9
50.0% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 37s 176.2
16.7% openrouter/qwen/qwen3-coder 28s 41.1
0.0% openrouter/deepseek/deepseek-chat-v3-0324 10m 0s 0.0