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

16
Models Tested
62.5%
Success Rate
1m 30s
Avg Duration
20s - 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 1m 22s 54.6
100.0% openrouter/anthropic/claude-opus-4.5 32s 42.5
100.0% openrouter/x-ai/grok-3-mini 1m 6s 44.7
100.0% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 39s 150.2
100.0% openrouter/openai/gpt-oss-20b 40s 224.4
100.0% openrouter/anthropic/claude-haiku-4.5 29s 44.7
100.0% openrouter/deepseek/deepseek-v3.1-terminus 1m 11s 134.0
100.0% litellm/GLM-4.5-Air-FP8-dev 2m 23s 101.7
100.0% openrouter/anthropic/claude-sonnet-4.5 38s 54.8
100.0% openrouter/x-ai/grok-code-fast-1 29s 35.8
83.3% openrouter/google/gemini-2.5-pro 59s 72.6
83.3% openrouter/openai/gpt-4o-mini 56s 57.1
16.7% openrouter/google/gemini-2.5-flash-preview-09-2025 29s 67.2
16.7% openrouter/qwen/qwen3-coder 2m 2s 213.5
0.0% openrouter/openai/gpt-oss-120b 20s 17.9
0.0% openrouter/deepseek/deepseek-chat-v3-0324 10m 0s 0.0