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
75.0%
Success Rate
1m 52s
Avg Duration
21s - 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-2.5-flash-preview-09-2025 21s 41.0
100.0% openrouter/google/gemini-3-pro-preview 1m 13s 68.6
100.0% openrouter/anthropic/claude-opus-4.5 27s 42.5
100.0% openrouter/openai/gpt-oss-120b 1m 3s 147.8
100.0% openrouter/x-ai/grok-3-mini 39s 224.0
100.0% openrouter/google/gemini-2.5-pro 2m 8s 116.1
100.0% openrouter/openai/gpt-oss-20b 7m 18s 2808.1
100.0% openrouter/anthropic/claude-haiku-4.5 26s 48.0
100.0% openrouter/deepseek/deepseek-v3.1-terminus 1m 5s 97.8
100.0% litellm/GLM-4.5-Air-FP8-dev 2m 41s 219.6
100.0% openrouter/anthropic/claude-sonnet-4.5 46s 60.5
100.0% openrouter/x-ai/grok-code-fast-1 28s 42.0
83.3% openrouter/qwen/qwen3-coder 33s 96.0
83.3% openrouter/openai/gpt-4o-mini 24s 54.5
0.0% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 21s 46.0
0.0% openrouter/deepseek/deepseek-chat-v3-0324 10m 0s 0.0