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 16s
Avg Duration
25s - 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 27s 87.1
100.0% openrouter/google/gemini-3-pro-preview 1m 1s 61.5
100.0% openrouter/anthropic/claude-opus-4.5 30s 45.7
100.0% openrouter/openai/gpt-oss-120b 35s 123.0
100.0% openrouter/qwen/qwen3-coder 42s 162.5
100.0% openrouter/x-ai/grok-3-mini 1m 4s 358.4
100.0% openrouter/openai/gpt-oss-20b 1m 3s 155.1
100.0% openrouter/anthropic/claude-haiku-4.5 25s 47.8
100.0% openrouter/deepseek/deepseek-v3.1-terminus 52s 100.1
100.0% litellm/GLM-4.5-Air-FP8-dev 33s 82.3
100.0% openrouter/anthropic/claude-sonnet-4.5 33s 46.7
100.0% openrouter/x-ai/grok-code-fast-1 27s 41.6
83.3% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 35s 208.8
66.7% openrouter/openai/gpt-4o-mini 34s 98.9
50.0% openrouter/google/gemini-2.5-pro 1m 0s 66.2
0.0% openrouter/deepseek/deepseek-chat-v3-0324 10m 0s 0.0