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
2m 21s
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 1m 39s 59.8
100.0% openrouter/anthropic/claude-opus-4.5 30s 43.8
100.0% openrouter/openai/gpt-oss-120b 29s 100.5
100.0% openrouter/x-ai/grok-3-mini 1m 13s 87.4
100.0% openrouter/google/gemini-2.5-pro 1m 16s 128.8
100.0% openrouter/openai/gpt-oss-20b 34s 198.8
100.0% openrouter/anthropic/claude-haiku-4.5 28s 44.1
100.0% openrouter/deepseek/deepseek-v3.1-terminus 35s 46.3
100.0% openrouter/anthropic/claude-sonnet-4.5 49s 57.5
100.0% openrouter/x-ai/grok-code-fast-1 43s 51.7
83.3% openrouter/google/gemini-2.5-flash-preview-09-2025 42s 161.8
83.3% litellm/GLM-4.5-Air-FP8-dev 2m 16s 97.5
66.7% openrouter/openai/gpt-4o-mini 32s 53.2
16.7% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 5m 52s 1732.8
0.0% openrouter/qwen/qwen3-coder 10m 0s 0.0
0.0% openrouter/deepseek/deepseek-chat-v3-0324 10m 0s 0.0