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
68.8%
Success Rate
1m 37s
Avg Duration
27s - 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 53s 37.7
100.0% openrouter/anthropic/claude-opus-4.5 35s 47.6
100.0% openrouter/openai/gpt-oss-120b 48s 119.5
100.0% openrouter/google/gemini-2.5-pro 1m 15s 96.7
100.0% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 1m 32s 131.0
100.0% openrouter/openai/gpt-oss-20b 44s 289.6
100.0% openrouter/anthropic/claude-haiku-4.5 43s 79.5
100.0% openrouter/deepseek/deepseek-v3.1-terminus 54s 95.9
100.0% litellm/GLM-4.5-Air-FP8-dev 4m 27s 127.2
100.0% openrouter/anthropic/claude-sonnet-4.5 54s 57.2
100.0% openrouter/x-ai/grok-code-fast-1 36s 50.4
83.3% openrouter/google/gemini-2.5-flash-preview-09-2025 27s 45.4
83.3% openrouter/qwen/qwen3-coder 29s 64.2
83.3% openrouter/x-ai/grok-3-mini 1m 1s 50.2
83.3% openrouter/openai/gpt-4o-mini 34s 71.7
0.0% openrouter/deepseek/deepseek-chat-v3-0324 10m 0s 0.0