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 19s
Avg Duration
22s - 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 37s 125.1
100.0% openrouter/google/gemini-3-pro-preview 1m 3s 51.6
100.0% openrouter/anthropic/claude-opus-4.5 34s 46.9
100.0% openrouter/openai/gpt-oss-120b 34s 92.7
100.0% openrouter/x-ai/grok-3-mini 56s 237.6
100.0% openrouter/google/gemini-2.5-pro 1m 20s 125.2
100.0% openrouter/openai/gpt-4o-mini 48s 116.6
100.0% openrouter/deepseek/deepseek-v3.1-terminus 1m 16s 143.6
100.0% openrouter/anthropic/claude-sonnet-4.5 53s 59.4
100.0% openrouter/x-ai/grok-code-fast-1 31s 38.8
83.3% openrouter/qwen/qwen3-coder 35s 68.0
83.3% openrouter/anthropic/claude-haiku-4.5 39s 86.0
66.7% litellm/GLM-4.5-Air-FP8-dev 36s 96.1
16.7% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 28s 70.4
0.0% openrouter/openai/gpt-oss-20b 22s 32.3
0.0% openrouter/deepseek/deepseek-chat-v3-0324 10m 0s 0.0