upd vendor colors and add platform info

Author: bogdanminko

README.md

@@ -30,7 +30,7 @@
 ---
 
 ## Overview
-**NoBS (Neural NetwOrks Benchmark Stash)** is an open-source benchmark suite
+**NoBS** is an open-source benchmark suite
 for evaluating *real AI hardware performance* — not synthetic FLOPS or polished demos.
 
 It's a collection of reproducible tests and community-submitted results for:
@@ -55,29 +55,29 @@ NoBS was built to understand how different devices — from everyday laptops and
 
 ### 🏆 Overall Ranking
 
-| Rank | Device | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |
-|------|--------|-----|-----|-----|------|------------|-----|-------------|
-| 🥇 1 | Mac16,6 | Apple M4 Max (14) | 36 GB | Apple M4 Max (32 cores) | shared with system RAM | 637.17 | 157.84 | **795.01** |
-| 🥈 2 | ASUSTeK COMPUTER INC. ASUS Vivobook Pro 15 N6506MV_N6506MV 1.0 | Intel(R) Core(TM) Ultra 9 185H (16) | 23 GB | NVIDIA GeForce RTX 4060 Laptop GPU | 8 GB | 539.73 | 26.42 | **566.15** |
+| Rank | Device | Platform | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |
+|------|--------|----------|-----|-----|-----|------|------------|-----|-------------|
+| 🥇 1 | Mac16,6 | 🍏 macOS | Apple M4 Max (14) | 36 GB | Apple M4 Max (32 cores) | shared with system RAM | 637.17 | 157.84 | **795.01** |
+| 🥈 2 | ASUSTeK COMPUTER INC. ASUS Vivobook Pro 15 N6506MV_N6506MV 1.0 | 🐧 Linux | Intel(R) Core(TM) Ultra 9 185H (16) | 23 GB | NVIDIA GeForce RTX 4060 Laptop GPU | 8 GB | 539.73 | 26.42 | **566.15** |
 
 
 ### 📊 By GPU Vendor
 
 <details open>
-<summary><b>🍎 Apple</b> (1 device)</summary>
+<summary><b>⚫ Apple</b> (1 device)</summary>
 
-| Rank | Device | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |
-|------|--------|-----|-----|-----|------|------------|-----|-------------|
-| 🥇 1 | Mac16,6 | Apple M4 Max (14) | 36 GB | Apple M4 Max (32 cores) | shared with system RAM | 637.17 | 157.84 | **795.01** |
+| Rank | Device | Platform | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |
+|------|--------|----------|-----|-----|-----|------|------------|-----|-------------|
+| 🥇 1 | Mac16,6 | 🍏 macOS | Apple M4 Max (14) | 36 GB | Apple M4 Max (32 cores) | shared with system RAM | 637.17 | 157.84 | **795.01** |
 
 </details>
 
 <details open>
 <summary><b>🟢 NVIDIA</b> (1 device)</summary>
 
-| Rank | Device | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |
-|------|--------|-----|-----|-----|------|------------|-----|-------------|
-| 🥇 1 | ASUSTeK COMPUTER INC. ASUS Vivobook Pro 15 N6506MV_N6506MV 1.0 | Intel(R) Core(TM) Ultra 9 185H (16) | 23 GB | NVIDIA GeForce RTX 4060 Laptop GPU | 8 GB | 539.73 | 26.42 | **566.15** |
+| Rank | Device | Platform | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |
+|------|--------|----------|-----|-----|-----|------|------------|-----|-------------|
+| 🥇 1 | ASUSTeK COMPUTER INC. ASUS Vivobook Pro 15 N6506MV_N6506MV 1.0 | 🐧 Linux | Intel(R) Core(TM) Ultra 9 185H (16) | 23 GB | NVIDIA GeForce RTX 4060 Laptop GPU | 8 GB | 539.73 | 26.42 | **566.15** |
 
 </details>
 
@@ -203,10 +203,21 @@ We welcome contributions! Whether it's adding new benchmarks, supporting new mod
    # Run benchmarks to ensure they work
    uv run python main.py
 
+   # Update benchmark results tables (if you modified results)
+   make
+
    # Run code quality checks manually (optional - pre-commit will run them automatically)
-   pre-commit run --all-files
+   make format
    ```
 
+   **Available Makefile commands:**
+   - `make` — Generate benchmark results tables (default)
+   - `make generate` — Generate benchmark results tables
+   - `make format` — Run pre-commit hooks on all files
+   - `make lint` — Run ruff linter only
+   - `make clean` — Clean Python cache files
+   - `make help` — Show all available commands
+
 4. **Commit your changes**
    ```sh
    git add .

src/generate_results_table.py

@@ -52,8 +52,8 @@ def generate_summary_table(results: list[dict[str, Any]]) -> str:
     scored_results.sort(key=lambda x: x["total_score"], reverse=True)
 
     lines = [
-        "| Rank | Device | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |",
-        "|------|--------|-----|-----|-----|------|------------|-----|-------------|",
+        "| Rank | Device | Platform | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |",
+        "|------|--------|----------|-----|-----|-----|------|------------|-----|-------------|",
     ]
 
     for rank, item in enumerate(scored_results, 1):
@@ -72,13 +72,23 @@ def generate_summary_table(results: list[dict[str, Any]]) -> str:
         else:
             vram_str = str(gpu_mem)
 
+        # Format platform with emoji
+        platform = device_info.get("platform", "Unknown")
+        platform_emoji_map = {
+            "Darwin": "🍏 macOS",
+            "Linux": "🐧 Linux",
+            "Windows": "🪟 Windows",
+        }
+        platform_str = platform_emoji_map.get(platform, platform)
+
         # Add medal emoji for top 3
         rank_emoji = {1: "🥇", 2: "🥈", 3: "🥉"}.get(rank, "")
         rank_str = f"{rank_emoji} {rank}" if rank_emoji else str(rank)
 
         lines.append(
-            f"| {rank_str} | {device_info['host']} | {device_info['processor']} | "
-            f"{device_info['ram_gb']:.0f} GB | {device_info['gpu_name']} | {vram_str} | "
+            f"| {rank_str} | {device_info['host']} | {platform_str} | "
+            f"{device_info['processor']} | {device_info['ram_gb']:.0f} GB | "
+            f"{device_info['gpu_name']} | {vram_str} | "
             f"{emb_str} | {llm_str} | **{total_str}** |"
         )
 
@@ -241,7 +251,7 @@ def generate_gpu_grouped_tables(results: list[dict[str, Any]]) -> str:
 
     # Vendor emojis
     vendor_emojis = {
-        "Apple": "🍎",
+        "Apple": "⚫",
         "NVIDIA": "🟢",
         "AMD": "🔴",
         "Intel": "🔵",
@@ -266,10 +276,10 @@ def generate_gpu_grouped_tables(results: list[dict[str, Any]]) -> str:
 
         # Table header
         sections.append(
-            "| Rank | Device | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |"
+            "| Rank | Device | Platform | CPU | RAM | GPU | VRAM | Embeddings | LLM | Total Score |"
         )
         sections.append(
-            "|------|--------|-----|-----|-----|------|------------|-----|-------------|"
+            "|------|--------|----------|-----|-----|-----|------|------------|-----|-------------|"
         )
 
         # Table rows
@@ -291,13 +301,23 @@ def generate_gpu_grouped_tables(results: list[dict[str, Any]]) -> str:
             else:
                 vram_str = str(gpu_mem)
 
+            # Format platform with emoji
+            platform = device_info.get("platform", "Unknown")
+            platform_emoji_map = {
+                "Darwin": "🍏 macOS",
+                "Linux": "🐧 Linux",
+                "Windows": "🪟 Windows",
+            }
+            platform_str = platform_emoji_map.get(platform, platform)
+
             # Add medal emoji for top 3 within vendor
             rank_emoji = {1: "🥇", 2: "🥈", 3: "🥉"}.get(rank, "")
             rank_str = f"{rank_emoji} {rank}" if rank_emoji else str(rank)
 
             sections.append(
-                f"| {rank_str} | {device_info['host']} | {device_info['processor']} | "
-                f"{device_info['ram_gb']:.0f} GB | {device_info['gpu_name']} | {vram_str} | "
+                f"| {rank_str} | {device_info['host']} | {platform_str} | "
+                f"{device_info['processor']} | {device_info['ram_gb']:.0f} GB | "
+                f"{device_info['gpu_name']} | {vram_str} | "
                 f"{emb_str} | {llm_str} | **{total_str}** |"
             )