Verison 0.3

app.py

@@ -55,6 +55,76 @@ MODELS = {
             "skipped": [],
             "error": ["system_crash"]
         }
+    },
+    "claude": {
+        "amd": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter", "load_balance", "circuit_break"],
+            "failed": ["gpu_accel", "cuda_ops", "ml_inference", "distributed", "multi_gpu", "opencl_init", "driver_conflict"],
+            "skipped": ["tensor_ops", "perf_test", "stress_test", "load_test", "endurance", "benchmark"],
+            "error": ["memory_bandwidth"]
+        },
+        "nvidia": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter", "load_balance", "circuit_break", "gpu_accel", "cuda_ops", "ml_inference", "tensor_ops"],
+            "failed": ["distributed", "multi_gpu", "cuda_version", "nvcc_compile"],
+            "skipped": ["perf_test", "stress_test", "load_test", "endurance"],
+            "error": []
+        }
+    },
+    "mistral": {
+        "amd": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring"],
+            "failed": ["gpu_accel", "cuda_ops", "ml_inference", "tensor_ops", "distributed", "multi_gpu", "opencl_init", "driver_conflict", "memory_bandwidth", "compute_units", "rocm_version", "hip_compile", "kernel_launch"],
+            "skipped": ["security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter", "load_balance", "circuit_break"],
+            "error": ["buffer_transfer", "atomic_ops"]
+        },
+        "nvidia": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "gpu_accel", "cuda_ops", "ml_inference", "tensor_ops", "security_scan"],
+            "failed": ["distributed", "multi_gpu", "cuda_version", "nvcc_compile", "stream_sync", "device_reset"],
+            "skipped": ["password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter"],
+            "error": ["peer_access"]
+        }
+    },
+    "phi": {
+        "amd": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection"],
+            "failed": ["gpu_accel", "cuda_ops", "ml_inference", "tensor_ops", "distributed", "multi_gpu", "opencl_init", "driver_conflict", "memory_bandwidth"],
+            "skipped": ["rate_limiter", "load_balance", "circuit_break", "retry_logic", "timeout_handle", "graceful_shutdown"],
+            "error": []
+        },
+        "nvidia": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "gpu_accel", "cuda_ops", "ml_inference", "tensor_ops", "rate_limiter"],
+            "failed": ["distributed", "multi_gpu", "cuda_version"],
+            "skipped": ["load_balance", "circuit_break", "retry_logic", "timeout_handle"],
+            "error": []
+        }
+    },
+    "qwen": {
+        "amd": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety"],
+            "failed": ["backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter", "load_balance", "circuit_break", "gpu_accel", "cuda_ops", "ml_inference", "tensor_ops", "distributed", "multi_gpu"],
+            "skipped": ["retry_logic", "timeout_handle", "graceful_shutdown", "hot_reload", "config_watch"],
+            "error": ["env_vars", "secrets_mgmt", "tls_cert"]
+        },
+        "nvidia": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "gpu_accel", "cuda_ops", "ml_inference", "tensor_ops"],
+            "failed": ["log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter", "load_balance", "circuit_break", "distributed", "multi_gpu", "cuda_version", "nvcc_compile"],
+            "skipped": ["retry_logic", "timeout_handle", "graceful_shutdown", "hot_reload"],
+            "error": ["config_watch", "env_vars"]
+        }
+    },
+    "deepseek": {
+        "amd": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter", "load_balance", "circuit_break", "retry_logic", "timeout_handle", "graceful_shutdown", "hot_reload", "config_watch", "env_vars", "secrets_mgmt", "tls_cert", "encryption", "compression"],
+            "failed": ["gpu_accel", "cuda_ops", "ml_inference", "tensor_ops", "opencl_init", "driver_conflict", "memory_bandwidth", "compute_units"],
+            "skipped": ["distributed", "multi_gpu", "serialization", "deserialization", "validation"],
+            "error": []
+        },
+        "nvidia": {
+            "passed": ["auth_login", "data_validation", "api_response", "file_upload", "cache_hit", "user_permissions", "db_query", "session_mgmt", "input_sanitize", "rate_limit", "error_handling", "memory_alloc", "thread_safety", "backup_restore", "config_load", "log_rotation", "health_check", "metrics", "alerts", "monitoring", "security_scan", "password_hash", "jwt_token", "oauth_flow", "csrf_protect", "xss_filter", "sql_injection", "rate_limiter", "load_balance", "circuit_break", "retry_logic", "timeout_handle", "graceful_shutdown", "hot_reload", "config_watch", "env_vars", "secrets_mgmt", "tls_cert", "encryption", "compression", "gpu_accel", "cuda_ops", "ml_inference", "tensor_ops"],
+            "failed": ["distributed", "multi_gpu"],
+            "skipped": ["serialization", "deserialization", "validation"],
+            "error": []
+        }
     }
 }
 
@@ -225,7 +295,7 @@ def get_model_stats_summary(model_name: str) -> tuple:
 
 def create_summary_page() -> plt.Figure:
     """Create a summary page with model names and both AMD/NVIDIA test stats bars."""
-    fig, ax = plt.subplots(figsize=(12, len(MODELS) * 4 + 1), facecolor='#000000')
+    fig, ax = plt.subplots(figsize=(16, len(MODELS) * 2.5 + 2), facecolor='#000000')
     ax.set_facecolor('#000000')
     
     colors = {
@@ -235,6 +305,8 @@ def create_summary_page() -> plt.Figure:
         'error': '#8B0000'
     }
     
+    visible_model_count = 0
+    max_y = 0
     for i, (model_name, model_data) in enumerate(MODELS.items()):
         # Process AMD and NVIDIA data
         amd_stats = {k: len(v) for k, v in model_data['amd'].items()}
@@ -245,11 +317,12 @@ def create_summary_page() -> plt.Figure:
         if amd_total == 0 and nvidia_total == 0:
             continue
             
-        # Position for this model - tighter spacing between groups
-        y_base = i * 2
+        # Position for this model - use visible model count for spacing
+        y_base = (2.2 + visible_model_count) * 1.8
         y_model_name = y_base    # Model name above AMD bar
         y_amd_bar = y_base + 0.45       # AMD bar
         y_nvidia_bar = y_base + 0.97    # NVIDIA bar
+        max_y = max(max_y, y_nvidia_bar + 0.5)
         
         # Model name centered above the AMD bar
         left_0 = 8
@@ -260,7 +333,7 @@ def create_summary_page() -> plt.Figure:
         
         # AMD label and bar on the same level
         if amd_total > 0:
-            ax.text(left_0 - 2, y_amd_bar, "AMD", 
+            ax.text(left_0 - 2, y_amd_bar, "amd", 
                    ha='right', va='center', color='#CCCCCC', 
                    fontsize=18, fontfamily='monospace', fontweight='normal')
             
@@ -269,7 +342,7 @@ def create_summary_page() -> plt.Figure:
             for category in ['passed', 'failed', 'skipped', 'error']:
                 if amd_stats[category] > 0:
                     width = amd_stats[category] / amd_total * bar_length
-                    ax.barh(y_amd_bar, width, left=left, height=0.45, 
+                    ax.barh(y_amd_bar, width, left=left, height=0.405, 
                            color=colors[category], alpha=0.9)
                     if width > 4:
                         ax.text(left + width/2, y_amd_bar, str(amd_stats[category]), 
@@ -279,7 +352,7 @@ def create_summary_page() -> plt.Figure:
         
         # NVIDIA label and bar on the same level
         if nvidia_total > 0:
-            ax.text(left_0 - 2, y_nvidia_bar, "NVIDIA", 
+            ax.text(left_0 - 2, y_nvidia_bar, "nvidia", 
                    ha='right', va='center', color='#CCCCCC', 
                    fontsize=18, fontfamily='monospace', fontweight='normal')
             
@@ -288,17 +361,20 @@ def create_summary_page() -> plt.Figure:
             for category in ['passed', 'failed', 'skipped', 'error']:
                 if nvidia_stats[category] > 0:
                     width = nvidia_stats[category] / nvidia_total * bar_length
-                    ax.barh(y_nvidia_bar, width, left=left, height=0.45, 
+                    ax.barh(y_nvidia_bar, width, left=left, height=0.405, 
                            color=colors[category], alpha=0.9)
                     if width > 4:
                         ax.text(left + width/2, y_nvidia_bar, str(nvidia_stats[category]), 
                                ha='center', va='center', color='black', 
                                fontweight='bold', fontsize=12, fontfamily='monospace')
                     left += width
+        
+        # Increment counter for next visible model
+        visible_model_count += 1
     
     # Style the axes to be completely invisible and span full width
     ax.set_xlim(0, 100)
-    ax.set_ylim(-1, len(MODELS) * 3.2)
+    ax.set_ylim(-0.5, max_y)
     ax.set_xlabel('')
     ax.set_ylabel('')
     ax.spines['bottom'].set_visible(False)
@@ -431,8 +507,46 @@ dark_theme_css = """
 .success-medium { background-color: #FF9800 !important; }
 .success-low { background-color: #F44336 !important; }
 
+/* Summary button styling - distinct from model buttons */
+.summary-button {
+    background: linear-gradient(135deg, #4a4a4a, #3e3e3e) !important;
+    color: white !important;
+    border: 2px solid #555555 !important;
+    margin: 2px 0 15px 0 !important;
+    border-radius: 5px !important;
+    padding: 12px 12px !important;
+    transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1) !important;
+    position: relative !important;
+    overflow: hidden !important;
+    box-shadow: 
+        0 4px 15px rgba(0, 0, 0, 0.3),
+        inset 0 1px 0 rgba(255, 255, 255, 0.2) !important;
+    font-weight: 600 !important;
+    font-size: 16px !important;
+    text-transform: uppercase !important;
+    letter-spacing: 0.5px !important;
+    font-family: monospace !important;
+    height: 60px !important;
+    display: flex !important;
+    flex-direction: column !important;
+    justify-content: center !important;
+    align-items: center !important;
+    line-height: 1.2 !important;
+}
+
+.summary-button:hover {
+    background: linear-gradient(135deg, #5a5a5a, #4e4e4e) !important;
+    color: #74b9ff !important;
+    border-color: #666666 !important;
+}
+
+.summary-button:active {
+    background: linear-gradient(135deg, #4a4a4a, #3e3e3e) !important;
+    color: #5a9bd4 !important;
+}
+
 /* Regular button styling for non-model buttons */
-.gr-button:not(.model-button) {
+.gr-button:not(.model-button):not(.summary-button) {
     background-color: #222222 !important;
     color: white !important;
     border: 1px solid #444444 !important;
@@ -441,7 +555,7 @@ dark_theme_css = """
     transition: all 0.3s ease !important;
 }
 
-.gr-button:not(.model-button):hover {
+.gr-button:not(.model-button):not(.summary-button):hover {
     background-color: #333333 !important;
     border-color: #666666 !important;
 }
@@ -740,15 +854,15 @@ with gr.Blocks(title="Model Test Results Dashboard", css=dark_theme_css) as demo
     with gr.Row():
         # Sidebar for model selection
         with gr.Column(scale=1, elem_classes=["sidebar"]):
-            gr.Markdown("# 🤖 AI Models")
-            gr.Markdown("**Select a model to analyze test results**\n\n*Interactive dashboard with detailed metrics*")
+            gr.Markdown("# 🤖 TCID")
+            gr.Markdown("**Transformer CI Dashboard**\n\n*Analyze transformers CI results across AMD and NVIDIA devices*\n")
             
             # Summary button at the top
             summary_button = gr.Button(
-                "summary", 
+                "summary\n📊", 
                 variant="primary",
                 size="lg",
-                elem_classes=["model-button"]
+                elem_classes=["summary-button"]
             )
             
             # Model selection buttons in sidebar
@@ -775,7 +889,6 @@ with gr.Blocks(title="Model Test Results Dashboard", css=dark_theme_css) as demo
             
             # Detailed view components (hidden by default)
             with gr.Column(visible=False, elem_classes=["detail-view"]) as detail_view:
-                gr.Markdown("# 📈 Test Results Dashboard")
                 
                 # Create the plot output
                 plot_output = gr.Plot(