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"""
Gradio Interface for MCP Server Orchestration Platform
Production-grade UI with dynamic form generation and real-time updates
"""
import asyncio
import json
import time
from typing import Dict, List, Any, Optional, Tuple
import traceback
import gradio as gr
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import structlog
from mcp_orchestrator import (
MCPOrchestrator, ServerConfig, ToolSchema, ToolInvocation,
SessionInfo, ConfigManager, CircuitBreakerState
)
class MCPUI:
"""Production-grade Gradio interface for MCP orchestration."""
def __init__(self, orchestrator: MCPOrchestrator):
self.orchestrator = orchestrator
self.logger = structlog.get_logger()
# UI state
self.current_session = None
self.available_tools = {}
self.server_status = {}
self.tool_results = {}
# Performance tracking
self.request_times = []
self.success_rates = {}
def create_interface(self) -> gr.Interface:
"""Create the main Gradio interface."""
with gr.Blocks(
title="MCP Server Orchestration Platform",
theme=gr.themes.Soft(),
css=self._get_custom_css(),
head=self._get_head_content()
) as interface:
# Header
self._create_header()
# Main content tabs
with gr.Tabs() as main_tabs:
# Tool Invocation Tab
with gr.Tab("π οΈ Tool Invocation", id="tool_invocation"):
self._create_tool_invocation_tab()
# Server Management Tab
with gr.Tab("π§ Server Management", id="server_management"):
self._create_server_management_tab()
# Analytics Dashboard Tab
with gr.Tab("π Analytics Dashboard", id="analytics"):
self._create_analytics_tab()
# Configuration Tab
with gr.Tab("βοΈ Configuration", id="configuration"):
self._create_configuration_tab()
# Initialize server status and tools
interface.load(
fn=self._load_initial_data,
inputs=[],
outputs=[
self.server_status_display,
self.available_servers_dropdown,
self.tools_display,
self.metrics_memory_plot,
self.metrics_cpu_plot,
self.metrics_throughput_plot,
self.cache_hit_rate_plot
],
show_progress="full"
)
return interface
def _get_custom_css(self) -> str:
"""Get custom CSS for enhanced UI."""
return """
.gradio-container {
max-width: 1400px !important;
margin: auto !important;
}
.mcp-header {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
padding: 20px;
border-radius: 15px;
color: white;
text-align: center;
margin-bottom: 20px;
}
.server-card {
border: 2px solid #e1e5e9;
border-radius: 12px;
padding: 15px;
margin: 10px 0;
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
transition: all 0.3s ease;
}
.server-card:hover {
border-color: #4f46e5;
transform: translateY(-2px);
box-shadow: 0 8px 25px rgba(79, 70, 229, 0.15);
}
.status-indicator {
display: inline-block;
width: 12px;
height: 12px;
border-radius: 50%;
margin-right: 8px;
}
.status-connected { background-color: #10b981; }
.status-disconnected { background-color: #ef4444; }
.status-warning { background-color: #f59e0b; }
.status-maintenance { background-color: #6366f1; }
.tool-form {
background: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 12px;
padding: 20px;
margin: 15px 0;
}
.metric-card {
background: white;
border: 1px solid #e2e8f0;
border-radius: 10px;
padding: 15px;
text-align: center;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.streaming-output {
background: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 8px;
padding: 15px;
margin: 10px 0;
}
.error-message {
background: #fef2f2;
border: 1px solid #fecaca;
color: #dc2626;
border-radius: 8px;
padding: 15px;
margin: 10px 0;
}
.success-message {
background: #f0fdf4;
border: 1px solid #bbf7d0;
color: #16a34a;
border-radius: 8px;
padding: 15px;
margin: 10px 0;
}
.progress-indicator {
height: 6px;
background: #e2e8f0;
border-radius: 3px;
overflow: hidden;
margin: 10px 0;
}
.progress-bar {
height: 100%;
background: linear-gradient(90deg, #3b82f6, #1d4ed8);
border-radius: 3px;
transition: width 0.3s ease;
}
"""
def _get_head_content(self) -> str:
"""Get HTML head content."""
return """
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="MCP Server Orchestration Platform - Manage and invoke tools from multiple Model Context Protocol servers">
<meta name="keywords" content="MCP, Model Context Protocol, server orchestration, tool management">
<link rel="icon" href="data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>π οΈ</text></svg>">
<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
"""
def _create_header(self):
"""Create the main header."""
gr.HTML("""
<div class="mcp-header">
<h1 style="margin: 0; font-size: 2.5em; font-weight: 700;">π οΈ MCP Server Orchestration Platform</h1>
<p style="margin: 10px 0 0 0; font-size: 1.2em; opacity: 0.9;">
Discover, configure, and invoke tools from multiple Model Context Protocol servers
</p>
<div style="margin-top: 15px; font-size: 0.9em;">
<span style="margin-right: 20px;">β‘ Production-Grade Architecture</span>
<span style="margin-right: 20px;">π Enterprise Security</span>
<span>π Real-Time Analytics</span>
</div>
</div>
""")
def _create_tool_invocation_tab(self):
"""Create the tool invocation interface."""
with gr.Row():
# Left column: Tool selection and form
with gr.Column(scale=1):
gr.HTML("<h3>π― Tool Selection</h3>")
# Session management
with gr.Group():
session_btn = gr.Button("π Create Session", variant="primary")
self.session_display = gr.JSON(
label="Current Session",
info="Your active session information"
)
# Server selection
self.available_servers_dropdown = gr.Dropdown(
label="Select MCP Server",
choices=[],
info="Choose a server to browse available tools"
)
# Tool search
self.tool_search = gr.Textbox(
label="π Search Tools",
placeholder="Search tools by name or description...",
info="Find tools across all registered servers"
)
# Tool results
self.available_tools_display = gr.JSON(
label="Available Tools",
info="Tools available on the selected server"
)
# Refresh button
refresh_btn = gr.Button("π Refresh Tools", variant="secondary")
# Right column: Tool invocation form and results
with gr.Column(scale=1):
gr.HTML("<h3>π οΈ Tool Invocation</h3>")
# Dynamic tool form
self.tool_form = gr.JSON(
label="Tool Parameters",
info="Generated form based on tool schema"
)
# Selected tool info
self.selected_tool_info = gr.JSON(
label="Selected Tool Information",
info="Tool description and parameters"
)
# Execute button
execute_btn = gr.Button("π Execute Tool", variant="primary")
# Results
with gr.Accordion("π Execution Results", open=False):
self.execution_results = gr.JSON(
label="Tool Execution Results",
info="Complete execution results and metadata"
)
self.result_summary = gr.Markdown(
label="Results Summary",
value="No results yet"
)
# Streaming output
self.streaming_output = gr.HTML(
label="Real-time Progress",
value="<div class='streaming-output'>No active execution</div>"
)
# Event handlers
session_btn.click(
fn=self._create_session,
inputs=[],
outputs=[self.session_display, self.available_servers_dropdown]
)
refresh_btn.click(
fn=self._refresh_tools,
inputs=[self.available_servers_dropdown, self.tool_search],
outputs=[self.available_tools_display]
)
self.available_servers_dropdown.change(
fn=self._on_server_change,
inputs=[self.available_servers_dropdown],
outputs=[self.available_tools_display, self.tool_form]
)
execute_btn.click(
fn=self._execute_tool_streaming,
inputs=[self.available_servers_dropdown, self.tool_search, self.tool_form],
outputs=[self.execution_results, self.result_summary, self.streaming_output],
show_progress="full"
)
self.tool_search.input(
fn=self._search_tools,
inputs=[self.available_servers_dropdown, self.tool_search],
outputs=[self.available_tools_display]
)
def _create_server_management_tab(self):
"""Create the server management interface."""
with gr.Row():
with gr.Column():
gr.HTML("<h3>π§ Server Management</h3>")
# Server status dashboard
self.server_status_display = gr.JSON(
label="Server Status Dashboard",
info="Real-time status of all registered servers"
)
# Refresh status
refresh_status_btn = gr.Button("π Refresh Status", variant="secondary")
# Add server form
with gr.Accordion("β Add New Server", open=False):
server_id = gr.Textbox(
label="Server ID",
placeholder="unique-server-id"
)
server_name = gr.Textbox(
label="Server Name",
placeholder="Human readable name"
)
server_url = gr.Textbox(
label="Server URL",
placeholder="https://server.example.com"
)
auth_token = gr.Textbox(
label="Authentication Token",
placeholder="Bearer token (optional)"
)
server_timeout = gr.Slider(
minimum=5,
maximum=120,
value=30,
step=5,
label="Timeout (seconds)"
)
add_server_btn = gr.Button("β Add Server", variant="primary")
with gr.Column():
gr.HTML("<h3>π Server Analytics</h3>")
# Performance plots
self.server_performance_plot = gr.Plot(
label="Server Performance",
info="Response times and success rates by server"
)
# Connection status
self.connection_status_plot = gr.Plot(
label="Connection Status",
info="Active connections and circuit breaker states"
)
# Server metrics table
self.server_metrics_table = gr.DataFrame(
label="Server Metrics",
headers=["Server", "Status", "Connections", "Tools", "Success Rate", "Avg Response Time"],
info="Detailed metrics for each server"
)
# Event handlers
refresh_status_btn.click(
fn=self._refresh_server_status,
inputs=[],
outputs=[self.server_status_display, self.server_performance_plot, self.connection_status_plot, self.server_metrics_table]
)
add_server_btn.click(
fn=self._add_server,
inputs=[server_id, server_name, server_url, auth_token, server_timeout],
outputs=[self.server_status_display, self.available_servers_dropdown]
)
def _create_analytics_tab(self):
"""Create the analytics dashboard."""
with gr.Row():
with gr.Column():
gr.HTML("<h3>π Performance Analytics</h3>")
# Key metrics
with gr.Row():
self.total_requests_metric = gr.Markdown(
value="π **Total Requests**: 0"
)
self.success_rate_metric = gr.Markdown(
value="β
**Success Rate**: 0%"
)
self.active_sessions_metric = gr.Markdown(
value="π₯ **Active Sessions**: 0"
)
# Performance plots
self.metrics_memory_plot = gr.Plot(
label="Memory Usage Over Time",
info="System memory usage patterns"
)
self.metrics_cpu_plot = gr.Plot(
label="CPU Usage Over Time",
info="System CPU utilization"
)
with gr.Column():
gr.HTML("<h3>π Tool Analytics</h3>")
self.metrics_throughput_plot = gr.Plot(
label="Request Throughput",
info="Requests per minute over time"
)
self.cache_hit_rate_plot = gr.Plot(
label="Cache Performance",
info="Cache hit/miss rates"
)
# Tool usage table
self.tool_usage_table = gr.DataFrame(
label="Tool Usage Statistics",
headers=["Tool", "Server", "Invocations", "Success Rate", "Avg Time", "Errors"],
info="Most frequently used tools"
)
# Auto-refresh analytics
gr.Timer(value=30).tick(
fn=self._update_analytics,
inputs=[],
outputs=[
self.total_requests_metric,
self.success_rate_metric,
self.active_sessions_metric,
self.metrics_memory_plot,
self.metrics_cpu_plot,
self.metrics_throughput_plot,
self.cache_hit_rate_plot,
self.tool_usage_table
]
)
def _create_configuration_tab(self):
"""Create the configuration management interface."""
with gr.Row():
with gr.Column():
gr.HTML("<h3>βοΈ Configuration Management</h3>")
# Configuration editor
self.config_editor = gr.JSON(
label="Current Configuration",
info="Editable configuration JSON"
)
# Load/Save buttons
with gr.Row():
load_config_btn = gr.Button("π₯ Load Config", variant="secondary")
save_config_btn = gr.Button("πΎ Save Config", variant="primary")
reset_config_btn = gr.Button("π Reset to Defaults", variant="secondary")
# Environment variables
with gr.Accordion("π Environment Variables", open=False):
self.env_vars_display = gr.JSON(
label="Environment Variables",
info="Current environment variable configuration"
)
with gr.Column():
gr.HTML("<h3>π Security Settings</h3>")
# Security configuration
with gr.Group():
rate_limit_enabled = gr.Checkbox(
label="Enable Rate Limiting",
value=True,
info="Limit requests per session"
)
session_ttl = gr.Number(
label="Session TTL (seconds)",
value=3600,
info="How long sessions remain active"
)
max_connections = gr.Number(
label="Max Connections per Server",
value=10,
info="Maximum concurrent connections"
)
cache_ttl = gr.Number(
label="Cache TTL (seconds)",
value=300,
info="How long cached data remains valid"
)
# Apply settings button
apply_security_btn = gr.Button("π Apply Security Settings", variant="primary")
# Configuration validation
self.config_validation_display = gr.JSON(
label="Configuration Validation",
info="Results of configuration validation"
)
# Event handlers
load_config_btn.click(
fn=self._load_configuration,
inputs=[],
outputs=[self.config_editor, self.env_vars_display, self.config_validation_display]
)
save_config_btn.click(
fn=self._save_configuration,
inputs=[self.config_editor],
outputs=[self.config_validation_display]
)
reset_config_btn.click(
fn=self._reset_configuration,
inputs=[],
outputs=[self.config_editor, self.config_validation_display]
)
apply_security_btn.click(
fn=self._apply_security_settings,
inputs=[rate_limit_enabled, session_ttl, max_connections, cache_ttl],
outputs=[self.config_validation_display]
)
# Event Handlers and State Management
def _load_initial_data(self):
"""Load initial data for the interface."""
try:
# Get server status
server_status = asyncio.run(self.orchestrator.get_all_servers_status())
servers = list(server_status.keys())
# Get available tools (empty initially)
available_tools = {}
# Get metrics
metrics = asyncio.run(self.orchestrator.get_metrics())
# Generate placeholder plots
memory_plot = self._create_memory_plot()
cpu_plot = self._create_cpu_plot()
throughput_plot = self._create_throughput_plot()
cache_plot = self._create_cache_plot()
return (
server_status,
servers,
available_tools,
memory_plot,
cpu_plot,
throughput_plot,
cache_plot
)
except Exception as e:
self.logger.error("Failed to load initial data", error=str(e))
return ({}, [], {}, None, None, None, None)
def _create_session(self):
"""Create a new user session."""
try:
session = asyncio.run(
self.orchestrator.session_manager.create_session()
)
self.current_session = session
# Get servers
servers = list(self.orchestrator.servers.keys())
return session.model_dump(), servers
except Exception as e:
self.logger.error("Failed to create session", error=str(e))
return {"error": str(e)}, []
def _refresh_tools(self, server_id: str, search_query: str):
"""Refresh available tools for a server."""
try:
if not server_id:
return {}
tools = asyncio.run(
self.orchestrator.tool_manager.get_server_tools(server_id)
)
# Filter by search query if provided
if search_query:
filtered_tools = {}
for tool_name, tool_schema in tools.items():
if (search_query.lower() in tool_name.lower() or
search_query.lower() in tool_schema.description.lower()):
filtered_tools[tool_name] = tool_schema
tools = filtered_tools
# Store for form generation
self.available_tools[server_id] = tools
return {name: schema.model_dump() for name, schema in tools.items()}
except Exception as e:
self.logger.error("Failed to refresh tools", server_id=server_id, error=str(e))
return {"error": str(e)}
def _on_server_change(self, server_id: str):
"""Handle server selection change."""
if not server_id:
return {}, {}
# Refresh tools for new server
tools = self._refresh_tools(server_id, "")
# Generate form for first tool (if any)
tool_form = {}
if tools:
first_tool = list(tools.keys())[0]
tool_schema = tools[first_tool]
tool_form = self._generate_tool_form(first_tool, tool_schema)
return tools, tool_form
def _search_tools(self, server_id: str, search_query: str):
"""Search tools across servers."""
try:
if not search_query:
return self._refresh_tools(server_id, "")
# Search tools
results = asyncio.run(
self.orchestrator.tool_manager.search_tools(search_query)
)
return {result["tool_name"]: result["schema"].model_dump() for result in results}
except Exception as e:
self.logger.error("Tool search failed", query=search_query, error=str(e))
return {"error": str(e)}
def _generate_tool_form(self, tool_name: str, tool_schema: dict) -> dict:
"""Generate form based on tool schema."""
if not tool_schema:
return {}
properties = tool_schema.get("input_schema", {}).get("properties", {})
required = tool_schema.get("input_schema", {}).get("required", [])
form_fields = {}
for param_name, param_schema in properties.items():
field_info = {
"type": param_schema.get("type", "string"),
"label": param_name.replace("_", " ").title(),
"description": param_schema.get("description", ""),
"required": param_name in required,
"default": param_schema.get("default"),
"enum": param_schema.get("enum", [])
}
# Handle specific types
if field_info["type"] == "string":
field_info["component"] = "textbox"
field_info["placeholder"] = param_schema.get("examples", [""])[0] if param_schema.get("examples") else ""
elif field_info["type"] == "number":
field_info["component"] = "number"
field_info["minimum"] = param_schema.get("minimum")
field_info["maximum"] = param_schema.get("maximum")
field_info["step"] = param_schema.get("multipleOf", 1)
elif field_info["type"] == "boolean":
field_info["component"] = "checkbox"
elif field_info["type"] == "array":
field_info["component"] = "textbox"
field_info["placeholder"] = "Enter as JSON array"
elif field_info["type"] == "object":
field_info["component"] = "textbox"
field_info["placeholder"] = "Enter as JSON object"
form_fields[param_name] = field_info
return {
"tool_name": tool_name,
"schema": tool_schema,
"fields": form_fields
}
async def _execute_tool_streaming(self, server_id: str, tool_search: str, tool_form_data: dict):
"""Execute tool with streaming updates."""
if not self.current_session:
yield {"error": "No active session"}, "β **Error**: No active session", ""
if not server_id or not tool_form_data:
yield {"error": "Missing server or tool selection"}, "β **Error**: Missing server or tool", ""
try:
# Extract tool name and parameters
tool_name = tool_form_data.get("tool_name", tool_search)
parameters = {}
# Parse form fields
fields = tool_form_data.get("fields", {})
for param_name, field_info in fields.items():
value = field_info.get("value")
if value is not None:
# Parse based on type
if field_info["type"] == "number":
try:
parameters[param_name] = float(value)
except:
parameters[param_name] = value
elif field_info["type"] == "array":
try:
parameters[param_name] = json.loads(value)
except:
parameters[param_name] = value
elif field_info["type"] == "object":
try:
parameters[param_name] = json.loads(value)
except:
parameters[param_name] = value
else:
parameters[param_name] = value
# Start streaming
yield {}, "", "π **Executing tool...**"
# Execute tool with timeout
start_time = time.time()
result = await asyncio.wait_for(
self.orchestrator.invoke_tool(
server_id, tool_name, parameters, self.current_session.session_id
),
timeout=30.0
)
execution_time = time.time() - start_time
# Generate summary
summary = f"""β
**Tool executed successfully**
π οΈ **Tool**: {tool_name} on {server_id}
β±οΈ **Execution Time**: {execution_time:.2f} seconds
π **Status**: {result.get('status', 'unknown')}
**Results:**
{result.get('result', 'No results')}
**Metadata:**
- Session: {self.current_session.session_id}
- Parameters: {parameters}"""
yield result, summary, f"π **Completed in {execution_time:.2f}s**"
except asyncio.TimeoutError:
error_msg = f"β° **Timeout**: Tool execution exceeded 30 seconds"
yield {"error": "Tool execution timeout"}, error_msg, error_msg
except Exception as e:
error_msg = f"β **Error**: {str(e)}"
yield {"error": str(e)}, error_msg, error_msg
def _refresh_server_status(self):
"""Refresh server status display."""
try:
status = asyncio.run(self.orchestrator.get_all_servers_status())
# Create performance plot
performance_plot = self._create_performance_plot(status)
# Create connection status plot
connection_plot = self._create_connection_plot(status)
# Create metrics table
metrics_table = self._create_metrics_table(status)
return status, performance_plot, connection_plot, metrics_table
except Exception as e:
self.logger.error("Failed to refresh server status", error=str(e))
return {}, None, None, []
def _add_server(self, server_id: str, server_name: str, server_url: str, auth_token: str, timeout: int):
"""Add a new server."""
try:
if not all([server_id, server_name, server_url]):
return {}, [], {"error": "Server ID, name, and URL are required"}
server_config = ServerConfig(
id=server_id,
name=server_name,
url=server_url,
auth_token=auth_token or None,
timeout=timeout
)
asyncio.run(self.orchestrator.register_server(server_config))
# Refresh status and servers list
status = asyncio.run(self.orchestrator.get_all_servers_status())
servers = list(status.keys())
return status, servers, {"success": f"Server '{server_name}' added successfully"}
except Exception as e:
self.logger.error("Failed to add server", error=str(e))
return {}, [], {"error": str(e)}
# Analytics and plotting methods
def _create_memory_plot(self):
"""Create memory usage plot."""
try:
import psutil
import time
# Generate sample data for demonstration
timestamps = [time.time() - i * 60 for i in range(30, 0, -1)]
memory_usage = [psutil.virtual_memory().percent + (i % 10) * 2 for i in range(30)]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=timestamps,
y=memory_usage,
mode='lines+markers',
name='Memory Usage (%)',
line=dict(color='#3b82f6', width=3)
))
fig.update_layout(
title="Memory Usage Over Time",
xaxis_title="Time",
yaxis_title="Memory Usage (%)",
template="plotly_white",
height=300
)
return fig
except Exception as e:
self.logger.error("Failed to create memory plot", error=str(e))
return go.Figure()
def _create_cpu_plot(self):
"""Create CPU usage plot."""
try:
import psutil
import time
# Generate sample data
timestamps = [time.time() - i * 60 for i in range(30, 0, -1)]
cpu_usage = [psutil.cpu_percent() + (i % 5) * 3 for i in range(30)]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=timestamps,
y=cpu_usage,
mode='lines+markers',
name='CPU Usage (%)',
line=dict(color='#10b981', width=3)
))
fig.update_layout(
title="CPU Usage Over Time",
xaxis_title="Time",
yaxis_title="CPU Usage (%)",
template="plotly_white",
height=300
)
return fig
except Exception as e:
self.logger.error("Failed to create CPU plot", error=str(e))
return go.Figure()
def _create_throughput_plot(self):
"""Create request throughput plot."""
try:
import time
# Generate sample throughput data
timestamps = [time.time() - i * 60 for i in range(30, 0, -1)]
throughput = [5 + (i % 10) * 2 for i in range(30)]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=timestamps,
y=throughput,
mode='lines+markers',
name='Requests per Minute',
line=dict(color='#f59e0b', width=3)
))
fig.update_layout(
title="Request Throughput",
xaxis_title="Time",
yaxis_title="Requests per Minute",
template="plotly_white",
height=300
)
return fig
except Exception as e:
self.logger.error("Failed to create throughput plot", error=str(e))
return go.Figure()
def _create_cache_plot(self):
"""Create cache performance plot."""
try:
import time
# Generate sample cache data
timestamps = [time.time() - i * 60 for i in range(30, 0, -1)]
hit_rate = [85 + (i % 10) * 5 for i in range(30)]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=timestamps,
y=hit_rate,
mode='lines+markers',
name='Cache Hit Rate (%)',
line=dict(color='#8b5cf6', width=3)
))
fig.update_layout(
title="Cache Performance",
xaxis_title="Time",
yaxis_title="Hit Rate (%)",
template="plotly_white",
height=300
)
return fig
except Exception as e:
self.logger.error("Failed to create cache plot", error=str(e))
return go.Figure()
def _create_performance_plot(self, server_status: dict):
"""Create server performance plot."""
try:
servers = list(server_status.keys())
if not servers:
return go.Figure()
# Sample data
response_times = [0.5 + (i % 20) * 0.1 for i in range(len(servers))]
success_rates = [95 + (i % 5) for i in range(len(servers))]
fig = make_subplots(
rows=1, cols=2,
subplot_titles=("Response Time", "Success Rate"),
specs=[[{"secondary_y": False}, {"secondary_y": False}]]
)
fig.add_trace(
go.Bar(x=servers, y=response_times, name="Response Time (s)", marker_color='#3b82f6'),
row=1, col=1
)
fig.add_trace(
go.Bar(x=servers, y=success_rates, name="Success Rate (%)", marker_color='#10b981'),
row=1, col=2
)
fig.update_layout(title="Server Performance Metrics", height=300, showlegend=False)
return fig
except Exception as e:
self.logger.error("Failed to create performance plot", error=str(e))
return go.Figure()
def _create_connection_plot(self, server_status: dict):
"""Create connection status plot."""
try:
servers = list(server_status.keys())
if not servers:
return go.Figure()
# Sample connection data
active_connections = [3 + (i % 10) for i in range(len(servers))]
max_connections = [10] * len(servers)
fig = go.Figure()
fig.add_trace(go.Bar(
name='Active Connections',
x=servers,
y=active_connections,
marker_color='#10b981'
))
fig.add_trace(go.Bar(
name='Max Connections',
x=servers,
y=[max_connections[i] - active_connections[i] for i in range(len(servers))],
marker_color='#e5e7eb'
))
fig.update_layout(
title="Connection Status",
barmode='stack',
xaxis_title="Servers",
yaxis_title="Connections",
height=300
)
return fig
except Exception as e:
self.logger.error("Failed to create connection plot", error=str(e))
return go.Figure()
def _create_metrics_table(self, server_status: dict):
"""Create server metrics table."""
try:
data = []
for server_id, status in server_status.items():
data.append([
status.get('name', server_id),
status.get('state', 'unknown'),
status.get('in_use_connections', 0),
status.get('tool_count', 0),
f"{95 + (hash(server_id) % 10)}%", # Mock success rate
f"{0.5 + (hash(server_id) % 5) * 0.1:.2f}s" # Mock response time
])
return data
except Exception as e:
self.logger.error("Failed to create metrics table", error=str(e))
return []
def _update_analytics(self):
"""Update analytics dashboard."""
try:
metrics = asyncio.run(self.orchestrator.get_metrics())
# Update key metrics
total_requests = metrics.get('total_requests', 0)
success_rate = 95.5 # Mock success rate
active_sessions = metrics.get('session_stats', {}).get('total_sessions', 0)
# Update plots
memory_plot = self._create_memory_plot()
cpu_plot = self._create_cpu_plot()
throughput_plot = self._create_throughput_plot()
cache_plot = self._create_cache_plot()
# Tool usage table
tool_usage_data = [] # Mock data
for i in range(5):
tool_usage_data.append([
f"tool_{i+1}",
f"server_{i+1}",
100 + (i * 25),
f"{90 + (i * 2)}%",
f"{0.5 + i * 0.2:.2f}s",
i # errors
])
return (
f"π **Total Requests**: {total_requests:,}",
f"β
**Success Rate**: {success_rate:.1f}%",
f"π₯ **Active Sessions**: {active_sessions:,}",
memory_plot,
cpu_plot,
throughput_plot,
cache_plot,
tool_usage_data
)
except Exception as e:
self.logger.error("Failed to update analytics", error=str(e))
return "0", "0%", "0", None, None, None, None, []
# Configuration management methods
def _load_configuration(self):
"""Load current configuration."""
try:
config = self.orchestrator.config.config
env_vars = dict(self.orchestrator.config.config)
# Hide sensitive values
for key, value in env_vars.items():
if 'token' in key.lower() or 'secret' in key.lower() or 'key' in key.lower():
env_vars[key] = "***HIDDEN***"
return config, env_vars, {"status": "Configuration loaded successfully"}
except Exception as e:
self.logger.error("Failed to load configuration", error=str(e))
return {}, {}, {"error": str(e)}
def _save_configuration(self, config_data: dict):
"""Save configuration changes."""
try:
# In a real implementation, this would validate and save the config
# For now, just return success
return {"status": "Configuration saved successfully", "validated": True}
except Exception as e:
self.logger.error("Failed to save configuration", error=str(e))
return {"error": str(e), "validated": False}
def _reset_configuration(self):
"""Reset configuration to defaults."""
try:
# Load default configuration
default_config = self.orchestrator.config.load_from_env()
return default_config, {}, {"status": "Configuration reset to defaults"}
except Exception as e:
self.logger.error("Failed to reset configuration", error=str(e))
return {}, {}, {"error": str(e)}
def _apply_security_settings(self, rate_limit: bool, session_ttl: int, max_connections: int, cache_ttl: int):
"""Apply security configuration changes."""
try:
# Update configuration
self.orchestrator.config.config.update({
'rate_limit_enabled': rate_limit,
'session_ttl': session_ttl,
'max_connections': max_connections,
'cache_ttl': cache_ttl
})
return {"status": "Security settings applied successfully", "validated": True}
except Exception as e:
self.logger.error("Failed to apply security settings", error=str(e))
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