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.gitignore

@@ -0,0 +1,35 @@
+# Virtual environments
+venv/
+env/
+.env
+
+# Python
+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+.Python
+*.so
+.pytest_cache/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+mco-protocol.code-workspace
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Logs
+*.log
+
+# Coding Agents
+.claude
+.qodo
+.windsurfrules
+.clinerules
+.blackboxai
+.goose

app.py

@@ -1,132 +1,166 @@
 #!/usr/bin/env python3
 """
-MCO Hackathon Final Submission - Main Entry Point
+MCO Hackathon Demo - Main Entry Point
 
-This script integrates all components of the MCO Hackathon project:
-1. Real Modal API integration for AutoGPT-like agent
-2. Real MCO MCP server for orchestration
-3. Single-page Gradio UI with agent thinking and MCO logs
-4. Visual SNLP generator with value/NLP editing toggle
-
-Author: Manus AI
-Date: June 10, 2025
+This script sets up and runs the MCO Hackathon project:
+1.  Starts the MCO MCP server for orchestration.
+2.  Launches the polished Gradio UI for the demonstration.
 """
 
 import os
 import sys
-import json
 import subprocess
-import tempfile
-from pathlib import Path
+import time
+import shutil
 
-# Set up environment
+# Set up environment variables before other imports
 APP_DIR = os.path.dirname(os.path.abspath(__file__))
 os.environ["MCO_CONFIG_DIR"] = os.path.join(APP_DIR, "mco-config")
-# The local mco-server.js defaults to port 3000
 os.environ["MCO_SERVER_URL"] = "http://localhost:3000"
 
-# Import components
-from modal_implementation import stub as modal_app
-from gradio_ui import create_ui
-from snlp_generator import SNLPGenerator
+# Import the Gradio UI creation function
+from gradio_ui import create_gradio_ui
 
-# Check if running in Hugging Face Spaces
-IS_HF_SPACE = os.environ.get("SPACE_ID") is not None
+print("--- app.py: Script execution started (top level) ---")
 
 # Global variable to hold the MCO server process
 mco_server_process = None
 
 def setup_mco_server():
-    """Ensures the MCO MCP server script is available and starts it."""
+    print("--- app.py: setup_mco_server() function started ---")
+    """Installs MCO dependencies via npm and starts the server."""
     global mco_server_process
-    print("Setting up and starting MCO MCP server...")
-    import shutil # For copying files
+    print("--- Setting up and starting MCO MCP server ---")
 
-    app_dir = os.path.dirname(os.path.abspath(__file__))
-    # Standard name for the server script, matching Dockerfile copy destination
-    server_script_name = "mco-mcp-server.js"
-    server_script_path = os.path.join(app_dir, server_script_name)
-    mco_config_dir = os.environ.get("MCO_CONFIG_DIR", os.path.join(app_dir, "mco-config"))
+    # Step 1: Ensure npm dependencies are installed (cleanly).
+    print("--- Performing a clean install of MCO server dependencies via npm... ---")
+    try:
+        # Clean up old artifacts
+        node_modules_path = os.path.join(APP_DIR, "node_modules")
+        package_lock_path = os.path.join(APP_DIR, "package-lock.json")
+        if os.path.isdir(node_modules_path):
+            print(f"Removing existing node_modules directory: {node_modules_path}")
+            shutil.rmtree(node_modules_path)
+        if os.path.exists(package_lock_path):
+            print(f"Removing existing package-lock.json: {package_lock_path}")
+            os.remove(package_lock_path)
 
-    if not os.path.exists(server_script_path):
-        print(f"MCO MCP server script '{server_script_name}' not found in '{app_dir}'.")
-        print("Attempting to install '@paradiselabs/mco-protocol' and copy server script...")
-        try:
-            # Ensure npm is available (basic check, validate_environment should do more)
-            subprocess.run(["npm", "--version"], check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-            
-            # Install/update the package - this will create node_modules if not present
-            print("Running: npm install @paradiselabs/mco-protocol")
-            subprocess.run(
-                ["npm", "install", "@paradiselabs/mco-protocol"],
-                check=True,
-                cwd=app_dir, # Run npm install in the application directory
-                stdout=subprocess.PIPE, stderr=subprocess.PIPE
-            )
-            print("'@paradiselabs/mco-protocol' package installed/updated.")
+        # General npm install for all dependencies
+        print("Running general 'npm install'...")
+        npm_install_command = ["npm", "install"]
+        print(f"Executing: {' '.join(npm_install_command)}")
+        npm_install_process = subprocess.run(npm_install_command, cwd=APP_DIR, check=True, capture_output=True, text=True)
+        print("--- npm install stdout ---")
+        print(npm_install_process.stdout)
+        print("--- npm install stderr ---")
+        print(npm_install_process.stderr)
+        print("'npm install' completed.")
 
-            # Define path to the script within node_modules
-            node_modules_path = os.path.join(app_dir, "node_modules")
-            source_server_script = os.path.join(node_modules_path, "@paradiselabs", "mco-protocol", "bin", server_script_name)
+        # Specifically install/update @paradiselabs/mco-protocol to the latest version
+        print("Ensuring latest '@paradiselabs/mco-protocol' is installed...")
+        npm_update_specific_pkg_command = ["npm", "install", "@paradiselabs/mco-protocol@latest"]
+        print(f"Executing: {' '.join(npm_update_specific_pkg_command)}")
+        npm_update_specific_pkg_process = subprocess.run(npm_update_specific_pkg_command, cwd=APP_DIR, check=True, capture_output=True, text=True)
+        print("--- npm install @paradiselabs/mco-protocol@latest stdout ---")
+        print(npm_update_specific_pkg_process.stdout)
+        print("--- npm install @paradiselabs/mco-protocol@latest stderr ---")
+        print(npm_update_specific_pkg_process.stderr)
+        print("'@paradiselabs/mco-protocol@latest' installed/updated.")
 
-            if os.path.exists(source_server_script):
-                shutil.copy(source_server_script, server_script_path)
-                print(f"Copied '{server_script_name}' to '{server_script_path}'.")
-            else:
-                print(f"ERROR: Could not find '{server_script_name}' in '{os.path.join(node_modules_path, '@paradiselabs/mco-protocol/bin')}' after npm install.")
-                print("Please check npm installation and package contents. Cannot start MCO server.")
-                return
-        except subprocess.CalledProcessError as e:
-            print(f"Error during npm operations: {e}")
-            print(f"stdout: {e.stdout.decode() if e.stdout else 'N/A'}")
-            print(f"stderr: {e.stderr.decode() if e.stderr else 'N/A'}")
-            print("Please ensure Node.js and npm are installed and accessible. Cannot start MCO server.")
-            return
-        except FileNotFoundError:
-            print("Error: npm command not found. Please ensure Node.js and npm are installed and in your PATH.")
-            return
+        # Hot-patch mco-server.js to fix internal pathing issue
+        mco_server_script_to_patch_path = os.path.join(APP_DIR, "node_modules", "@paradiselabs", "mco-protocol", "bin", "mco-server.js")
+        if os.path.exists(mco_server_script_to_patch_path):
+            print(f"Attempting to hot-patch {mco_server_script_to_patch_path}...")
+            try:
+                with open(mco_server_script_to_patch_path, 'r') as f:
+                    content = f.read()
+                
+                original_substring = "require('./lib/"
+                corrected_substring = "require('../lib/"
+                
+                if original_substring in content:
+                    content = content.replace(original_substring, corrected_substring)
+                    with open(mco_server_script_to_patch_path, 'w') as f:
+                        f.write(content)
+                    print(f"Successfully patched {mco_server_script_to_patch_path}: replaced all instances of '{original_substring}' with '{corrected_substring}'.")
+                else:
+                    print(f"Hot-patch warning: Original substring '{original_substring}' not found in {mco_server_script_to_patch_path}. The script might already be patched or has changed.")
+            except Exception as patch_err:
+                print(f"Error during hot-patching {mco_server_script_to_patch_path}: {patch_err}")
+        else:
+            print(f"Hot-patch error: {mco_server_script_to_patch_path} not found. Cannot apply patch.")
+
+    except subprocess.CalledProcessError as e:
+        print(f"ERROR: npm command failed with exit code {e.returncode}.")
+        print(f"Command: {' '.join(e.cmd)}")
+        print(f"stdout:\n{e.stdout}")
+        print(f"stderr:\n{e.stderr}")
+        sys.exit(1)
+    except FileNotFoundError:
+        print("ERROR: `npm` command not found. Please ensure Node.js and npm are installed.")
+        sys.exit(1)
+    except Exception as e:
+        print(f"An unexpected error occurred during npm setup: {e}")
+        sys.exit(1)
+
+    # Step 2: Attempt to run the server using mco-cli.js, with CWD at package root.
+    server_script_name = "mco-cli.js" # Using the CLI script as an alternative entry point
+    server_script_path = os.path.join(APP_DIR, "node_modules", "@paradiselabs", "mco-protocol", "bin", server_script_name)
+    mco_config_dir = os.environ["MCO_CONFIG_DIR"]
 
-    # Command to start the MCO server directly with node
+    if not os.path.exists(server_script_path):
+        print(f"ERROR: MCO CLI script not found at '{server_script_path}' after npm install.")
+        sys.exit(1)
+
+    # Construct the command to run the CLI script directly with node, using the 'serve' subcommand.
     server_command = [
         "node",
-        server_script_path, # Use the now ensured server_script_path
-        "--config-dir", mco_config_dir,
-        "--host", "0.0.0.0", # Listen on all interfaces for container accessibility
-        "--port", "3000" # Explicitly set port, matches MCO_SERVER_URL
+        server_script_path,
+        "serve", # The 'serve' subcommand for mco-cli.js
+        mco_config_dir,
+        "--host", "0.0.0.0",
+        "--port", os.environ.get("MCO_PORT", "3001")
     ]
 
     try:
-        print(f"Starting MCO server with command: {' '.join(server_command)}")
-        mco_server_process = subprocess.Popen(
-            server_command,
-            stdout=subprocess.PIPE,
-            stderr=subprocess.PIPE,
-            text=True,
-            cwd=app_dir
-        )
-        print(f"MCO MCP server process started with PID: {mco_server_process.pid}")
-        # Give the server a moment to start up
-        import time
-        time.sleep(3) # Increased sleep to allow server to fully initialize
-        print("MCO MCP server setup and start complete.")
+        print(f"Starting MCO server: {' '.join(server_command)}")
+        package_root_dir = os.path.join(APP_DIR, "node_modules", "@paradiselabs", "mco-protocol")
+        if not os.path.isdir(package_root_dir):
+            print(f"ERROR: MCO package directory not found at '{package_root_dir}'. This is unexpected after npm install.")
+            sys.exit(1)
 
+        # The server's stdout and stderr will now go to the main console.
+        mco_server_process = subprocess.Popen(server_command, cwd=package_root_dir)
+        
+        print(f"MCO server process started with PID: {mco_server_process.pid} (CWD: {package_root_dir})")
+        time.sleep(5) # Allow server more time to initialize and write to logs
     except Exception as e:
-        print(f"Error starting MCO MCP server: {e}")
-        if mco_server_process:
-            mco_server_process.terminate()
-        mco_server_process = None
-
-    # SNLP files are assumed to be present in MCO_CONFIG_DIR
-    # create_sample_snlp_files() # Removed this call
+        print(f"Error starting MCO server: {e}")
+        sys.exit(1)
 
+def main():
+    print("--- app.py: main() function started ---")
+    """Main function to run the server and UI."""
+    global mco_server_process
+    try:
+        setup_mco_server()
+        if mco_server_process and mco_server_process.poll() is None:
+            print("--- MCO server is running. Launching Gradio UI... ---")
+            gradio_app = create_gradio_ui()
+            print("--- Calling gradio_app.launch() locally... ---")
+            gradio_app.launch()
+            print("--- Gradio UI has been shut down. --- ")
+            # If we reach here, it means Gradio's launch() returned.
+            # We should still try to shut down the server cleanly.
+            print("--- Shutting down MCO server... ---")
+            if mco_server_process:
+                print("--- Terminating MCO server process... ---")
+                mco_server_process.terminate()
+                mco_server_process.wait()
+                print("--- MCO server stopped. ---")
+    except Exception as e:
+        print(f"An unexpected error occurred: {e}")
 
-# def create_sample_snlp_files(): # Function removed as SNLP files are expected to exist
-#     """Create sample SNLP files if they don't exist"""
-#     generator = SNLPGenerator()
-#     
-#     # Check if any SNLP files exist
-#     if not any(os.path.exists(os.path.join(os.environ["MCO_CONFIG_DIR"], file)) 
-#                for file in ["mco.core", "mco.sc", "mco.features", "mco.styles"]):
 #         print("Creating sample SNLP files...")
 #         generator.generate_sample_files("General", "Python")
 #         print("Sample SNLP files created")

gradio_ui.py

@@ -1,257 +1,140 @@
-""" 
-Gradio UI for MCO Agent Orchestration
-
-This script creates a Gradio user interface for interacting with a Modal-based agent 
-that is orchestrated by the MCO protocol. The UI provides two main tabs:
-
-1.  **Agent Demo**: Allows users to input a high-level goal for SNLP (Structured 
-    Natural Language Processing) generation. The agent's thinking process, MCO 
-    orchestration logs, and final results are displayed in real-time.
-
-2.  **SNLP File Editor**: A static tool for loading, editing, and downloading SNLP 
-    orchestration files. It supports two editing modes:
-    -   **Values Only**: A simplified view for editing values and NLP content in JSON format.
-    -   **Full Edit**: A code editor for viewing and editing the raw SNLP file content.
+"""
+Gradio UI for MCO Agent Orchestration - Hackathon Demo
 
-Helper functions are included for parsing, generating, and manipulating SNLP files, 
-as well as for handling file downloads as individual files or as a single zip archive.
+This script creates a polished Gradio user interface to showcase the MCO protocol.
+The UI is designed for a compelling presentation, focusing on the agent's
+orchestrated task execution without requiring user input.
 """
 
-import os
-import json
 import gradio as gr
-import modal
-import tempfile
-import zipfile
-from pathlib import Path
-
-# --- Constants and Setup ---
+import asyncio
 
 # Attempt to import the Modal app; handle gracefully if not available
 try:
-    from modal_implementation import app as modal_app
+    from modal_implementation import run_mco_agent
 except (ImportError, ModuleNotFoundError):
     print("Warning: Modal app not found. Running in local simulation mode.")
-    modal_app = None
-
-# Define paths and file names
-ORCHESTRATION_DIR = Path(__file__).parent / "snlp_orchestrations"
-SNLP_FILES = ["mco.core", "mco.sc", "mco.features", "mco.styles"]
-ORCHESTRATION_DIR.mkdir(exist_ok=True)
-
-# --- Helper Functions ---
-
-def get_available_orchestrations():
-    """Scans the orchestration directory for available orchestration sets."""
-    return [d.name for d in ORCHESTRATION_DIR.iterdir() if d.is_dir()]
-
-def parse_snlp_file(content):
-    """Parses SNLP file content into a dictionary of sections."""
-    sections = {}
-    current_section, current_content = None, []
-    for line in content.splitlines():
-        if line.startswith("@"):
-            if current_section:
-                sections[current_section] = "\n".join(current_content)
-            parts = line.split(" ", 1)
-            current_section = parts[0][1:]
-            current_content = [parts[1]] if len(parts) > 1 else []
-        elif current_section:
-            current_content.append(line)
-    if current_section:
-        sections[current_section] = "\n".join(current_content)
-    return sections
-
-def extract_values_and_nlp(content):
-    """Extracts structured values and NLP text from SNLP content."""
-    values, nlp = {}, {}
-    for section, section_content in parse_snlp_file(content).items():
-        nlp_lines = [line[1:].strip() for line in section_content.splitlines() if line.startswith(">")]
-        value_lines = [line for line in section_content.splitlines() if not line.startswith(">")]
-        if nlp_lines:
-            nlp[section] = "\n".join(nlp_lines)
-        if value_lines:
-            values[section] = "\n".join(value_lines).strip()
-    return values, nlp
-
-def create_ui():
-    """Creates and configures the Gradio user interface."""
-    available_orchestrations = get_available_orchestrations()
-
-    with gr.Blocks(theme=gr.themes.Soft(), title="MCO Protocol Agent") as app:
-        gr.Markdown(""" 
-        # MCO Protocol: Agent Orchestration Demo
-        Demonstrates a Modal-based agent orchestrated by the MCO MCP server to generate SNLP files.
-        """)
-
-        with gr.Tabs():
-            with gr.TabItem("Agent Demo"):
-                with gr.Row():
-                    with gr.Column(scale=2):
-                        task_input = gr.Textbox(
-                            label="High-Level Goal for SNLP Generation",
-                            placeholder="e.g., Generate a new MCO orchestration for a 'Security' review of 'Python' code.",
-                            lines=4,
-                        )
-                        run_button = gr.Button("Run Agent to Generate SNLP Files", variant="primary")
-                    with gr.Column(scale=1):
-                        status = gr.Markdown("Status: Ready")
-
-                with gr.Row():
-                    thinking_output = gr.Markdown(label="Agent Thinking Process")
-                    orchestration_log = gr.JSON(label="MCO Orchestration Log")
-                results_output = gr.Markdown(label="Agent Results")
-
-            with gr.TabItem("SNLP File Editor"):
-                gr.Markdown("### Static SNLP File Editor and Generator")
-                gr.Markdown("Load, edit, and download SNLP files. This is a static tool and does not use an LLM.")
-                with gr.Row():
-                    orchestration_select = gr.Dropdown(
-                        label="Select Orchestration",
-                        choices=available_orchestrations,
-                        value=available_orchestrations[0] if available_orchestrations else None,
-                    )
-                    load_button = gr.Button("Load", variant="secondary")
-                    edit_mode = gr.Radio(choices=["Values Only", "Full Edit"], value="Values Only", label="Edit Mode")
-
-                snlp_ui_map = {}
-                with gr.Tabs():
-                    for file in SNLP_FILES:
-                        with gr.TabItem(file):
-                            with gr.Row(visible=True) as values_row:
-                                values_json = gr.JSON(label="Values")
-                                nlp_json = gr.JSON(label="NLP")
-                            content_code = gr.Code(label=f"{file} Content", language="markdown", visible=False)
-                            snlp_ui_map[file] = {
-                                "values_row": values_row,
-                                "values": values_json,
-                                "nlp": nlp_json,
-                                "content": content_code,
-                            }
-
-                with gr.Row():
-                    download_buttons = [gr.Button(f"Download {f}") for f in SNLP_FILES]
-                    download_all = gr.Button("Download All as ZIP", variant="primary")
-
-        # --- Event Handlers ---
-
-        def handle_run_agent(task):
-            """Streams agent output to the UI when the 'Run Agent' button is clicked."""
-            yield {status: "Status: Starting agent...", thinking_output: "", orchestration_log: {}, results_output: ""}
-            if not modal_app:
-                yield {status: "Status: Error - Modal app not available."}
-                return
-
-            try:
-                # Ensure the correct function name is called
-                for chunk in modal_app.run_agent.remote_gen(task):
-                    yield {
-                        thinking_output: chunk.get("thinking_output", ""),
-                        orchestration_log: chunk.get("orchestration_log", {}),
-                        results_output: chunk.get("results_output", ""),
-                        status: f"Status: {chunk.get('status', 'Running...')}",
-                    }
-            except Exception as e:
-                yield {status: f"Status: Error - {e}"}
-
-        def load_snlp_files(orchestration_name):
-            """Loads the selected SNLP orchestration files into the editor."""
-            updates = {}
-            if not orchestration_name:
-                # Create empty updates for all components to clear them
-                for ui_comps in snlp_ui_map.values():
-                    updates[ui_comps["content"]] = gr.update(value="")
-                    updates[ui_comps["values"]] = gr.update(value={})
-                    updates[ui_comps["nlp"]] = gr.update(value={})
-                return updates
-
-            orchestration_path = ORCHESTRATION_DIR / orchestration_name
-            for file, ui_comps in snlp_ui_map.items():
-                file_path = orchestration_path / file
-                if file_path.exists():
-                    content = file_path.read_text(encoding="utf-8")
-                    values, nlp = extract_values_and_nlp(content)
-                    updates[ui_comps["content"]] = gr.update(value=content)
-                    updates[ui_comps["values"]] = gr.update(value=values)
-                    updates[ui_comps["nlp"]] = gr.update(value=nlp)
-                else:
-                    not_found_msg = f"// {file} not found in {orchestration_name}."
-                    updates[ui_comps["content"]] = gr.update(value=not_found_msg)
-                    updates[ui_comps["values"]] = gr.update(value={})
-                    updates[ui_comps["nlp"]] = gr.update(value={})
-            return updates
-
-        def handle_edit_mode(mode):
-            """Toggles between the simplified 'Values Only' and 'Full Edit' views."""
-            is_values_only = mode == "Values Only"
-            updates = {}
-            for comps in snlp_ui_map.values():
-                updates[comps["values_row"]] = gr.update(visible=is_values_only)
-                updates[comps["content"]] = gr.update(visible=not is_values_only)
-            return updates
-
-        def download_file(content):
-            """Creates a temporary file for downloading."""
-            with tempfile.NamedTemporaryFile(delete=False, mode="w", suffix=".txt", encoding="utf-8") as f:
-                f.write(content or "")
-                return f.name
-
-        def create_zip_file(*contents):
-            """Creates a ZIP archive of all SNLP files for download."""
-            # Create a temporary file with a .zip extension
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".zip", mode='w+b') as f:
-                zip_path = f.name
+    # Define a dummy sync generator for local testing
+    def run_mco_agent(prompt):
+        for i in range(5):
+            yield {"type": "status", "message": f"<thinking>Simulation step {i+1} for prompt: {prompt}</thinking>"}
+            time.sleep(1)
+        yield {"type": "final_result", "result": "<thinking>Simulation complete.</thinking>"}
+
+def run_orchestration_and_stream_results():
+    """
+    Runs the MCO agent with a fixed prompt and streams back thinking and log updates.
+    """
+    user_prompt = "Use the mco server to orchestrate your tasks. use <thinking> xml each step of the way, while you learn about the mco orchestration."
+    
+    full_log = ""
+    thinking_stream = ""
+    
+    try:
+        # The agent runner is a synchronous generator from Modal
+        for result in run_mco_agent.remote_gen(user_prompt):
+            message = result.get("message", result.get("result", ""))
+
+            if result.get("type") == "status":
+                full_log += message + "\n\n"
+                thinking_stream = message
+            elif result.get("type") == "error":
+                error_msg = f"<error>ERROR: {message}</error>"
+                full_log += error_msg + "\n\n"
+                thinking_stream = error_msg
+            elif result.get("type") == "final_result":
+                 final_msg = message
+                 full_log += f"\n--- ORCHESTRATION COMPLETE ---\n{final_msg}"
+                 thinking_stream = final_msg
             
-            # Write to the zip file
-            with zipfile.ZipFile(zip_path, "w") as zf:
-                for i, content in enumerate(contents):
-                    zf.writestr(SNLP_FILES[i], content or "")
-            return zip_path
-
-        # --- Wire up UI Components ---
-
-        run_button.click(
-            fn=handle_run_agent,
-            inputs=[task_input],
-            outputs=[status, thinking_output, orchestration_log, results_output],
-        )
-
-        # Collect all output components for load_snlp_files and handle_edit_mode
-        snlp_ui_outputs = []
-        for comps in snlp_ui_map.values():
-            snlp_ui_outputs.extend([comps["content"], comps["values"], comps["nlp"], comps["values_row"]])
+            yield thinking_stream, full_log
+
+    except Exception as e:
+        error_message = f"<error>An unexpected error occurred: {e}</error>"
+        yield error_message, full_log + f"\n{error_message}"
+
+def create_gradio_ui():
+    """Creates and returns the Gradio UI Blocks for the MCO Hackathon Demo."""
+    
+    css = """
+    body { background-color: #f7f7f7; }
+    .main-title { text-align: center; font-size: 2.8em; color: #4A00E0; font-weight: bold; letter-spacing: -1px; margin-bottom: 10px; }
+    .subtitle { text-align: center; font-size: 1.3em; color: #555; margin-bottom: 25px; line-height: 1.6; }
+    .thinking-box { 
+        border: 2px solid #8E2DE2; 
+        padding: 20px; 
+        border-radius: 12px; 
+        background-color: #ffffff; 
+        font-family: 'Courier New', Courier, monospace;
+        font-size: 1.1em;
+        min-height: 60px;
+        box-shadow: 0 4px 15px rgba(0,0,0,0.05);
+    }
+    .log-box { 
+        font-family: 'Menlo', 'Monaco', 'Consolas', monospace; 
+        background-color: #1e1e1e; 
+        color: #d4d4d4;
+        border: 1px solid #333;
+        border-radius: 12px;
+        padding: 15px;
+    }
+    .orchestrate-button { 
+        background: linear-gradient(45deg, #8E2DE2, #4A00E0) !important; 
+        color: white !important; 
+        font-weight: bold !important; 
+        font-size: 1.2em !important;
+        border-radius: 10px !important;
+        padding: 15px 30px !important;
+        border: none !important;
+        box-shadow: 0 4px 15px rgba(74, 0, 224, 0.4);
+        transition: all 0.3s ease;
+    }
+    .orchestrate-button:hover {
+        transform: translateY(-2px);
+        box-shadow: 0 6px 20px rgba(74, 0, 224, 0.5);
+    }
+    .gr-label { display: none !important; }
+    """
+
+    with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue"), css=css, title="MCO Protocol Demo") as demo:
+        gr.Markdown("""
+        <h1 class='main-title'>🏆 The Missing Layer of Agentic AI: Orchestration 🏆</h1>
+        <p class='subtitle'>
+        Welcome to the future of agentic systems with the <strong>MCO Protocol</strong>. <br>
+        This agent, powered by Claude on Modal, connects to an <strong>MCO Server</strong> that orchestrates its every move. <br>
+        Click below to witness a complex task unfold, step-by-step, guided entirely by MCO.
+        </p>
+        """)
 
-        load_button.click(
-            fn=load_snlp_files,
-            inputs=[orchestration_select],
-            outputs=snlp_ui_outputs,
+        with gr.Row():
+            orchestrate_button = gr.Button("🚀 Orchestrate! 🚀", elem_classes="orchestrate-button")
+        
+        gr.Markdown("### 🧠 Agent's Real-time Thinking")
+        agent_thinking_box = gr.Textbox(
+            label="Current Status", 
+            elem_classes="thinking-box",
+            interactive=False,
+            show_label=False
         )
-
-        edit_mode.change(
-            fn=handle_edit_mode,
-            inputs=[edit_mode],
-            outputs=snlp_ui_outputs,
+        
+        gr.Markdown("### 📜 Full Orchestration Log")
+        agent_log_box = gr.Textbox(
+            label="Log", 
+            elem_classes="log-box",
+            lines=20, 
+            interactive=False,
+            show_label=False
         )
 
-        # Wire up download buttons
-        for i, button in enumerate(download_buttons):
-            button.click(
-                fn=download_file, 
-                inputs=[snlp_ui_map[SNLP_FILES[i]]["content"]], 
-                outputs=gr.File(label=f"Download {SNLP_FILES[i]}")
-            )
-
-        download_all.click(
-            fn=create_zip_file,
-            inputs=[snlp_ui_map[f]["content"] for f in SNLP_FILES],
-            outputs=gr.File(label="Download All as ZIP"),
+        orchestrate_button.click(
+            fn=run_orchestration_and_stream_results,
+            inputs=[],
+            outputs=[agent_thinking_box, agent_log_box]
         )
-
-    return app
-
-# --- Main Execution ---
+    
+    return demo
 
 if __name__ == "__main__":
-    gradio_ui = create_ui()
+    gradio_ui = create_gradio_ui()
     gradio_ui.launch(share=True)
 

mcp_host_config.json

@@ -0,0 +1,10 @@
+{
+  "mcpServers": {
+    "mco-orchestration": {
+      "command": "npx",
+      "args": ["@paradiselabs/mco-protocol", "--config-dir", "/app/mco-config"],
+      "workingDirectory": "/app",
+      "description": "MCO Orchestration Server"
+    }
+  }
+}

modal_implementation.py

@@ -12,7 +12,6 @@ import json
 import asyncio
 import websockets
 import modal
-import anthropic
 from typing import Dict, Any, Optional
 
 # --- Modal App Setup ---
@@ -21,7 +20,6 @@ stub = modal.App(
     name="mco-autogpt-agent",
     secrets=[modal.Secret.from_dotenv()],
     image=modal.Image.debian_slim(python_version="3.10").pip_install(
-        "anthropic",
         "websockets",
     )
 )
@@ -302,22 +300,18 @@ async def arun_mco_agent(user_prompt: str):
             yield {"type": "status", "message": "<thinking>MCP client shut down.</thinking>"}
 
 @stub.function(
-    timeout=900,
-    container_idle_timeout=300,
-    cpu=2
+    secrets=[modal.Secret.from_dotenv()],
+    timeout=600,
+    scaledown_window=120,
 )
 def run_mco_agent(user_prompt: str):
-    """Synchronous wrapper for the async agent runner to be called by Gradio."""
-    # This is how Gradio will call our Modal generator
-    # It needs to iterate over the results from the generator
-    # and yield them back to Gradio's streaming mechanism.
-    # print(f"run_mco_agent called with user_prompt: {user_prompt}")
-    for item in arun_mco_agent(user_prompt=user_prompt):
-        # print(f"run_mco_agent yielding: {item}")
-        yield item
-
-@stub.local_entrypoint()
-def main(prompt: str = "Review the provided code snippet for potential bugs."):
-    """Local entrypoint for testing the Modal app via the command line."""
-    for update in run_mco_agent.remote_gen(prompt=prompt):
-        print(json.dumps(update, indent=2))
+    """Synchronous wrapper for the async generator, exposed as a Modal Function.
+    This allows Gradio to call the agent and stream results.
+    """
+    import asyncio
+    g = arun_mco_agent(user_prompt)
+    try:
+        while True:
+            yield asyncio.run(g.__anext__())
+    except StopAsyncIteration:
+        pass

package-lock.json

@@ -0,0 +1,1430 @@
+{
+  "name": "mco-protocol",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "dependencies": {
+        "@paradiselabs/mco-protocol": "^0.2.8"
+      }
+    },
+    "node_modules/@paradiselabs/mco-protocol": {
+      "version": "0.2.8",
+      "resolved": "https://registry.npmjs.org/@paradiselabs/mco-protocol/-/mco-protocol-0.2.8.tgz",
+      "integrity": "sha512-+5ovItKgkKu8kMDnRTk7bxas6rKtDMF7ngL1By//E0kbwrWoega8Gvw0vQePMRxEZAXbByPqyNqAEnTWT2IpSw==",
+      "license": "MIT",
+      "dependencies": {
+        "commander": "^11.0.0",
+        "express": "^4.18.2",
+        "fs-extra": "^11.1.1",
+        "open": "^9.1.0",
+        "uuid": "^9.0.0",
+        "ws": "^8.13.0",
+        "yaml": "^2.3.1"
+      },
+      "bin": {
+        "mco": "bin/mco-cli.js"
+      },
+      "engines": {
+        "node": ">=16.0.0"
+      }
+    },
+    "node_modules/accepts": {
+      "version": "1.3.8",
+      "resolved": "https://registry.npmjs.org/accepts/-/accepts-1.3.8.tgz",
+      "integrity": "sha512-PYAthTa2m2VKxuvSD3DPC/Gy+U+sOA1LAuT8mkmRuvw+NACSaeXEQ+NHcVF7rONl6qcaxV3Uuemwawk+7+SJLw==",
+      "license": "MIT",
+      "dependencies": {
+        "mime-types": "~2.1.34",
+        "negotiator": "0.6.3"
+      },
+      "engines": {
+        "node": ">= 0.6"
+      }
+    },
+    "node_modules/array-flatten": {
+      "version": "1.1.1",
+      "resolved": "https://registry.npmjs.org/array-flatten/-/array-flatten-1.1.1.tgz",
+      "integrity": "sha512-PCVAQswWemu6UdxsDFFX/+gVeYqKAod3D3UVm91jHwynguOwAvYPhx8nNlM++NqRcK6CxxpUafjmhIdKiHibqg==",
+      "license": "MIT"
+    },
+    "node_modules/big-integer": {
+      "version": "1.6.52",
+      "resolved": "https://registry.npmjs.org/big-integer/-/big-integer-1.6.52.tgz",
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+}

package.json

@@ -0,0 +1,5 @@
+{
+  "dependencies": {
+    "@paradiselabs/mco-protocol": "^0.2.8"
+  }
+}