import gradio as gr
import httpx
import json
from huggingface_hub import HfApi
import random
import re

def find_endpoints(openapi_spec_url, api_base_url, paths, methods):
    print(f"Finding endpoints for {openapi_spec_url} with methods {methods}")
    if openapi_spec_url.startswith(("http://", "https://")):
        response = httpx.get(openapi_spec_url)
        response.raise_for_status()
        content = response.text
    else:
        raise gr.Error("Invalid URL for OpenAPI spec")

    try:
        spec = json.loads(content)
    except json.JSONDecodeError as e:
        raise gr.Error("Invalid JSON for OpenAPI spec")

    api_paths = spec.get("paths", {})
    if not api_paths:
        raise gr.Error("No valid paths found in the OpenAPI specification")

    valid_api_paths = []
    for path, path_item in api_paths.items():
        for method, operation in path_item.items():
            if methods and method.lower() not in [m.lower() for m in methods]:
                continue
            if not paths:
                valid_api_paths.append({
                    "path": path,
                    "method": method.upper(),
                })
            else:
                for path_regex in paths.split(","):
                    if re.match(path_regex, path):
                        valid_api_paths.append({
                            "path": path,
                            "method": method.upper(),
                        })
                        break

    return gr.JSON(valid_api_paths, label=f"🔍 {len(valid_api_paths)} endpoints found")

def update_bottom(oauth_token: gr.OAuthToken | None):
    if oauth_token:
        return "Click the 🚀 Create button to create a new MCP Space", gr.Button(interactive=True)
    else:
        return gr.skip()

gradio_app_code = """
import gradio as gr

gr.load_openapi(
    openapi_spec=\"{}\",
    base_url=\"{}\",
    paths={},
    methods={},
).launch(mcp_server=True)
"""

def create_hf_space(token, space_name, app_code):
    """
    Create a new Hugging Face Space with optional app.py file
    
    Args:
        token (str): Your Hugging Face API token
        space_name (str): The name of the space to create
        app_code (str): String content for the app.py file
    
    Returns:
        SpaceInfo: Information about the created space
    """
    
    api = HfApi(token=token)
    user_info = api.whoami()
    username = user_info["name"]
    space_name = space_name or f"my-mcp-space-{random.randint(100000, 999999)}" 
    space_id = f"{username}/{space_name}"
    
    try:
        gr.Info(f"Creating space {space_id}...", duration=20)
        space_info = api.create_repo(
            repo_id=space_id,
            repo_type="space",
            private=False,
            space_sdk="gradio"
        )
        api.upload_file(
            path_or_fileobj=app_code.encode('utf-8'),
            path_in_repo="app.py",
            repo_id=space_id,
            repo_type="space",
            commit_message="Add app.py"
        )
        space_url = f"https://huggingface.co/spaces/{space_id}"
        gr.Success(f"🚀 Your space will be available at: <a href='{space_url}' target='_blank'>{space_url} ⤴</a>", duration=None)        
        return space_info
        
    except Exception as e:
        gr.Error(f"❌ Error creating space: {str(e)}")


def launch_mcp_server(openapi_spec_url, api_base_url, paths, methods, space_name_box, oauth_token: gr.OAuthToken | None):
    if oauth_token:
        if not paths:
            paths = None
        else:
            paths = f"[\"{paths}\"]"
        create_hf_space(
            oauth_token.token, 
            space_name_box,
            gradio_app_code.format(
                openapi_spec_url,
                api_base_url,
                paths,
                methods
            )
        )
    else:
        pass

with gr.Blocks(theme="ocean") as demo:
    gr.Markdown("## OpenAPI ➪ MCP")
    gr.Markdown("""
    This is a tool that converts an OpenAPI spec to a MCP server that you can launch as a Space and then use with any MCP Client (e.g. ChatGPT, Claude, Cursor, Cline).
    """)
    with gr.Row():
        with gr.Column():
            openapi_spec_url = gr.Textbox(label="OpenAPI Spec URL", value="https://petstore3.swagger.io/api/v3/openapi.json")
            api_base_url = gr.Textbox(label="API Base URL", value="https://petstore3.swagger.io/api/v3/")
            paths = gr.Textbox(label="Optional regex to filter paths by", placeholder=".*user.*")
            methods = gr.CheckboxGroup(label="Methods", choices=["GET", "POST", "PUT", "DELETE"], value=["GET", "POST", "PUT", "DELETE"])
            find_endpoints_button = gr.Button("🔍 Find Endpoints")
        with gr.Column():
            endpoints = gr.JSON(label="🔍 endpoints found", value=[], max_height=400)
            message = gr.Markdown("_Note:_ you must be signed in through your Hugging Face account to create the MCP Space")
            space_name_box = gr.Textbox(show_label=False, placeholder="Optional space name (e.g. my-mcp-space)")
            with gr.Row():
                login_button = gr.LoginButton()
                launch_button = gr.Button("🚀 Create MCP Space", variant="primary", interactive=False)

        gr.on(
            [demo.load, find_endpoints_button.click],
            find_endpoints,
            inputs=[openapi_spec_url, api_base_url, paths, methods],
            outputs=endpoints,
        )

        gr.on(
            [demo.load],
            update_bottom,
            inputs=None,
            outputs=[message, launch_button]
        )

        gr.on(
            [launch_button.click],
            launch_mcp_server,
            inputs=[openapi_spec_url, api_base_url, paths, methods, space_name_box],
            outputs=None
        )

demo.launch()