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import gradio as gr

models = [
    {"name": "Claudfuen 1", "url": "claudfuen/photorealistic-fuen-v1"},
    {"name": "Deliberate", "url": "Masagin/Deliberate"},
    {"name": "Seek Art Mega", "url": "coreco/seek.art_MEGA"},
    {"name": "Realistic Vision 1.4", "url": "SG161222/Realistic_Vision_V1.4"},
    {"name": "Dreamshaper", "url": "Lykon/DreamShaper"},
]

current_model = models[0]

text_gen = gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion_link")

models2 = []
for model in models:
    model_url = f"models/{model['url']}"
    loaded_model = gr.Interface.load(model_url, live=True, preprocess=True)
    models2.append(loaded_model)


def text_it(inputs, text_gen=text_gen):
    return text_gen(inputs)


def set_model(current_model_index):
    global current_model
    current_model = models[current_model_index]
    return gr.update(label=f"{current_model['name']}")


def send_it(inputs, model_choice):
    proc = models2[model_choice]
    return proc(inputs)


css = """
<style>
    .searchable-dropdown {
        position: relative;
    }

    .searchable-dropdown input {
        width: 100%;
        padding: 0.5rem;
        border-radius: 5px;
        border: 1px solid #ccc;
    }

    .searchable-dropdown select {
        width: 100%;
        padding: 0.5rem;
        border-radius: 5px;
        border: 1px solid #ccc;
        position: absolute;
        top: 0;
        left: 0;
        opacity: 0;
        pointer-events: none;
    }
</style>
"""


def make_dropdown_searchable(dropdown_id):
    script = f"""
    <script>
        function makeDropdownSearchable(dropdownId) {{
            const input = document.getElementById(dropdownId);
            input.addEventListener("input", function() {{
                const value = this.value.toLowerCase();
                const options = Array.from(document.querySelectorAll(`#${dropdownId} option`));
                let found = false;
                for (let i = 0; i < options.length; i++) {{
                    const option = options[i];
                    const text = option.text.toLowerCase();
                    const match = text.includes(value);
                    option.style.display = match ? "block" : "none";
                    if (match) {{
                        found = true;
                    }}
                }}
                if (value && !found) {{
                    const firstOption = options[0];
                    if (firstOption) {{
                        firstOption.selected = true;
                    }}
                }}
            }});
        }}

        makeDropdownSearchable("{dropdown_id}");
    </script>
    """
    return gr.outputs.HTML(script)


with gr.Interface(
    fn=text_it,
    inputs="text",
    outputs="text",
    css=css,
    capture_session=True
) as iface:
    model_dropdown = gr.inputs.Dropdown(
        label="Choose Model",
        choices=[m["name"] for m in models],
        type="index",
        value=current_model["name"],
        interactive=True,
        component_id="model_dropdown"
I apologize for the incomplete code. It seems that there was an error in the last part. Here's the corrected code:

```python
import gradio as gr

models = [
    {"name": "Claudfuen 1", "url": "claudfuen/photorealistic-fuen-v1"},
    {"name": "Deliberate", "url": "Masagin/Deliberate"},
    {"name": "Seek Art Mega", "url": "coreco/seek.art_MEGA"},
    {"name": "Realistic Vision 1.4", "url": "SG161222/Realistic_Vision_V1.4"},
    {"name": "Dreamshaper", "url": "Lykon/DreamShaper"},
]

current_model = models[0]

text_gen = gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion_link")

models2 = []
for model in models:
    model_url = f"models/{model['url']}"
    loaded_model = gr.Interface.load(model_url, live=True, preprocess=True)
    models2.append(loaded_model)


def text_it(inputs, text_gen=text_gen):
    return text_gen(inputs)


def set_model(current_model_index):
    global current_model
    current_model = models[current_model_index]
    return gr.outputs.Label(f"Current Model: {current_model['name']}")


def send_it(inputs, model_choice):
    proc = models2[model_choice]
    return proc(inputs)


css = """
<style>
    .searchable-dropdown {
        position: relative;
    }

    .searchable-dropdown input {
        width: 100%;
        padding: 0.5rem;
        border-radius: 5px;
        border: 1px solid #ccc;
    }

    .searchable-dropdown select {
        width: 100%;
        padding: 0.5rem;
        border-radius: 5px;
        border: 1px solid #ccc;
        position: absolute;
        top: 0;
        left: 0;
        opacity: 0;
        pointer-events: none;
    }
</style>
"""


def make_dropdown_searchable(dropdown_id):
    script = f"""
    <script>
        function makeDropdownSearchable(dropdownId) {{
            const input = document.getElementById(dropdownId);
            input.addEventListener("input", function() {{
                const value = this.value.toLowerCase();
                const options = Array.from(document.querySelectorAll(`#${dropdownId} option`));
                let found = false;
                for (let i = 0; i < options.length; i++) {{
                    const option = options[i];
                    const text = option.text.toLowerCase();
                    const match = text.includes(value);
                    option.style.display = match ? "block" : "none";
                    if (match) {{
                        found = true;
                    }}
                }}
                if (value && !found) {{
                    const firstOption = options[0];
                    if (firstOption) {{
                        firstOption.selected = true;
                    }}
                }}
            }});
        }}

        makeDropdownSearchable("{dropdown_id}");
    </script>
    """
    return gr.outputs.HTML(script)


iface = gr.Interface(
    fn=text_it,
    inputs="text",
    outputs="text",
    css=css,
    capture_session=True
)

model_dropdown = gr.inputs.Dropdown(
    label="Choose Model",
    choices=[m["name"] for m in models],
    type="index",
    value=current_model["name"],
    interactive=True,
    description="Select the model to use for text generation"
)

iface.add_input(model_dropdown, set_model)
iface.add_input("text", send_it, "output")
iface.launch()