updated interface and error handling

app.py

@@ -8,6 +8,8 @@ import gradio as gr
 from huggingface_hub import HfApi
 from huggingface_hub import ModelCard
 
+from gradio_huggingfacehub_search import HuggingfaceHubSearch
+
 from textwrap import dedent
 
 HF_PATH = "https://huggingface.co/"
@@ -69,8 +71,14 @@ QUANTIZATIONS = ["q0f16",
                  "q4f16_awq"]
 
 def button_click(hf_model_id, conv_template, quantization, oauth_token: gr.OAuthToken | None):
-    if not oauth_token.token:
-        raise ValueError("Log in to Huggingface to use this")
+    if oauth_token.token == None:
+        return "Log in to Huggingface to use this"
+    elif not hf_model_id:
+        return "Enter a Huggingface model ID"
+    elif not conv_template:
+        return "Select a conversation template"
+    elif not quantization:
+        return "Select a quantization method"
     
     api = HfApi(token=oauth_token.token)
     model_dir_name = hf_model_id.split("/")[1]
@@ -81,13 +89,17 @@ def button_click(hf_model_id, conv_template, quantization, oauth_token: gr.OAuth
 
     api.snapshot_download(repo_id=hf_model_id, local_dir=f"./dist/models/{model_dir_name}")
 
-    os.system("mlc_llm convert_weight ./dist/models/" + model_dir_name + "/" + \
+    convert_weight_result = subprocess.run(["mlc_llm convert_weight ./dist/models/" + model_dir_name + "/" + \
               " --quantization " + quantization + \
-              " -o dist/" + mlc_model_name)
+              " -o dist/" + mlc_model_name], shell=True, capture_output=True, text=True)
+    if convert_weight_result.stderr:
+        return convert_weight_result.stderr
     
-    os.system("mlc_llm gen_config ./dist/models/" + model_dir_name + "/" + \
+    gen_config_result = subprocess.run(["mlc_llm gen_config ./dist/models/" + model_dir_name + "/" + \
               " --quantization " + quantization + " --conv-template " + conv_template + \
-              " -o dist/" + mlc_model_name + "/")
+              " -o dist/" + mlc_model_name + "/"], shell=True, capture_output=True, text=True)
+    if gen_config_result.stderr:
+        return gen_config_result.stderr
     
     # push to HF
     user_name = api.whoami()["name"]
@@ -131,11 +143,20 @@ def button_click(hf_model_id, conv_template, quantization, oauth_token: gr.OAuth
 
     os.system("rm -rf dist/")
     
-    return "Successful"
+    return "Successful, please find your compiled LLM model on your personal account"
 
 with gr.Blocks() as demo:
     gr.LoginButton()
-    model_id = gr.Textbox(label="HF Model ID")
+    gr.Markdown(
+    """
+    # Compile your LLM model with MLC-LLM and run it locally!
+    ### This space takes in Huggingface model ID, and converts it for you using your selected conversation template and quantization method!
+    """)
+    model_id = HuggingfaceHubSearch(
+        label="HF Model ID",
+        placeholder="Search for your model on Huggingface",
+        search_type="model",
+    )
     conv = gr.Dropdown(CONV_TEMPLATES, label="Conversation Template")
     quant = gr.Dropdown(QUANTIZATIONS, label="Quantization Method")
     btn = gr.Button("Convert to MLC")