Update app.py

app.py

@@ -1,36 +1,28 @@
 import spaces
-import gradio as gr
 from model_runner import ModelRunner
 from parser import parse_to_files
 from zip_util import make_zip_from_files
-import os
+import gradio as gr
 
-# Path or model identifier for your GGUF model
-MODEL_PATH = os.environ.get("tHottie/NeuralDaredevil-8B-abliterated-Q4_K_M-GGUF", "neuraldaredevil-8b-abliterated-q4_k_m-imat.gguf")
+# Same model you referenced
+MODEL_REPO = "tHottie/NeuralDaredevil-8B-abliterated-Q4_K_M-GGUF"
+MODEL_FILE = "neuraldaredevil-8b-abliterated-q4_k_m-imat.gguf"
 
-# Instantiate once
-runner = ModelRunner(MODEL_PATH)
+runner = ModelRunner(repo_id=MODEL_REPO, filename=MODEL_FILE)
 
-@spaces.GPU(duration=120)
-def process_and_zip(ai_response: str) -> str:
-    """
-    Given the pasted AI response, do model interpretation → parse → zip → return zip path
-    """
+@spaces.GPU(duration=120) 
+def process_and_zip(ai_response: str):
     model_output = runner.interpret_code_description(ai_response)
     file_list = parse_to_files(model_output)
     zip_path = make_zip_from_files(file_list)
     return zip_path
 
 with gr.Blocks() as demo:
-    gr.Markdown("### Paste your AI model response (with code descriptions) below")
-    input_box = gr.Textbox(lines=15, placeholder="Paste AI response here")
-    output_zip = gr.DownloadButton(
-        "Download code zip",
-        value=lambda resp: resp,  # will be provided after processing
-    )
-    submit = gr.Button("Generate Code Bundle")
+    gr.Markdown("### Paste your AI output with multiple files below:")
+    input_box = gr.Textbox(lines=15, placeholder="Paste codegen or AI output here...")
+    submit = gr.Button("Generate Zip")
+    download = gr.File(label="Download zip")
 
-    # When clicked, run process_and_zip
-    submit.click(fn=process_and_zip, inputs=input_box, outputs=output_zip)
+    submit.click(fn=process_and_zip, inputs=input_box, outputs=download)
 
 demo.launch()