Update app.py

app.py

@@ -1,135 +1,68 @@
 # app.py
-
 import os
-
 import gradio as gr
-
 import keras
-
 import keras_hub
-
 from huggingface_hub import from_pretrained_keras
 
-
-
 # Set Keras backend
-
 os.environ["KERAS_BACKEND"] = "jax"
-
 os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = "1.00"
 
-
-
 # --- 1. LOAD THE MERGED MODEL FROM THE HUB ---
-
-# !!! IMPORTANT: Change this to your username and repo name !!!
-
-repo_id = "Tarive/lora_research_abstracts" 
+# Make sure this repo_id is correct and does not have any hidden characters at the end
+repo_id = "Tarive/lora_research_abstracts"
 print(f"Loading merged model from Hub: {repo_id}")
 gemma_lm = from_pretrained_keras(repo_id)
 
-
-
 # Compile the model with a sampler for generation
-
 gemma_lm.compile(sampler=keras_hub.samplers.TopKSampler(k=5))
-
 print("Model loaded and compiled successfully.")
 
-
-
-
-
 # --- 2. DEFINE THE INFERENCE FUNCTION ---
-
 def revise_abstract(draft_abstract, grant_type):
-
-    if not draft_abstract or not grant_type:
-
-        return "Error: Please provide both a draft abstract and a grant type."
-
-
-
-    template = (
-
-        "Instruction:\n"
-
-        "You are an expert grant writer. Rewrite the following draft abstract to be more impactful and clear, "
-
-        "following the specific conventions of a {activity_code} grant. Ensure the most compelling claims are front-loaded.\n\n"
-
-        "Input Draft:\n"
-
-        "{unoptimized_abstract}\n\n"
-
-        "Revised Abstract:"
-
-    )
-
-    prompt = template.format(unoptimized_abstract=draft_abstract, activity_code=grant_type)
-
-    output = gemma_lm.generate(prompt, max_length=1024)
-
-    
-
-    parts = output.split("Revised Abstract:")
-
-    return parts[1].strip() if len(parts) > 1 else output.strip()
-
-
+    if not draft_abstract or not grant_type:
+        return "Error: Please provide both a draft abstract and a grant type."
+
+    template = (
+        "Instruction:\n"
+        "You are an expert grant writer. Rewrite the following draft abstract to be more impactful and clear, "
+        "following the specific conventions of a {activity_code} grant. Ensure the most compelling claims are front-loaded.\n\n"
+        "Input Draft:\n"
+        "{unoptimized_abstract}\n\n"
+        "Revised Abstract:"
+    )
+    prompt = template.format(unoptimized_abstract=draft_abstract, activity_code=grant_type)
+    output = gemma_lm.generate(prompt, max_length=1024)
+    
+    parts = output.split("Revised Abstract:")
+    return parts[1].strip() if len(parts) > 1 else output.strip()
 
 # --- 3. CREATE THE GRADIO INTERFACE ---
-
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-
-    gr.Markdown("# Grant Abstract Revision Tool (Fine-Tuned on Gemma)")
-
-    gr.Markdown("Enter a draft abstract and select its grant type. The model will rewrite it to be more impactful, based on patterns from successfully funded NIH grants.")
-
-    
-
-    with gr.Row():
-
-        draft_input = gr.Textbox(lines=15, label="Input Draft Abstract", placeholder="Paste your draft abstract here...")
-
-        grant_type_input = gr.Dropdown(
-
-            ["R01", "R21", "F32", "T32", "P30", "R41", "R43", "R44", "K99"], 
-
-            label="Grant Type (Activity Code)",
-
-            info="Select the grant mechanism you are targeting."
-
-        )
-
-    
-
-    submit_button = gr.Button("Revise Abstract", variant="primary")
-
-    revised_output = gr.Textbox(lines=15, label="Model's Revised Abstract", interactive=False)
-
-    
-
-    submit_button.click(fn=revise_abstract, inputs=[draft_input, grant_type_input], outputs=revised_output)
-
-    
-
-    gr.Examples(
-
-        examples=[
-
-            ["SUMMARY \nA pressing concern exists regarding lead poisoning...This study aimed to optimize and validate a dried blood spot collection device...", "R41"],
-
-            ["This project is about figuring out how macrophages and S. flexneri interact...Our study will look at this in vitro and in vivo...", "R21"]
-
-        ],
-
-        inputs=[draft_input, grant_type_input]
-
-    )
-
-
+    gr.Markdown("# Grant Abstract Revision Tool (Fine-Tuned on Gemma)")
+    gr.Markdown("Enter a draft abstract and select its grant type. The model will rewrite it to be more impactful, based on patterns from successfully funded NIH grants.")
+    
+    with gr.Row():
+        draft_input = gr.Textbox(lines=15, label="Input Draft Abstract", placeholder="Paste your draft abstract here...")
+        grant_type_input = gr.Dropdown(
+            ["R01", "R21", "F32", "T32", "P30", "R41", "R43", "R44", "K99"],
+            label="Grant Type (Activity Code)",
+            info="Select the grant mechanism you are targeting."
+        )
+    
+    submit_button = gr.Button("Revise Abstract", variant="primary")
+    revised_output = gr.Textbox(lines=15, label="Model's Revised Abstract", interactive=False)
+    
+    submit_button.click(fn=revise_abstract, inputs=[draft_input, grant_type_input], outputs=revised_output)
+    
+    gr.Examples(
+        examples=[
+            ["SUMMARY \nA pressing concern exists regarding lead poisoning...This study aimed to optimize and validate a dried blood spot collection device...", "R41"],
+            ["This project is about figuring out how macrophages and S. flexneri interact...Our study will look at this in vitro and in vivo...", "R21"]
+        ],
+        inputs=[draft_input, grant_type_input]
+    )
 
 print("Launching Gradio app...")
-
 demo.launch()