Delete app.py

app.py

@@ -1,77 +0,0 @@
-import gradio as gr
-from llama_cpp import Llama
-import os
-
-# Initialize the model
-model_path = "medgemma-4b-it-q4_k_m.gguf"
-llm = Llama(
-    model_path=model_path,
-    n_ctx=2048,  # Context window
-    n_threads=2,  # Use 2 threads for free CPU
-    n_gpu_layers=0  # CPU only
-)
-
-def medical_orchestrator(user_input, symptoms, history):
-    """
-    Main orchestration function for Nivra
-    Takes user symptoms and coordinates between ClinicalBERT results
-    """
-    prompt = f"""
-    You are Nivra, an Indian AI healthcare assistant. You are a helpful medical advisor. 
-    Though unlicensed and uncertified, you possess the medical knowledge required to assist people with clinical advice
-    
-Based on the following symptoms and clinical analysis, provide a clear, 
-empathetic response in simple language understandable to Indian patients.
-
-Symptoms: {symptoms}
-User Question: {user_input}
-
-Provide:
-1. A brief explanation of possible conditions
-2. Severity assessment
-3. Immediate actions to take
-4. When to seek medical attention
-
-Response:"""
-    
-    response = llm(
-        prompt,
-        max_tokens=512,
-        temperature=0.3,  # Lower for medical accuracy
-        top_p=0.9,
-        stop=["User:", "Symptoms:"]
-    )
-    
-    return response['choices'][0]['text']
-
-# Gradio Interface
-with gr.Blocks() as demo:
-    gr.Markdown("# Nivra Medical AI Orchestrator")
-    
-    with gr.Row():
-        with gr.Column():
-            symptoms_input = gr.Textbox(
-                label="Symptoms (from ClinicalBERT)",
-                placeholder="Enter detected symptoms...",
-                lines=3
-            )
-            user_query = gr.Textbox(
-                label="User Question",
-                placeholder="Ask about your symptoms...",
-                lines=2
-            )
-            submit_btn = gr.Button("Get Medical Guidance")
-        
-        with gr.Column():
-            output = gr.Textbox(
-                label="Nivra's Response",
-                lines=10
-            )
-    
-    submit_btn.click(
-        fn=medical_orchestrator,
-        inputs=[user_query, symptoms_input, gr.State([])],
-        outputs=output
-    )
-
-demo.launch()