Testing

app.py

@@ -1,13 +1,53 @@
-from transformers import pipeline
+import gradio as gr
 
-# Load the fine-tuned model from Hugging Face
-generator = pipeline("text2text-generation", model="DetectiveShadow/inspiration-message-generator")
+def readiness_predictor(
+    savings, income, bills, entertainment, sales_skills, dependents, assets, age
+):
+    # Simple heuristic formula for "entrepreneurial readiness"
+    disposable_income = income - bills - entertainment
+    score = (
+        (savings + assets) / 1000
+        + disposable_income / 500
+        + sales_skills * 2
+        - dependents
+        + (40 - abs(35 - age)) / 5
+    )
+    score = max(0, min(100, score))  # clamp between 0 and 100
+    
+    if score < 30:
+        prediction = "Low readiness"
+    elif score < 60:
+        prediction = "Moderate readiness"
+    else:
+        prediction = "High readiness"
+    
+    return {
+        "Readiness Score": round(score, 2),
+        "Prediction": prediction
+    }
 
-# Define test prompt
-prompt = "Age: 32 | Profession: Engineer | Archetype: Innovator"
+with gr.Blocks() as demo:
+    gr.Markdown("# Entrepreneurial Readiness Predictor")
+    
+    with gr.Row():
+        with gr.Column():
+            savings = gr.Number(label="Savings Amount ($)", value=1000)
+            income = gr.Number(label="Monthly Income ($)", value=4000)
+            bills = gr.Number(label="Monthly Bills ($)", value=2500)
+            entertainment = gr.Number(label="Monthly Entertainment ($)", value=300)
+            sales_skills = gr.Slider(label="Sales Skills (1–5)", minimum=1, maximum=5, step=1, value=3)
+            dependents = gr.Slider(label="Dependents (0–6)", minimum=0, maximum=6, step=1, value=1)
+            assets = gr.Number(label="Assets ($)", value=8000)
+            age = gr.Number(label="Age", value=28)
+            
+        with gr.Column():
+            output = gr.JSON(label="Prediction")
+            btn = gr.Button("Predict")
+            btn.click(
+                readiness_predictor,
+                inputs=[savings, income, bills, entertainment, sales_skills, dependents, assets, age],
+                outputs=output
+            )
 
-# Run model
-result = generator(prompt, max_new_tokens=100)[0]["generated_text"]
+demo.launch()
 
-# Print output
-print(result)