Create app.py

app.py

@@ -0,0 +1,118 @@
+import gradio as gr
+import torch
+import json
+from pathlib import Path
+from model import (
+    GreesyGPT, 
+    generate_moderation, 
+    ReasoningMode, 
+    OutputFormat, 
+    DEVICE,
+    describe_reasoning_modes
+)
+
+# 1. Initialize Model
+model = GreesyGPT()
+weights_path = Path("greesy_gpt.pt")
+
+if weights_path.exists():
+    model.load_state_dict(torch.load(weights_path, map_location=DEVICE))
+    print(f"Loaded weights from {weights_path}")
+else:
+    print("Warning: No trained weights found. Using fresh initialization.")
+
+model.to(DEVICE)
+model.eval()
+
+def moderate(text, mode_str, format_str):
+    if not text.strip():
+        return "Please enter some text to analyze.", ""
+
+    # Map strings from UI to Enums
+    mode = ReasoningMode(mode_str.lower())
+    fmt = OutputFormat(format_str.lower())
+
+    # Generate
+    result = generate_moderation(
+        model, 
+        prompt=text, 
+        mode=mode, 
+        output_format=fmt
+    )
+
+    verdict_output = result["verdict_fmt"]
+    # If JSON format is selected, prettify it for the textbox
+    if fmt == OutputFormat.JSON:
+        verdict_output = json.dumps(verdict_output, indent=2)
+    
+    thinking_process = result.get("thinking", "No reasoning generated.")
+    
+    return verdict_output, thinking_process
+
+# 2. Build Gradio UI
+theme = gr.themes.Soft(
+    primary_hue="orange",
+    secondary_hue="gray",
+)
+
+with gr.Blocks(theme=theme, title="GreesyGPT Content Moderation") as demo:
+    gr.Markdown("# 🛡️ GreesyGPT Content Moderation")
+    gr.Markdown(
+        "A reasoning-based safety model that analyzes content for violations "
+        "using chain-of-thought deliberation."
+    )
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            input_text = gr.Textbox(
+                label="Message to Review",
+                placeholder="Type the message you want to moderate here...",
+                lines=5
+            )
+            
+            with gr.Row():
+                mode_dropdown = gr.Dropdown(
+                    choices=[m.value for m in ReasoningMode],
+                    value="low",
+                    label="Reasoning Mode",
+                    info="Higher modes are more thorough but slower."
+                )
+                format_dropdown = gr.Dropdown(
+                    choices=[f.value for f in OutputFormat],
+                    value="markdown",
+                    label="Output Format"
+                )
+            
+            submit_btn = gr.Button("Analyze Content", variant="primary")
+
+        with gr.Column(scale=3):
+            output_verdict = gr.Markdown(label="Verdict")
+            
+            with gr.Accordion("View Internal Reasoning (Thinking Process)", open=False):
+                output_thinking = gr.Textbox(
+                    label="Chain of Thought",
+                    interactive=False,
+                    lines=10
+                )
+
+    gr.Examples(
+        examples=[
+            ["You're so stupid, nobody likes you.", "medium", "markdown"],
+            ["How do I fix a bug in my Python code?", "none", "markdown"],
+            ["CONGRATULATIONS! You won a $1000 gift card! Click here!", "low", "json"],
+            ["I feel really hopeless and don't want to continue.", "high", "markdown"],
+        ],
+        inputs=[input_text, mode_dropdown, format_dropdown]
+    )
+
+    with gr.Expander("System Information"):
+        gr.Code(describe_reasoning_modes(), language="text")
+
+    submit_btn.click(
+        fn=moderate,
+        inputs=[input_text, mode_dropdown, format_dropdown],
+        outputs=[output_verdict, output_thinking]
+    )
+
+if __name__ == "__main__":
+    demo.launch()