add instruction and mcp

app.py

@@ -5,7 +5,23 @@ heinsight = HeinSight(vial_model_path="models/best_vessel.pt",
                       config=HeinSightConfig())
 
 import gradio as gr
+description = """
+[🔗 HeinSight GitLab Repository](https://gitlab.com/heingroup/heinsight4.0)
 
+HeinSight detects vials and their contents in a single vessel image.
+
+**Instructions:**
+- Upload an image of a container (e.g., a HPLC vial or a reactor).
+- Adjust the **Cap Size Ratio** slider if there is a lid on the vial.This ratio helps the detector estimate the relative size of the vial caps.
+- The output image will highlight detection zones with detected classes. JSON output lists contents info.
+
+**Classifications:**
+- **🟫 Empty**: No liquid; dry walls above expected fill line.
+- **🟧 Residue**: Visible solid deposit or stain above liquid level.
+- **🟥 Homogeneous**: Clear liquid, optically uniform.
+- **🟪 Heterogeneous**: Cloudy, turbid, or with phase separation.
+- **🟦 Solid**: Dispersed solid in liquid or a separate solid phase visible.
+"""
 # Gradio UI
 demo = gr.Interface(
     fn=heinsight.image_demo,
@@ -18,9 +34,9 @@ demo = gr.Interface(
         gr.JSON(label="Detection Info")  # or gr.Textbox() if you prefer plain text
     ],
     title="HeinSight",
-    description="Upload an image with vials to detect their contents"
+    description=description
 )
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(mcp_server=True)