Update app.py

app.py

@@ -1,36 +1,73 @@
+# app.py
 import gradio as gr
 import os
-from openai import OpenAI
+from data_service import DataAssessmentService
+import json
 
-# Initialize OpenAI client
-client = OpenAI(
-    api_key=os.environ.get("OPENAI_API_KEY"),
-)
+# Initialize service
+service = DataAssessmentService(api_key=os.environ.get("OPENAI_API_KEY"))
 
-def generate_response(prompt):
+def process_request(request_text: str) -> str:
+    """Process the data request and return formatted results"""
     try:
-        response = client.chat.completions.create(
-            model="gpt-4o-mini",  # Note: "gpt-4o-mini" is not a valid model name
-            messages=[
-                {
-                    "role": "user",
-                    "content": prompt,  # Use the actual prompt instead of hardcoded text
-                }
-            ]
-        )
-        # The correct way to access the response content
-        return response.choices[0].message.content
+        result = service.assess_request(request_text)
+        return json.dumps(result, indent=2)
     except Exception as e:
-        return f"Error: {str(e)}"
+        return json.dumps({
+            "status": "error",
+            "message": str(e)
+        }, indent=2)
+
+demo_text = """Example requests:
+1. "Show me OPD patients from January 2024, including their diagnoses and waiting times"
+2. "Get all emergency surgeries from last month with their durations and costs"
+3. "List top 100 diagnoses from pediatric clinic in 2023"
+"""
 
 # Create Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("## Test OpenAI GPT API")
-    user_input = gr.Textbox(label="Enter your prompt")
-    output = gr.Textbox(label="GPT Response")
-    submit = gr.Button("Generate Response")
+    gr.Markdown("# Hospital Data Assessment Service")
+    gr.Markdown("Enter your data request in English to find available reports and data sources.")
+    
+    with gr.Row():
+        request_input = gr.Textbox(
+            label="Data Request",
+            placeholder="Example: I need information about OPD patients who visited in January 2024, including their diagnoses and treating doctors",
+            lines=3
+        )
+    
+    with gr.Row():
+        submit_btn = gr.Button("Analyze Request")
+        clear_btn = gr.Button("Clear")
     
-    submit.click(generate_response, inputs=user_input, outputs=output)
+    with gr.Row():
+        output = gr.Textbox(
+            label="Analysis Result",
+            lines=10,
+            show_copy_button=True
+        )
+    
+    with gr.Accordion("Example Requests", open=False):
+        gr.Markdown(demo_text)
+    
+    submit_btn.click(
+        fn=process_request,
+        inputs=[request_input],
+        outputs=[output]
+    )
+    
+    clear_btn.click(
+        fn=lambda: (None, None),
+        inputs=[],
+        outputs=[request_input, output]
+    )
+
+    gr.Markdown("""
+    ### Notes:
+    - Please provide specific date ranges when requesting data
+    - The system will check availability across OPD, IPD, OR, and other hospital systems
+    - Results will show which reports are immediately available and which need additional processing
+    """)
 
 if __name__ == "__main__":
     demo.launch()