Update app.py

app.py

@@ -1,3 +1,4 @@
+import gradio as gr
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -213,7 +214,11 @@ def generate_project_timeline(boq_file, weather, workforce, location, project_ti
         output_path = os.path.join(temp_dir, output_filename)
         logger.debug(f"Gantt chart will be saved to: {output_path}")
 
-        df = pd.read_csv(boq_file)
+        if isinstance(boq_file, str):
+            df = pd.read_csv(boq_file)
+        else:
+            df = pd.read_csv(boq_file.name)
+
         if "Task Name" not in df.columns or "Duration" not in df.columns:
             raise ValueError("CSV must contain 'Task Name' and 'Duration' columns")
 
@@ -242,6 +247,116 @@ def generate_project_timeline(boq_file, weather, workforce, location, project_ti
             shutil.rmtree(temp_dir)
         return None, str(e), None
 
+# Gradio interface function
+def gradio_interface(boq_file, weather, workforce, location, project_title):
+    temp_dir = None
+    try:
+        logger.info("Starting gradio_interface...")
+        if not boq_file:
+            return None, "Error: No BOQ file uploaded"
+
+        boq_file_path = boq_file.name if hasattr(boq_file, 'name') else boq_file
+        file_path, risk_tags, temp_dir = generate_project_timeline(boq_file_path, weather, workforce, location, project_title)
+        if not file_path:
+            return None, f"Error: Failed to generate timeline: {risk_tags}"
+
+        df = pd.read_csv(boq_file_path)
+        estimated_duration = sum(df["Duration"])
+        ai_plan_score = min(100, max(0, 100 - (estimated_duration / 100)))
+        logger.debug(f"Estimated duration: {estimated_duration}, AI plan score: {ai_plan_score}")
+
+        record_id = send_to_salesforce(
+            project_title=project_title,
+            gantt_chart_url="",
+            ai_plan_score=ai_plan_score,
+            estimated_duration=estimated_duration,
+            status="Draft",
+            record_id=None,
+            location=location,
+            weather_type=weather
+        )
+        
+        if not record_id:
+            return None, f"Error: Failed to create Salesforce record - check logs for details\n\nRisk Tags:\n{risk_tags}"
+
+        work_items_id = upload_file_to_salesforce(boq_file_path, "Boq_data.csv", record_id)
+        if not work_items_id:
+            logger.warning("Failed to upload BOQ file, but proceeding with record creation")
+
+        record_data = {
+            "project_title": project_title,
+            "estimated_duration": estimated_duration,
+            "ai_plan_score": ai_plan_score,
+            "status": "Draft",
+            "risk_tags": risk_tags,
+        }
+        pdf_file = generate_pdf(record_data)
+        if not pdf_file:
+            logger.warning("Failed to generate PDF, but proceeding with record creation")
+
+        pdf_content_id, pdf_url = None, None
+        if pdf_file:
+            pdf_content_id, pdf_url = upload_pdf_to_salesforce(pdf_file, project_title, record_id)
+            if not pdf_content_id:
+                logger.warning("Failed to upload PDF, but proceeding with record creation")
+
+        update_result = send_to_salesforce(
+            project_title=project_title,
+            gantt_chart_url=pdf_url if pdf_url else "",
+            ai_plan_score=ai_plan_score,
+            estimated_duration=estimated_duration,
+            status="Draft",
+            record_id=record_id,
+            location=location,
+            weather_type=weather,
+            work_items_id=work_items_id if work_items_id else ""
+        )
+        if not update_result:
+            logger.warning("Failed to update record with PDF URL, but record was created")
+
+        image_content_id = upload_file_to_salesforce(fileLf_path, f"{project_title}_Gantt_Chart.png", record_id)
+        image_url = None
+        if image_content_id:
+            sf = get_salesforce_connection()
+            if sf:
+                image_url = f"https://{sf.sf_instance}/sfc/servlet.shepherd/version/download/{image_content_id}"
+                logger.debug(f"Generated image URL: {image_url}")
+
+        logger.info("Gradio interface completed successfully.")
+        return image_url if image_url else file_path, f"Successfully created Salesforce record ID: {record_id}\n\nRisk Tags:\n{risk_tags}"
+    except Exception as e:
+        logger.error(f"Error in Gradio interface: {str(e)}", exc_info=True)
+        return None, f"Error in Gradio interface: {str(e)}"
+    finally:
+        if temp_dir and os.path.exists(temp_dir):
+            shutil.rmtree(temp_dir)
+            logger.debug(f"Cleaned up temporary directory: {temp_dir}")
+
+# Create Gradio interface
+demo = gr.Blocks(theme="default")
+with demo:
+    gr.Markdown("## AI Civil Work Planner")
+    gr.Markdown("Generate a project timeline (Gantt chart) and risk tags based on BOQ data and site parameters.")
+
+    with gr.Row():
+        with gr.Column():
+            boq_file = gr.File(label="Upload BOQ Data (CSV format)")
+            weather = gr.Dropdown(label="Weather", choices=["sunny", "rainy", "cloudy"], value="sunny")
+            workforce = gr.Number(label="Workforce Size", value=10, precision=0)
+            location = gr.Textbox(label="Location", placeholder="Enter project location")
+            project_title = gr.Textbox(label="Project Title", placeholder="Enter project title")
+            submit_btn = gr.Button("Generate Timeline")
+
+        with gr.Column():
+            output_image = gr.Image(label="Gantt Chart")
+            risk_tags = gr.Textbox(label="Risk Tags and Salesforce Status")
+
+    submit_btn.click(
+        fn=gradio_interface,
+        inputs=[boq_file, weather, workforce, location, project_title],
+        outputs=[output_image, risk_tags],
+    )
+
 # Create a FastAPI app with CORS support
 app = FastAPI()
 app.add_middleware(
@@ -361,5 +476,5 @@ async def api_gradio_interface(
             logger.debug(f"Cleaned up temporary directory: {temp_dir}")
 
 if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    # Run Gradio UI
+    demo.launch(server_name="0.0.0.0", server_port=7860)