added form submission handling

.gitignore

@@ -0,0 +1 @@
+.env

app.py

@@ -1,4 +1,5 @@
 import gradio as gr
+import pandas as pd
 from services.huggingface import init_huggingface, update_dataset
 from services.json_generator import generate_json
 from ui.form_components import (
@@ -18,9 +19,13 @@ init_huggingface()
 
 # Create Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("## Data Collection Form")
+    gr.Markdown("## ML-related Data Collection Form")
     gr.Markdown("Welcome to this Huggingface space that helps you fill in a form for monitoring the energy consumption of an AI model.")
 
+
+    csv_upload = gr.File(label="Upload CSV", file_types=[".csv"])
+    gr.Label("Please upload a CSV file with the data you want to analyze.")
+
     # Create form tabs
     header_components = create_header_tab()
     task_components = create_task_tab()
@@ -31,6 +36,116 @@ with gr.Blocks() as demo:
     environment_components = create_environment_tab()
     quality_components = create_quality_tab()
     hash_components = create_hash_tab()
+    
+    # Gather all form components in the order they appear in the inputs
+
+    all_form_components = (
+    header_components          # 11 items (indices 0-10)
+    + task_components          # 28 items (indices 11-38)
+    + measures_components      # 14 items (indices 39-52)
+    + system_components        # 3 items (indices 53-55)
+    + software_components      # 2 items (indices 56-57)
+    + infrastructure_components # 10 items (indices 58-67)
+    + environment_components   # 7 items (indices 68-74)
+    + quality_components       # 1 item (index 75)
+    + hash_components          # 3 items (indices 76-78)
+)
+    
+    # Parse CSV and update form values
+    def parse_csv_and_update_form(csv_file, *current_values):
+        updated_values = list(current_values)
+        if csv_file is None:
+            return updated_values
+        
+        try:
+            df = pd.read_csv(csv_file.name)
+            csv_data = df.iloc[0].to_dict()
+            
+            # ========== HEADER ==========
+            updated_values[3] = csv_data.get('run_id', '')  # reportId (index 3)
+            updated_values[4] = csv_data.get('timestamp', '')  # reportDatetime (4)
+            updated_values[8] = csv_data.get('project_name', '')  # publisher_projectName (8)
+            
+            # ========== SYSTEM ==========
+            updated_values[53] = csv_data.get('os', '')  # os (index 53)
+            updated_values[54] = ""  # distribution (54)
+            updated_values[55] = ""  # distributionVersion (55)
+            
+            # ========== MEASURES ==========
+            updated_values[39] = csv_data.get('tracking_mode', '')  # measurementMethod (39)
+            updated_values[47] = "kWh"  # unit (47)
+            updated_values[50] = csv_data.get('energy_consumed', '')  # powerConsumption (50)
+            
+            # Duration conversion (hours → seconds)
+            if 'duration' in csv_data:
+                try:
+                    hours = float(csv_data['duration'])
+                    updated_values[51] = str(round(hours * 3600, 2))  # measurementDuration (51)
+                except:
+                    updated_values[51] = ""
+            
+            updated_values[52] = ""  # measurementDateTime (52)
+            
+            # ========== SOFTWARE ==========
+            updated_values[56] = "Python"  # language (56)
+            updated_values[57] = csv_data.get('python_version', '')  # version_software (57)
+            
+            # ========== INFRASTRUCTURE ==========
+            # infraType (58) - Dropdown
+            on_cloud = str(csv_data.get('on_cloud', 'No')).lower().strip()
+            updated_values[58] = "publicCloud" if on_cloud == "yes" else "onPremise"
+            
+            # Cloud fields (59-60)
+            updated_values[59] = csv_data.get('cloud_provider', '') if on_cloud == "yes" else ""
+            updated_values[60] = csv_data.get('cloud_region', '') if on_cloud == "yes" else ""
+            
+            # Component logic (61-67)
+            gpu_count = int(csv_data.get('gpu_count', 0))
+            cpu_count = int(csv_data.get('cpu_count', 0))
+            
+            if gpu_count > 0:
+                updated_values[61] = "GPU"  # componentName (61)
+                updated_values[62] = str(gpu_count)  # nbComponent (62)
+                model = csv_data.get('gpu_model', '')
+            elif cpu_count > 0:
+                updated_values[61] = "CPU"  # componentName (61)
+                updated_values[62] = str(cpu_count)  # nbComponent (62)
+                model = csv_data.get('cpu_model', '')
+            else:
+                model = ""
+            
+            # Memory size (63)
+            ram_size = csv_data.get('ram_total_size', '')
+            updated_values[63] = f"{ram_size} GB" if ram_size and float(ram_size) > 0 else ""
+            
+            # Split model into manufacturer/family/series (64-66)
+            if model:
+                parts = model.replace("(R)", "").replace("(TM)", "").split()
+                updated_values[64] = parts[0] if parts else ""  # manufacturer_infra (64)
+                updated_values[65] = " ".join(parts[1:3]) if len(parts) >= 3 else ""  # family (65)
+                updated_values[66] = " ".join(parts[3:]) if len(parts) > 3 else ""  # series (66)
+            else:
+                updated_values[64] = updated_values[65] = updated_values[66] = ""
+            
+            updated_values[67] = ""  # share (67)
+            
+            # ========== ENVIRONMENT ==========
+            updated_values[68] = csv_data.get('country_name', '')  # country (68)
+            updated_values[69] = csv_data.get('latitude', '')  # latitude (69)
+            updated_values[70] = csv_data.get('longitude', '')  # longitude (70)
+            updated_values[71] = csv_data.get('region', '')  # location (71)
+            
+        except Exception as e:
+            print(f"CSV Processing Error: {str(e)}")
+        
+        return updated_values
+
+    # Parse CSV and update form values
+    csv_upload.change(
+        fn=parse_csv_and_update_form,
+        inputs=[csv_upload] + all_form_components,
+        outputs=all_form_components
+    )
 
     # Submit and Download Buttons
     submit_button = gr.Button("Submit")
@@ -59,5 +174,9 @@ with gr.Blocks() as demo:
         outputs=output
     )
 
+
+
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()
+
+

services/huggingface.py

@@ -1,3 +1,6 @@
+from dotenv import load_dotenv
+load_dotenv('/home/hlymly/Documents/rse/group1/EcoMindAI/.env')  # Load .env before importing config.py
+
 from huggingface_hub import login
 from datasets import load_dataset, Dataset, concatenate_datasets
 import json