Update app.py

app.py

@@ -1,58 +1,66 @@
-# Import necessary libraries
-import streamlit as st
+import gradio as gr
 from docx import Document
 import matplotlib.pyplot as plt
 import io
+from collections import Counter
 
-# Function to read data from the Word file
-def extract_data_from_word(file):
+# Function to extract Name and Status from the Word file
+def extract_name_status(file):
     document = Document(file)
-    text = []
+    name_status_list = []
+
     for paragraph in document.paragraphs:
-        text.append(paragraph.text)
-    return " ".join(text)
-
-# Function to calculate performance metric (example)
-def calculate_performance(data):
-    # Dummy calculation: length of the text as a percentage of 1000
-    return min(len(data) / 1000 * 100, 100)  # Cap at 100%
-
-# Function to create a performance meter using matplotlib
-def create_performance_meter(value):
-    fig, ax = plt.subplots(figsize=(6, 3))
-    ax.set_xlim(0, 100)
-    ax.set_ylim(0, 1)
-    ax.barh(0.5, value, color="green", height=0.5, label=f"Performance: {value:.2f}%")
-    ax.barh(0.5, 100 - value, left=value, color="red", height=0.5)
-    ax.set_xticks(range(0, 101, 10))
-    ax.set_yticks([])
-    ax.set_title("Performance Meter", fontsize=16)
-    ax.legend(loc="upper right")
+        if "Name:" in paragraph.text and "Status:" in paragraph.text:
+            parts = paragraph.text.split(",")
+            name_part = next((part for part in parts if "Name:" in part), None)
+            status_part = next((part for part in parts if "Status:" in part), None)
+            
+            if name_part and status_part:
+                name = name_part.split(":")[1].strip()
+                status = status_part.split(":")[1].strip()
+                name_status_list.append((name, status))
+    
+    return name_status_list
+
+# Function to create a bar chart for Name vs Status
+def create_graph(file):
+    data = extract_name_status(file)
+    
+    if not data:
+        return "No valid Name-Status data found in the file."
+
+    names = [item[0] for item in data]
+    statuses = [item[1] for item in data]
+
+    # Count statuses
+    status_counts = Counter(statuses)
+
+    # Plotting the graph
+    fig, ax = plt.subplots(figsize=(8, 6))
+    ax.bar(status_counts.keys(), status_counts.values(), color="skyblue")
+    ax.set_xlabel("Status", fontsize=14)
+    ax.set_ylabel("Count", fontsize=14)
+    ax.set_title("Graph: Name vs Status", fontsize=16)
     plt.tight_layout()
 
-    # Save plot to a BytesIO buffer
+    # Save the plot to a buffer
     buffer = io.BytesIO()
     plt.savefig(buffer, format="png")
     buffer.seek(0)
     return buffer
 
-# Streamlit App
-st.title("Dashboard Meter Application")
-st.write("Upload a Word file to analyze and visualize the performance.")
-
-# File upload section
-uploaded_file = st.file_uploader("Upload a Word file (.docx)", type="docx")
-if uploaded_file:
-    # Step 1: Extract text data
-    data = extract_data_from_word(uploaded_file)
-    st.write("Extracted Text:")
-    st.text_area("Data Preview", value=data, height=200)
-
-    # Step 2: Calculate performance metric
-    performance = calculate_performance(data)
+# Gradio interface
+def interface(file):
+    return create_graph(file)
 
-    # Step 3: Display the performance meter
-    st.write(f"Performance Score: {performance:.2f}%")
-    meter_image = create_performance_meter(performance)
-    st.image(meter_image, caption="Performance Meter")
+# Launch the Gradio app
+inputs = gr.inputs.File(label="Upload Word File (.docx)")
+outputs = gr.outputs.Image(type="file", label="Graph: Name vs Status")
 
+gr.Interface(
+    fn=interface,
+    inputs=inputs,
+    outputs=outputs,
+    title="Name vs Status Graph",
+    description="Upload a Word file containing 'Name: <Name>, Status: <Status>' data to generate a graph."
+).launch()