Update app.py

app.py

@@ -1,41 +1,46 @@
 import gradio as gr
-import matplotlib.pyplot as plt
-import seaborn as sns
-import numpy as np
-import pandas as pd
-import plotly.express as px
+import requests
+from PIL import Image
+from io import BytesIO
+import os
 
-# Function to generate graphical output based on topic
-def generate_graph(topic):
-    # Example function that generates a bar chart for demonstration
-    if topic.lower() == 'animals':
-        data = {'Animals': ['Lion', 'Tiger', 'Bear', 'Elephant'],
-                'Count': [10, 12, 5, 8]}
-        df = pd.DataFrame(data)
-        fig = px.bar(df, x='Animals', y='Count', title='Animal Count')
-    elif topic.lower() == 'fruits':
-        data = {'Fruit': ['Apple', 'Banana', 'Cherry', 'Date'],
-                'Count': [20, 15, 30, 10]}
-        df = pd.DataFrame(data)
-        fig = px.pie(df, names='Fruit', values='Count', title='Fruit Distribution')
-    else:
-        # Default graph if no matching topic
-        data = {'Topic': ['A', 'B', 'C', 'D'],
-                'Value': [25, 40, 15, 20]}
-        df = pd.DataFrame(data)
-        fig = px.line(df, x='Topic', y='Value', title='Example Line Graph')
+# Hugging Face API endpoint and model (Stable Diffusion in this case)
+HF_MODEL_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-2"
+
+# Get API key securely from environment variable
+HF_API_KEY = os.getenv("HF_API_KEY")
 
-    return fig
+# Function to generate image based on topic
+def generate_image(topic):
+    # Prepare the payload for the Hugging Face API
+    payload = {
+        "inputs": topic,
+        "options": {"use_gpu": True}
+    }
+    
+    headers = {"Authorization": f"Bearer {HF_API_KEY}"}
+    
+    # Make the API call to Hugging Face
+    response = requests.post(HF_MODEL_URL, headers=headers, json=payload)
+    
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Convert the response content (image) into a PIL Image object
+        image = Image.open(BytesIO(response.content))
+        return image
+    else:
+        return "Error generating image. Please try again."
 
 # Build the Gradio interface
 interface = gr.Interface(
-    fn=generate_graph,
-    inputs=gr.Textbox(label="Enter Topic (e.g., Animals, Fruits)"),
-    outputs=gr.Plot(),
+    fn=generate_image,
+    inputs=gr.Textbox(label="Enter Topic (e.g., Dog, Space, Nature)"),
+    outputs=gr.Image(),
     live=True,
-    title="Children's School Project Graph Generator",
-    description="Enter a topic and see a graphical representation of related data."
+    title="Children's School Project Image Generator",
+    description="Enter a topic and generate an image related to it for school projects. Example topics: Dog, Space, Nature."
 )
 
 # Launch the app
 interface.launch(share=True)
+