Update app.py

app.py

@@ -1,13 +1,25 @@
 import gradio as gr
 from groq import Groq
 import os
-import openai  # For integration with OpenAI's image generation API (e.g., DALL·E)
+import requests  # For DeepAI API
 
 # Initialize Groq client
 client = Groq(api_key=os.environ["GROQ_API_KEY"])
 
-# Initialize OpenAI API client for image generation
-openai.api_key = os.environ["OPENAI_API_KEY"]
+# Function to generate image from DeepAI API
+def generate_visual_answer(prompt):
+    # Replace with DeepAI image generation API URL
+    url = "https://api.deepai.org/api/text2img"
+    response = requests.post(
+        url, 
+        data={'text': prompt},  # The prompt will be the text description for image generation
+        headers={'api-key': os.environ["DEEP_AI_API_KEY"]}  # Use DeepAI's API key here
+    )
+    if response.status_code == 200:
+        image_url = response.json()['output_url']  # URL for the generated image
+        return image_url
+    else:
+        return "Error generating image"
 
 def generate_tutor_output(subject, difficulty, student_input):
     prompt = f"""
@@ -39,15 +51,6 @@ def generate_tutor_output(subject, difficulty, student_input):
 
     return completion.choices[0].message.content
 
-def generate_visual_answer(prompt):
-    response = openai.Image.create(
-        prompt=prompt,
-        n=1,
-        size="1024x1024"
-    )
-    image_url = response['data'][0]['url']
-    return image_url
-
 with gr.Blocks() as demo:
     gr.Markdown("# 🎓 Your AI Tutor by Farhan")
     
@@ -89,7 +92,7 @@ with gr.Blocks() as demo:
     def process_output(output, prompt):
         try:
             parsed = eval(output)
-            visual_answer = generate_visual_answer(prompt)  # Get the image URL
+            visual_answer = generate_visual_answer(prompt)  # Get the image URL from DeepAI
             return parsed["lesson"], parsed["question"], parsed["feedback"], visual_answer
         except:
             return "Error parsing output", "No question available", "No feedback available", None