diff --git a/demo/fastapi_client.py b/demo/fastapi_client.py
new file mode 100644
index 0000000..1a0977b
--- /dev/null
+++ b/demo/fastapi_client.py
@@ -0,0 +1,78 @@
+import requests
+from PIL import Image
+import io
+# Endpoint URLs
+understand_image_url = "http://localhost:8000/understand_image_and_question/"
+generate_images_url = "http://localhost:8000/generate_images/"
+
+# Use your image file path here
+image_path = "images/equation.png"
+
+# Function to call the image understanding endpoint
+def understand_image_and_question(image_path, question, seed=42, top_p=0.95, temperature=0.1):
+    files = {'file': open(image_path, 'rb')}
+    data = {
+        'question': question,
+        'seed': seed,
+        'top_p': top_p,
+        'temperature': temperature
+    }
+    response = requests.post(understand_image_url, files=files, data=data)
+    response_data = response.json()
+    print("Image Understanding Response:", response_data['response'])
+
+
+# Function to call the text-to-image generation endpoint
+def generate_images(prompt, seed=None, guidance=5.0):
+    data = {
+        'prompt': prompt,
+        'seed': seed,
+        'guidance': guidance
+    }
+    response = requests.post(generate_images_url, data=data, stream=True)
+    
+    if response.ok:
+        img_idx = 1
+
+        # We will create a new BytesIO for each image
+        buffers = {}
+
+        try:
+            for chunk in response.iter_content(chunk_size=1024):
+                if chunk:
+                    # Use a boundary detection to determine new image start
+                    if img_idx not in buffers:
+                        buffers[img_idx] = io.BytesIO()
+
+                    buffers[img_idx].write(chunk)
+
+                    # Attempt to open the image
+                    try:
+                        buffer = buffers[img_idx]
+                        buffer.seek(0)
+                        image = Image.open(buffer)
+                        img_path = f"generated_image_{img_idx}.png"
+                        image.save(img_path)
+                        print(f"Saved: {img_path}")
+
+                        # Prepare the next image buffer
+                        buffer.close()
+                        img_idx += 1
+
+                    except Exception as e:
+                        # Continue loading data into the current buffer
+                        continue
+
+        except Exception as e:
+            print("Error processing image:", e)
+    else:
+        print("Failed to generate images.")
+
+
+# Example usage
+if __name__ == "__main__":
+    # Call the image understanding API
+    understand_image_and_question(image_path, "What is this image about?")
+    
+    # Call the image generation API
+    generate_images("A beautiful sunset over a mountain range, digital art.")