Rename app.py to synthscope.py

app.py

@@ -1,58 +0,0 @@
-from google import genai
-from google.genai import types
-from PIL import Image
-from io import BytesIO
-import gradio as gr
-import base64
-import os
-
-api_key = os.getenv("GEMINI_API_KEY")
-
-def generate_image(prompt):  
-
-  """
-  Transforms text into an image.
-
-  Args:
-      prompt: A natural language instruction that is used to generate an image.
-
-  Returns:
-        An image.
-  """  
-    
-  client = genai.Client(api_key=api_key)
-
-  prompt = tuple(prompt)
-
-  response = client.models.generate_content(
-    model="gemini-2.0-flash-preview-image-generation",
-    contents=prompt,
-    config=types
-    .GenerateContentConfig(
-      response_modalities=['TEXT', 'IMAGE']
-    )
-  )
-
-  for part in response.candidates[0].content.parts:
-    if part.text is not None:
-      pass
-    elif part.inline_data is not None:
-      image = Image.open(BytesIO((part.inline_data.data)))
-      # image.save('gemini-native-image.png')
-      # display(image)
-  return image 
-
-# build gradio interface
-app = gr.Interface(fn = generate_image, 
-                   inputs = gr.Text(label="Prompt",placeholder="Type your prompt here. . ."),
-                   outputs = gr.Image(label="Generated Image"),
-                   title="Gemini Image Generator",
-                   examples=["A 3D rendering of a little black girl wearing a colorful dress and smiling broadly at the camera",
-                             "Disney and Pixar-style playful bunny skipping about in a garden full of carrots and lettuce",
-                             "A strong black female superhero with braided hair flying in the bright blue sky",
-                             "A jazz musician playing his saxophone and surrounded by colorful musical notes."])
-
-
-# launch application
-if __name__ == "__main__":
-    app.launch(mcp_server = True)

synthscope.py

@@ -0,0 +1,81 @@
+from google import genai
+from google.genai.types import Tool, GenerateContentConfig, GoogleSearch
+from google.colab import userdata
+from google.genai import types
+from PIL import Image
+from io import BytesIO
+
+def GoogleSearchImageGen(prompt, image_style):
+    # Define style-specific prompts
+    style_prompts = {
+        "Comic": f"{prompt}. Convert the search result into a well-crafted text-to-image prompt that generates a comic book-style image.",
+        "Cartoon": f"{prompt}. Convert the search result into a well-crafted text-to-image prompt that generates a cartoon-style image.",
+        "3D": f"{prompt}. Convert the search result into a well-crafted text-to-image prompt that generates a Pixar-style 3D image.",
+        "Anime": f"{prompt}. Convert the search result into a well-crafted text-to-image prompt that generates an Anime-style image.",
+        "Ghibli": f"{prompt}. Convert the search result into a well-crafted text-to-image prompt that generates a Ghibli-style image.",
+        "Victorian": f"{prompt}. Convert the search result into a well-crafted text-to-image prompt that generates a Victorian-era image."
+    }
+    
+    # Check if the image_style is supported
+    if image_style in style_prompts:
+      image_gen_prompt = style_prompts[image_style]
+    
+    # Initialize variables to avoid UnboundLocalError
+    search_result = ""
+    image = None
+    
+    try:
+        # Get search result to be displayed to the user
+        response = client.models.generate_content(
+            model=model_id,
+            contents=prompt,
+            config=GenerateContentConfig(
+                tools=[google_search_tool],
+                response_modalities=["TEXT"],
+            )
+        )
+
+        # Extract search result
+        for each in response.candidates[0].content.parts:
+            if each.text:
+                search_result += each.text
+
+        # Generate image prompt from search result
+        output = client.models.generate_content(
+            model=model_id,
+            contents=image_gen_prompt,
+            config=GenerateContentConfig(
+                tools=[google_search_tool],
+                response_modalities=["TEXT"],
+            )
+        )
+
+        prompt_image = ""
+        for single in output.candidates[0].content.parts:
+            if single.text:
+                prompt_image += single.text
+
+        # Generate image
+        if prompt_image:  # Only generate image if we have a prompt
+            response = client.models.generate_content(
+                model="gemini-2.0-flash-preview-image-generation",
+                contents=prompt_image,
+                config=types.GenerateContentConfig(
+                    response_modalities=['TEXT', 'IMAGE']
+                )
+            )
+
+            # Extract image from response
+            for part in response.candidates[0].content.parts:
+                if part.text is not None:
+                    pass  # Handle text if needed
+                elif part.inline_data is not None:
+                    image = Image.open(BytesIO(part.inline_data.data))
+                    break  # Exit loop once we find the image
+
+    except Exception as e:
+        print(f"Error occurred: {e}")
+        # Return default values in case of error
+        return search_result or "No search result available", None
+
+    return search_result, image