Update

colab.ipynb

@@ -15,7 +15,6 @@
     "from img_gen_logic import generate_image\n",
     "from config_colab import models, prompts, api_token\n",
     "\n",
-    "\n",
     "# Initialize the InferenceClient with the default model\n",
     "client = InferenceClient(models[0][\"name\"], token=api_token)\n",
     "\n",
@@ -110,6 +109,8 @@
     "def on_generate_button_clicked(b):\n",
     "    with output:\n",
     "        clear_output(wait=True)  # Clear previous output\n",
+    "\n",
+    "        # Get selected values from widgets\n",
     "        selected_prompt = prompt_dropdown.value\n",
     "        selected_team = team_dropdown.value\n",
     "        selected_model = model_dropdown.value\n",
@@ -121,17 +122,6 @@
     "        custom_prompt = custom_prompt_input.value\n",
     "\n",
     "        # Debug: Show selected parameters\n",
-    "        print(f\"Selected Model: {model_dropdown.label}\")\n",
-    "        print(f\"Selected Prompt: {prompt_dropdown.label}\")\n",
-    "        print(f\"Selected Team: {selected_team}\")\n",
-    "        print(f\"Height: {height}\")\n",
-    "        print(f\"Width: {width}\")\n",
-    "        print(f\"Inference Steps: {num_inference_steps}\")\n",
-    "        print(f\"Guidance Scale: {guidance_scale}\")\n",
-    "        print(f\"Seed: {seed}\")\n",
-    "        print(f\"Custom Prompt: {custom_prompt}\")\n",
-    "\n",
-    "            # Debug: Show selected parameters\n",
     "        print(\"=== Debug: Selected Parameters ===\")\n",
     "        print(f\"Selected Model: {selected_model} (Alias: {model_dropdown.label})\")\n",
     "        print(f\"Selected Prompt: {selected_prompt} (Alias: {prompt_dropdown.label})\")\n",
@@ -143,18 +133,32 @@
     "        print(f\"Seed: {seed}\")\n",
     "        print(f\"Custom Prompt: {custom_prompt}\")\n",
     "        print(\"==================================\")\n",
+    "\n",
     "        # Generate the image\n",
+    "        print(\"=== Debug: Calling generate_image ===\")\n",
     "        image, message = generate_image(selected_prompt, selected_team, selected_model, height, width, num_inference_steps, guidance_scale, seed, custom_prompt)\n",
     "\n",
+    "        # Debug: Check the output of generate_image\n",
+    "        print(\"=== Debug: generate_image Output ===\")\n",
+    "        print(f\"Image: {image}\")\n",
+    "        print(f\"Message: {message}\")\n",
+    "        print(\"====================================\")\n",
+    "\n",
     "        if isinstance(image, str):\n",
+    "            print(\"=== Debug: Error ===\")\n",
     "            print(image)\n",
     "        else:\n",
     "            # Debug: Indicate that the image is being displayed and saved\n",
+    "            print(\"=== Debug: Image Generation ===\")\n",
     "            print(\"Image generated successfully!\")\n",
     "            print(\"Displaying image...\")\n",
     "\n",
     "            # Display the image in the notebook\n",
-    "            display(image)\n",
+    "            if image is not None:\n",
+    "                display(image)\n",
+    "            else:\n",
+    "                print(\"=== Debug: Error ===\")\n",
+    "                print(\"No image was returned by generate_image.\")\n",
     "\n",
     "# Attach the button click event handler\n",
     "generate_button.on_click(on_generate_button_clicked)\n",

img_gen_logic copy.py

@@ -0,0 +1,65 @@
+# img_gen_logic.py
+import random
+from huggingface_hub import InferenceClient
+from PIL import Image
+from datetime import datetime
+from config import api_token, models, prompts  # Direct import
+
+
+def generate_image(prompt_alias, team, model_alias, custom_prompt, height=360, width=640, num_inference_steps=20, guidance_scale=2.0, seed=-1):
+    # Debugging: Check if the token is available
+    if not api_token:
+        return None, "ERROR: Hugging Face token (HF_CTB_TOKEN) is missing. Please set it as an environment variable."
+
+    # Find the selected prompt and model
+    try:
+        prompt = next(p for p in prompts if p["alias"] == prompt_alias)["text"]
+        model_name = next(m for m in models if m["alias"] == model_alias)["name"]
+    except StopIteration:
+        return None, "ERROR: Invalid prompt or model selected."
+
+    # Determine the enemy color
+    enemy_color = "blue" if team.lower() == "red" else "red"
+    prompt = prompt.format(enemy_color=enemy_color)
+
+    if team.lower() == "red":
+        prompt += " The winning army is dressed in red armor and banners."
+    elif team.lower() == "blue":
+        prompt += " The winning army is dressed in blue armor and banners."
+
+    # Append the custom prompt (if provided)
+    if custom_prompt and len(custom_prompt.strip()) > 0:
+        prompt += " " + custom_prompt.strip()
+
+    # Randomize the seed if needed
+    if seed == -1:
+        seed = random.randint(0, 1000000)
+
+    # Initialize the InferenceClient
+    try:
+        client = InferenceClient(model_name, token=api_token)
+    except Exception as e:
+        return None, f"ERROR: Failed to initialize InferenceClient. Details: {e}"
+
+    # Generate the image
+    try:
+        image = client.text_to_image(
+            prompt,
+            guidance_scale=guidance_scale,
+            num_inference_steps=num_inference_steps,
+            width=width,
+            height=height,
+            seed=seed
+        )
+    except Exception as e:
+        return None, f"ERROR: Failed to generate image. Details: {e}"
+
+    # Save the image with a timestamped filename
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    output_filename = f"{timestamp}_{model_alias.replace(' ', '_').lower()}_{prompt_alias.replace(' ', '_').lower()}_{team.lower()}.png"
+    try:
+        image.save(output_filename)
+    except Exception as e:
+        return None, f"ERROR: Failed to save image. Details: {e}"
+
+    return output_filename, "Image generated successfully!"

img_gen_logic.py

@@ -1,65 +1,31 @@
 # img_gen_logic.py
-import random
-from huggingface_hub import InferenceClient
 from PIL import Image
-from datetime import datetime
-from config import api_token, models, prompts  # Direct import
-
-
-def generate_image(prompt_alias, team, model_alias, custom_prompt, height=360, width=640, num_inference_steps=20, guidance_scale=2.0, seed=-1):
-    # Debugging: Check if the token is available
-    if not api_token:
-        return None, "ERROR: Hugging Face token (HF_CTB_TOKEN) is missing. Please set it as an environment variable."
-
-    # Find the selected prompt and model
-    try:
-        prompt = next(p for p in prompts if p["alias"] == prompt_alias)["text"]
-        model_name = next(m for m in models if m["alias"] == model_alias)["name"]
-    except StopIteration:
-        return None, "ERROR: Invalid prompt or model selected."
-
-    # Determine the enemy color
-    enemy_color = "blue" if team.lower() == "red" else "red"
-    prompt = prompt.format(enemy_color=enemy_color)
-
-    if team.lower() == "red":
-        prompt += " The winning army is dressed in red armor and banners."
-    elif team.lower() == "blue":
-        prompt += " The winning army is dressed in blue armor and banners."
-
-    # Append the custom prompt (if provided)
-    if custom_prompt and len(custom_prompt.strip()) > 0:
-        prompt += " " + custom_prompt.strip()
-
-    # Randomize the seed if needed
-    if seed == -1:
-        seed = random.randint(0, 1000000)
-
-    # Initialize the InferenceClient
-    try:
-        client = InferenceClient(model_name, token=api_token)
-    except Exception as e:
-        return None, f"ERROR: Failed to initialize InferenceClient. Details: {e}"
-
-    # Generate the image
+import numpy as np
+
+def generate_image(prompt, team, model, height, width, num_inference_steps, guidance_scale, seed, custom_prompt):
+    print("=== Debug: Inside generate_image ===")
+    print(f"Prompt: {prompt}")
+    print(f"Team: {team}")
+    print(f"Model: {model}")
+    print(f"Height: {height}")
+    print(f"Width: {width}")
+    print(f"Inference Steps: {num_inference_steps}")
+    print(f"Guidance Scale: {guidance_scale}")
+    print(f"Seed: {seed}")
+    print(f"Custom Prompt: {custom_prompt}")
+
+    # Simulate API call or image generation logic
     try:
-        image = client.text_to_image(
-            prompt,
-            guidance_scale=guidance_scale,
-            num_inference_steps=num_inference_steps,
-            width=width,
-            height=height,
-            seed=seed
-        )
+        # Replace this with your actual image generation logic
+        print("=== Debug: Simulating API Call ===")
+        # Example: Return a placeholder image or error message
+        if not prompt:
+            return "Error: Prompt is required.", None
+        else:
+            # Simulate a successful image generation
+            image = Image.fromarray(np.random.randint(0, 255, (height, width, 3), dtype=np.uint8))
+            return image, "Image generated successfully."
     except Exception as e:
-        return None, f"ERROR: Failed to generate image. Details: {e}"
-
-    # Save the image with a timestamped filename
-    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-    output_filename = f"{timestamp}_{model_alias.replace(' ', '_').lower()}_{prompt_alias.replace(' ', '_').lower()}_{team.lower()}.png"
-    try:
-        image.save(output_filename)
-    except Exception as e:
-        return None, f"ERROR: Failed to save image. Details: {e}"
-
-    return output_filename, "Image generated successfully!"
+        print(f"=== Debug: Error in generate_image ===")
+        print(str(e))
+        return str(e), None