Update mcp_server.py

mcp_server.py

@@ -13,12 +13,12 @@ from mcp.server.fastmcp import FastMCP
 
 mcp = FastMCP("modal_flux_testing", timeout=500)
 
-# Global variables to store secrets
-MODAL_API_URL = os.getenv('MODAL_API_URL',"https://rajkumarcmppl--flux-api-server-fastapi-server.modal.run")
-MISTRAL_API_KEY = os.getenv("MISTRAL_API_KEY","DRdpSRosSmwjj62cbdb3b04xjaPrMKpa")
+
+MODAL_API_URL = os.environ.get("MODAL_API_URL")
+MISTRAL_API_KEY = os.environ.get("MISTRAL_API_KEY")
 MISTRAL_API_URL = "https://api.mistral.ai/v1/chat/completions"
 
-# Social Media Size Presets
+
 SIZE_PRESETS = {
     "instagram_post": (1080, 1080),
     "instagram_story": (1080, 1920),
@@ -28,8 +28,7 @@ SIZE_PRESETS = {
     "youtube_thumbnail": (1280, 720),
 }
 
-# Prompt Templates for Marketing
-# Updated Prompt Templates for Cinematic Marketing (based on your examples)
+
 PROMPT_TEMPLATES = {
     "product_hero": """A professional, cinematic product photography composition featuring {product} as the center subject against a {background} backdrop. The scene is illuminated with dramatic studio lighting creating golden highlights and deep shadows. The {product} appears to float with ethereal light emanating from beneath, surrounded by subtle glowing particles and atmospheric mist. The composition uses cinematic depth of field with the product razor-sharp in focus while the background fades into artistic bokeh. Luxurious materials and textures are emphasized with photorealistic detail, showcasing premium quality and craftsmanship.""",
     
@@ -48,7 +47,7 @@ PROMPT_TEMPLATES = {
     "luxury_product": """An ultra-premium product showcase featuring {product} in a luxurious, museum-quality presentation. The item sits on pristine surfaces with perfect reflections, surrounded by architectural elements like marble, gold accents, and crystal. Dramatic lighting creates spectacular highlights and deep shadows, emphasizing every detail and texture. The background features elegant negative space with subtle gradient lighting and floating particles that suggest exclusivity. The entire composition exudes opulence and sophistication, with photorealistic detail that showcases premium craftsmanship and materials."""
 }
 
-# Enhanced Style Modifiers (matching your cinematic examples)
+
 STYLE_MODIFIERS = {
     "professional": """professional studio lighting, cinematic composition, dramatic shadows and highlights, premium materials and textures, photorealistic detail, magazine-quality photography, sophisticated color grading, architectural precision, corporate elegance, high-end commercial aesthetics""",
     
@@ -105,7 +104,7 @@ VARIATION_STRATEGIES = {
     ]
 }
 
-# Content creator specific variations
+
 CONTENT_CREATOR_VARIATIONS = {
     "social_media": [
         "Instagram-optimized with bold text overlay space",
@@ -131,7 +130,7 @@ CONTENT_CREATOR_VARIATIONS = {
 }
 
 
-# In-memory storage for history (in production, use a database)
+
 generation_history = []
 
 
@@ -238,7 +237,6 @@ Make it sound like a professional movie poster description with rich visual deta
             "fallback_prompt": f"Cinematic {style} style image of {user_input}, dramatic lighting, high detail, professional composition, vivid colors"
         })
 
-# Additional function to improve prompt quality based on your examples
 @mcp.tool()
 async def enhance_prompt_with_details(base_prompt: str, enhancement_type: str = "cinematic") -> str:
     """
@@ -357,7 +355,7 @@ async def generate_and_save_image(prompt: str, num_inference_steps: int = 50, wi
                         "prompt": prompt,
                         "timestamp": datetime.now().isoformat(),
                         "dimensions": f"{width}x{height}",
-                        "image_base64": image_b64[:100] + "..."  # Store preview only
+                        "image_base64": image_b64[:100] + "..." 
                     })
                     
                     return image_b64
@@ -388,15 +386,15 @@ async def batch_generate_smart_variations(prompt: str, count: int = 3, variation
     variations = []
     
     if variation_type == "mixed":
-        # Mix different strategies for comprehensive testing
+
         all_variations = []
         for strategy in VARIATION_STRATEGIES.values():
-            all_variations.extend(strategy[:2])  # Take 2 from each strategy
+            all_variations.extend(strategy[:2]) 
         
-        # Add content creator specific ones
+       
         all_variations.extend(CONTENT_CREATOR_VARIATIONS["engagement_hooks"][:2])
         
-        # Randomly select variations
+        
         import random
         selected_variations = random.sample(all_variations, min(count, len(all_variations)))
         
@@ -405,7 +403,7 @@ async def batch_generate_smart_variations(prompt: str, count: int = 3, variation
     elif variation_type in CONTENT_CREATOR_VARIATIONS:
         selected_variations = CONTENT_CREATOR_VARIATIONS[variation_type][:count]
     else:
-        # Fallback to mixed
+       
         selected_variations = [
             "with vibrant, attention-grabbing colors",
             "with professional, clean aesthetic", 
@@ -543,7 +541,7 @@ async def generate_social_media_set(prompt: str, platforms: List[str], num_infer
             platform_prompt = f"{prompt}, optimized for {platform.replace('_', ' ')}"
             
             try:
-                # Now pass the actual dimensions to the generation function
+               
                 image_b64 = await generate_and_save_image(
                     platform_prompt, 
                     num_inference_steps, 
@@ -596,8 +594,7 @@ async def create_image_package(image_data_list: List[Dict], package_name: str =
     Create a downloadable package of generated images with metadata.
     Useful for bulk content creation and organization.
     """
-    # This would create a zip file with images and a metadata JSON
-    # For now, return structured data
+
     
     package_info = {
         "package_name": package_name,