Upload app.py with huggingface_hub

app.py

@@ -73,19 +73,22 @@ def query_databank(filename: str) -> str:
 
 @mcp.tool()
 def generate_image(prompt: str) -> str:
-    """Generate an image with multiple model fallbacks to ensure operation even without credits."""
+    """Generate an image with multiple model fallbacks using the free hf-inference provider."""
     try:
         from huggingface_hub import InferenceClient
-        hf_client = InferenceClient(token=HF_TOKEN)
+        hf_client = InferenceClient(
+            provider="hf-inference", 
+            token=HF_TOKEN,
+            headers={"x-wait-for-model": "true"}
+        )
         
         business_name = os.environ.get("BUSINESS_NAME", "Fair Dinkum Publishing")
         owner = os.environ.get("BUSINESS_OWNER", "BRETT SJOBERG")
         brand_context = f"Professional brand asset for {business_name} (Owner: {owner}). Style: Modern, clean, high-quality. "
         full_prompt = brand_context + prompt
         
-        # Priority list of models
+        # Truly free models on hf-inference
         models = [
-            "black-forest-labs/FLUX.1-schnell", 
             "stabilityai/stable-diffusion-xl-base-1.0",
             "runwayml/stable-diffusion-v1-5",
             "CompVis/stable-diffusion-v1-4"
@@ -98,18 +101,18 @@ def generate_image(prompt: str) -> str:
             try:
                 image = hf_client.text_to_image(full_prompt, model=model_id)
                 model_used = model_id
-                break # Success!
+                break
             except Exception as e:
                 print(f"Model {model_id} failed: {str(e)}")
-                continue # Try next model
+                continue
         
         if not image:
-            return "Error: All image generation models failed or credits are depleted across providers."
+            return "Error: All free image generation models failed. The serverless API may be overloaded."
                 
         os.makedirs("exports/images", exist_ok=True)
         image_path = f"exports/images/{abs(hash(prompt))}.png"
         image.save(image_path)
-        return f"Branded Image Generated using {model_used}: {image_path}"
+        return f"Branded Image Generated using {model_used} (Free Tier): {image_path}"
     except Exception as e:
         return f"System Error during image generation: {str(e)}"
 
@@ -213,10 +216,14 @@ def aussie_router(user_input, history):
         )
         return response.choices[0].message.content
     except Exception as e:
-        # Fallback to Free Llama 3.1 on Hugging Face
+        # Fallback to Free Llama 3.1 on Hugging Face (FORCED FREE TIER)
         try:
             from huggingface_hub import InferenceClient
-            hf_client = InferenceClient(token=HF_TOKEN)
+            hf_client = InferenceClient(
+                provider="hf-inference", 
+                token=HF_TOKEN,
+                headers={"x-wait-for-model": "true"}
+            )
             response = hf_client.chat_completion(
                 model="meta-llama/Meta-Llama-3.1-8B-Instruct",
                 messages=messages,