Upload app.py with huggingface_hub

app.py

@@ -109,6 +109,53 @@ def search_market_trends(topic: str) -> str:
     prompt = f"Conduct a professional market research analysis for the niche: '{topic}'. Suggest a pricing strategy and identify potential competitors."
     return llm_worker(prompt, system_prompt="You are an expert Ebook and Dropshipping Market Analyst.")
 
+@mcp.tool()
+def source_dropshipping_products(niche: str) -> str:
+    """Sourcing high-demand products for a dropshipping niche."""
+    prompt = f"Find and describe 3 high-demand, high-margin dropshipping products for the niche: '{niche}'. Include estimated cost and retail price."
+    return llm_worker(prompt, system_prompt="You are an expert E-commerce Sourcing Agent.")
+
+@mcp.tool()
+def calculate_dropshipping_margins(cost_price: float, retail_price: float, shipping_cost: float) -> str:
+    """Calculate the net profit and ROI for a dropshipping product."""
+    stripe_fee = (retail_price * 0.029) + 0.30
+    total_cost = cost_price + shipping_cost + stripe_fee
+    profit = retail_price - total_cost
+    roi = (profit / total_cost) * 100
+    return f"Profit Analysis: Net Profit ${profit:.2f}, ROI {roi:.2f}%. (Stripe fee estimated at ${stripe_fee:.2f})"
+
+@mcp.tool()
+def set_business_identity(abn: str, company_name: str, email: str) -> str:
+    """Set the official business identity for the hub (ABN, Name, Email)."""
+    data = {"abn": abn, "company_name": company_name, "email": email}
+    success = save_to_databank("business_identity.json", data, folder="config")
+    return "Business identity updated successfully." if success else "Failed to update identity."
+
+@mcp.tool()
+def launch_ebook_business(title: str, author: str, topic: str) -> str:
+    """Automated sequence for ebook business generation."""
+    chapters = [{"title": "Introduction", "content": f"A guide to {topic}."}]
+    epub_path, pdf_path = create_ebook_files(title, author, chapters, base_name=title.lower().replace(" ", "_"))
+    return f"Business Launched: '{title}' created. Files: {epub_path}, {pdf_path}. Ready for launch."
+
+@mcp.tool()
+def audit_store_cro(url: str = "Preview Mode") -> str:
+    """Audit a storefront for Conversion Rate Optimization (CRO) and speed."""
+    prompt = f"Perform a detailed CRO and user experience audit for the storefront: {url}. Suggest 3 actionable improvements."
+    return llm_worker(prompt, system_prompt="You are a Conversion Rate Optimization Expert.")
+
+@mcp.tool()
+def generate_store_layout(niche: str, store_type: str = "Dropshipping") -> str:
+    """Generate a high-conversion store layout/wireframe draft."""
+    prompt = f"Design a high-conversion store layout for a {store_type} business in the '{niche}' niche. Include sections for hero, social proof, and product grids."
+    return llm_worker(prompt, system_prompt="You are an E-commerce Store Architect.")
+
+@mcp.tool()
+def post_to_business_platforms(title: str, content: str, platforms: list) -> str:
+    """Distribute blog content to popular business platforms."""
+    # Simulation: Log the distribution
+    return f"Multi-Platform Distribution: '{title}' posted to {', '.join(platforms)}."
+
 @mcp.tool()
 def check_plagiarism(text: str) -> str:
     """Audit content for original integrity and potential copyright issues."""
@@ -188,17 +235,17 @@ def aussie_router(user_input, history):
 with gr.Blocks(title="Aussie MCP Agent Hub") as demo:
     gr.Markdown("# 🐨 Aussie MCP Server Agent Hub")
     with gr.Tab("Chat with Hub"):
-        chatbot = gr.Chatbot(type="messages")
+        chatbot = gr.Chatbot()
         msg = gr.Textbox(placeholder="Ask your Aussie Agent anything...")
         clear = gr.Button("Clear")
 
         def user(user_message, history):
-            return "", history + [{"role": "user", "content": user_message}]
+            return "", history + [[user_message, None]]
 
         def bot(history):
-            user_message = history[-1]["content"]
+            user_message = history[-1][0]
             bot_message = aussie_router(user_message, history[:-1])
-            history.append({"role": "assistant", "content": bot_message})
+            history[-1][1] = bot_message
             return history
 
         msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(bot, chatbot, chatbot)