update

app.py

@@ -29,7 +29,16 @@ from smolagents import (
 )
 
 # Set your HuggingFace token here
-HF_TOKEN = os.getenv("HF_TOKEN", "your_hf_token_here")
+# In HuggingFace Spaces, this will be automatically loaded from secrets
+HF_TOKEN = os.environ.get("HF_TOKEN") or os.environ.get("HUGGINGFACE_HUB_TOKEN")
+
+# Validate HF token
+if not HF_TOKEN or HF_TOKEN == "your_hf_token_here":
+    print("⚠️ WARNING: HF_TOKEN not set!")
+    print("Set it with: export HF_TOKEN=your_actual_token")
+    print("Get token from: https://huggingface.co/settings/tokens")
+    print("Continuing with limited functionality...")
+    HF_TOKEN = None
 
 @dataclass
 class Task:
@@ -242,11 +251,19 @@ class PersonalProductivityAgent:
     """Main productivity agent class"""
     
     def __init__(self):
-        # Initialize the model
-        self.model = InferenceClientModel(
-            model="Qwen/Qwen2.5-Coder-32B-Instruct",
-            token=HF_TOKEN
-        )
+        # Initialize the model with fallback
+        try:
+            self.model = InferenceClientModel(
+                model="Qwen/Qwen2.5-Coder-32B-Instruct",
+                token=HF_TOKEN
+            )
+        except Exception as e:
+            print(f"⚠️ Primary model failed, using fallback: {e}")
+            # Fallback to a smaller, more reliable model
+            self.model = InferenceClientModel(
+                model="microsoft/DialoGPT-medium",
+                token=HF_TOKEN
+            )
         
         # Initialize tools
         self.search_tool = DuckDuckGoSearchTool()
@@ -263,7 +280,24 @@ class PersonalProductivityAgent:
             create_meeting_summary
         ]
         
-        # Initialize the CodeAgent
+        # Custom system prompt
+        custom_system_prompt = """You are an advanced Personal Productivity Assistant named Alfred. 
+
+You help users manage their daily tasks, schedule, communications, and information needs.
+
+Key capabilities:
+- Task management (add, list, complete tasks)
+- Time and date calculations
+- Weather information
+- Web search and research
+- Email composition (mock)
+- Meeting planning and templates
+- General calculations and code execution
+
+Always be helpful, concise, and proactive in suggesting productivity improvements.
+When users ask for help, offer multiple options and explain your reasoning."""
+
+        # Initialize the CodeAgent with custom prompt
         self.agent = CodeAgent(
             tools=[self.search_tool] + self.custom_tools,
             model=self.model,
@@ -271,37 +305,45 @@ class PersonalProductivityAgent:
             planning_interval=3   # Plan every 3 steps
         )
         
-        # System prompt customization
-        self.agent.system_prompt = """You are an advanced Personal Productivity Assistant named Alfred. 
-        
-        You help users manage their daily tasks, schedule, communications, and information needs.
+        # Set system prompt using prompt_templates (proper way)
+        if hasattr(self.agent, 'prompt_templates'):
+            self.agent.prompt_templates['system_prompt'] = custom_system_prompt
         
-        Key capabilities:
-        - Task management (add, list, complete tasks)
-        - Time and date calculations
-        - Weather information
-        - Web search and research
-        - Email composition (mock)
-        - Meeting planning and templates
-        - General calculations and code execution
-        
-        Always be helpful, concise, and proactive in suggesting productivity improvements.
-        When users ask for help, offer multiple options and explain your reasoning.
-        """
+        print("✅ Personal Productivity Agent initialized successfully!")
+        print(f"🤖 Model: {self.model.model if hasattr(self.model, 'model') else 'Unknown'}")
+        print(f"🔧 Tools available: {len(self.custom_tools) + 1} custom + base tools")
     
     def run(self, query: str, reset_memory: bool = False) -> str:
         """Run the agent with a user query"""
+        if not HF_TOKEN:
+            return "❌ Cannot run agent: HuggingFace token not set. Please set HF_TOKEN environment variable."
+        
         try:
             response = self.agent.run(query, reset=reset_memory)
             return str(response)
         except Exception as e:
-            return f"I apologize, but I encountered an error: {str(e)}"
+            error_msg = str(e)
+            if "401" in error_msg or "authentication" in error_msg.lower():
+                return "❌ Authentication error: Please check your HuggingFace token permissions."
+            elif "timeout" in error_msg.lower():
+                return "⏱️ Request timed out. The model might be busy. Please try again."
+            else:
+                return f"❌ I encountered an error: {error_msg}"
 
-# Initialize the global agent
-productivity_agent = PersonalProductivityAgent()
+# Initialize the global agent with error handling
+try:
+    productivity_agent = PersonalProductivityAgent()
+except Exception as e:
+    print(f"❌ Failed to initialize agent: {e}")
+    productivity_agent = None
 
 def chat_interface(message, history, reset_conversation):
     """Gradio chat interface function"""
+    if not productivity_agent:
+        response = "❌ Agent not initialized. Please check your HuggingFace token and restart the application."
+        history.append([message, response])
+        return history, ""
+    
     if reset_conversation:
         # Reset the conversation memory
         response = productivity_agent.run(message, reset_memory=True)
@@ -408,8 +450,20 @@ def create_gradio_interface():
     return demo
 
 if __name__ == "__main__":
+    # Startup validation
+    if not productivity_agent:
+        print("\n❌ STARTUP FAILED")
+        print("Possible solutions:")
+        print("1. Set HuggingFace token: export HF_TOKEN=your_token")
+        print("2. Install dependencies: pip install smolagents gradio huggingface_hub")
+        print("3. Check internet connection")
+        exit(1)
+    
     # Create and launch the interface
     demo = create_gradio_interface()
+    print("\n🚀 Launching Gradio interface...")
+    print("📍 Local URL will be displayed below")
+    
     demo.launch(
         share=True,
         debug=True,

requirements.txt

@@ -1,8 +1,8 @@
 smolagents>=0.4.0
 gradio>=4.0.0
-huggingface_hub>=0.19.0
+huggingface_hub>=0.20.0
 transformers>=4.35.0
 torch>=2.0.0
 requests>=2.31.0
 python-dateutil>=2.8.2
-duckduckgo_search
+duckduckgo_search