Create agent/rica_agent.py

agent/rica_agent.py

@@ -0,0 +1,72 @@
+"""
+RICA Agent optimized for Hugging Face Spaces
+"""
+
+import os
+from smolagents import CodeAgent
+from openai import OpenAI
+from agent_tools.ml_tools import predict_customer_churn_hf, get_model_status
+
+def create_rica_agent_hf():
+    """Create RICA agent optimized for HF Spaces"""
+    
+    # HF Spaces optimized tools
+    hf_tools = [
+        predict_customer_churn_hf,
+        get_model_status
+    ]
+    
+    try:
+        agent = CodeAgent(
+            tools=hf_tools,
+            model=OpenAI(api_key=os.getenv("OPENAI_API_KEY")),
+            add_base_tools=False,
+            max_iterations=3  # Reduced for HF Spaces performance
+        )
+        return agent
+    except Exception as e:
+        raise Exception(f"Agent creation failed: {str(e)}")
+
+def execute_rica_analysis_hf(analysis_type: str, parameters: dict = None):
+    """Execute RICA analysis optimized for HF Spaces"""
+    
+    agent = create_rica_agent_hf()
+    
+    # Simplified goals for HF Spaces
+    hf_goals = {
+        "comprehensive": f"""
+        Execute business intelligence analysis:
+        1) Check model status with get_model_status()
+        2) Predict customer churn with predict_customer_churn_hf()
+        3) Provide executive summary with key insights and recommendations
+        
+        Focus on actionable insights for business decision-making.
+        Parameters: {parameters}
+        """,
+        
+        "churn_focus": f"""
+        Focus on customer churn analysis:
+        1) Predict customer churn with predict_customer_churn_hf(risk_threshold={parameters.get('risk_threshold', 0.6)})
+        2) Identify high-risk customers requiring immediate attention
+        3) Provide specific intervention strategies
+        
+        Parameters: {parameters}
+        """,
+        
+        "quick_insights": f"""
+        Provide quick business insights:
+        1) Get model status with get_model_status()
+        2) Run limited churn analysis with predict_customer_churn_hf()
+        3) Summarize top 3 business priorities
+        
+        Parameters: {parameters}
+        """
+    }
+    
+    goal = hf_goals.get(analysis_type, hf_goals["comprehensive"])
+    
+    try:
+        result = agent.run(goal)
+        return result
+    except Exception as e:
+        return f"Analysis failed: {str(e)}. Please check your API key and try again."