QAgent good first initialization for test

agent.py

@@ -1,23 +1,102 @@
 import os
-from smolagents import CodeAgent, DuckDuckGoSearchTool, VisitWebpageTool, Tool, tool, InferenceClientModel
-
-
-class QAgent(Tool):
-    def __init__(self):
-        print("BasicAgent initialized.")
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        # provider = "nebius"
-        model = "Qwen/Qwen2.5-Coder-32B-Instruct"
-        api_key = os.environ.get('SP_HF_TOK')
-
-        agent = CodeAgent(tools=[DuckDuckGoSearchTool, VisitWebpageTool], 
-            model=InferenceClientModel(
-                model=model, 
-                # provider=provider, 
-                api_key=api_key),
-            add_base_tools=True)
-
-        fixed_answer = agent.run(question)
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+from smolagents import (
+    CodeAgent, 
+    DuckDuckGoSearchTool,
+    VisitWebpageTool, 
+    InferenceClientModel,
+    HfApiModel,
+    tool
+)
+
+
+
+class QAgent:
+    def __init__(
+        self,
+        model_type: str = "InferenceClientModel",
+        model_id: Optional[str] = None,
+        api_key: Optional[str] = None,
+        provider: Optional[str] = None,  # for InferenceClientModel
+        timeout: Optional[int] = None,   # for InferenceClientModel
+        system_prompt: Optional[str] = None,
+        verbose: bool = false # Verbose logging or not
+    ):
+        """ 
+        QAgent description 
+        """
+
+        self.verbose = verbose
+        self.system_prompt = system_prompt
+
+
+        if model_type == "HfApiModel":
+            if api_key is None:
+                api_key = os.getenv("SP_HF_TOK")
+                if not api_key:
+                    raise ValueError("No API Key found for HuggingFace. Please set SP_HF_TOK or pass api_key.")
+            
+            if self.verbose:
+                print(f"Using Hugging Face token: {api_key[:5]}... (HfApiModel mode)")
+                
+            self.model = HfApiModel(
+                model_id=model_id or "Qwen/Qwen2.5-Coder-32B-Instruct", # précédemment : or "meta-llama/Llama-3-70B-Instruct",
+                token=api_key
+                # temperature=temperature
+            )
+        elif model_type == "InferenceClientModel":
+            if api_key is None:
+                api_key = os.getenv("SP_HF_TOK")
+                if not api_key:
+                    raise ValueError("No API Key found for HuggingFace. Please set SP_HF_TOK or pass api_key.")
+            
+            if self.verbose:
+                print(f"Using Hugging Face token: {api_key[:5]}... (InferenceClientModel mode)")
+                
+            self.model = InferenceClientModel(
+                model_id=model_id or "Qwen/Qwen2.5-Coder-32B-Instruct", # précédemment : or "meta-llama/Llama-3-70B-Instruct",
+                provider=provider or "hf-inference",
+                token=api_key,
+                timeout=timeout or 120
+                # temperature=temperature
+            )
+        else:
+            raise ValueError(f"Unknown model type: {model_type}")
+        
+        if self.verbose:
+            print(f"Model initialized: {model_type} - {self.model.model_id} - prov: {self.model.provider}")
+
+        # Initialize tools
+        self.tools = [
+            DuckDuckGoSearchTool(),
+            PythonInterpreterTool(),
+            # save_and_read_file,
+            # download_file_from_url,
+            # analyze_csv_file,
+            # analyze_excel_file
+        ]
+
+        # Setup imports
+        self.imports = ["pandas", "numpy", "datetime", "json", "re", "math", "os", "requests", "csv", "urllib"]
+
+        # Create CodeAgent
+        self.agent = CodeAgent(
+            tools=self.tools,
+            model=self.model,
+            # additional_authorized_imports=self.imports,
+            # executor_type=executor_type,
+            # executor_kwargs=executor_kwargs,
+            verbosity_level=2 if self.verbose else 0
+        )
+        
+        if self.verbose:
+            print("CodeAgent initialized")
+
+    def invoke(self, prompt: str) -> str:
+        print(f"Agent invoked with prompt: {prompt[:80]}...")
+
+        result = self.agent.run(prompt)
+        print(result) 
+        )
+        return result
+
+