Create agent.py

Still under construction, must parametrize tool calling from mcp server

agent.py

@@ -0,0 +1,88 @@
+import math
+from typing import Optional, Tuple
+from smolagents import tool
+
+
+
+@tool
+def real_number_calculator(
+    a: float, b: float, operation: Literal["add", "subtract", "multiply", "divide"]
+) -> float:
+        """
+    Perform basic arithmetic operations on two real numbers.
+
+    This function acts as a simple calculator that can add, subtract, 
+    multiply, or divide two floating-point numbers.
+
+    Args:
+        a (float): The first number.
+        b (float): The second number.
+        operation (Literal["add", "subtract", "multiply", "divide"]): 
+            The arithmetic operation to perform.
+
+    Returns:
+        float: The result of the arithmetic operation.
+
+    Raises:
+        ValueError: If the operation is invalid or if division by zero is attempted.
+
+    Example:
+        >>> real_number_calculator(10, 5, "add")
+        15.0
+        >>> real_number_calculator(10, 5, "divide")
+        2.0
+    """
+
+    if operation == "add":
+        return a + b
+    elif operation == "subtract":
+        return a - b
+    elif operation == "multiply":
+        return a * b
+    elif operation == "divide":
+        if b == 0:
+            raise ValueError("Division by zero is not allowed.")
+        return a / b
+    else:
+        raise ValueError(f"Invalid operation: {operation}")
+
+
+
+
+    class CourseAgent:
+        def __init__(self):
+            
+            # import code agent and basic tool from smolagent
+            from smolagents import CodeAgent, OpenAIServerModel, DuckDuckGoSearchTool, FinalAnswerTool, VisitWebpageTool
+
+            # import additional tool from langchain @ https://docs.langchain.com/oss/python/integrations/tools
+            from langchain.agents import load_tools
+            from smolagents import Tool
+            wikipedia_tool = Tool.from_langchain(load_tools(["wikipedia"])[0])
+
+            # import tools from MCP servers @ https://github.com/mcp
+            from mcp import StdioServerParameters
+            server_parameters = StdioServerParameters(command="uvx",
+                                                      args=["--quiet", "pubmedmcp@0.1.3"],
+                                                      env={"UV_PYTHON": "3.12", **os.environ},
+                                                     )
+            
+            model = OpenAIServerModel(model_id="gpt-4o")
+            model = InferenceClientModel("Qwen/Qwen2.5-Coder-32B-Instruct")
+            # Instantiate the agent
+            self.agent = CodeAgent(
+                tools=[real_number_calculator(),        # homemade tool
+                       DuckDuckGoSearchTool(),          # basic tools from smolagent
+                       VisitWebpageTool(),
+                       wikipedia_tool(top_k_results=3), # tool from langchain with extra parmaeters
+                       FinalAnswerTool()],
+                model=model,
+                max_steps=3,
+                verbosity_level=2
+            )
+
+        def __call__(self, question: str) -> str:
+            print(f"Agent received question (first 50 chars): {question[:50]}...")
+            answer = self.agent.invoke(question)
+            print(f"Agent returning his answer: {answer}")
+            return fixed_answer