second draft

agent.py

@@ -0,0 +1,67 @@
+from smolagents import CodeAgent, InferenceClientModel, ToolCallingAgent, DuckDuckGoSearchTool
+from dotenv import load_dotenv
+import os
+load_dotenv()
+model_id = "meta-llama/Llama-3.3-70B-Instruct" 
+
+
+def basic_inference(
+    prompt: str,
+    model_id: str = "meta-llama/Llama-3.3-70B-Instruct",
+    provider: str = "groq",
+):
+    """
+    Run a basic inference using the specified model and provider.
+
+    Args:
+        prompt (str): The input prompt for the model.
+        model_id (str): The ID of the model to use.
+        provider (str): The provider to use for inference.
+
+    Returns:
+        str: The model's response.
+    """
+    # Load the model
+    model = InferenceClientModel(model_id=model_id, token=os.environ.get("HUGGINGFACEHUB_API_TOKEN")) # You can choose to not pass any model_id to InferenceClientModel to use a default model
+    # you can also specify a particular provider e.g. provider="together" or provider="sambanova"
+
+    # Create an agent with the specified tools and model
+    agent = CodeAgent(tools=[], model=model, add_base_tools=True)
+
+    # Run the agent with the provided prompt
+    return agent.run(prompt)
+
+def toolcalling(
+    prompt: str,
+    model_id: str = "meta-llama/Llama-3.3-70B-Instruct",
+    provider: str = "groq",
+):
+    """
+    Run a tool calling inference using the specified model and provider.
+
+    Args:
+        prompt (str): The input prompt for the model.
+        model_id (str): The ID of the model to use.
+        provider (str): The provider to use for inference.
+
+    Returns:
+        str: The model's response.
+    """
+    # Load the model
+    model = InferenceClientModel(model_id=model_id, token=os.environ.get("HUGGINGFACEHUB_API_TOKEN")) # You can choose to not pass any model_id to InferenceClientModel to use a default model
+    # you can also specify a particular provider e.g. provider="together" or provider="sambanova"
+
+    # Create an agent with the specified tools and model
+    agent = ToolCallingAgent(tools=[], model=model, add_base_tools=True)
+
+    # Run the agent with the provided prompt
+    return agent.run(prompt)
+
+def web_search(query: str) -> str:
+    """Search DuckDuckGo for a query and return maximum 3 result.
+
+    Args:
+        query: The search query."""
+    search_tool = DuckDuckGoSearchTool()
+    search_docs = search_tool(query)
+    return search_docs