Interfaces to support code explainer feature in ValidMind

This update introduces an experimental feature for text generation tasks within the ValidMind project. It includes interfaces to utilize the code_explainer LLM feature, currently in the experimental namespace to gather feedback.

How to use:

1. Read the source code as a string:

   with open("customer_churn.py", "r") as f:
       source_code = f.read()

2. Define the input for the run_task task. The input requires two variables in dictionary format:

   code_explainer_input = {
       "source_code": source_code,
       "additional_instructions": """
       Please explain the code in a way that is easy to understand.
       """
   }

3. Run the code_explainer task with generation_type="code_explainer":

   result = vm.experimental.agents.run_task(
       task="code_explainer",
       input=code_explainer_input
   )

Example Output: