Create Folder Structure using LLM

import json
import os
import cohere

# Initialize the Cohere client with a more secure approach
co = cohere.Client(api_key='YOUR_COHERE_KEY')

def create_project_structure(structure, base_path="/content/"):
    """
    Create a directory and file structure based on a nested dictionary.
    """
    try:
        for folder, files in structure.items():
            folder_path = os.path.join(base_path, folder)
            os.makedirs(folder_path, exist_ok=True)
            for file_name, content in files.items():
                file_path = os.path.join(folder_path, file_name)
                if isinstance(content, dict):
                    create_project_structure(content, base_path=folder_path)
                else:
                    with open(file_path, "w") as file:
                        file.write(content)
        return "Project structure created successfully."
    except Exception as e:
        return f"An error occurred: {str(e)}"

# JSON schema for the function argument
tools = [{
    "name": "create_project_structure",
    "description": "Create an entire project structure with specified files and contents.",
    "parameter_definitions": {
        "structure": {
            "description": "Dictionary specifying folders and files with their contents.",
            "type": "dict",
            "required": True
        },
        "base_path": {
            "description": "Base path where the project structure will be created.",
            "type": "str",
            "required": False
        }
    }
}]

functions_map = {
    'create_project_structure': create_project_structure
}

# Placeholder for example user request and handling
message = "write complete flappy bird game using unity"
preamble = """
## Task & Context
Answer questions and handle requests on a variety of topics using appropriate tools and research methods.

## Style Guide
Respond in full sentences, using proper grammar and spelling, unless requested otherwise.
"""

# Simulate handling a user request
response = co.chat(
    message=message,
    tools=tools,
    preamble=preamble,
    model="command-r",
    force_single_step=True
)

# Process and execute the recommended tool calls
tool_results = []
for tool_call in response.tool_calls:
    output = functions_map[tool_call.name](**tool_call.parameters)
    tool_result = {
        "name": tool_call.name,
        "parameters": tool_call.parameters,
        "outputs": [output],
        "call": tool_call
    }
    tool_results.append(tool_result)

print("\nTool execution results:\n")
print(json.dumps(tool_results, indent=4))

# Handle the final response using the results from tool calls
final_response = co.chat(
    message=message,
    tools=tools,
    tool_results=tool_results,
    preamble=preamble,
    model="command-r",
    temperature=0.3,
    force_single_step=True
)

print("Final answer:")
print(final_response.text)