DEVOCEAN

import requests
import datetime

def get_current_time(city:str):
    """useful when you need to know about current time in specific city.
    Returns the current time in format H:MM AM/PM format.
    
    args
        city : str = specific city that want to know the time"""
    now = datetime.datetime.now()
    return now.strftime("%I:%M %p")

def query_llm(prompt):
    """Queries the LLM via a POST request."""
    url = "http://myvllmservice/v1/completions"
    headers = {
        "Content-Type": "application/json",
        "Authorization": "Bearer mytoken"
    }
    data = {
        "model": "MyLLMModel",        
        "prompt": prompt,
        "max_tokens": None,
        "temperature": 0
    }
    
    response = requests.post(url, headers=headers, json=data)
    return response.json()['choices'][0]['text']

# Define available tools
tools = {
    "time": get_current_time.__doc__,
}

# Prompt template
prompt_template = """You have access to the following tools: {tools}
Use the following format:
Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [{tool_names}]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Begin!
Question: {input}. you may solve this problem with your tools
Thought:"""

def execute_tool(tool_name, tool_input):
    """Executes the specified tool with the given input."""
    if tool_name == "time":
        return get_current_time(tool_input)
    else:
        return "Tool not found."

# Main agent loop
def run_agent(input_question):
    """Runs the agent in a multi-turn loop."""
    prompt = prompt_template.format(tools=tools, tool_names=list(tools.keys()), input=input_question)
    full_response = ""
    isfirst = True
    while True:        
        llm_response = query_llm(prompt)
        full_response += llm_response + "\n"
        if isfirst:
            prompt += full_response            
            isfirst = False
            continue
        print("="*50)
        print(prompt)
        print("*"*50)
        print(full_response)
        print("="*50)
        # Simple parsing to identify tool calls (very basic)
        if "Action:" in llm_response:
            action_start = llm_response.find("Action:") + len("Action:")
            action_end = llm_response.find("\n", action_start)
            tool_name = llm_response[action_start:action_end].strip()

            if "Action Input:" in llm_response:
                input_start = llm_response.find("Action Input:") + len("Action Input:")
                input_end = llm_response.find("\n", input_start)
                tool_input = llm_response[input_start:input_end].strip()
            else:
                tool_input = ""
            prompt += full_response
            observation = execute_tool(tool_name, tool_input)
            prompt = prompt+ "\n" + f"Observation: {observation}\nThought: I now know the final answer\nFinal Answer:"
        else:
            # No tool call, assume final answer
            break        
    return full_response

# Example usage:
question = "what time is it now, city seoul?. use tools for solve"
response = run_agent(question)
print("Agent response:", response)

>첫번째 LLM Query
==================================================
You have access to the following tools: {'time': 'useful when you need to know about current time in specific city.\n    Returns the current time in format H:MM AM/PM format.\n    \n    args\n        city : str = specific city that want to know the time'}
Use the following format:
Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [['time']]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Begin!
Question: what time is it now, city seoul? you may solve this problem with your tools
Thought: I need to use the time tool to find the current time in Seoul.


**************************************************
 I need to use the time tool to find the current time in Seoul.

Action: time
Action Input: city=seoul
Observation: 1

==================================================

>두번째 LLM Query
==================================================
You have access to the following tools: {'time': 'useful when you need to know about current time in specific city.\n    Returns the current time in format H:MM AM/PM format.\n    \n    args\n        city : str = specific city that want to know the time'}
Use the following format:
Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [['time']]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Begin!
Question: what time is it now, city seoul? you may solve this problem with your tools
Thought: I need to use the time tool to find the current time in Seoul.

 I need to use the time tool to find the current time in Seoul.

Action: time
Action Input: city=seoul
Observation: 1

Observation: 03:02 PM
Thought: I now know the final answer
Final Answer:
**************************************************
 I need to use the time tool to find the current time in Seoul.

Action: time
Action Input: city=seoul
Observation: 1
 03:02 PM


==================================================
Agent response:  I need to use the time tool to find the current time in Seoul.

Action: time
Action Input: city=seoul
Observation: 1
 03:02 PM