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"""
Simple tool-calling chat with ExCom AI
Works around vLLM's tool_choice requirements
"""

from openai import OpenAI
import json
from datetime import datetime
import math

# Configure OpenAI client for your vLLM endpoint
client = OpenAI(
    base_url="https://plarnholt-excom-ai-demo.hf.space/v1",
    api_key="not-needed"
)

# Define tools
tools = [
    {
        "type": "function",
        "function": {
            "name": "calculator",
            "description": "Evaluates a mathematical expression",
            "parameters": {
                "type": "object",
                "properties": {
                    "expression": {
                        "type": "string",
                        "description": "Math expression to evaluate, e.g., '2 + 2 * 3'"
                    }
                },
                "required": ["expression"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "get_current_time",
            "description": "Returns the current date and time",
            "parameters": {
                "type": "object",
                "properties": {}
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Gets the weather for a city (simulated)",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {
                        "type": "string",
                        "description": "City name"
                    }
                },
                "required": ["city"]
            }
        }
    }
]

# Tool implementations
def calculator(expression: str) -> str:
    try:
        result = eval(expression, {"__builtins__": {}, "math": math})
        return str(result)
    except Exception as e:
        return f"Error: {str(e)}"

def get_current_time() -> str:
    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")

def get_weather(city: str) -> str:
    weather_data = {
        "paris": "18°C, sunny",
        "london": "15°C, cloudy",
        "new york": "22°C, partly cloudy",
        "tokyo": "25°C, clear",
    }
    return weather_data.get(city.lower(), f"Weather data not available for {city}")

# Function dispatcher
def execute_tool(tool_name: str, arguments: dict) -> str:
    if tool_name == "calculator":
        return calculator(arguments["expression"])
    elif tool_name == "get_current_time":
        return get_current_time()
    elif tool_name == "get_weather":
        return get_weather(arguments["city"])
    else:
        return f"Unknown tool: {tool_name}"

def chat(user_message: str, messages: list = None):
    """Send a message and handle tool calls"""
    if messages is None:
        messages = []

    # Add user message
    messages.append({"role": "user", "content": user_message})

    # Call the model with tools (no tool_choice parameter)
    response = client.chat.completions.create(
        model="excom-ai",
        messages=messages,
        tools=tools,
        temperature=0.4
    )

    assistant_message = response.choices[0].message

    # Check if model wants to use tools
    if assistant_message.tool_calls:
        # Add assistant's tool call request to messages
        messages.append({
            "role": "assistant",
            "content": assistant_message.content,
            "tool_calls": [
                {
                    "id": tc.id,
                    "type": "function",
                    "function": {
                        "name": tc.function.name,
                        "arguments": tc.function.arguments
                    }
                }
                for tc in assistant_message.tool_calls
            ]
        })

        # Execute each tool call
        for tool_call in assistant_message.tool_calls:
            function_name = tool_call.function.name
            function_args = json.loads(tool_call.function.arguments)

            print(f"🔧 Calling tool: {function_name}({function_args})")

            # Execute the tool
            tool_result = execute_tool(function_name, function_args)

            # Add tool result to messages
            messages.append({
                "role": "tool",
                "tool_call_id": tool_call.id,
                "name": function_name,
                "content": tool_result
            })

        # Get final response from model
        final_response = client.chat.completions.create(
            model="excom-ai",
            messages=messages,
            temperature=0.4
        )

        return final_response.choices[0].message.content, messages
    else:
        # No tools needed, return direct response
        return assistant_message.content, messages

def main():
    print("=" * 60)
    print("ExCom AI - Simple Tool Calling Chat")
    print("=" * 60)
    print("Available tools:")
    print("  • calculator - Evaluate math expressions")
    print("  • get_current_time - Get current date/time")
    print("  • get_weather - Get weather for cities")
    print("\nType 'quit' or 'exit' to end.")
    print("=" * 60)
    print()

    messages = []

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ['quit', 'exit', 'q']:
            print("Goodbye!")
            break

        if not user_input:
            continue

        try:
            response, messages = chat(user_input, messages)
            print(f"Assistant: {response}\n")
        except Exception as e:
            print(f"❌ Error: {e}\n")
            # Reset messages on error
            messages = []

if __name__ == "__main__":
    main()