diff --git a/tool_call_llama3.py b/tool_call_llama3.py
new file mode 100644
index 0000000..2c41e76
--- /dev/null
+++ b/tool_call_llama3.py
@@ -0,0 +1,122 @@
+import autogen 
+from autogen import AssistantAgent, UserProxyAgent, config_list_from_json 
+from typing_extensions import Annotated
+import requests
+import os
+import json
+import json
+from typing import Literal
+
+
+
+
+
+config_list = [
+    {
+        "model": "llama3.1",
+        "api_type": "ollama",
+        "client_host": "http://localhost:11434",
+        "timeout": 30,
+    }
+]
+
+llm_config = {"config_list": config_list}
+
+chatbot = autogen.AssistantAgent(
+    name="chatbot",
+    system_message="""For currency exchange and weather forecasting tasks,
+        only use the functions you have been provided with.
+        Example of the return JSON is:
+        {
+            "parameter_1_name": 100.00,
+            "parameter_2_name": "ABC",
+            "parameter_3_name": "DEF",
+        }.
+        Another example of the return JSON is:
+        {
+            "parameter_1_name": "GHI",
+            "parameter_2_name": "ABC",
+            "parameter_3_name": "DEF",
+            "parameter_4_name": 123.00,
+        }.
+        Output 'HAVE FUN!' when an answer has been provided.""",
+    llm_config={"config_list": config_list},
+)
+
+# Note that we have changed the termination string to be "HAVE FUN!"
+user_proxy = autogen.UserProxyAgent(
+    name="user_proxy",
+    is_termination_msg=lambda x: x.get("content", "") and "HAVE FUN!" in x.get("content", ""),
+    human_input_mode="NEVER",
+    max_consecutive_auto_reply=1,
+)
+
+# Currency Exchange function
+
+CurrencySymbol = Literal["USD", "EUR"]
+
+# Define our function that we expect to call
+
+
+def exchange_rate(base_currency: CurrencySymbol, quote_currency: CurrencySymbol) -> float:
+    if base_currency == quote_currency:
+        return 1.0
+    elif base_currency == "USD" and quote_currency == "EUR":
+        return 1 / 1.1
+    elif base_currency == "EUR" and quote_currency == "USD":
+        return 1.1
+    else:
+        raise ValueError(f"Unknown currencies {base_currency}, {quote_currency}")
+
+
+# Register the function with the agent
+
+
+@user_proxy.register_for_execution()
+@chatbot.register_for_llm(description="Currency exchange calculator.")
+def currency_calculator(
+    base_amount: Annotated[
+        float,
+        "Amount of currency in base_currency. Type is float, not string, return value should be a number only, e.g. 987.65.",
+    ],
+    base_currency: Annotated[CurrencySymbol, "Base currency"] = "USD",
+    quote_currency: Annotated[CurrencySymbol, "Quote currency"] = "EUR",
+) -> str:
+    quote_amount = exchange_rate(base_currency, quote_currency) * base_amount
+    return f"{format(quote_amount, '.2f')} {quote_currency}"
+# Weather function
+
+
+# Example function to make available to model
+def get_current_weather(location, unit="fahrenheit"):
+    """Get the weather for some location"""
+    if "chicago" in location.lower():
+        return json.dumps({"location": "Chicago", "temperature": "13", "unit": unit})
+    elif "san francisco" in location.lower():
+        return json.dumps({"location": "San Francisco", "temperature": "55", "unit": unit})
+    elif "new york" in location.lower():
+        return json.dumps({"location": "New York", "temperature": "11", "unit": unit})
+    else:
+        return json.dumps({"location": location, "temperature": "unknown"})
+
+
+# Register the function with the agent
+
+
+@user_proxy.register_for_execution()
+@chatbot.register_for_llm(description="Weather forecast for US cities.")
+def weather_forecast(
+    location: Annotated[str, "City name"],
+) -> str:
+    weather_details = get_current_weather(location=location)
+    weather = json.loads(weather_details)
+    return f"{weather['location']} will be {weather['temperature']} degrees {weather['unit']}"
+
+# start the conversation
+res = user_proxy.initiate_chat(
+    chatbot,
+    message="What's the weather in New York and can you tell me how much is 123.45 EUR in USD so I can spend it on my holiday? Throw a few holiday tips in as well.",
+    summary_method="reflection_with_llm",
+)
+
+print(f"LLM SUMMARY: {res.summary['content']}")
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