# # Function Calling with OpenAI APIs
import requests
import os
import json
from dotenv import load_dotenv
import streamlit as st
load_dotenv()

from groq import Groq

# client = Groq(
#     api_key=os.getenv("GROQ_API_KEY"),
# )

# st.title("Weather App with Chat Interface")

# input_text = st.text_input("Hi, I am a weather chatbot. Ask me anything!")

# if st.button("Ask me"):
#     if not input_text:
#         st.error("Please enter a location!")

# ### Define Dummy Function

# Defines a dummy function to get the current weather
def get_current_weather(location):
    url = f'https://api.openweathermap.org/data/2.5/weather?q={location}&appid={os.getenv("OPENWEATHER_API_KEY")}'
    response = requests.get(url)
    data=response.json()
    if data['cod'] == 200:
        return data
    else:
        return json.dumps({"city": location, "weather": "Data Fetch Error", "temperature": "N/A"})

# print(get_current_weather("London"))
# ### Define Functions
# 
# As demonstrated in the OpenAI documentation, here is a simple example of how to define the functions that are going to be part of the request. 
# 
# The descriptions are important because these are passed directly to the LLM and the LLM will use the description to determine whether to use the functions or how to use/call.



# # define a function as tools
# tools = [
#     {
#         "type": "function",
#         "function": {
#             "name": "get_current_weather",
#             "description": "Get the current weather in a given location",
#             "parameters": {
#                 "type": "object",
#                 "properties": {
#                     "location": {
#                         "type": "string",
#                         "description": "The city and state, e.g. San Francisco, CA"
#                     }
#                 },
#                 "required": ["location"]
#             }
#         }
#     },
# ]


def get_response(input_text,client):
    
    tools = [
    {
        "type": "function",
        "function": {
            "name": "get_current_weather",
            "description": "Get the real time weather of a given location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "The city, state and country, e.g. San Francisco, CA, US"
                    }
                },
                "required": ["location"]
            }
        }
    },
]
    response = client.chat.completions.create(
      model="mixtral-8x7b-32768",
        messages=[
          {
            "role": "system",
            "content": "You are a helpful assistant. You will asked details regarding the weather. If there is no question with respect to a weather, show a polite error message."
        },
        {
            "role": "user",
            "content": input_text+" Use a tool given to you",
             }
        ],
        temperature=0,
        max_tokens=300,
        tools=tools,
        tool_choice="auto"
    )
    # print(response)
    # print(response.choices[0].message.content)

    # print(response['choices'][0]['message']['tool_calls'][0]['function']['arguments'])

    groq_response = response.choices[0].message
    if groq_response is None:
        return "No response from Groq"
    else:
        groq_response = response.choices[0].message
        args = json.loads(groq_response.tool_calls[0].function.arguments)
    #    print(args)

        output=get_current_weather(**args)
    # print(groq_response)


    # response.tool_calls[0].function.arguments

    # We can now capture the arguments:



    # print(output)
    from groq import Groq

    client = Groq()
    completion = client.chat.completions.create(
    model="mixtral-8x7b-32768",
    messages=[
        {
            "role": "system",
            "content": "You are a helpful assistant. You are given the weather details in json format. Read the data and give a brief description of the weather and then answer the question. All temperatures are in kelvin. Only mention details about the weather. If the JSON mentions data fetch error, only give a polite error message and tell the user to ask questions related to the weather of a place. "
        },
        {
            "role": "user",
            "content": json.dumps(output)
        }
    ],
    temperature=0.25,
    max_tokens=200,
    top_p=1,
    stream=True,
    stop=None,
    )
    output=""
    # st.write("Response:")
    for chunk in completion:
        output+=chunk.choices[0].delta.content or ""
    # output+="\n"
    return output

def main():
    st.title("WeatherWizard")
    st.caption("Ask about any location's weather in plain English, get answers faster than you can say umbrella")
    client = Groq(
        api_key=os.getenv("GROQ_API_KEY"),
        )
    # User input
    # st.write("Hi, I am a weather chatbot. Ask me anything!")
    if "messages" not in st.session_state:
        st.session_state["messages"] = [{"role": "assistant", "content": "How can I help you?"}]

    for msg in st.session_state.messages:
        st.chat_message(msg["role"]).write(msg["content"])
        
    # input_text = st.text_input("Type in your question")

    # Ask me button
    if prompt := st.chat_input():
    

        st.session_state.messages.append({"role": "user", "content": prompt})
        st.chat_message("user").write(prompt)
        response = get_response(prompt,client)
        st.session_state.messages.append({"role": "assistant", "content": response})
        st.chat_message("assistant").write(response)
if __name__ == "__main__":
    main()