app.py

import streamlit as st
import requests
import os
import json
import pandas as pd
import time
import matplotlib.pyplot as plt

# Function to call the Together AI model
def call_ai_model(all_message):
    url = "https://api.together.xyz/v1/chat/completions"
    payload = {
        "model": "NousResearch/Nous-Hermes-2-Yi-34B",
        "temperature": 1.05,
        "top_p": 0.9,
        "top_k": 50,
        "repetition_penalty": 1,
        "n": 1,
        "messages": [{"role": "user", "content": all_message}],
        "stream_tokens": True,
    }

    TOGETHER_API_KEY = os.getenv('TOGETHER_API_KEY')
    if TOGETHER_API_KEY is None:
        raise ValueError("TOGETHER_API_KEY environment variable not set.")
    
    headers = {
        "accept": "application/json",
        "content-type": "application/json",
        "Authorization": f"Bearer {TOGETHER_API_KEY}",
    }

    response = requests.post(url, json=payload, headers=headers, stream=True)
    response.raise_for_status()  # Ensure HTTP request was successful

    return response

# Function to request numerical performance data from AI
def get_performance_data(temperature):
    all_message = (
        f"Provide the expected sports performance value (as a numerical score) at a temperature of {temperature}°C."
    )
    while True:
        response = call_ai_model(all_message)
        generated_text = ""
        for line in response.iter_lines():
            if line:
                line_content = line.decode('utf-8')
                if line_content.startswith("data: "):
                    line_content = line_content[6:]  # Strip "data: " prefix
                try:
                    json_data = json.loads(line_content)
                    if "choices" in json_data:
                        delta = json_data["choices"][0]["delta"]
                        if "content" in delta:
                            generated_text += delta["content"]
                except json.JSONDecodeError:
                    continue
        try:
            performance_value = float(generated_text.strip())
            return performance_value
        except ValueError:
            continue

# Streamlit app layout
st.title("Climate Impact on Sports Performance and Infrastructure")
st.write("Analyze and visualize the impact of climate conditions on sports performance and infrastructure.")

# Inputs for climate conditions
temperature = st.number_input("Temperature (°C):", min_value=-50, max_value=50, value=25)

if st.button("Generate Prediction"):
    try:
        with st.spinner("Generating predictions..."):
            st.success("Predictions generated. Generating performance data...")

            # Generate performance data for different temperatures
            temperatures = range(-10, 41, 5)  # Temperatures from -10°C to 40°C in 5°C increments
            performance_values = []
            for temp in temperatures:
                performance_value = get_performance_data(temp)
                performance_values.append(performance_value)
                time.sleep(1)

            # Generate line graph
            fig, ax = plt.subplots()
            ax.plot(temperatures, performance_values, marker='o')
            ax.set_xlabel('Temperature (°C)')
            ax.set_ylabel('Performance Score')
            ax.set_title('Temperature vs. Sports Performance')
            st.pyplot(fig)

    except ValueError as ve:
        st.error(f"Configuration error: {ve}")
    except requests.exceptions.RequestException as re:
        st.error(f"Request error: {re}")
    except Exception as e:
        st.error(f"An unexpected error occurred: {e}")