app.py

# app.py
# app.py
import os
import streamlit as st
from PIL import Image
from groq import Groq
import base64

# Set up Groq API
GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
client = Groq(api_key=GROQ_API_KEY)

# Helper function to encode image as base64
def encode_image(image):
    buffered = image.getvalue()
    return base64.b64encode(buffered).decode()

# Streamlit UI
st.set_page_config(page_title="AI Trade Predictor", layout="centered")
st.markdown("""
    <style>
    .main {
        background-color: #1e1e1e;
        color: #ffffff;
    }
    .stButton>button {
        background-color: #4CAF50;
        color: white;
        font-size: 18px;
    }
    </style>
""", unsafe_allow_html=True)

st.title("🤖 AI Trade Predictor")
st.write("Upload your candlestick chart image and let AI analyze the trading signals for you.")

uploaded_file = st.file_uploader("Upload a candlestick chart image", type=["png", "jpg", "jpeg"])

if uploaded_file:
    image = Image.open(uploaded_file)
    st.image(image, caption="Uploaded Chart", use_column_width=True)

    if st.button("Analyze Chart"):
        with st.spinner("Analyzing..."):
            encoded_image = encode_image(uploaded_file)

            prompt = f"""
You are an AI trading assistant. A user has uploaded a candlestick chart. Based on the chart image, perform the following:
1. Identify key signals like bullish/bearish patterns, RSI, MACD etc.
2. Predict BUY/SELL/WAIT decisions for multiple timeframes (e.g., 30m, 1h, 4h, 1d).
3. Give a confidence percentage for each prediction.
4. Explain in simple terms for beginners — avoid complex jargon unless explained.
5. List the risks involved with each prediction.
6. Provide a summary with what a beginner should do next.
7. Format output cleanly with emojis and bullet points.

Here is the chart (as base64): {encoded_image}
"""

            try:
                response = client.chat.completions.create(
                    messages=[{"role": "user", "content": prompt}],
                    model="llama-3.3-70b-versatile"
                )
                st.success("Analysis Complete!")
                st.markdown(response.choices[0].message.content)

            except Exception as e:
                st.error(f"Something went wrong: {e}")