Update app.py

app.py

@@ -1,69 +1,69 @@
 # app.py
+# app.py
 import os
 import streamlit as st
 from PIL import Image
 from groq import Groq
-import io
-
-# Set your GROQ API key here or export as environment variable before running
-os.environ["GROQ_API_KEY"] = "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"
+import base64
 
-client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+# Set up Groq API
+GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
+client = Groq(api_key=GROQ_API_KEY)
 
-st.set_page_config(page_title="AI Trade Predictor", layout="wide")
+# 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: #0d1117;
-        color: white;
+        background-color: #1e1e1e;
+        color: #ffffff;
     }
     .stButton>button {
-        background-color: #1f6feb;
+        background-color: #4CAF50;
         color: white;
-        font-weight: bold;
-    }
-    .stFileUploader label {
-        color: #58a6ff;
+        font-size: 18px;
     }
     </style>
 """, unsafe_allow_html=True)
 
-st.title("💰 AI Trade Predictor")
-st.markdown("Upload a candlestick chart image, and the AI will analyze it using common trading strategies.")
+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 Candlestick Chart Image", type=["jpg", "png", "jpeg"])
+uploaded_file = st.file_uploader("Upload a candlestick chart image", type=["png", "jpg", "jpeg"])
 
-if uploaded_file is not None:
+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 chart and generating predictions..."):
-            # Instead of sending the full image, just notify AI that user uploaded a chart image
-            prompt = (
-                "You are a trading expert AI. "
-                "A user uploaded a candlestick chart image (image content not available). "
-                "Based on your knowledge of standard technical strategies (RSI, MACD, moving averages, "
-                "candlestick patterns, support/resistance), analyze this chart and provide:\n"
-                "1. Should the user BUY or SELL?\n"
-                "2. Confidence level in percentage.\n"
-                "3. Best timeframe for this trade.\n"
-                "4. Risks involved and how this prediction might go wrong.\n"
-                "5. Explanation of your reasoning.\n"
-                "Answer concisely and clearly."
-            )
+    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:
-                chat_completion = client.chat.completions.create(
+                response = client.chat.completions.create(
                     messages=[{"role": "user", "content": prompt}],
-                    model="llama-3.3-70b-versatile",
+                    model="llama-3.3-70b-versatile"
                 )
-                result = chat_completion.choices[0].message.content
-                st.markdown("### 📈 Prediction Result")
-                st.markdown(result)
-            except Exception as e:
-                st.error(f"Error communicating with GROQ API: {e}")
-else:
-    st.info("Please upload a candlestick chart image to begin analysis.")
+                st.success("Analysis Complete!")
+                st.markdown(response.choices[0].message.content)
 
+            except Exception as e:
+                st.error(f"Something went wrong: {e}")