Create ai.py

ai.py

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+import requests
+import time
+import pytz
+from news import get_news_about
+from datetime import datetime, timedelta
+from timeframe import fetch_financial_data
+
+
+def get_times():
+    """Get current time in different financial centers"""
+    # Define the time zones
+    greenwich_tz = pytz.timezone('GMT')
+    london_tz = pytz.timezone('Europe/London')
+    newyork_tz = pytz.timezone('America/New_York')
+    dubai_tz = pytz.timezone('Asia/Dubai')
+
+    # Get current UTC time
+    utc_now = datetime.now(pytz.utc)
+
+    # Convert to each timezone
+    greenwich_time = utc_now.astimezone(greenwich_tz)
+    london_time = utc_now.astimezone(london_tz)
+    newyork_time = utc_now.astimezone(newyork_tz)
+    dubai_time = utc_now.astimezone(dubai_tz)
+
+    # Format the times
+    time_format = "%Y-%m-%d %H:%M:%S %Z%z"
+
+    times = {
+        "Greenwich": greenwich_time.strftime(time_format),
+        "London": london_time.strftime(time_format),
+        "New York": newyork_time.strftime(time_format),
+        "Dubai": dubai_time.strftime(time_format)
+    }
+
+    return times
+
+
+def capture_screenshot(url, browser_width=1280, browser_height=3000, full_page=True,
+                      device_scale_factor=1, format="png"):
+    """Capture a screenshot of a webpage using the Imagy API"""
+    api_endpoint = "https://gcp.imagy.app/screenshot/createscreenshot"
+
+    payload = {
+        "url": url,
+        "browserWidth": browser_width,
+        "browserHeight": browser_height,
+        "fullPage": full_page,
+        "deviceScaleFactor": device_scale_factor,
+        "format": format
+    }
+
+    headers = {
+        "Content-Type": "application/json",
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Safari/537.36"
+    }
+
+    try:
+        response = requests.post(api_endpoint, json=payload, headers=headers)
+        response.raise_for_status()
+        data = response.json()
+        return data.get("fileUrl")
+    except Exception as e:
+        print(f"Error capturing screenshot: {e}")
+        return None
+
+
+def chat_with_ai(chat_history, temperature=0.7):
+    """Send chat history to AI and get response"""
+    url = "https://corvo-ai-xx-ry.hf.space/chat"
+
+    headers = {
+        "Content-Type": "application/json",
+    }
+
+    payload = {
+        "chat_history": chat_history,
+        "temperature": temperature,
+    }
+
+    max_retries = 3
+    retry_delay = 5
+
+    for attempt in range(max_retries):
+        try:
+            response = requests.post(url, headers=headers, json=payload, timeout=120)
+            response.raise_for_status()
+            result = response.json()
+            return result.get("assistant_response", "No response received.")
+        except Exception as e:
+            if attempt < max_retries - 1:
+                time.sleep(retry_delay)
+                print(f"Retry {attempt+1}: Communication error - {str(e)}")
+            else:
+                print(f"Final attempt failed: {str(e)}")
+
+    return "عذراً، واجهت مشكلة في الاتصال. يرجى المحاولة مرة أخرى لاحقاً. 🙁"
+
+
+def get_forex_data(pair, timeframes=["1d", "1h"]):
+    """Get forex data for a specific pair and timeframes"""
+    data = {}
+
+    # Convert timeframes to Yahoo Finance format
+    timeframe_mapping = {
+        "1m": "1m",
+        "5m": "5m",
+        "15m": "15m",
+        "30m": "30m",
+        "1h": "60m",
+        "4h": "4h",
+        "1d": "1d"
+    }
+
+    # List of special symbols that don't need =X suffix
+    special_symbols = ["DX-Y.NYB", "GC=F", "^SPX", "WTI", "^TNX" , "^FTSE"]
+
+    for tf in timeframes:
+        if tf in timeframe_mapping:
+            yahoo_tf = timeframe_mapping[tf]
+
+            # Check if the pair is in the special symbols list
+            if pair in special_symbols:
+                yahoo_symbol = pair  # Use symbol as is, without appending =X
+            else:
+                # Append =X to make it a proper Yahoo Finance forex symbol
+                yahoo_symbol = f"{pair}=X"
+
+            print(f"Fetching {yahoo_symbol} data for {tf} timeframe...")
+
+            # Set appropriate start date based on timeframe
+            if tf == "1d":
+                # For daily timeframe, get 7 days of data
+                start_date = datetime.now() - timedelta(days=7)
+            elif tf == "1h":
+                # For hourly timeframe, get 3 days of data
+                start_date = datetime.now() - timedelta(days=3)
+            else:
+                # Default fallback (shouldn't be needed with the current implementation)
+                start_date = datetime.now() - timedelta(days=5)
+
+            # Use the fetch_financial_data function from timeframe.py
+            result = fetch_financial_data(
+                symbol=yahoo_symbol,
+                start_date=start_date,
+                interval=yahoo_tf
+            )
+
+            if result['success']:
+                data[tf] = {
+                    'dataframe': result['data'],
+                    'stats': result['stats'],
+                    'table': result['table'],
+                    'meta_info': result['meta_info']
+                }
+                print(f"Successfully fetched {tf} data for {pair}")
+            else:
+                print(f"Failed to fetch {tf} data for {pair}: {result['message']}")
+                data[tf] = None
+        else:
+            print(f"Unsupported timeframe: {tf}")
+
+    return data
+
+
+def analyze_forex_group(group, description, relationships):
+    """Main function to analyze a group of forex pairs with their relationships"""
+    print(f"Analyzing forex group: {', '.join(group)}")
+
+    # Step 1: Get current times in financial centers
+    market_times = get_times()
+    times_text = "\n".join([f"{k}: {v}" for k, v in market_times.items()])
+
+    # Step 2: Capture FinViz forex performance chart
+    finviz_url = "https://finviz.com/forex.ashx"
+    print("📸 Capturing Forex Performance Chart...")
+    performance_screenshot = capture_screenshot(finviz_url)
+    if performance_screenshot:
+        print(f"✅ Forex Performance Chart captured: {performance_screenshot}")
+    else:
+        print("❌ Failed to capture Forex Performance Chart")
+
+    # Prepare system prompt with market times, group context and relationships
+    system_prompt = f"""You are a Principal Forex Analyst specializing in technical analysis and correlation-based trading.
+Your task is to analyze the entire forex group: {', '.join(group)} and identify the strongest trading opportunities within this correlated group.
+
+🕒 Current Market Times:
+{times_text}
+
+📌 Group Context: {description}
+
+🔗 Relationship Analysis:
+{relationships}
+
+Your analysis must include the following:
+
+1. Current market hours and which financial centers are active now.
+2. Comprehensive group analysis showing how these correlated pairs are moving together or if there are any notable divergences.
+3. Individual analysis of each pair in the group.
+4. Key support and resistance zones for each pair.
+5. How the described relationships are reflected in the current price action.
+6. Which pairs in the group show the strongest technical patterns.
+7. Volatility and liquidity conditions across the group.
+8. Impact of upcoming news events (if any) on the group dynamics.
+9. Potential for 40 to 70 pip price movement in any of the pairs.
+
+---
+
+Your response **must** follow this exact structure:
+
+<Group Analysis>
+Analyze the group as a whole, focusing on how the pairs interact according to their known correlations. Identify whether the correlations are still holding or if there are any notable divergences.
+</Group Analysis>
+
+<Individual Pair Analysis>
+Provide a concise technical analysis for each pair in the group:
+
+PAIR1:
+- Current price action and technical structure
+- Key levels and patterns
+- Trend strength
+- Potential targets
+
+PAIR2:
+- Current price action and technical structure
+- Key levels and patterns
+- Trend strength
+- Potential targets
+
+(Continue for the rest of the pairs in the group following the same format)
+</Individual Pair Analysis>
+
+<Best Opportunities>
+Identify one or two pairs from the group that represent the strongest technical setups with a potential 40–70 pip movement. Explain why these opportunities stand out compared to other pairs in the group and how the correlation context strengthens this case.
+</Best Opportunities>
+
+<Prediction>
+For each identified opportunity, clearly state:
+- The expected direction (bullish/bearish)
+- Specific price targets for the 40–70 pip move
+- Key levels that confirm or invalidate the prediction
+- Estimated timeframe for the move to develop
+</Prediction>
+
+<Trading Strategy>
+Provide a strategic plan for trading the identified opportunities, including:
+- Entry zones
+- Stop loss considerations
+- Take profit targets
+- Risk management approach
+- How to use other pairs in the group as confirmation tools
+</Trading Strategy>
+
+<Correlation Warning>
+Highlight any potential risks or considerations when trading multiple pairs from the same correlated group.
+</Correlation Warning>
+
+<Forward>
+For the strongest one or two setups identified, indicate that they must be forwarded to the Deep Analyst specialized in the 15-minute timeframe for precise entry analysis. Explain:
+- Why this setup requires more detailed analysis on the 15-minute timeframe
+- What patterns, breakouts, or pullbacks the analyst should look for on the lower timeframe
+- Critical price zones for optimal entry with minimal risk
+- How the correlation with other pairs can be used to time entries precisely
+- The analyst should also consider what is happening on both the 1-hour and 1-day timeframes for each pair to understand the full context and optimize entry timing.
+</Forward>
+
+Always make sure to close tags properly (e.g., </Forward>)
+
+📌 Forwarding to the 15-minute timeframe analyst is crucial for:
+- Finding precise entry points with minimal risk
+- Identifying intraday patterns supporting the 1-hour analysis
+- Timing entries during pullbacks or breakout confirmations
+- Improving risk-to-reward ratio through tighter stop placement
+
+⚠️ This is **not** financial advice — only professional chart analysis for potential price movements.
+"""
+
+
+    # Build chat history with system prompt
+    chat_history = [
+        {"role": "system", "content": system_prompt}
+    ]
+
+    # Add Forex Performance screenshot
+    if performance_screenshot:
+        chat_history.append({
+            "role": "user",
+            "type": "multipart",
+            "content": [
+                {"type": "image", "url": performance_screenshot},
+                {"type": "text", "text": "Current Forex Relative Performance USD chart from FinViz"}
+            ]
+        })
+
+    # Get forex data for each pair and add to chat history
+    for pair in group:
+        timeframe_data = get_forex_data(pair, ["1d", "1h"])
+
+        # Add 1-day timeframe data
+        if timeframe_data.get("1d"):
+            chat_history.append({
+                "role": "user",
+                "content": f"**{pair} - Daily (1D) Timeframe Data**\n\n{timeframe_data['1d']['table']}\n\n**Stats:**\n{timeframe_data['1d']['stats']}\n\n**Meta Info:**\n{timeframe_data['1d']['meta_info']}"
+            })
+
+        # Add 1-hour timeframe data
+        if timeframe_data.get("1h"):
+            chat_history.append({
+                "role": "user",
+                "content": f"**{pair} - Hourly (1H) Timeframe Data**\n\n{timeframe_data['1h']['table']}\n\n**Stats:**\n{timeframe_data['1h']['stats']}\n\n**Meta Info:**\n{timeframe_data['1h']['meta_info']}"
+            })
+
+    # Get AI analysis
+    analysis = chat_with_ai(chat_history)
+    print(analysis)
+    print("Analysis complete!")
+
+    return analysis