app.py

import os
import sys
import gradio as gr
from PIL import Image
import ollama
from lightweight_charts import Chart

# Add ai-analyzer's src to path
current_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, current_dir)

# Initialize both AI models
vision_client = ollama.Client()
code_client = ollama.Client()

VISION_MODEL = "llama3.2-vision:latest"
CODE_MODEL = "codellama:latest"

# Local imports
from src.model.vision_model import ChartVisionModel
from src.model.chart_generator import ChartGeneratorModel
from src.analysis.chart_processor import ChartProcessor
from src.analysis.pattern_generator import PatternGenerator
from src.analysis.indicator_generator import IndicatorGenerator
from src.analysis.chart_analyzer import ChartAnalyzer
from src.data.market_data import MarketData

def analyze_full_chart(chart_image, symbol):
    # Vision analysis using ChartVisionModel
    vision_model = ChartVisionModel()
    vision_analysis = vision_model.analyze_chart(chart_image)
    
    # Chart generation using ChartGeneratorModel
    chart_generator = ChartGeneratorModel()
    
    market_data = MarketData()
    historical_data = market_data.fetch_ohlcv(symbol)
    
    # Pattern Generation
    pattern_gen = PatternGenerator()
    pattern_images = pattern_gen.generate_all_patterns(chart_image, historical_data)
    
    # Indicator Generation
    indicator_gen = IndicatorGenerator()
    indicator_charts = indicator_gen.generate_all_indicators(historical_data)
    
    # Process chart
    processor = ChartProcessor()
    processed_results = processor.process_chart(chart_image)
    
    # Full chart analysis
    analyzer = ChartAnalyzer()
    analysis_results = analyzer.analyze_full(
        chart_image=chart_image,
        pattern_images=pattern_images,
        indicator_charts=indicator_charts,
        historical_data=historical_data
    )
    
    return {
        'pattern_analysis': analysis_results.patterns,
        'indicator_analysis': analysis_results.indicators,
        'predictions': analysis_results.predictions,
        'interactive_charts': indicator_charts,
        'chart_analysis': processed_results,
        'vision_results': vision_analysis
    }

interface = gr.Interface(
    fn=analyze_full_chart,
    inputs=[
        gr.Image(type="pil", label="Chart Image"),
        gr.Textbox(label="Symbol")
    ],
    outputs=[
        gr.Gallery(label="Pattern Overlays"),
        gr.Gallery(label="Indicator Charts"),
        gr.JSON(label="Analysis Results"),
        gr.Plot(label="Interactive Indicators")
    ]
)

if __name__ == "__main__":
    interface.launch()