from langchain_core.tools import tool import os import io import base64 import uuid from PIL import Image from typing import List, Dict, Any, Optional import numpy as np from PIL import Image, ImageDraw, ImageFont, ImageEnhance, ImageFilter # Helper functions for image processing def encode_image(image_path: str) -> str: """Convert an image file to base64 string.""" with open(image_path, "rb") as image_file: return base64.b64encode(image_file.read()).decode("utf-8") def decode_image(base64_string: str) -> Image.Image: """Convert a base64 string to a PIL Image.""" image_data = base64.b64decode(base64_string) return Image.open(io.BytesIO(image_data)) def save_image(image: Image.Image, directory: str = "image_outputs") -> str: """Save a PIL Image to disk and return the path.""" os.makedirs(directory, exist_ok=True) image_id = str(uuid.uuid4()) image_path = os.path.join(directory, f"{image_id}.png") image.save(image_path) return image_path @tool def analyze_image(image_input: str) -> str: """ Analyze an image and provide a detailed description. Args: image_input (str): Either a file path to an image or a base64 encoded image string Returns: A string description of the image """ try: # Check if input is a file path if os.path.exists(image_input): print(f"Processing image from file path: {image_input}") img = Image.open(image_input) else: # Try to decode as base64 try: print("Input not a file path, trying base64 decoding") # Add padding if necessary missing_padding = len(image_input) % 4 if missing_padding != 0: image_input += '=' * (4 - missing_padding) image_data = base64.b64decode(image_input) img = Image.open(io.BytesIO(image_data)) except Exception as base64_error: return f"Error: Could not process image. Not a valid file path or base64 string: {str(base64_error)}" # Get basic image properties width, height = img.size mode = img.mode format = getattr(img, 'format', 'Unknown') # Basic image analysis description = "Image analysis:\n" description += f"- Dimensions: {width}x{height} pixels\n" description += f"- Color mode: {mode}\n" description += f"- Format: {format}\n" # More advanced analysis based on image content if mode in ("RGB", "RGBA"): # Sample colors from different regions regions = [ ("top-left", (width//4, height//4)), ("top-right", (width*3//4, height//4)), ("center", (width//2, height//2)), ("bottom-left", (width//4, height*3//4)), ("bottom-right", (width*3//4, height*3//4)) ] description += "\nColor sampling:\n" for region_name, (x, y) in regions: pixel = img.getpixel((x, y)) if len(pixel) >= 3: r, g, b = pixel[:3] description += f"- {region_name}: RGB({r},{g},{b})\n" # Analyze overall brightness try: if mode in ("RGB", "RGBA", "L"): # Convert to numpy array for faster processing arr = np.array(img) if mode == "L": brightness = arr.mean() description += f"\nOverall brightness: {brightness:.1f}/255 " if brightness < 85: description += "(quite dark)" elif brightness < 170: description += "(medium brightness)" else: description += "(quite bright)" else: # For RGB/RGBA if arr.shape[2] >= 3: avg_colors = arr[:,:,:3].mean(axis=(0, 1)) brightness = avg_colors.mean() description += f"\nOverall brightness: {brightness:.1f}/255 " if brightness < 85: description += "(quite dark)" elif brightness < 170: description += "(medium brightness)" else: description += "(quite bright)" # Determine dominant color r, g, b = avg_colors if max(avg_colors) == r: description += "\nDominant color channel: Red" elif max(avg_colors) == g: description += "\nDominant color channel: Green" else: description += "\nDominant color channel: Blue" except Exception as analysis_error: description += f"\nError during color analysis: {str(analysis_error)}" return description except Exception as e: return f"Error analyzing image: {str(e)}" @tool def transform_image( image_base64: str, operation: str, params: Optional[Dict[str, Any]] = None ) -> Dict[str, Any]: """ Apply transformations: resize, rotate, crop, flip, brightness, contrast, blur, sharpen, grayscale. Args: image_base64 (str): Base64 encoded input image operation (str): Transformation operation params (Dict[str, Any], optional): Parameters for the operation Returns: Dictionary with transformed image (base64) """ try: img = decode_image(image_base64) params = params or {} if operation == "resize": img = img.resize( ( params.get("width", img.width // 2), params.get("height", img.height // 2), ) ) elif operation == "rotate": img = img.rotate(params.get("angle", 90), expand=True) elif operation == "crop": img = img.crop( ( params.get("left", 0), params.get("top", 0), params.get("right", img.width), params.get("bottom", img.height), ) ) elif operation == "flip": if params.get("direction", "horizontal") == "horizontal": img = img.transpose(Image.FLIP_LEFT_RIGHT) else: img = img.transpose(Image.FLIP_TOP_BOTTOM) elif operation == "adjust_brightness": img = ImageEnhance.Brightness(img).enhance(params.get("factor", 1.5)) elif operation == "adjust_contrast": img = ImageEnhance.Contrast(img).enhance(params.get("factor", 1.5)) elif operation == "blur": img = img.filter(ImageFilter.GaussianBlur(params.get("radius", 2))) elif operation == "sharpen": img = img.filter(ImageFilter.SHARPEN) elif operation == "grayscale": img = img.convert("L") else: return {"error": f"Unknown operation: {operation}"} result_path = save_image(img) result_base64 = encode_image(result_path) return {"transformed_image": result_base64} except Exception as e: return {"error": str(e)} @tool def draw_on_image( image_base64: str, drawing_type: str, params: Dict[str, Any] ) -> Dict[str, Any]: """ Draw shapes (rectangle, circle, line) or text onto an image. Args: image_base64 (str): Base64 encoded input image drawing_type (str): Drawing type params (Dict[str, Any]): Drawing parameters Returns: Dictionary with result image (base64) """ try: img = decode_image(image_base64) draw = ImageDraw.Draw(img) color = params.get("color", "red") if drawing_type == "rectangle": draw.rectangle( [params["left"], params["top"], params["right"], params["bottom"]], outline=color, width=params.get("width", 2), ) elif drawing_type == "circle": x, y, r = params["x"], params["y"], params["radius"] draw.ellipse( (x - r, y - r, x + r, y + r), outline=color, width=params.get("width", 2), ) elif drawing_type == "line": draw.line( ( params["start_x"], params["start_y"], params["end_x"], params["end_y"], ), fill=color, width=params.get("width", 2), ) elif drawing_type == "text": font_size = params.get("font_size", 20) try: font = ImageFont.truetype("arial.ttf", font_size) except IOError: font = ImageFont.load_default() draw.text( (params["x"], params["y"]), params.get("text", "Text"), fill=color, font=font, ) else: return {"error": f"Unknown drawing type: {drawing_type}"} result_path = save_image(img) result_base64 = encode_image(result_path) return {"result_image": result_base64} except Exception as e: return {"error": str(e)} @tool def generate_simple_image( image_type: str, width: int = 500, height: int = 500, params: Optional[Dict[str, Any]] = None, ) -> Dict[str, Any]: """ Generate a simple image (gradient, noise, pattern, chart). Args: image_type (str): Type of image width (int), height (int) params (Dict[str, Any], optional): Specific parameters Returns: Dictionary with generated image (base64) """ try: params = params or {} if image_type == "gradient": direction = params.get("direction", "horizontal") start_color = params.get("start_color", (255, 0, 0)) end_color = params.get("end_color", (0, 0, 255)) img = Image.new("RGB", (width, height)) draw = ImageDraw.Draw(img) if direction == "horizontal": for x in range(width): r = int( start_color[0] + (end_color[0] - start_color[0]) * x / width ) g = int( start_color[1] + (end_color[1] - start_color[1]) * x / width ) b = int( start_color[2] + (end_color[2] - start_color[2]) * x / width ) draw.line([(x, 0), (x, height)], fill=(r, g, b)) else: for y in range(height): r = int( start_color[0] + (end_color[0] - start_color[0]) * y / height ) g = int( start_color[1] + (end_color[1] - start_color[1]) * y / height ) b = int( start_color[2] + (end_color[2] - start_color[2]) * y / height ) draw.line([(0, y), (width, y)], fill=(r, g, b)) elif image_type == "noise": noise_array = np.random.randint(0, 256, (height, width, 3), dtype=np.uint8) img = Image.fromarray(noise_array, "RGB") else: return {"error": f"Unsupported image_type {image_type}"} result_path = save_image(img) result_base64 = encode_image(result_path) return {"generated_image": result_base64} except Exception as e: return {"error": str(e)} @tool def combine_images( images_base64: List[str], operation: str, params: Optional[Dict[str, Any]] = None ) -> Dict[str, Any]: """ Combine multiple images (collage, stack, blend). Args: images_base64 (List[str]): List of base64 images operation (str): Combination type params (Dict[str, Any], optional) Returns: Dictionary with combined image (base64) """ try: images = [decode_image(b64) for b64 in images_base64] params = params or {} if operation == "stack": direction = params.get("direction", "horizontal") if direction == "horizontal": total_width = sum(img.width for img in images) max_height = max(img.height for img in images) new_img = Image.new("RGB", (total_width, max_height)) x = 0 for img in images: new_img.paste(img, (x, 0)) x += img.width else: max_width = max(img.width for img in images) total_height = sum(img.height for img in images) new_img = Image.new("RGB", (max_width, total_height)) y = 0 for img in images: new_img.paste(img, (0, y)) y += img.height else: return {"error": f"Unsupported combination operation {operation}"} result_path = save_image(new_img) result_base64 = encode_image(result_path) return {"combined_image": result_base64} except Exception as e: return {"error": str(e)}