import base64 import mimetypes import os import PIL.Image import requests import uuid from smolagents import tool # Function to encode the image def encode_image(image_path): if image_path.startswith("http"): user_agent = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36 Edg/119.0.0.0" request_kwargs = { "headers": {"User-Agent": user_agent}, "stream": True, } # Send a HTTP request to the URL response = requests.get(image_path, **request_kwargs) response.raise_for_status() content_type = response.headers.get("content-type", "") extension = mimetypes.guess_extension(content_type) if extension is None: extension = ".download" fname = str(uuid.uuid4()) + extension download_path = os.path.abspath(os.path.join("downloads", fname)) with open(download_path, "wb") as fh: for chunk in response.iter_content(chunk_size=512): fh.write(chunk) image_path = download_path with open(image_path, "rb") as image_file: return base64.b64encode(image_file.read()).decode("utf-8") def resize_image(image_path): img = PIL.Image.open(image_path) width, height = img.size img = img.resize((int(width / 2), int(height / 2))) new_image_path = f"resized_{image_path}" img.save(new_image_path) return new_image_path @tool def visualizer(image_path: str, question: str | None = None) -> str: """A tool that can answer questions about attached images. Args: image_path: The path to the image on which to answer the question. This should be a local path to downloaded image. question: The question to answer. """ add_note = False if not question: add_note = True question = "Please write a detailed caption for this image." if not isinstance(image_path, str): raise Exception("You should provide at least `image_path` string argument to this tool!") mime_type, _ = mimetypes.guess_type(image_path) base64_image = encode_image(image_path) payload = { "model": "gpt-4o", "messages": [ { "role": "user", "content": [ {"type": "text", "text": question}, {"type": "image_url", "image_url": {"url": f"data:{mime_type};base64,{base64_image}"}}, ], } ], "max_tokens": 1000, } headers = {"Content-Type": "application/json", "Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}"} response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload) try: output = response.json()["choices"][0]["message"]["content"] except Exception: raise Exception(f"Response format unexpected: {response.json()}") if add_note: output = f"You did not provide a particular question, so here is a detailed caption for the image: {output}" return output