mirror of
https://github.com/kennethreitz/instructor.git
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Jason Liu
66 lines
1.8 KiB
Python
66 lines
1.8 KiB
Python
import instructor
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from openai import OpenAI
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from pydantic import BaseModel
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import base64
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client = instructor.patch(OpenAI(), mode=instructor.function_calls.Mode.MD_JSON)
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class Circle(BaseModel):
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x: int
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y: int
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color: str
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def encode_image(image_path):
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with open(image_path, "rb") as image_file:
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return base64.b64encode(image_file.read()).decode("utf-8")
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def draw_circle(image_size, num_circles, path):
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from PIL import Image, ImageDraw
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import random
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image = Image.new("RGB", image_size, "white")
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draw = ImageDraw.Draw(image)
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for _ in range(num_circles):
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# Randomize the circle properties
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radius = 100 # random.randint(10, min(image_size)//5) # Radius between 10 and 1/5th of the smallest dimension
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x = random.randint(radius, image_size[0] - radius)
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y = random.randint(radius, image_size[1] - radius)
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color = ["red", "black", "blue", "green"][random.randint(0, 3)]
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circle_position = (x - radius, y - radius, x + radius, y + radius)
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print(f"Generating circle at {x, y} with color {color}")
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draw.ellipse(circle_position, fill=color, outline="black")
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image.save(path)
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img_path = "circle.jpg"
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draw_circle((1024, 1024), 1, img_path)
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base64_image = encode_image(img_path)
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response = client.chat.completions.create(
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model="gpt-4-vision-preview",
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max_tokens=1800,
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response_model=Circle,
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messages=[
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "find the circle"},
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{
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"type": "image_url",
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"image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
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},
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],
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}
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],
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)
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print(
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f"Found circle with center at x: {response.x}, y: {response.y} and color: {response.color}"
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)
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