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from PIL import Image, ImageDraw
import io
import base64
import requests
import json
from typing import List, Dict, Any
from openai import OpenAI
def resize_image(image: Image.Image) -> Image.Image:
new_height = int(image.height * 512 / image.width)
return image.resize((512, new_height))
def convert_image_to_base64(image: Image.Image) -> str:
buffered = io.BytesIO()
image.save(buffered, format="PNG")
return base64.b64encode(buffered.getvalue()).decode()
def post_request_and_parse_response(url: str, payload: Dict[str, Any]) -> Dict[str, Any]:
headers = {"Content-Type": "application/json"}
response = requests.post(url, json=payload, headers=headers)
byte_data = response.content
decoded_string = byte_data.decode("utf-8")
dict_data = json.loads(decoded_string)
return dict_data
def draw_bounding_boxes_for_textract(image: Image.Image, json_data: str) -> Image.Image:
draw = ImageDraw.Draw(image)
try:
data = json_data
blocks = json.loads(data['body']) if 'body' in data else None
except json.JSONDecodeError:
return image
if blocks is None:
return image
for item in blocks:
if 'BlockType' in item and item['BlockType'] in ['LINE', 'WORD']:
bbox = item['Geometry']['BoundingBox']
left, top, width, height = bbox['Left'], bbox['Top'], bbox['Width'], bbox['Height']
left_top = (left * image.width, top * image.height)
right_bottom = ((left + width) * image.width, (top + height) * image.height)
draw.rectangle([left_top, right_bottom], outline='red', width=2)
return image
def extract_text_from_textract_blocks(blocks: List[Dict[str, Any]]) -> str:
extracted_text = []
blocks = json.loads(blocks)
for block in blocks:
if isinstance(block, dict):
if block.get('BlockType') in ['LINE', 'WORD'] and 'Text' in block:
extracted_text.append(block['Text'])
return ' '.join(extracted_text)
class ChatGPTClient:
def __init__(self, api_key: str, protocol: str = "You are a helpful assistant.", body=None):
self.api_key = api_key
self.client = OpenAI(api_key=self.api_key)
self.protocol = protocol
self.body = body
self.history: List[Dict[str, str]] = [
{"role": "system", "content": self.protocol},
{"role": "user", "content": f"The content provided: {self.body}"}
]
def append_message(self, role: str, content: str) -> None:
if role in ["system", "user", "assistant"]:
self.history.append({"role": role, "content": content})
def generate_response(self, question: str) -> str:
try:
self.append_message("user", question)
response = self.client.chat.completions.create(
model="gpt-3.5-turbo",
messages=self.history
)
output = response.choices[0].message.content
self.append_message("assistant", output)
except Exception as e:
output = "Sorry, I couldn't get an answer for that."
return output
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